Saturated Zone Flow and Transport Model Abstraction Rev 02, ICN 00 MDL-NBS-HS-000021 October 2004 1. PURPOSE The purpose of the saturated zone (SZ) flow and transport model abstraction task is to provide radionuclide-transport simulation results for use in the total system performance assessment (TSPA) for license application (LA) calculations. This task includes assessment of uncertainty in parameters that pertain to both groundwater flow and radionuclide transport in the models used for this purpose. This model report documents the following: • The SZ transport abstraction model, which consists of a set of radionuclide breakthrough curves at the accessible environment for use in the TSPA-LA simulations of radionuclide releases into the biosphere. These radionuclide breakthrough curves contain information on radionuclide-transport times through the SZ. • The SZ one-dimensional (1-D) transport model, which is incorporated in the TSPA-LA model to simulate the transport, decay, and ingrowth of radionuclide decay chains in the SZ. • The analysis of uncertainty in groundwater-flow and radionuclide-transport input parameters for the SZ transport abstraction model and the SZ 1-D transport model. • The analysis of the background concentration of alpha-emitting species in the groundwater of the SZ. Figure 1-1 shows the relationship of this report to other model reports that also pertain to flow and transport in the SZ. Figure 1-1 also shows the flow of key information among the SZ reports. It should be noted that Figure 1-1 does not contain a complete representation of the data and parameter inputs and outputs of all SZ reports, nor does it show inputs external to this suite of SZ reports. The primary input model to this report is the SZ site-scale transport model, which forms the basis for the SZ transport abstraction model and the SZ 1-D transport model, as developed in this report. The output models from this report are direct feeds to the TSPA-LA model. Several other SZ reports provide information used to define the uncertainty distributions for groundwater flow and radionuclide transport parameters. The following reports, through their output DTNs, provide direct input to this report: • Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model (BSC 2004 [DIRS 170009]) • Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036]) • Probability Distributions for Flowing Interval Spacing (BSC 2004 [DIRS 170014]) • Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006]) • Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010]) • Analysis of Hydrologic Properties Data (BSC 2004 [DIRS 170038]) • UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]) • Rock Properties Model (BSC 2004 [DIRS 170032]) • Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary (BSC 2004 [DIRS 170025]). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 1-2 October 2004 The following reports use this report or its output DTNs as direct input: • Total System Performance Assessment (TSPA) Model/Analysis for the License Application • Drift-Scale Radionuclide Transport • Features, Events, and Processes in SZ Flow and Transport • Features, Events, and Processes: Disruptive Events. Revision 02 of this report includes several changes relative to Revision 01 [Saturated Zone Flow and Transport Model Abstraction (BSC 2003 [DIRS 167651])]. Numerous comments from the Regulatory Integration Team have been addressed in this revision of the report. Additional simulations and corrections are presented, which compare the SZ site-scale transport model to the SZ 1-D transport model, to clarify the correspondence of these models to each other on a realization-by-realization basis. Using a re-sampling of the input parameters, the entire suite of radionuclide transport simulations from the SZ transport abstraction model is presented. Regeneration of the transport simulation results is performed as an impact analysis, to address CR (Condition Report) 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009). Documentation of this impact analysis for CR 2222 is contained in Appendix B of this report. This model report provides the technical basis for SZ-related features, events, and processes (FEPs) included in the TSPA-LA model, and contributes to the characterization of the SZ as part of the natural barrier below the repository. The natural-barrier characterization provides evidence pertaining to the capability of the SZ to delay movement of radionuclides through the SZ to the accessible environment. This report also contributes to the technical basis for the SZ transport-system description that is used in the LA, and provides evidence for the acceptance criteria specified in the Yucca Mountain Review Plan, Final Report (YMRP) (NRC 2003 [DIRS 163274]). The scope of this model report is limited to adaptation of an existing model (the SZ site-scale transport model) for the uncertainty analysis, as reflected in the SZ radionuclide breakthrough curves developed in this model report. Use of the SZ transport abstraction model and the SZ 1-D transport model in this report and in the TSPA-LA is subject to the limitations imposed by the assumptions listed in Section 5 of this report. Limitations in knowledge of specific parameter values are addressed in this report in the analysis of parameter uncertainties in Section 6.5.2. The radionuclide breakthrough curves generated for the SZ transport abstraction model are limited to a simulation period of 100,000 years, for present-day climatic conditions. This limits the time period that can be simulated with the TSPA-LA model when using these breakthrough curves for the SZ. Because the SZ breakthrough curves are scaled for higher groundwater flow rates under future climatic conditions (i.e., the time scale of the breakthrough curve is divided by the multiplier of groundwater flux), the time period that can be simulated with the TSPA-LA model would be significantly less than 100,000 years. If the glacial-transition climate state is applied for most of the simulation period in the TSPA-LA model, the SZ breakthrough curves would be scaled by a factor of approximately four, thereby limiting the TSPA-LA model simulation time to about 25,000 years. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 1-3 October 2004 Information on the correlation between distribution coefficients (Kds) used in the sampling of uncertain parameters for the SZ transport abstraction model and for the SZ 1-D transport model is provided in Table 4-3 and Table 6-8. The technical bases for correlations between distribution coefficients (or the lack thereof) are documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Section C1.2.1). Evaluation of uncertainty in horizontal anisotropy in permeability is summarized in Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is given in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6). Implementation of uncertainty in horizontal anisotropy in the SZ transport abstraction model and in the SZ 1-D transport model is discussed in Section 6.5.3.1 and Section 6.5.1.2, respectively. The impacts of spatial variability of parameters that affect radionuclide transport in the alluvium are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. The technical bases for uncertainty in distribution coefficients are documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix C). Information on geological uncertainty in the location of the contact between tuff and alluvium, and the consequent uncertainty in flow-path lengths in the alluvium, is presented in Section 6.5.2.2. This evaluation of uncertainty includes information from the Nye County early warning drilling program. The sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in the assessment of alternative conceptual models (ACMs) in Section 6.4. This model report is governed by Technical Work Plan For: Natural System – Saturated Zone Analysis and Model Report Integration (BSC 2004 [DIRS 171421], Work Package ARTM01). The work documented in this model report was conducted in accordance with the quality assurance (QA) procedure AP-SIII.10Q, Models. In this report, a unique six-digit numerical identifier (the Document Input Reference System (DIRS) number) is placed in the text after the reference callout (e.g., BSC 2001 [DIRS 163566]). The DIRS numbers are provided to assist readers to locate specific references in the DIRS database. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 1-4 October 2004 NOTE: This figure is a simplified representation of the flow of information among SZ reports. See the DIRS of each report for a complete listing of data and parameter inputs. This figure does not show inputs external to this suite of SZ reports. Figure 1-1. Generalized Flow of Information Among Reports Pertaining to Flow and Transport in the SZ Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 2-1 October 2004 2. QUALITY ASSURANCE Development of this model report and the supporting modeling activities is subject to the Yucca Mountain Project (YMP) QA program (BSC 2004 [DIRS 171421], Section 8, Work Package ARTM01). Approved QA procedures identified in the technical work plan (BSC 2004 [DIRS 171421], Section 4) have been used to conduct and document the activities described in this model report. The technical work plan also identifies the methods used to control the electronic management of data (BSC 2004 [DIRS 171421], Section 8). This model report provides values for hydrologic properties of the SZ as part of the natural barrier below the repository that is important to the demonstration of compliance with the postclosure performance objectives prescribed in 10 CFR 63.113 [DIRS 156605]. Therefore, it is classified on the Q-List (BSC 2004 [DIRS 168361]) as “SC” (Safety Category), reflecting its importance to waste isolation, as defined in AP-2.22Q, Classification Analyses and Maintenance of the Q-List [DIRS 170665]. The report contributes to the analysis and modeling data used to support postclosure performance assessment; the conclusions do not directly impact preclosureengineered features important to safety, as defined in AP-2.22Q [DIRS 170665]. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 2-2 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 3-1 October 2004 3. USE OF SOFTWARE 3.1 SOFTWARE TRACKED BY CONFIGURATION MANAGEMENT The computer software codes used directly in this model report are listed in Table 3-1. The qualification status of the software is noted in the Software Configuration Management database. All software was obtained from Software Configuration Management and is appropriate for the application, considering the simulation capabilities of the software, the range of inputs, and the functionality required by the computational task. Qualified codes were used only within the range of validation as required by LP-SI.11Q-BSC, Software Management. Table 3-1. Computer Software Used in This Model Report Software Name and Version (V) Software Tracking Number (STN) Description Computer Type, Platform, and Location Date Baselined FEHM (finite element heat and mass model) V2.20 [DIRS 161725] 10086-2.20- 00 This code is a finite-element heat- and mass-transport code that simulates nonisothermal, multiphase, multicomponent flow, and solute transport in porous media. Sun UltraSPARC - SunOS 5.7 Sandia National Laboratories 01/28/2003 GoldSim V7.50.100 [DIRS 161572] 10344- 7.50.100-00 This code is the modeling software used in the TSPA-LA. Probabilistic simulations are represented graphically in GoldSim. Dell OptiPlex GX260 Windows 2000 Professional 5.0.2195 Sandia National Laboratories 01/07/2003 GoldSim V8.01 SP4 [DIRS 169695] 10344- 8.01SP4-00 GoldSim (GS) is a Windows-2000–based program that provides the following general capabilities: • Quantitatively address the inherent variability. • Superimposes the occurrence and consequences of discrete events onto continuously varying systems. • Builds top-down models, dynamically links external programs or spreadsheets directly to the GS model. • Directly exchanges data between any ODBC-compliant database to the GS model. Computer: Master 06 Windows 2000 Advanced Server YMP Offices, Las Vegas, Building 3 04/01/2004 SZ_Pre V2.0 [DIRS 163281] 10914-2.0- 00 This software is an automated method for preparing the FEHM input files for the SZ site-scale flow and transport model a for use in TSPA-LA analyses. Sun UltraSPARC - SunOS 5.7 Sandia National Laboratories 04/28/2003 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 3-2 October 2004 Table 3-1. Computer Software Used in This Model Report (Continued) Software Name and Version (V) Software Tracking Number (STN) Description Computer Type, Platform, and Location Date Baselined SZ_Post V3.0 [DIRS 163571] 10915-3.0- 00 This software is used to translate the output files from the SZ site-scale model b into the format used by the SZ_Convolute software code. SZ_Post reads the output files from the FEHM software code and writes the breakthrough curve data for radionuclide transport in the SZ. Sun UltraSPARC - SunOS 5.7, Solaris 2.7 Sandia National Laboratories 05/22/2003 CORPSCON V 5.11.08 [DIRS 155082] 10547- 5.11.08-00 This software is used to convert coordinate data to the Universal Transverse Mercator (UTM) coordinate system. IBM Thinkpad 770Z - Windows NT 4.0 Sandia National Laboratories 08/27/2001 SZ_Convolute V2.2 [DIRS 163344] 10207-2.2- 00 This software is used to calculate SZ response curves based on unsaturated zone (UZ) radionuclide source terms, generic SZ responses, and climate scenarios for the YMP. Dell OptiPlex GX260 - Windows 2000 Professional 5.0.2195 Sandia National Laboratories 01/13/2003 a SZ site-scale flow and transport model refers to the SZ transport abstraction model. b SZ site-scale model refers to the SZ transport abstraction model. NOTE: The SZ_Convolute V2.2 software code (STN: 10207-2.2-00, SNL 2003 [DIRS 163344]) was used in the modeling and analyses in this report. SZ_Convolute V3.0 (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]) will be used for implementation of the SZ transport abstraction model in TSPA-LA. The summary description of the changes in the SZ_Convolute software code in the software baseline report between versions 2.2 and 3.0 gives no indication that the changes in functionality would have any impact on the model validation performed in this report. Software descriptions are taken directly from the software baseline report. FEHM=finite element heat and mass model; LA=license application; ODBC=Open Database Connectivity; SZ=Saturated Zone; TSPA=Total System Performance Assessment; UZ=Unsaturated Zone; YMP=Yucca Mountain Project 3.2 EXEMPT SOFTWARE The commercially available software cited in this section is appropriate for use in this application, considering the functionality required for the computational tasks. These software products were used primarily for plotting of graphs and the visualization of modeling results, and for simple spreadsheet operations. Different graphical software programs were used for different plotting requirements, as appropriate. The results were spot-checked by hand to ensure the results were correct. The computer that was used was a Dell OptiPlex GX1 with Pentium II processor, running Microsoft Windows 2000 Version 5.0.2195. The range of validation for Excel, Surfer, and Grapher is the set of real numbers. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 3-3 October 2004 Commercially available software: • Excel 2000: Used for simple spreadsheet calculations in support of plotting and visualization. The formulas, listing of inputs, listing of outputs, and other required information can be found in the following spreadsheets: Eff_MtrxDif_11.xls, bulkd_matr_eff_La.xls, and geonames.xls. These spreadsheets can be found in DTN (data tracking number): SN0306T0502103.006. • Surfer 8.0: Used for plotting and visualization. • Grapher 4.0: Used for plotting graphs. • Igor 4.07: Used for plotting graphs. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 3-4 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-1 October 2004 4. INPUTS 4.1 DIRECT INPUT All data, parameters, and other model inputs documented in Section 4.1 are used as direct inputs to the analyses of parameter uncertainty and/or the SZ transport abstraction model and SZ 1-D transport model. 4.1.1 Data and Other Model Inputs The data providing input for the development of parameters used in the models documented in this report are identified in Table 4-1. These input data are considered appropriate for the development of uncertain parameters for the SZ transport abstraction model and the SZ 1-D transport model, considering the processes being simulated and the geological material in the model domain. The data that are used as direct input to the models developed in this report are the best relevant qualified data because they are taken from the Yucca Mountain site and region. Where available and appropriate, nonqualified data are used to corroborate those data that are used as direct input (see Section 6.5.2). Table 4-1. Direct Inputs Data Name Originating Report DTN Matrix Porosity in the Volcanic Units (HFM Units 15-8) MDL-NBS-GS-000004 (HFM Units 15-13, 10-8) (BSC 2004 [DIRS 170032]) OFR 94-469 (Buesch et al. 1996 [DIRS 100106]); Flint 1998 [DIRS 100033]; OFR 94-460 (Moyer and Geslin 1995 [DIRS 101269]); (HFM Units 12 and 11) TDR-NBS-HS-000014 (BSC 2001 [DIRS 163566]) TDR-NBS-GS-000020, BSC 2001 [DIRS 163479] (HFM Units 12 and 11) SN0004T0501399.003 [DIRS 155045] (HFM Units 15-13, 10-8) MO0109HYMXPROP.001 [DIRS 155989] (HFM Units 12 and 11) MO0010CPORGLOG.002 [DIRS 155229] (HFM Units 12 and 11) Effective Porosity Alluvium Bedinger, et al. 1989 [DIRS 129676], p. A18, Table 1 (HFM Units 19 and 7) EDCON 2000 [DIRS 154704] (HFM Units 19 and 7) Burbey and Wheatcraft 1986 [DIRS 129679] (HFM Units 19 and 7) DOE (U. S. Department of Energy) 1997 [DIRS 103021], Table 8-2, p. 8-6, Table 8-1 p. 8-5 (HFM Units 19 and 7) MO0105HCONEPOR.000 [DIRS 155044] (HFM Units 19 and 7) MO0105GPLOG19D.000 [DIRS 163480] (HFM Units 19 and 7) Burbey and Wheatcraft 1986 [DIRS 129679] is an outside source of direct input (see table note). (HFM Units 19 and 7) DOE 1997 [DIRS 103021] is an outside source of direct input (see table note). (HFM Units 19 and 7) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-2 October 2004 Table 4-1. Direct Inputs (Continued) Data Name Originating Report DTN Effective Porosity in the Other Units Bedinger, et al. 1989 DIRS 129676] (HFM Units, 18, 17, 16, 6-2, 1) MO0105HCONEPOR.000 [DIRS 155044] (HFM Units, 18, 17, 16, 6-2, 1) Bulk Density in the Volcanic Units MDL-NBS-GS-000004 (HFM Units 15-13, 10-8) (BSC 2004 [DIRS 170032]) OFR 94-469 (Buesch et al. 1996 [DIRS 100106]); Flint 1998 [DIRS 100033]; OFR 94-460 (Moyer and Geslin 1995 [DIRS 101269]), (HFM Units 12, 11, and 9) TDR-NBS-HS-000014, (BSC 2001 [DIRS 163566]) TDR-NBS-GS-000020, BSC 2001 [DIRS 163479] (HFM Units 17, 12, 11, 6-2) SN0004T0501399.002 [DIRS 155046] (HFM Units 15-13, 10, 8) SN0004T0501399.003 [DIRS 155045] (HFM Units 15-13, 10-8) MO0109HYMXPROP.001 [DIRS 155989] (HFM Units 12, 11, and 9) MO0010CPORGLOG.002 [DIRS 155229] (HFM Units 17, 12, and 11, 6-2) Effective Diffusion Coefficient BSC 2001 [DIRS 163566] (HFM Units 8-15) MO0109HYMXPROP.001 [DIRS 155989] (HFM Units 8-15) Bulk Density - Alluvium EDCON 2000 [DIRS 154704] (HFM Units 19 and 7) MO0105GPLOG19D.000 [DIRS 163480] (HFM Units 19 and 7) Flowing Interval Porosity in the Volcanic Units BSC 2004 [DIRS 170038], Section 6.1.3 (HFM Units 8-15) BSC 2004 [DIRS 170010] DOE 1997 [DIRS 103021], p. 5-14 (HFM Units 8-15) LB0205REVUZPRP.001 [DIRS 159525] (HFM Units 8-15) LA0303PR831231.005 [DIRS 166259] GS031008312315.002 [DIRS 166261] DOE 1997 [DIRS 103021] is an outside source of direct input (see table note). (HFM Units 8-15) Lithostratigraphy in Wells EWDP- 10SA and EWDP-22SA N/A GS030108314211.001 [DIRS 163483] Coordinates of Well Locations and Depth to Water Table USGS 2001 [DIRS 157611] GS010908312332.002 [DIRS 163555] Uncertainty in Groundwater Specific Discharge CRWMS M&O 1998 [DIRS 100353] MO0003SZFWTEEP.000 [DIRS 148744] Uncertainty in Groundwater Specific Discharge at the Alluvial Tracer Complex (ATC) BSC 2004 [DIRS 170010] LA0303PR831231.002 [DIRS 163561] UZ Site-Scale Model Flow Fields – Infiltration for Climate States BSC 2004 [DIRS 169861] LB03023DSSCP9I.001 [DIRS 163044] Gross Alpha Concentrations in Groundwater CRWMS M&O 1999 [DIRS 150420], Section 3.2.1, Table 3 MO9904RWSJJS98.000 [DIRS 165866] NOTE: The column containing the originating report is provided for reference only. The direct source of the data used in this report is listed in the DTN column. The given HFM Unit numbers refer to the unit definitions in Table 6-9. DTN=Data Tracking Number; HFM=hydrogeologic framework model; UZ=Unsaturated Zone Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-3 October 2004 The data on effective porosity in alluvium from the Burbey and Wheatcraft report (1986 DIRS 129679]) are obtained from an outside source and are not established fact. The suitability of these data is justified for this specific application, as outlined in AP-SIII.10Q, Section 5.2.1. U. S. Department of Energy (DOE) directed the collection of these data as part of the investigation of contaminant migration from underground nuclear testing at the Nevada Test Site (NTS). The porosity data in the alluvium were collected in Frenchman Flat from below the water table. That these data come from an area near Yucca Mountain and in a similar physiographic and hydrogeologic setting provides confidence that the data demonstrate the property of interest. The model of contaminant transport presented in the 1986 Burbey and Wheatcraft report was calibrated with measurements of contaminant concentrations during pumping near the Cambric nuclear test and no changes to the values of porosity were suggested as a result of the calibration process. This supports the values of porosity measured in the alluvium at the site. These porosity data generally are corroborated by comparison with other data sources, as discussed in Section 6.5.2.3, and fall within the total range of estimates from other sources. The data on effective porosity in alluvium from Regional Groundwater Flow and Tritium Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, Nevada (DOE 1997 DIRS 103021]) are obtained from an outside source and are not established fact. The suitability of these data is justified for this specific application, as outlined in AP-SIII.10Q. DOE directed the analyses of these data as part of a study of regional groundwater flow and tritium migration at the NTS. That these data come from an area near Yucca Mountain and in a similar hydrogeologic setting provides confidence that the data demonstrate the property of interest. The data on porosity in alluvium presented in the 1997 DOE report are based on a statistical analysis of measurements by several different methods and at different locations in the NTS. The average value of porosity is corroborated by comparison with another source in Table 8-2 of the 1997 DOE report, and the comparison for porosity in alluvium is very close. These porosity data generally are corroborated by comparison with other data sources, as discussed in Section 6.5.2.3, and fall within the total range of estimates from other sources. The data on fracture spacing and aperture from Regional Groundwater Flow and Tritium Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, Nevada (DOE 1997 [DIRS 103021]) used to estimate flowing interval porosity are obtained from an outside source and are not established fact. The suitability of these data is justified for this specific application, as outlined in AP-SIII.10Q. DOE directed the analyses of these data as part of a study of regional groundwater flow and tritium migration at the NTS. The data used in the 1997 DOE study were from seven cores from Pahute Mesa on the NTS, and were taken for volcanic rocks that are analogous to the volcanic units in the SZ at Yucca Mountain, providing confidence that the data demonstrate the property of interest. The resulting range of estimated fracture porosity is broad and generally is corroborated by comparison to other sources of information in Section 5.5.2.2 of the 1997 DOE report. These data also are corroborated by comparison to estimates of fracture porosity in Total-System Performance Assessment for Yucca Mountain – SNL Second Iteration (TSPA-1993) (Wilson et al. 1994 [DIRS 100191], Volume 1, Table 7-19), as described in Section 6.5.2.5 of this report. Uncertainty associated with the model, including development of parameter values and their implementation in the SZ transport abstraction model and the SZ 1-D transport model, is Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-4 October 2004 discussed in Sections 6.5.1 and 6.5.2. Parameter uncertainties are addressed by providing ranges, probability distributions, and bounding assumptions, as appropriate for each parameter. Other model, analysis, design, and regulatory input information is listed in Table 4-2. Table 4-2. Other Direct Inputs (Model, Analysis, Design, and Regulations) Input Name Input Description DTN/IED Site-Scale Saturated Zone Transport Model The SZ site-scale model that forms the basis of the SZ transport abstraction model. LA0306SK831231.001 [DIRS 164362] Matrix Diffusion Type Curves The analytical solution type curves for matrix diffusion in fractured media. These type curves are used in the particletracking algorithm of the FEHM software to simulate radionuclide transport in fractured porous media. LA0302RP831228.001 [DIRS 163557] Repository Design The coordinates of the outline of the repository design are used in defining the SZ source regions at the water table below the repository. 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]) Boundary of Accessible Environment Latitude of the accessible environment, as defined by regulation. 10 CFR 63.302 [DIRS 156605] (regulatory input, technical information, no DTN) DTN=Data Tracking Number; FEHM=finite element heat and mass model; IED=information exchange drawing; SZ=Saturated Zone 4.1.2 Parameters and Parameter Uncertainty The parameters and parameter uncertainties from external sources used directly in the modeling documented in this report are shown in Table 4-3. Parameters are those variables that are used as direct inputs to the models documented in this report. The input parameters are considered appropriate as direct input to the SZ transport abstraction model and the SZ 1-D transport model. The data used in this report are appropriate for this study because they represent various parameter properties of the SZ at Yucca Mountain. Table 4-3. Direct Input (Parameter Uncertainty) Parameter Name Parameter Source DTN Value(s) Units Parameter Type KDNPVO (neptunium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF (cumulative distribution function): Probability Value 0.0 0.0 0.05 0.99 0.90 1.83 1.0 6.0 mL/g Distribution KDNPAL (neptunium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 1.8 0.05 4.0 0.95 8.7 1.0 13.0 mL/g Distribution Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-5 October 2004 Table 4-3. Direct Input (Parameter Uncertainty) (Continued) Parameter Name Parameter Source DTN Value(s) Units Parameter Type KDSRVO (strontium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 20. Maximum 400. mL/g Distribution KDSRAL (strontium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 20. Maximum 400. mL/g Distribution KDUVO (uranium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 0.0 0.05 5.39 0.95 8.16 1.0 20.0 mL/g Distribution KDUAL (uranium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 1.7 0.05 2.9 0.95 6.3 1.0 8.9 mL/g Distribution KDRAVO (radium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 100. Maximum 1000. mL/g Distribution KDRAAL (radium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 100. Maximum 1000. mL/g Distribution KD_Pu_Vo (plutonium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 10. 0.25 89.9 0.95 129.87 1.0 300. mL/g Distribution KD_Pu_Al (plutonium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Beta: Mean 100. Standard Deviation 15. Minimum 50. Maximum 300. mL/g Distribution Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-6 October 2004 Table 4-3. Direct Input (Parameter Uncertainty) (Continued) Parameter Name Parameter Source DTN Value(s) Units Parameter Type KD_Am_Vo (americium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. mL/g Distribution KD_Am_Al (americium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. mL/g Distribution KD_Cs_Vo (cesium sorption coefficient in volcanic units) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 100. 0.05 3000.59 1.0 6782.92 mL/g Distribution KD_Cs_Al (cesium sorption coefficient in alluvium) BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 728. Standard Deviation 464. Minimum 100. Maximum 1000. mL/g Distribution FISVO (flowing interval spacing in the volcanic units) BSC 2004 [DIRS 170014] SN9907T0571599.001 [DIRS 122261] CDF: (Log10-transformed) Probability Value 0.0 0.087 0.05 0.588 0.25 1.00 0.50 1.29 0.75 1.58 0.95 1.90 1.0 2.62 m Distribution CORAL (colloid retardation factor in the alluvium) BSC 2004 [DIRS 170006] LA0303HV831352.004 [DIRS 163559] CDF : (Log10-transformed) Probability Value 0.0 0.903 0.331 0.904 0.50 1.531 1.0 3.715 N/A Distribution CORVO (colloid retardation factor in the volcanic units) BSC 2004 [DIRS 170006] LA0303HV831352.002 [DIRS 163558] CDF : (Log10-transformed) Probability Value 0.0 0.778 0.15 0.779 0.25 1.010 0.50 1.415 0.80 1.778 1.0 2.903 N/A Distribution Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-7 October 2004 Table 4-3. Direct Input (Parameter Uncertainty) (Continued) Parameter Name Parameter Source DTN Value(s) Units Parameter Type HAVO (ratio of horizontal anisotropy in permeability) BSC 2004 [DIRS 170010] SN0302T0502203.001 [DIRS 163563] CDF : Probability Value 0.0 0.05 0.10 1.0 0.60 5. 1.0 20. N/A Distribution LDISP (longitudinal dispersivity) CRWMS M&O 1998 [DIRS 100353] MO0003SZFWTEEP.000 [DIRS 148744] Truncated Normal: (Log10- transformed) Mean 2.0 Standard Deviation 0.75 m Distribution Kd_Pu_Col (plutonium sorption coefficient onto colloids) BSC 2004 [DIRS 170025] SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e3 0.04 5.e3 0.12 1.e4 0.37 5.e4 0.57 1.e5 0.92 5.e5 1.0 1.e6 mL/g Distribution Kd_Am_Col (americium sorption coefficient onto colloids) BSC 2004 [DIRS 170025] SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e4 0.07 5.e4 0.17 1.e5 0.40 5.e5 0.60 1.e6 0.92 5.e6 1.0 1.e7 mL/g Distribution Kd_Cs_Col (cesium sorption coefficient onto colloids) BSC 2004 [DIRS 170025] SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e2 0.2 5.e2 0.45 1.e3 0.95 5.e3 1.0 1.e4 mL/g Distribution Conc_Col (groundwater concentration of colloids) BSC 2004 [DIRS 170025] SN0306T0504103.005 [DIRS 164132] CDF: (Log10-transformed) Probability Value 0.0 -9.0 0.50 -7.0 0.75 -6.0 0.90 -5.0 0.98 -4.3 1.0 -3.7 g/mL Distribution Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-8 October 2004 Table 4-3. Direct Input (Parameter Uncertainty) (Continued) Parameter Name Parameter Source DTN Value(s) Units Parameter Type Correlation coefficient for U Kd in volcanic units and alluvium BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] 0.75 N/A Single Value Correlation coefficient for Np Kd in volcanic units and alluvium BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] 0.75 N/A Single Value Correlation coefficient for Pu Kd in volcanic units and alluvium BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] 0.50 N/A Single Value Correlation coefficient for U Kd and Np Kd BSC 2004 [DIRS 170036] LA0310AM831341.002 [DIRS 165891] 0.50 N/A Single Value NOTE: DTN: MO0003SZFWTEEP.000 [DIRS 148744] contains qualified data from an expert elicitation that was determined to comply with expert elicitation procedure AP-AC.1Q, which is consistent with the branch technical position on expert elicitation, NUREG-1563 (Kotra et al. 1996 [DIRS 100909]). 4.2 CRITERIA The general requirements to be satisfied by the TSPA-LA are stated in 10 CFR 63.114 (10 CFR 63 [DIRS 156605]). Technical requirements to be satisfied by the TSPA-LA are identified in the Yucca Mountain Project Requirements Document (Canori and Leitner 2003 [DIRS 166275], Section 3). The acceptance criteria that will be used by the U.S. Nuclear Regulatory Commission (NRC) to determine whether the technical requirements have been met are identified in the Yucca Mountain Review Plan, Final Report (YMRP) (NRC 2003 [DIRS 163274]). The pertinent requirements and criteria for this report are summarized in Table 4-4. Table 4-4. Project Requirements for This Model Report Requirement Numbera Requirement Titlea 10 CFR 63 Link YMRP Acceptance Criteriab PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 [DIRS 156605] 2.2.1.3.8.3, criteria 1 to 5; 2.2.1.3.9.3, criteria 1 to 5 a Canori and Leitner 2003 [DIRS 166275]. b NRC 2003 [DIRS 163274]. YMRP=Yucca Mountain Review Plan In this section, the acceptance criteria identified in Sections 2.2.1.3.8.3, and 2.2.1.3.9.3 of the YMRP (NRC 2003 [DIRS 163274]) are given below. In cases where subsidiary criteria are listed in the YMRP for a given criterion, only the subsidiary criteria addressed by this model report are listed below. Where a subcriterion includes several components, only some of those Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-9 October 2004 components may be addressed. How these components are addressed is summarized in Section 8.3 of this report. Acceptance criteria from Section 2.2.1.3.8, Flow Paths in the Saturated Zone Acceptance Criterion 1, System Description and Model Integration are Adequate: (1) Total system performance assessment adequately incorporates important design features, physical phenomena, and couplings, and uses consistent and appropriate assumptions, throughout the flow paths in the SZ abstraction process. (2) The description of the aspects of hydrology, geology, geochemistry, design features, physical phenomena, and couplings that may affect flow paths in the SZ is adequate. Conditions and assumptions in the abstraction of flow paths in the SZ are readily identified and consistent with the body of data presented in the description. (3) The abstraction of flow paths in the SZ uses assumptions, technical bases, data, and models that are appropriate and consistent with other related DOE abstractions. For example, the assumptions used for flow paths in the SZ are consistent with the total system performance assessment abstraction of representative volume (Section 2.2.1.3.12 of NRC 2003 [DIRS 163274]). The descriptions and technical bases provide transparent and traceable support for the abstraction of flow paths in the SZ. (4) Boundary and initial conditions used in the total system performance assessment abstraction of flow paths in the SZ are propagated throughout its abstraction approaches. For example, abstractions are based on initial and boundary conditions consistent with site-scale modeling and regional models of the Death Valley groundwater flow system. (5) Sufficient data and technical bases to assess the extent to which features, events, and processes have been included in this abstraction are provided. (7) Long-term climate change, based on known patterns of climatic cycles during the Quaternary period, particularly the last 500,000 years, and other paleoclimate data, are adequately evaluated. (9) The impact of the expected water table rise on potentiometric heads and flow directions, and consequently on repository performance, is adequately considered. (10) Guidance in NUREG-1297 (Altman et al. 1988 [DIRS 103597]) and NUREG-1298 (Altman et al. 1988 [DIRS 103750]) or other acceptable approaches for peer review and data qualification is followed. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-10 October 2004 Acceptance Criterion 2, Data are Sufficient for Model Justification: (1) Geological, hydrological, and geochemical values used in the license application to evaluate flow paths in the SZ are adequately justified. Adequate descriptions of how the data were used, interpreted, and appropriately synthesized into the parameters are provided. (3) Data on the geology, hydrology, and geochemistry of the SZ used in the total system performance assessment abstraction are based on appropriate techniques. These techniques may include laboratory experiments, site-specific field measurements, natural analogue research, and processlevel modeling studies. As appropriate, sensitivity or uncertainty analyses used to support the U.S. Department of Energy total system performance assessment abstraction are adequate to determine the possible need for additional data. Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the Model Abstraction: (1) Models use parameter values, assumed ranges, probability distributions, and/or bounding assumptions that are technically defensible, and reasonably account for uncertainties and variabilities, and do not result in an under-representation of the risk estimate. (2) Uncertainty is appropriately incorporated in model abstractions of hydrologic effects of climate change, based on a reasonably complete search of paleoclimate data. (3) Uncertainty is adequately represented in parameter development for conceptual models, process-level models, and ACMs considered in developing the abstraction of flow paths in the SZ. This may be done either through sensitivity analyses or use of conservative limits. For example, sensitivity analyses and/or similar analyses are sufficient to identify saturated zone flow parameters that are expected to significantly affect the abstraction model outcome. (4) Where sufficient data do not exist, the definition of parameter values and conceptual models is based on appropriate use of expert elicitation, conducted in accordance with NUREG-1563 (Kotra et al. 1996 [DIRS 100909]). If other approaches are used, the U.S. Department of Energy adequately justifies their uses. Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the Model Abstraction: (1) Alternative modeling approaches of features, events, and processes are considered and are consistent with available data and current scientific understanding, and the results and limitations are appropriately considered in the abstraction. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-11 October 2004 (2) Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed. For example, uncertainty in data interpretations is considered by analyzing reasonable conceptual flow models that are supported by site data, or by demonstrating through sensitivity studies that the uncertainties have little impact on repository performance. (3) Consideration of conceptual model uncertainty is consistent with available site characterization data, laboratory experiments, field measurements, natural analog information and process-level modeling studies; and the treatment of conceptual model uncertainty does not result in an under-representation of the risk estimate; and (4) Appropriate alternative modeling approaches are consistent with available data and current scientific knowledge and appropriately consider their results and limitations, using tests and analyses that are sensitive to the processes modeled. Acceptance Criterion 5, Model Abstraction Output Is Supported by Objective Comparisons: (1) The models implemented in this total system performance assessment abstraction provide results consistent with output from detailed process-level models and/or empirical observations (laboratory and field testing and/or natural analogues). (2) Outputs of flow paths in the SZ abstractions reasonably produce or bound the results of corresponding process-level models, empirical observations, or both. (3) Well-documented procedures that have been accepted by the scientific community for the construction and testing of the mathematical and numerical models are used to simulate flow paths in the SZ. (4) Sensitivity analyses or bounding analyses are provided to support the abstraction of flow paths in the saturated zone that cover ranges consistent with site data, field or laboratory experiments and tests, and natural analog research. Acceptance criteria from Section 2.2.1.3.9, Radionuclide Transport in the Saturated Zone Acceptance Criterion 1, System Description and Model Integration are Adequate: (1) Total system performance assessment adequately incorporates important design features, physical phenomena, and couplings, and uses consistent and appropriate assumptions throughout the radionuclide transport in the saturated zone abstraction process. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-12 October 2004 (2) The description of the aspects of hydrology, geology, geochemistry, design features, physical phenomena, and couplings that may affect radionuclide transport in the SZ is adequate. For example, the description includes changes into transport properties in the saturated zone, from water-rock interaction. Conditions and assumptions in the abstraction of radionuclide transport in the saturated zone are readily identified, and consistent with the body of data presented in the description. (3) The abstraction of radionuclide transport in the SZ uses assumptions, technical bases, data, and models that are appropriate and consistent with other related DOE abstractions. For example, assumptions used for radionuclide transport in the saturated zone are consistent with the total system performance assessment abstractions of radionuclide release rates and solubility limits, and flow paths in the saturated zone (Sections 2.2.1.3.4 and 2.2.1.3.8 of the Yucca Mountain Review Plan, respectively). The descriptions and technical bases provide transparent and traceable support for the abstraction of radionuclide transport in the saturated zone. (4) Boundary and initial conditions used in the abstraction of radionuclide transport in the SZ are propagated throughout its abstraction approaches. For example, the conditions and assumptions used to generate transport parameter values are consistent with other geological, hydrological, and geochemical conditions in the total system performance assessment abstraction of the saturated zone. (5) Sufficient data and technical bases for the inclusion of features, events, and processes related to radionuclide transport in the SZ in the total system performance assessment abstraction are provided. (6) Guidance in NUREG-1297 (Altman et al. 1988 [DIRS 103597]) and NUREG-1298 (Altman et al. 1988 [DIRS 103750]) or other acceptable approaches for peer review and data qualification is followed. Acceptance Criterion 2, Data are Sufficient for Model Justification: (1) Geological, hydrological, and geochemical values used in the license application are adequately justified (e.g., flow path lengths, sorption coefficients, retardation factors, colloid concentrations, etc.). Adequate descriptions of how the data were used, interpreted, and appropriately synthesized into the parameters are provided (2) Sufficient data have been collected on the characteristics of the natural system toestablish initial and boundary conditions for the total system performance assessmentabstraction of radionuclide transport in the saturated zone Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-13 October 2004 Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the Model Abstraction: (1) Models use parameter values, assumed ranges, probability distributions, and/or bounding assumptions that are technically defensible, and reasonably account for uncertainties and variabilities, and do not result in an under-representation of the risk estimate. (4) Parameter values for processes, such as matrix diffusion, dispersion, and groundwater mixing, are based on reasonable assumptions about climate, aquifer properties, and groundwater volumetric fluxes (Section 2.2.1.3.8 of NRC 2003 [DIRS 163274]). (5) Uncertainty is adequately represented in parameter development for conceptual models, process-level models, and ACMs considered in developing the abstraction of radionuclide transport in the SZ. This may be done either through sensitivity analyses or use of conservative limits. (6) Where sufficient data do not exist, the definition of parameter values and conceptual models is based on appropriate use of expert elicitation, conducted in accordance with NUREG-1563 (Kotra et al. 1996 [DIRS 100909]). If other approaches are used, the U.S. Department of Energy adequately justifies their use. Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the Model Abstraction: (1) Alternative modeling approaches of features, events, and processes are considered and are consistent with available data and current scientific understanding, and the results and limitations are appropriately considered in the abstraction. (2) Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed. (3) Consideration of conceptual model uncertainty is consistent with available site characterization data, laboratory experiments, field measurements, natural analog information and process-level modeling studies; and the treatment of conceptual model uncertainty does not result in an under-representation of the risk estimate; and (4) Appropriate alternative modeling approaches are consistent with available data and current scientific knowledge and appropriately consider their results and limitations, using tests and analyses that are sensitive to the processes modeled. For example, for radionuclide transport through fractures, the U.S. Department of Energy adequately considers alternative modeling approaches to develop its understanding of fracture distributions and ranges of fracture flow and transport properties in the saturated zone. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 4-14 October 2004 Acceptance Criterion 5, Model Abstraction Output is Supported by Objective Comparisons: (1) The models implemented in this total system performance assessment abstraction provide results consistent with output from detailed process-level models and/or empirical observations (laboratory and field testing and/or natural analogs); (2) Outputs of radionuclide transport in the SZ abstractions reasonably produce or bound the results of coresponding process-level models, empirical observations, or both. The U.S. Department of Energyabstracted models for radionuclide transport in the saturated zone are based on the same hydrological, geological, and geochemical assumptions and approximations shown to be appropriate for closely analogous natural systems or laboratory experimental systems. (3) Well-documented procedures that have been accepted by the scientific community for the construction and testing of the mathematical and numerical models are used to simulate radionuclide transport through the SZ. (4) Sensitivity analyses or bounding analyses are provided, to support the total system performance assessment abstraction of radionuclide transport in the SZ, that cover ranges consistent with site data, field or laboratory experiments and tests, and natural analogue research. 4.3 CODES, STANDARDS, AND REGULATIONS No codes, standards, or regulations other than those identified in the Project Requirements Document (Canori and Leitner 2003 [DIRS 166275], Table 2-3) and determined to be applicable (Table 4-4) were used in this analysis. Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 5-1 October 2004 5. ASSUMPTIONS Several types of assumptions pertain to model development. The assumptions listed in this section of the report are restricted to those that meet the definition given in the QA procedure AP-SIII.10Q, Models. This definition states that an assumption is “a statement or proposition that is taken to be true or representative in the absence of direct confirming data or evidence.” Additional technical modeling bases (assumptions) pertaining to the modeling framework are documented in Section 6 of this report (primarily in Section 6.3). 1. For the transport of radionuclides irreversibly attached to colloids in the SZ, it is assumed that radionuclides will not desorb from colloids. This assumption is carried forward from the scientific analysis report Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.3) and is consistent with the mineralogic characteristics of colloids from the degradation of the glass waste form. This assumption is also conservative with regard to repository performance due to the comparatively high mobility of colloids in the SZ relative to the sorptive characteristics of the radionuclides (Pu and Am) that are subject to colloid-facilitated transport. This assumption is used in Sections 6.3.1, 6.3.2, 6.5.1, and 6.5.2.11. This assumption needs no further confirmation, given that it is a bounding assumption that maximizes the rate of radionuclide migration in the SZ. 2. Colloids with irreversibly attached radionuclides are assumed to be subject to attachment and detachment to mineral grains in the aquifer, but not to be subject to permanent filtration from the groundwater of the SZ. This assumption is carried forward from the scientific analysis report Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.3). The kinetically controlled attachment and detachment of colloids in the aquifer is consistent with tracer testing in the SZ using microspheres. The permanent filtration of colloids in the SZ has not been demonstrated by field-testing, although this process can occur. This assumption’s alternative, in which permanent filtration were simulated to occur, would lead to significant attenuation of the migration of radionuclides irreversibly attached to colloids. This assumption is used in Sections 6.3.1, 6.3.2, 6.5.1, and 6.5.2.11. This assumption needs no further confirmation, given that it is a bounding assumption that maximizes the migration of radionuclides in the SZ. 3. The assumption is made that the average concentration of radionuclides in the groundwater supply of the hypothetical community in which the reasonably maximally exposed individual (RMEI) resides is an appropriate estimate of radionuclide concentration for the calculation of radiological dose. This assumption applies to the calculation of radionuclide concentrations for evaluation of compliance with 10 CFR 63.332 (10 CFR 63 [DIRS 156605]) and with groundwater protection in 10 CFR 63.331. Realistically, the concentrations of radionuclides encountered by wells in the hypothetical community in which the RMEI resides would vary from location to location within the contaminant plume in the SZ. However, radionuclide transfer processes within the biosphere (e.g., redistribution of agricultural products, communal water supplies, etc.) would tend to average the overall dose received by the population of the community in which the RMEI resides. This assumption is used in Section 6.3.3. This assumption needs no further confirmation, given that there is a regulatory basis for Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 5-2 October 2004 this approach to calculating average concentrations of radionuclides and radiological dose in 10 CFR 63.332 (10 CFR 63 [DIRS 156605]). 4. The assumption is made that the horizontal anisotropy in permeability applies to the fractured and faulted volcanic units of the SZ system along the groundwater flow path from the repository to the south and east of Yucca Mountain. This assumption is carried forward from the scientific analysis report Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6). The inferred flow path from beneath the repository extends to the south and east. This is the area in which pumping tests were conducted at the C-holes well complex (BSC 2004 [DIRS 170010]), from which horizontal anisotropy was inferred. Given the conceptual basis for the anisotropy model, it is appropriate to apply anisotropy only to those hydrogeologic units that are dominated by groundwater flow in fractures because it is the preferential orientations of open fractures that impart anisotropy in the system. This assumption is used in Section 6.5.2.10. This assumption needs no further confirmation, given the wide range of uncertainty in horizontal anisotropy used in the SZ transport abstraction model. 5. It is assumed that the change in groundwater flow in the SZ from one climatic state to another occurs rapidly and is approximated by an instantaneous shift from one steady-state flow condition to another steady-state flow condition. In actuality, even an extremely rapid shift in climatic conditions would result in a transient response of the SZ flow system because of changes in groundwater storage associated with water table rise or fall and because of the response time in the unsaturated zone (UZ) flow system. The assumption of instantaneous shifts to new steady-state conditions would tend to overestimate the rate of radionuclide transport in the TSPA-LA calculations. The progression of climate states in the 10,000 years following repository closure is anticipated to be from drier to wetter climatic conditions and thus from slower to more rapid groundwater flow in the SZ. By assuming an instantaneous shift to higher groundwater flux in the SZ, the simulations tend to overestimate the radionuclide transport velocities during the period of transition from drier conditions to wetter conditions. This assumption is used in Section 6.5. This assumption needs no further confirmation, given that this simplified approach underestimates the transport times for radionuclides in the SZ and is thus pessimistic with regard to repository performance. 6. Groundwater flow pathways in the SZ from beneath the repository to the accessible environment are assumed not to be significantly altered for wetter climatic states. Scaling of present-day groundwater flux and radionuclide mass breakthrough curves by a proportionality factor implies that only the groundwater velocities are changed in the SZ system in response to climate change. This assumption is supported by the observation that the shape of the simulated potentiometric surface downgradient from Yucca Mountain remains essentially the same under glacial-transition climatic conditions in simulations using the Death Valley regional flow model (D’Agnese et al. 1999 [DIRS 120425], p. 30). Water table rise directly beneath the repository under wetter climatic conditions would tend to place volcanic units higher in the stratigraphic sequence at or just below the water table. These higher volcanic units (Prow Pass Tuff and Calico Hills Formation) have lower values of permeability than the underlying Bullfrog Tuff. This approximation of climate change with unaltered SZ flow paths is Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 5-3 October 2004 shown to underestimate radionuclide transport times in sensitivity studies documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix E). This assumption is used in Section 6.5. This assumption needs no further confirmation, given that this simplified approach tends to underestimate the transport times for radionuclides in the SZ. Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 5-4 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 6-1 October 2004 6. MODEL DISCUSSION 6.1 MODELING OBJECTIVES The primary objective of the SZ transport abstraction model and the SZ 1-D transport model is to provide a method of simulating radionuclide transport in the SZ for use in the TSPA-LA model of repository performance. Analyses of parameter uncertainty and multiple realizations of the SZ system using the SZ transport abstraction model constitute an assessment of uncertainty in the SZ system for direct implementation in the TSPA-LA model. Model uncertainty is addressed by generating a suite of radionuclide breakthrough curves based on the multiple realizations of the SZ system. The general approach to modeling radionuclide migration and the assessment of uncertainty in the SZ is also described by Arnold et al. in “Radionuclide Transport Simulation and Uncertainty Analyses with the Saturated-Zone Site-Scale Model at Yucca Mountain, Nevada” (2003 [DIRS 163857]). The objective of the SZ 1-D transport model is to provide a simplified, yet accurate, representation of SZ transport for the simulation of four radionuclide decay chains for implementation with the TSPA-LA model. Figure 1-1 shows the flow of information among the SZ reports used in the development of the SZ transport abstraction model and the SZ 1-D transport model as outputs from this report. In the TSPA-LA analyses, the convolution integral method is used by the SZ transport abstraction model to determine the radionuclide mass flux at the SZ/biosphere interface, 18 km downgradient of the repository at 36°40'13.6661” north latitude (10 CFR 63.302 [DIRS 156605]) as a function of the transient radionuclide mass flux at the water table beneath the repository. This computationally efficient method combines information about the unit response of the system, as simulated by the SZ transport abstraction model, with the radionuclide source history from the UZ, to calculate transient system behavior. The fundamental concepts of the convolution integral method, as applied to solute transport in groundwater, are presented by Jury et al. (1986 [DIRS 164314]), in which the method is called the transfer function model. The most important assumptions of the convolution method are linear system behavior and steadystate flow conditions in the SZ. The SZ 1-D transport model is used in the TSPA-LA analyses for the purpose of simulating radioactive decay and ingrowth for four decay chains. This simplified model is required because the radionuclide transport methodology used in the SZ transport abstraction model is not capable of simulating ingrowth by radioactive decay. Although it is not anticipated that the decay products generated from these radioactive decay chains during transport in the SZ are significant contributors to the total radiological dose, regulations concerning groundwater protection contained in 10 CFR 63.331 (10 CFR 63 [DIRS 156605]) require explicit analysis of the total concentrations of 226Ra plus 228Ra, gross alpha emitters, and beta plus photon emitters in the water supply of the RMEI. Consequently, only the results for decay product-radionuclides from the SZ 1-D transport model are input to the TSPA-LA simulations. Although transport of the parent radionuclides is also included in the SZ 1-D transport model, the results for parent-radionuclides input to the TSPA-LA simulations are those derived from the SZ transport abstraction model. The SZ 1-D transport model for TSPA-LA differs in implementation from the SZ transport abstraction model in that it is constructed directly within the GoldSim V7.50.100 software code (GoldSim V7.50.100, STN: 10344-7.50.100-00 [DIRS 161572]) in the TSPA-LA model. It should be noted that transport of the first-generation decay products in the Saturated Zone Flow and Transport Abstraction MDL-NBS-HS-0000021 REV 02 6-2 October 2004 four decay chains is simulated with the SZ transport abstraction model using a simplified method of inventory boosting, as described in Section 6.3.1. 6.2 FEATURES, EVENTS, AND PROCESSES FOR THIS MODEL REPORT As stipulated in Technical Work Plan For: Natural System - Saturated Zone Analysis Model Report Integration (BSC 2004 [DIRS 171421], Section 2.1.5) this model report addresses the SZ FEPs pertaining to the abstraction of SZ flow and transport that are included in the TSPA-LA model (Table 6-1). Table 6-1 provides a list of FEPs that are relevant to the models documented in this report, in accordance with their assignment in the LA FEP list (DTN: MO0407SEPFEPLA.000 ([DIRS 170760]). Specific reference to the various sections within this document where issues related to each FEP are addressed is provided in Table 6-1. The detailed discussions of these FEPs and their implementation in TSPA-LA are documented in the Features, Events, and Processes in SZ Flow and Transport (BSC 2004 [DIRS 170013]) report. Saturated zone FEPs that were excluded from the TSPA-LA modeling also are described in Features, Events, and Processes in SZ Flow and Transport. Table 6-1. Features, Events, and Processes Included in TSPA-LA and Relevant to This Model Report FEP No. FEP Name Sections Where Disposition is Supported FEP Topic Addressed in Other SZ Analysis or Model Reports 1.2.02.01.0A Fractures 6.5.2.1, 6.5.2.4, 6.5.2.5, 6.5.2.9, 6.5.2.10, 6.5.2.11, 6.5.2.12, 6.5.2.15 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170014] Corroboratingb—BSC 2004 [DIRS 170010] 1.2.02.02.0A Faults 6.3.1, 6.5.2.1, 6.5.2.10 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170037], BSC 2004 [DIRS 170008] Corroboratingb—BSC 2004 [DIRS 170010] 1.3.07.02.0A Water table rise affects SZ 5 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170009] 1.4.07.01.0A Water management activities 6.3.3, 6.7.2 Upstream Feedsa—BSC 2004 [DIRS 170009] 1.4.07.02.0A Wells 6.3.3 Upstream Feedsa—BSC 2004 [DIRS 170009] 2.2.03.01.0A Stratigraphy 6.5.2, 6.5.2.1, 6.5.2.2, 6.5.2.3, 6.5.2.6, 6.5.2.18, 6.5.2.19 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170008], BSC 2004 [DIRS 170037] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170014] 2.2.03.02.0A Rock properties of host rock and other units 6.5.2.1, 6.5.2.2, 6.5.2.3, 6.5.2.4, 6.5.2.5, 6.5.2.7, 6.5.2.8, 6.5.2.9, 6.5.2.10, 6.5.2.14, 6.5.2.15, 6.5.2.16, 6.5.2.17, 6.5.2.18, 6.5.2.19, 6.5.2.20 Upstream Feedsa—BSC 2004 [DIRS 170036] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170014], BSC 2004 [DIRS 170008] Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-3 October 2004 Table 6-1. Features, Events, and Processes Included in TSPA-LA and Relevant to This Model Report (Continued) FEP No. FEP Name Sections Where Disposition is Supported FEP Topic Addressed in Other SZ Analysis or Model Reports 2.2.07.12.0A Saturated groundwater flow in the geosphere 6.3, 6.5, 6.5.2.1, 6.5.2.10 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170037] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170037], BSC 2004 [DIRS 170014] 2.2.07.13.0A Water-conducting features in the SZ 6.5.2.1, 6.5.2.4, 6.5.2.5, 6.5.2.9, 6.5.2.10 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170037] Corroboratingb—BSC 2004 [DIRS 170014], BSC 2004 [DIRS 170010] 2.2.07.15.0A Advection and dispersion in the SZ 6.3, 6.5.2.1, 6.5.2.9, 6.5.2.10 Upstream Feedsa—BSC 2004 [DIRS 170036] Corroboratingb—BSC 2004 [DIRS 170010] 2.2.07.16.0A Dilution of radionuclides in groundwater 6.5.2.9, 6.7.2 Upstream Feedsa—BSC 2004 [DIRS 170036] 2.2.07.17.0A Diffusion in the SZ 6.3, 6.5.2.6 Upstream Feedsa—BSC 2004 [DIRS 170036] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170006] 2.2.08.01.0A Chemical characteristics of groundwater in the SZ 6.5.2.8, 6.5.2.11, 6.5.2.12 Upstream Feedsa—BSC 2004 [DIRS 170036] Corroboratingb—BSC 2004 [DIRS 170037] 2.2.08.06.0A Complexation in the SZ 6.5.2.8, 6.5.2.11, 6.5.2.12 Upstream Feedsa—BSC 2004 [DIRS 170036] 2.2.08.08.0A Matrix diffusion in the SZ 6.3, 6.5.2.4, 6.5.2.5, 6.5.2.6 Upstream Feedsa—BSC 2004 [DIRS 170036] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170014], BSC 2004 [DIRS 170006] 2.2.08.09.0A Sorption in the SZ 6.3, 6.5.2.8, 6.5.2.11, 6.5.2.12 Upstream Feedsa—BSC 2004 [DIRS 170036] 2.2.08.10.0A Colloidal transport in the SZ 6.3.1, 6.5.1, 6.5.2.11, 6.5.2.12 Upstream Feedsa—BSC 2004 [DIRS 170036], BSC 2004 [DIRS 170006] 2.2.10.03.0A Natural geothermal effects on flow in the SZ 6.5.2.6 Upstream Feedsa—BSC 2004 [DIRS 170036] Expanded Discussionc—BSC 2004 [DIRS 170037] 2.2.12.00.0B Undetected features in the SZ 6.5.2.1, 6.5.2.3, 6.5.2.4, 6.5.2.10 Upstream Feedsa—BSC 2004 [DIRS 170036], BSC 2004 [DIRS 170014] Corroboratingb—BSC 2004 [DIRS 170010], BSC 2004 [DIRS 170037] 3.1.01.01.0A Radioactive decay and in-growth 6.3.1, 6.5, 6.5.1 Upstream Feedsa—N/A a Upstream Feeds – Aspects of the SZ FEP discussion adopted in this report are a result of SZ analyses performed in a directly upstream SZ model or analyses. b Corroborating – Corroborative aspect(s) of the FEP topic is (are) discussed in a SZ analysis report. c Expanded Discussion – The primary discussion of the FEP topic is discussed in the referenced SZ report. NOTE: See Table 6-2 for key to SZ Analysis and Model Reports (e.g., BSC 2004 [DIRS 170036]) FEP=feature, event, or process; SZ=saturated zone Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-4 October 2004 Table 6-2 provides a key to the SZ analysis and model reports listed in Table 6-1. SZ FEPs that are excluded from the models in the SZ are listed in Table 6-3. Screening arguments for the exclusion of the excluded FEPs are provided in Features, Events, and Processes in SZ Flow and Transport (BSC 2004 [DIRS 170013]. Table 6-2. SZ Analysis and Model Reports SZ Analysis or Model Report Number Report Title Document Identification Number BSC 2004 [DIRS 170008] Hydrogeologic Framework Model for the Saturated Zone Site Scale Flow and Transport Model MDL-NBS-HS-000024 BSC 2004 [DIRS 170009] Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model ANL-NBS-HS-000034 BSC 2004 [DIRS 170015] Recharge and Lateral Groundwater Flow Boundary Conditions for the Saturated Zone Site-Scale Flow and Transport Model ANL-NBS-MD-000010 BSC 2004 [DIRS 170036] Site-Scale Saturated Zone Transport MDL-NBS-HS-000010 BSC 2004 [DIRS 170014] Probability Distribution for Flowing Interval Spacing ANL-NBS-MD-000003 BSC 2004 [DIRS 170006] Saturated Zone Colloid Transport ANL-NBS-HS-000003 BSC 2004 [DIRS 170037] Saturated Zone Site-Scale Flow Model MDL-NBS-HS-000011 BSC 2004 [DIRS 170042] Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 BSC 2004 [DIRS 170013] Features, Events, and Processes in SZ Flow and Transport ANL-NBS-MD-000002 BSC 2004 [DIRS 170010] Saturated Zone In-Situ Testing ANL-NBS-HS-000039 SZ=saturated zone Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-5 October 2004 Table 6-3. SZ Excluded FEPs FEP Number FEP Name 1.2.04.02.0A Igneous activity changes rock properties 1.2.04.07.0B Ash redistribution in groundwater 1.2.06.00.0A Hydrothermal activity 1.2.09.02.0A Large-scale dissolution 1.2.10.01.0A Hydrologic response to seismic activity 1.2.10.02.0A Hydrologic response to igneous activity 1.3.07.01.0A Water table decline 1.4.07.03.0A Recycling of accumulated radionuclides from soils to groundwater 2.1.09.21.0B Transport of particles larger than colloids in the SZ 2.2.06.01.0A Seismic activity changes porosity and permeability of rock 2.2.06.02.0A Seismic activity changes porosity and permeability of faults 2.2.06.02.0B Seismic activity changes porosity and permeability of fractures 2.2.07.14.0A Chemically-induced density effects on groundwater flow 2.2.08.03.0A Geochemical interactions and evolution in the SZ 2.2.08.07.0A Radionuclide solubility limits in the SZ 2.2.08.11.0A Groundwater discharge to surface within the reference biosphere 2.2.09.01.0A Microbial activity in the SZ 2.2.10.02.0A Thermal convection cell develops in SZ 2.2.10.04.0A Thermo-mechanical stresses alter characteristics of fractures near repository 2.2.10.04.0B Thermo-mechanical stresses alter characteristics of faults near repository 2.2.10.05.0A Thermo-mechanical stresses alter characteristics of rocks near repository 2.2.10.08.0A Thermo-Chemical Alteration in the SZ (Solubility, Speciation, Phase Changes, Precipitation/Dissolution 2.2.10.13.0A Repository-induced thermal effects on flow in the SZ 2.2.11.01.0A Gas effects in the SZ 2.3.11.04.0A Groundwater discharge to surface outside the reference biosphere 3.2.07.01.0A Isotopic dilution FEP=feature, event, or process; SZ=saturated zone 6.3 BASE-CASE CONCEPTUAL MODEL The base-case conceptual model for radionuclide transport, as implemented in the SZ transport abstraction model, implicitly includes the conceptual models of groundwater flow and transport incorporated in the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.3) and the SZ site-scale transport model (BSC 2004 [DIRS 170036], Sections 6.3). The SZ site-scale flow model and alternative conceptualizations of groundwater flow are also described by Zyvoloski et al. (2003 [DIRS 163341]). The base-case conceptual model for the SZ 1-D transport model also implicitly includes the conceptual models in these underlying models, with the conceptual simplifications in flow associated with representation by 1-D groundwater flow. The SZ transport abstraction model and the SZ 1-D transport model also include the concept of uncertainty in key model parameters. The probabilistic analysis of uncertainty is implemented through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA simulations. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-6 October 2004 6.3.1 SZ Transport Abstraction Model The conceptual model of groundwater flow in the SZ includes steady-state flow conditions in a three-dimensional (3-D) flow system (BSC 2004 [DIRS 170037], Section 6.3.3). Groundwater flow occurs in a continuum fracture network in the fractured volcanic rocks beneath the repository site, at the scale of individual grid blocks in the SZ transport abstraction model. The effective continuum conceptual model is appropriate, given the relatively large horizontal scale (500 m by 500 m) of the grid in the model. Grid resolution studies with the SZ site-scale flow model indicate that the 500 m grid resolution and the effective continuum conceptual model are adequate to capture the flow behavior of the SZ system and to calibrate the model (Bower et al. 2000 [DIRS 149161]). Groundwater flow is conceptualized to occur in a continuum porous medium in the alluvium and valley-fill units of the SZ transport abstraction model. Contrasting values of average permeability among hydrogeologic units influence the patterns of groundwater flow in the SZ (BSC 2004 [DIRS 170037], Sections 6.3 and 6.6). Some of the major faults and other discrete geological features are conceptualized to impact the groundwater flow due to contrasts in permeability with surrounding hydrogeologic units. In addition, the prevailing structural fabric in the volcanic hydrogeologic units near Yucca Mountain can possibly impart horizontal anisotropy in the permeability between the major faults in this area of the SZ system. Significant variations in the hydraulic gradient near Yucca Mountain occur to the north of Yucca Mountain at the Large Hydraulic Gradient and to the west of Yucca Mountain at the Moderate Hydraulic Gradient, corresponding to the Solitario Canyon fault (Luckey et al. 1996 [DIRS 100465], pp. 21 to 26). Analysis of the different conceptualizations of the Large Hydraulic Gradient showed that the specific discharge was only mildly sensitive to choice of conceptual model if the hydraulic head measurements along the flow path were reasonably well matched by the numerical model (BSC 2004 [DIRS 170037], Section 6.4.1). Groundwater flow enters the SZ site-scale flow system primarily as underflow at the lateral boundaries of the model domain (BSC 2004 [DIRS 170037], Section 6.3.2). The conceptual model of recharge to the SZ includes distributed recharge, primarily in the northern part of the model domain, and focused recharge along the Fortymile Wash channel (BSC 2004 [DIRS 170037], Section 6.3.2). Recharge within the area of the SZ transport abstraction model domain constitutes a small fraction of the entire groundwater budget of the site-scale flow system. Groundwater flow paths from beneath Yucca Mountain to the south are conceptualized to occur near the water table, due to the generally small amount of recharge in this area. The conceptual model of the SZ flow system for future climatic conditions includes significant changes in the groundwater flow rates for potential wetter, cooler climate states. Increases in recharge at both the local and regional scales for monsoonal and glacial-transition climatic conditions would increase the specific discharge of groundwater in the SZ. Given the likelihood of such climatic variations within the 10,000-year period of regulatory concern, the conceptual model of SZ flow includes higher groundwater fluxes for the future. The conceptual model of radionuclide transport in the SZ includes the processes of advection, dispersion, matrix diffusion in fractured volcanic units, sorption, and colloid-facilitated transport (BSC 2004 [DIRS 170036], Section 6.3). In addition, radionuclides are subject to radioactive Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-7 October 2004 decay and ingrowth during migration in the SZ in the TSPA-LA analyses. These processes are illustrated in Figures 6-1 and 6-2. Figure 6-1. Illustration of the Conceptual Model of Radionuclide Transport Processes in the SZ Groundwater advection is the primary mechanism to drive the migration of contaminants from the SZ beneath the repository to the accessible environment. Advective transport of radionuclides is conceptualized to occur primarily within the fracture network of the volcanic hydrogeologic units (BSC 2004 [DIRS 170036], Section 6.3) due to the very high contrast in permeability between the fractures and the rock matrix. The conceptual model of advection within the porous medium of the alluvium units envisions the flow of groundwater to be much more widely distributed, but excludes groundwater flow from zones or sedimentary facies of lower permeability material within the alluvium. Dispersion of contaminant mass during transport in the SZ is conceptualized to occur because of hydrodynamic dispersion and molecular diffusion. Hydrodynamic dispersion is the result of variations in groundwater flow rates induced by heterogeneities within the aquifer, both in fractured and porous media. The conceptual model of hydrodynamic dispersion distinguishes between longitudinal dispersion, which occurs in the direction of groundwater flow, and transverse dispersion, which occurs perpendicular to the direction of groundwater flow. Longitudinal dispersion is typically much greater than transverse dispersion (see Section 6.5.2.9). Molecular diffusion also contributes to dispersion in radionuclide transport in the advective domain, but to a much lesser degree than hydrodynamic dispersion. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-8 October 2004 The dual-porosity conceptual model of matrix diffusion in fractured media describes the transfer of radionuclide mass from the flowing groundwater within the fractures to the relatively stagnant groundwater contained in the pores of the rock matrix. This mass transfer, either into or out of the rock matrix, occurs by molecular diffusion, which is driven by differences in the concentration of the contaminant in the fractures and matrix. The simplified conceptual model of the spatial distribution of groundwater-conducting fractures and matrix is a set of parallel, uniformly spaced fractures, separated by blocks of porous matrix (BSC 2004 [DIRS 170036], Section 6.4.2.4). This conceptual model considers that groundwater flow occurs only in the fractures and that the groundwater in the rock matrix has no advective groundwater movement. Although this aspect of the dual-porosity conceptual model is difficult to confirm, the contrast in permeability between the rock matrix and the fracture network in fractured tuff supports this approach. Groundwater flow is conceptualized to not necessarily occur in all fractures of the system, but is limited to those fractures that are interconnected in the through-going fracture network. The matrix diffusion process is controlled primarily by the effective diffusion coefficient in the rock matrix, the spacing between fractures carrying flowing groundwater, and the aperture of the fractures. The conceptual model of matrix diffusion also recognizes the possibility of groundwater flow in fracture zones, in which numerous, closely spaced fractures can possibly transmit groundwater. Such fracture zones could exist along faults, which have experienced multiple episodes of displacement and potentially contain zones of rubblized bedrock. Diffusion of contaminants into the relatively small blocks of matrix within a fracture zone would be rapid in comparison to the matrix diffusion that would occur into the large blocks that exist between such zones. The contaminant storage capacity of the small blocks within such a fracture zone would be the total matrix porosity (and sorption capacity of mineral grains) of the blocks, corresponding to essentially complete matrix diffusion within the small matrix blocks. The conceptual model of radionuclide sorption in the SZ is local equilibrium distribution of radionuclide mass between the aqueous phase and the mineral grains of the aquifer. This equilibrium distribution of contaminant mass is defined by the linear sorption coefficient relationship (BSC 2004 [DIRS 170036], Section 6.4.2.5). In fractured media, sorption is conceptualized to occur in the rock matrix; no sorption of solutes is conceptualized to occur on the fracture surfaces or coatings. Although sorption can possibly occur on fracture surfaces or coatings, there are no definitive measurements of this process. Discounting possible sorption on fracture surfaces in the conceptual model results in more rapid radionuclide migration in numerical simulations of transport in the SZ. In the porous media of the alluvium, sorption is conceptualized to occur in that portion of the aquifer corresponding to the effective porosity of the alluvium. In other words, sorption can occur in that part of the alluvium through which significant groundwater flow occurs; zones or layers of low permeability are effectively excluded from the sorption process. In the conceptual model of colloid-facilitated transport radionuclide migration associated with colloids can occur by two modes (BSC 2004 [DIRS 170006], Section 6.3), as illustrated in Figure 6-2. In the first mode, radionuclides that are reversibly attached to colloids are in equilibrium with the aqueous phase and the aquifer material. In this mode of transport, the effective retardation of these radionuclides during transport in the SZ is dependent on the sorption coefficient of the radionuclide onto colloids, the concentration of colloids in the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-9 October 2004 groundwater, and the sorption coefficient of the radionuclide onto the aquifer material. In the second mode, radionuclides that are irreversibly attached to colloids are transported at the same rate as the colloids. The colloids with the irreversibly attached radionuclides are themselves retarded by interaction (attachment and detachment) with the aquifer material. Specifically, the colloids undergo reversible filtration, which is represented by a retardation factor in the model. This conceptual model also recognizes that a small fraction of colloids with irreversibly attached radionuclides could be transported through the SZ with no retardation, due to kinetic effects of colloid attachment and detachment. This fast fraction of the colloids with irreversibly attached radionuclides is transported with no retardation in the SZ (similar to nonsorbing solutes), but without diffusion into the matrix of the volcanic units. The conceptual model of radioactive decay in the SZ transport abstraction model is that radionuclides experience a decrease in mass during transport time using the first-order decay constant for that radionuclide. Because the ingrowth of radionuclides is not explicitly included in the SZ transport abstraction model, a simplified approach is used to account for this process for some of the radionuclides that have parent radionuclides. In this simplified approach, the mass of the decay product-radionuclide is boosted by the maximum mass of the parent radionuclide that would decay over the remaining TSPA-LA simulation time (BSC 2004 [DIRS 168504], Section 6.3.10). The boosting of the decay product-radionuclide mass occurs for the input to the SZ transport abstraction model (i.e., at the UZ-SZ interface). The decay product-radionuclides that are boosted in this manner are 239Pu (from 243Am), 237Np (from 241Am), 236U (from 240Pu), 238U (from 242Pu), and 234U (from 238U and 238Pu). It should be noted that the parent radionuclides of these boosted decay products are not diminished and that, consequently, this approach overestimates the mass of radionuclides being transported in the SZ. Transport of subsequent decay products in the four decay chains is explicitly simulated using the SZ 1-D transport model, as described in Section 6.3.2. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-10 October 2004 Figure 6-2. Illustration of the Conceptual Model of Colloid-Facilitated Radionuclide Transport in Fractured Tuff in the SZ Homogeneous material properties are assigned to individual hydrogeologic units. The assumption of intra-unit homogeneity is justified primarily on the basis of scale in the SZ transport abstraction model. The horizontal grid resolution of 500 m implies averaging of spatially variable properties over a very large volume. In addition, variations among realizations for stochastic parameters in the analysis encompass probable spatial variations in material properties within the model domain. The groundwater flow conditions in the SZ system are also assumed to be in steady state. This approach is carried forward from the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 5). The site-scale SZ flow model is a steady-state model of the flow conditions, reflecting the conclusion that a steady-state representation of the SZ system is accurate. This conclusion is supported by the lack of consistent, large-magnitude variations in water levels observed in wells near Yucca Mountain (Luckey et al. 1996 [DIRS 100465], pp. 29 to 32). The convolution integral method has been extended to incorporate multiple steady-state flow conditions for future climate states in the TSPA-LA analyses. The conceptual model of matrix diffusion in the fractured volcanic units of the SZ assumes groundwater flow in evenly spaced, parallel-walled fractures separated by impermeable matrix (BSC 2004 [DIRS 170036], Section 6.4.2.4). Although this dual-porosity conceptual model of radionuclide transport represents a significant simplification of the complex fracture network Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-11 October 2004 observed in fractured volcanic rocks at the site, it is an acceptable approximation at the scale of individual grid blocks in the SZ transport abstraction model. Individual grid blocks in the transport model have horizontal dimensions of 500 m by 500 m, in comparison to a geometric mean flowing interval spacing of approximately 21 m. This comparison indicates that the grid blocks in the numerical model are more than an order of magnitude larger than the expected spacing between fracture zones that contain flowing groundwater. In addition, the relatively broad range of uncertainty in the flowing interval spacing used in this analysis encompasses the variability in spacing of the actual fracture network. Thus, the variability in flowing interval spacing among stochastic realizations in the TSPA-LA simulations captures the impact of variable spacing between fractures in an ensemble fashion. For transport of radionuclides reversibly attached to colloids in the SZ, it is assumed that equilibrium conditions exist among radionuclides sorbed onto colloids, the aqueous phase concentration, and those sorbed onto the aquifer material. This approach is carried forward from the SZ site-scale transport model (BSC 2004 [DIRS 170036], Section 6.3) and is related to the general assumption regarding linear, equilibrium sorption presented in Section 5. This approach is consistent with laboratory observations of sorption onto colloids, particularly given the time scales of transport in the SZ. This modeling approach is appropriate, given the broad ranges of uncertainty applied to parameters underlying the simulated transport of radionuclides reversibly attached to colloids in the SZ. Pumping of groundwater by the hypothetical community in which the RMEI resides is assumed not to alter significantly the groundwater pathways or radionuclide travel times in the SZ. Calibration of the SZ site-scale flow model is based on the present-day potentiometric surface observed in the model domain. Whereas the SZ site-scale model does not explicitly include the withdrawal of groundwater by pumping at the location of the hypothetical community in which the RMEI resides, the model does implicitly account for the drawdown of water levels associated with pumping at the southern boundary of the model domain. The values of specified head along the western part of the southern boundary reflect the lower water levels resulting from pumping in the Amargosa Farms region. Consequently, the model does implicitly include the influence of pumping in terms of increased hydraulic head gradients. 6.3.2 SZ 1-D Transport Model Many components of the conceptual model for the SZ transport abstraction model also apply to the SZ 1-D transport model. Representation of the groundwater flow processes in the 3-D SZ transport abstraction model is simplified to 1-D streamtubes in the SZ 1-D transport model. However, characteristics of the conceptual model of groundwater flow in the SZ transport abstraction model are implicitly included in the SZ 1-D transport model because the average values of groundwater flow rate used in the SZ 1-D transport model are extracted from the three dimensional (3-D) flow model. The conceptual model of aquifer properties has also been simplified in the SZ 1-D transport model, relative to the SZ transport abstraction model. Material properties in the SZ 1-D transport model streamtubes are for average fractured tuff or for alluvium; no distinctions among volcanic hydrogeologic units are made. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-12 October 2004 The conceptual model of radionuclide transport in the SZ 1-D transport model includes the same processes of advection, dispersion, matrix diffusion in fractured volcanic units, sorption, and colloid-facilitated transport described in the previous section. The conceptualization of dispersion in the SZ 1-D transport model is simplified to the extent that transverse dispersion is precluded in the streamtube representation of the SZ system. The conceptual model of radionuclide decay in the SZ 1-D transport model includes both decay and ingrowth of radionuclides in decay chains. The final radionuclide decay product in three of the radionuclide decay chains simulated in the 1-D radionuclide transport model is calculated to be in secular equilibrium with its parent radionuclide (see Section 6.5.1.2). This is a reasonable approach because it simplifies the analysis and the final decay product-radionuclides have relatively short half-lives (less than 25 years). This approach overestimates the concentration of decay products because it implies an instantaneous increase in the mass of the final decay product to be in equilibrium with the mass of parent radionuclide present. The groundwater flux within each 1-D “pipe” segment used in the model is assumed to be constant along the length of the pipe. Each pipe segment used in the model consists of homogenous material properties, for which the radionuclide transport process is simulated. This constitutes a reasonable approach because the average groundwater flux along that portion of the radionuclide flow path is derived from the corresponding region of the 3-D SZ transport abstraction model. 6.3.3 Interfaces with the UZ and the Biosphere The source of radionuclides in the SZ transport abstraction model is conceptualized to be a point source from the UZ transport model. The location of this source is treated as uncertain and constant for a given realization of the system. This conceptual model is consistent with a contaminant source to the SZ resulting from a single leaking waste package, focused groundwater flow in the UZ, or the human intrusion scenario in which a borehole intersects a waste package and extends to the water table (CRWMS M&O 2000 [DIRS 153246], Section 4.4). The conceptual model of radionuclide releases from the SZ to the biosphere includes discharge of groundwater from wells to the hypothetical community in which the RMEI resides. The extent of the controlled area is specified in the regulations for the Yucca Mountain site (10 CFR 63.302 (10 CFR 63 [DIRS 156605])) and the location of the hypothetical community in which the RMEI resides is taken to be adjacent to the controlled area. In addition, the quantity of groundwater in the representative volume from which contaminated water is withdrawn by the RMEI is specified by the regulations to be 3,000 acre-ft/year (10 CFR 63.332 (10 CFR 63 [DIRS 156605])). The conceptualization of the SZ system is that the entire mass flux of radionuclides that crosses the regulatory boundary in the SZ would be contained in the representative volume of groundwater from which the RMEI obtains water and that these contaminants would be homogeneously distributed in the specified volume of groundwater. The interface between radionuclide transport in the UZ and the SZ is assumed to be a point source near the water table. This approach is physically consistent with a single leaking waste Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-13 October 2004 package and highly focused transport of radionuclides in the UZ flow system, as can possibly occur early in the history of the repository. This approach is also consistent with the human intrusion scenario, in which a borehole penetrates a waste package and provides a direct pathway for radionuclide migration to the SZ. The approach of a point source for radionuclides in the SZ transport simulations, while not physically realistic for the situation in which multiple, dispersed leaking waste packages exist, provides a generally conservative approximation of the source term to the SZ. This approximation results in less dispersion of the radionuclide transport times through the SZ and thus to less attenuation of peaks in radionuclide discharge. Although in situ concentrations of radionuclides are not utilized in the analysis of SZ transport, a point source maximizes the simulated concentrations of radionuclides at the outlet to the accessible environment. The location of the point source of radionuclides for transport in the SZ site-scale flow and transport model is assumed to be randomly located within the four source regions defined at the water table (Section 6.5.2.13). This approach implies that there are no consistent spatial patterns of waste package failure or delivery of radionuclides at the water table within each of the four source regions. Many of the processes that may lead to waste package failure are spatially random (e.g., manufacturing defects, seepage onto waste packages, etc.). The spatial pattern of preferential groundwater flow pathways in the UZ flow model is represented in a general sense by the locations of the four source regions (e.g., the southeastern source region corresponds to focused vertical groundwater flow along the Ghost Dance fault). An assumption inherent to the convolution integral method is that the system being simulated exhibits a linear response to the input function. In the case of solute transport in the SZ system, this approach implies, for example, that a doubling of the input mass flux results in a doubling of the output mass flux. This approach is valid for the SZ transport abstraction model because the underlying transport processes (e.g., advection and sorption) are all linear with respect to solute mass (BSC 2004 [DIRS 170036], Section 6.4.2). The processes of colloid filtration and sorption are both represented as equilibrium retardation processes. Simple retardation affects the timing of the release of radionuclides from the SZ, but still constitutes a linear relationship between mass input and mass output to the SZ. It is assumed that all radionuclide mass crossing the regulatory boundary at approximately 18 km distance from the repository at the boundary of the controlled area (10 CFR 63.302 (10 CFR 63 [DIRS 156605])) in the SZ is contained in the representative volume of groundwater, which serves as a source of water to the RMEI, based on 10 CFR 63.332 (10 CFR 63 [DIRS 156605]). This approach implies that the representative volume of groundwater is large relative to the volumetric flow in the plume of contaminated groundwater in the SZ. This approach is justified on the basis of conservatism with respect to the analysis of repository performance. The total mass of radionuclides released to the biosphere for a given time period cannot be larger than the amount of radionuclide mass delivered by groundwater flow (for the nominal case). 6.4 CONSIDERATION OF ALTERNATIVE CONCEPTUAL MODELS Two significant ACMs regarding groundwater flow and radionuclide transport in the SZ have been considered in this report. Both of these ACMs are encompassed in the range of uncertainty evaluated in the SZ transport abstraction model and the SZ 1-D Transport model and are thus Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-14 October 2004 implicitly carried forward to the TSPA-LA modeling analyses. Consequently, these ACMs need not be separately evaluated from the base case. Information on ACMs is summarized in Table 6-4. The ACMs are consistent with available data and current scientific knowledge and appropriately consider their results and limitations. Table 6-4. ACMs Considered ACM Key Assumptions Screening Assessment and Basis Minimal Matrix Diffusion Diffusion of radionuclides into the pore space of the rock matrix in the fractured volcanic units is extremely limited due to highly channelized groundwater flow, fracture coatings, or other factors. This ACM is implicitly included in the SZ transport abstraction model and in the SZ 1-D transport model through the range of uncertainty in key input parameters. The uncertain input parameters influencing matrix diffusion include effective diffusion coefficient (DCVO), flowing interval spacing (FISVO), and flowing interval porosity (FPVO). Horizontal Anisotropy in Permeability Alternative interpretations of pump test results in the fractured volcanic units indicate preferential permeability along structural features oriented in the NNESSW direction or in the WNW-ESE direction. This ACM is implicitly included in the SZ transport abstraction model and in the SZ 1-D transport model through the range of uncertainty in an input parameter. The uncertain input parameter influencing horizontal anisotropy in permeability in the volcanic units near Yucca Mountain is the ratio of N-S to E-W permeability (HAVO, see Section 6.5.2.10). This continuously distributed parameter varies from less than one to greater than one with most of the realizations greater than one. ACM=alternative conceptual model; SZ=saturated zone A sensitivity analysis using the SZ transport abstraction model was conducted to show that the minimal matrix diffusion ACM is included within the range of parameter uncertainties considered. Figure 6-3 shows the solute mass breakthrough curves for a nonsorbing tracer, using the expected values of flow and transport parameters. The short-dashed line shows the simulated breakthrough curve for transport with no diffusion into the matrix of the fractured volcanic units, and the long-dashed line shows the breakthrough curve for maximum matrix diffusion. The solid line shows the simulated breakthrough curve using the 95th percentile value for flowing interval spacing (79.4 m) from the uncertainty distribution in this parameter. These results indicate that the breakthrough curve using the 95th percentile value of flowing interval spacing is very near the bounding case of no matrix diffusion. Similarly, low values of effective diffusion coefficient and low values of flowing interval porosity would produce breakthrough curves tending toward the no-matrix-diffusion case. This sensitivity analysis demonstrates that the minimal matrix diffusion ACM is captured within the range of uncertainty used in the model. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-15 October 2004 10 100 1000 10000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass NOTE: The case of no matrix diffusion is shown with the short-dashed line. The case of maximum matrix diffusion is shown with the long-dashed line. The case for which flowing interval spacing is set to its 95th percentile value (79.4 m) is shown with the solid line. Mass breakthrough curves are for present climate and do not include radionuclide decay. Figure 6-3. Mass Breakthrough Curves at 18-km Distance Showing Sensitivity to Matrix Diffusion for a Non-Sorbing Radionuclide The incorporation of the horizontal anisotropy ACM into the SZ transport abstraction model is inherent in the range of parameter values used for the parameter HAVO in the analyses. A complete discussion of uncertainty in horizontal anisotropy of permeability and the basis for the uncertainty distribution are provided in the Saturated Zone In Situ Testing scientific analysis report (BSC 2004 [DIRS 170010], Section 6.2.6). The uncertainty distribution for HAVO indicates that there is a 10 percent probability that the direction of maximum horizontal permeability is east-west with a ratio between 1 and 20. The uncertainty distribution also indicates that there is a 90 percent probability that the direction of maximum horizontal permeability is north-south with a ratio between 1 and 20. The isotropic case, corresponding to a horizontal permeability ratio of one, is included in this continuous uncertainty distribution for the parameter HAVO. 6.5 MODEL FORMULATION FOR BASE-CASE MODELS SZ Transport Abstraction Model The SZ site-scale flow model (BSC 2004 [DIRS 170037]) and the SZ site-scale transport model (BSC 2004 [DIRS 170036]) form the bases for the SZ transport abstraction model. The progression in the development of models is from the SZ site-scale flow model to the SZ site-scale transport model to the SZ transport abstraction model. The SZ site-scale flow model includes the implementation of the hydrogeologic framework, the numerical grid, and the boundary conditions for steady-state groundwater flow. The SZ site-scale flow model is calibrated to water-level measurements in wells and estimates of groundwater flow rates at the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-16 October 2004 lateral boundaries. The SZ site-scale transport model begins with the SZ site-scale flow model and adds the model input files required for the simulation of radionuclide transport using the particle-tracking method. A set of representative parameter values for radionuclide transport is included in the SZ site-scale transport model and the range of behavior associated with parameter uncertainty is examined. Finally, the SZ transport abstraction model begins with the SZ site-scale transport model and adds the capability to perform probabilistic uncertainty analyses using multiple Monte Carlo realizations of the SZ flow and transport system. The resulting radionuclide breakthrough curves are then used in the convolution integral method to couple the SZ transport abstraction model with the TSPA-LA model. The SZ site-scale flow model, the SZ site-scale transport model, and the SZ transport abstraction model share a common model domain, hydrogeologic framework, numerical grid, and groundwater flow boundary conditions. The model domain is shown in Figure 6-4 with the blue dashed line overlain on a shaded relief map of the surface topography. The nodes that constitute the model grid form an orthogonal mesh with 500-m spacing in the north-south and east-west directions. The repository outline is shown with the bold blue line and the nodes that occur along the regulatory boundary of the accessible environment are shown as overlapping red crosses. The groundwater flow boundary conditions for the SZ site-scale flow model, the SZ site-scale transport model, and the SZ transport abstraction model are specified head at the lateral boundaries and specified groundwater flux for recharge at the upper boundary. These boundary conditions are described in detail in Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037], Section 6.3.2) and are the same for all three models with the following exception: for the SZ transport abstraction model, the specified flux for recharge is scaled in proportion to the uncertainty in groundwater specific discharge (see Section 6.5.2.1). Scaling the recharge flux and the values of permeability in proportion to the groundwater specific discharge uncertainty factor maintains the calibration of the flow model with regard to water-level measurements. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-17 October 2004 530000 535000 540000 545000 550000 555000 560000 565000 UTM Easting (m) 4045000 4050000 4055000 4060000 4065000 4070000 4075000 4080000 4085000 4090000 UTM Northing (m) Source: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]). NOTE: The dashed blue line indicates the boundaries of the SZ transport abstraction model, the solid blue line shows the outline of the repository, and the red crosses indicate the boundary to the accessible environment for radionuclide transport in the SZ. Figure 6-4. Model Domain of the SZ Site-Scale Flow Model, SZ Site-Scale Transport Model, and the SZ Transport Abstraction Model Radionuclide transport is simulated in the SZ transport abstraction model using a particle tracking method. This method, as implemented by the FEHM (finite element heat and mass model) V2.20 software code (FEHM V2.20 STN: 10086-2.20-00 [DIRS 161725]), simulates advection along groundwater streamlines, random-walk dispersion, retardation due to sorption, and matrix diffusion. Each simulation uses 500 particles, which results in a continuous, Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-18 October 2004 generally smooth cumulative mass breakthrough curve at the boundary of the accessible environment. The time-step size that determines output intervals varies from 10 years to 100 years, depending on the radionuclide. Internally, the simulation uses local flow conditions to determine time steps for dispersion and matrix diffusion calculations. This internal time step is controlled such that the particles take approximately 20 internal time steps to traverse each cell in the model. The convolution integral method used in the SZ transport abstraction model for the TSPA-LA analyses provides an approximation of the transient radionuclide mass flux at a specific point downgradient in the SZ in response to the transient radionuclide mass flux from transport in the UZ. This coupling method makes full use of detailed SZ flow and transport simulations for a given realization of the system, without requiring complete numerical simulation of the SZ for the duration of each TSPA-LA realization. The two input functions to the convolution integral method are: 1) a unit radionuclide mass breakthrough curve in response to a step-function mass flux source as simulated by the SZ transport abstraction model. 2) the radionuclide mass flux history as simulated for transport in the UZ. The output function is the radionuclide mass flux history downgradient in the SZ. There are several important assumptions in the use of the convolution integral method. Groundwater flow in the SZ is assumed to be steady state. The transport processes in the SZ must be linear with respect to the solute source term (i.e., a doubling of the solute mass source results in a doubling of mass flux). In addition, the flow and transport processes in the UZ and the SZ must be independent of one another. Radioactive decay is also applied to radionuclide mass flux calculated with the convolution integral computer code SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]) in the TSPA-LA analyses. The convolution integral method consists of numerical integration that accounts for the contributions to the outlet radionuclide mass flux from a series of time intervals. Because the travel time for each contribution to radionuclide mass flux is known, the loss of radionuclide mass (and consequent decrease in mass flux) during transport is calculated by first-order decay for that time interval. The effects of climate change on radionuclide transport in the SZ are incorporated into the convolution integral analysis in the TSPA-LA by assuming instantaneous change from one steady-state flow condition to another steady-state condition in the SZ. A description of the mathematical and numerical implementation of multiple steady-state flow conditions is given in DOE 2003 [DIRS 167588], Equation 3. Changes in climate state are assumed to affect the magnitude of groundwater flux through the SZ system but have a negligible impact on flow paths. The effect of changes in groundwater flux is incorporated into the convolution method by scaling the timing of radionuclide mass breakthrough curves proportionally to the change in SZ-specific discharge. For the base-case TSPA-LA analyses, present-day climatic conditions are modeled to occur from the time of repository closure and to be followed by monsoonal conditions and glacial-transition Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-19 October 2004 climatic conditions. The monsoonal climatic state is wetter than present-day conditions and the glacial-transition state is conceptualized to be wetter and cooler than present-day conditions (BSC 2004 [DIRS 170002]). Note that the glacial-transition climate state is approximately equivalent to the long-term average climate state, as referenced in Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 [DIRS 100365], Table 8-16, p. T8-20). Estimates of the scaling factors for groundwater flux in the SZ under alternative climatic conditions are based on simulations using the Death Valley regional flow model (D’Agnese et al., 1999 [DIRS 120425]; CRWMS M&O 1998 [DIRS 100365]) and on the infiltration for the UZ site-scale flow model (BSC 2004 [DIRS 169861], Section 6.1.4). Simulations using the Death Valley regional flow model were conducted for the past-climate state that likely existed about 21,000 years ago (D’Agnese et al., 1999 [DIRS 120425]). This climatic state approximately corresponds to the glacial-transition state, as defined for TSPA-LA calculations. A comparison of the groundwater flux in the SZ near Yucca Mountain under pastclimate conditions (i.e., 21,000 years ago) using the Death Valley regional flow model indicates that the simulated flux under the past-climate conditions was approximately 3.9 times the flux of present-day simulations, as shown in Table 6-5. Simulations of SZ flow under monsoonal climatic conditions have not been performed using the Death Valley regional flow model. Information on the increased infiltration through the UZ site-scale flow model is used as the basis for estimating flux increases in the SZ for monsoonal conditions (DTN: LB03023DSSCP9I.001 [DIRS 163044]) (see also UZ Flow Models and Submodels (BSC 2004 [DIRS 169861], Table 6.1-2)). Values of average infiltration in the model domain of the UZ site-scale flow model (second column of Table 6-5) are taken from the “GENER” card of the TOUGH2 input files “preq_mA.dat”, “glaq_mA.dat”, and “monq_mA.dat”. This value of average infiltration is the mean groundwater flux at the upper boundary of the UZ site-scale flow model, as stated in the three input files named above. Similarly, the total infiltration through the UZ site-scale flow model for present and glacialtransition climatic conditions is calculated (DTN: LB03023DSSCP9I.001 [DIRS 163044]). Note in Table 6-5 that the ratio of glacial-transition infiltration in the UZ model to the presentday infiltration (a factor of 3.8) is approximately the same value as the estimate of increased SZ groundwater flux from the Death Valley regional flow model (i.e., 3.9). This correspondence suggests that the UZ infiltration ratio provides a reasonable estimate of the flux ratio for the SZ. Thus, the values of the SZ groundwater flux ratio for TSPA-LA simulations of future climatic states are derived from the estimates of increased UZ infiltration at Yucca Mountain. For monsoonal climatic conditions, the ratio of UZ infiltration to the infiltration for present-day conditions is 2.7 (see Table 6-5) and this value is applied to the SZ flux as well. The values of flux ratio used as scaling factors of SZ flow and transport for alternative climate states are given in the last column of Table 6-5. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-20 October 2004 Table 6-5. Groundwater Flow Scaling Factors for Climate Change Climate State Average Infiltration, UZ Model (Mean Case) (mm/year) a Ratio to Present Climate, UZ Model SZ Groundwater Flux Ratio from Death Valley Regional Flow Model SZ Groundwater Flux Ratio for TSPA-LA Simulations Present-Day 4.43 1.0 1.0 1.0 Glacial- Transition 17.0 3.8 3.9 b 3.9 Monsoonal 11.8 2.7 N/A 2.7 a Source: DTN: LB03023DSSCP9I.001 [DIRS 163044]. b Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 [DIRS 100365], Table 8-16, p. T8-20). SZ 1-D Transport Model The SZ 1-D transport model is a simplified model of radionuclide transport for the purpose of simulating decay chains and is implemented with the GoldSim V7.50.100 software code in the TSPA-LA simulator as a series of “pipes.” The same radionuclide transport processes that are simulated in the 3-D SZ transport abstraction model (e.g., sorption, matrix diffusion in fractured units, and colloid-facilitated transport) are analyzed in the “pipe” segments, with the exception of transverse dispersion. Transverse dispersion is not very important to the modeling results, given the assumption that all radionuclide mass is captured by the wells of the receptor group. Although strict consistency between the SZ 1-D transport model and the 3-D SZ transport abstraction model is not possible, average groundwater flow and transport characteristics of the SZ transport abstraction model are used to define flow and transport properties within the “pipe” segments of the 1-D model. Average specific discharge along different segments of the flow path is estimated using the 3-D SZ transport abstraction model. The resulting values of average specific discharge are applied to the individual “pipe” segments in the 1-D transport model. 6.5.1 Mathematical Description of Base-Case Conceptual Model 6.5.1.1 SZ Transport Abstraction Model The mathematical descriptions of the processes of groundwater flow and radionuclide transport in the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.5) and the SZ site-scale transport model (BSC 2004 [DIRS 170036], Section 6.4.2) are presented in the corresponding reports for these models. The SZ site-scale flow model forms the direct basis for the SZ site-scale transport model, which forms the direct basis for the SZ transport abstraction model. Therefore, the mathematical bases for those models, as implemented by the FEHM V2.20 software code [DIRS 161725], apply to the SZ transport abstraction model and are not reproduced here. The particle tracking method is used to simulate radionuclide transport in the SZ transport abstraction model (see Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-21 October 2004 Section 6.4.2) for a description of the particle tracking method). This method exhibits very limited numerical dispersion relative to standard finite-difference and finite-element methods of solute transport simulation. Consequently, particle tracking is appropriate for use in the SZ transport abstraction model, in which the spatial discretization (500 m) exceeds the values of dispersivity being simulated for many of the model realizations. Convolution Integral The convolution integral method is used to couple the radionuclide transport in the UZ with the simulations of mass transport in the SZ in the TSPA-LA analyses. The convolution integral method takes the radionuclide mass breakthrough curve for a continuous, unitary mass source (step function input of mass) from the SZ and the time-varying radionuclide mass from the UZ as inputs. The output is the time-varying radionuclide mass exiting the SZ. The mathematical expression for the convolution integral method is written as: . ' ' ' - = t p sz uz sz t d m t M t t m t M 0 ) ( ) ( ) ( & (Eq. 6-1) where Msz(t) = radionuclide mass flux downstream in the SZ [M] t = time [T], ) (t mUZ & = time dependent radionuclide mass flux entering the SZ from the UZ [M] t' = time lag [T] ) (t M ' = derivative of the downstream radionuclide mass flux-time response curve [M] to a step input of mass mp [M] Note that symbols in brackets are generalized dimensions with T denoting time and M denoting mass. This expression is taken from the convolution integral for concentration (CRWMS M&O 1998 [DIRS 100365], p. 8-39) and rewritten in terms of radionuclide mass. A description of the mathematical implementation of multiple steady-state flow conditions for alternative climate states is given in DOE 2003 [DIRS 167588], Equation 3. Correction of Retardation The retardation factor for linear sorption of radionuclides during transport in porous media is defined (Freeze and Cherry 1979 [DIRS 101173], p. 404) as: d b f K R f . + = 1 (Eq. 6-2) where Rf is the retardation factor in the porous media [-] (the symbol - denotes a dimensionless parameter), .b is the bulk density [M/L3], f is the porosity of the porous media [-], and Kd is the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-22 October 2004 distribution coefficient [L3/M]. The FEHM V2.20 software code [DIRS 161725] to be used in the SZ transport abstraction model automatically calculates Rf based on input values of .b , f, and Kd. Effective porosity ( fe ) [-] is a macroscopic parameter that helps account for discrete flow paths and channelized flow in the porous medium of the alluvium (see Section 6.5.2.3). The effective porosity is defined as the fraction of the total volume of the medium through which significant groundwater flow occurs. The effective porosity parameter in the alluvium is used to correctly calculate the pore velocity of groundwater. Effective porosity is not intended to be used to estimate surface areas in Equation 6-2. Therefore, it is necessary to adjust another parameter in the equation to compensate for the lower effective porosity that is entered. If this were not done, then the calculated values of Rf would be overestimated, given that values of Kd used in Equation 6-2 are based on laboratory-scale measurements. For the SZ transport abstraction model and the SZ 1-D transport model, the Kd values for the alluvium are adjusted according to the following relationship (CRWMS M&O 1998 [DIRS 100365], Equation 8-4, p. 8-55): T e d new d K K f f · = (Eq. 6-3) where Kd new is the adjusted distribution coefficient [L3/M] and fT is the total porosity [-]. The total porosity is 0.30, which is the upper bound of the effective porosity uncertainty distribution and also documented in Section 6.5.2.14. Colloid-Facilitated Transport For colloid-facilitated radionuclide transport in which radionuclides are reversibly attached to colloids, a partition coefficient is defined to represent the potential for enhanced migration of radionuclides in association with colloids. This unitless constant, Kc, is defined as: coll coll d c C K K = (Eq. 6-4) where Kd coll is the sorption coefficient for the radionuclide onto colloids [L3/M] and Ccoll is the concentration of colloids in the groundwater [M/L3]. The conceptual model of colloid-facilitated transport of reversibly sorbed radionuclides is described in Section 6.3, and the underlying theoretical derivation of the model is presented in The Site-Scale Unsaturated Zone Transport Model of Yucca Mountain (CRWMS M&O 1997 [DIRS 124052], pp. 8-32 to 8-36). For equilibrium conditions in a porous medium, the effective sorptive capacity of the aquifer is reduced when the groundwater colloids carry a significant fraction of radionuclide mass in the system. The values of the sorption coefficient in the alluvium and undifferentiated valley fill hydrogeologic units for the colloid-facilitated transport of radionuclides with the Kc model are modified by the value of Kc, according to the relationship: ) 1 ( c new d adjusted d K K K + = (Eq. 6-5) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-23 October 2004 as derived from Equation 6-2 and Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 [DIRS 100365], Equation 8-8, pp. 8-54 and 8-56), and assigning the retardation factor for colloids with reversibly attached radionuclides a value of one. Kd adjusted is the adjusted distribution coefficient [L3/M] to account for reversible sorption onto colloids. For transport in fractured media, the effective diffusion coefficient into the rock matrix is reduced due to the affinity of radionuclides for sorption onto colloids in the fractures. To evaluate this effect with constant velocity and dispersion, consider the 1-D advection-dispersion equation for a solute in the fractures (BSC 2004 [DIRS 170036], Section 6.4.2) with a term for retardation and a final term added for diffusion into the matrix: b q x C v x C D t C R f f - . . - . . = . . 2 2 , (Eq. 6-6) where f f R , is the retardation factor in the fractures [-], D is the dispersion coefficient in the fracture [L2/T], C is aqueous concentration of the solute [M/L3], t is time [T], x is distance [L], v is groundwater velocity in the fractures [L/T], q is the diffusive flux into the rock matrix [M/L2T], and b is the half-aperture of the fracture [L]. For that part of the solute mass that is sorbed onto colloids the advection-dispersion equation is: x C v x C D t C R coll coll coll col . . - . . = . . 2 2 (Eq. 6-7) where Rcol is the retardation factor of the colloids in the fractures [-] and coll C is the concentration of the solute in the groundwater [M/L3]. Adding the two advection dispersion equations and using the relationship that Kc = coll C /C, the combined advection-dispersion equation for colloid-facilitated transport of radionuclides reversibly sorbed onto colloids can be written as: ) 1 ( 1 2 2 , c c col c f f K b q x C v x C D t C K R K R + - . . - . . = . . . . . . . . + + (Eq. 6-8) As seen by comparing this equation with Equation 6-6, the term for diffusive mass flux into the rock matrix is modified by dividing by the factor (1 + Kc) to account for the equilibrium colloid-facilitated transport. One approach would be to adjust the value of fracture half-aperture by multiplying by the factor (1 + Kc). An alternative approach is possible based on examination of the . term in the analytical solution for transport in fractures with matrix diffusion by Sudicky and Frind (1982 [DIRS 105043], Equation 34, p. 1638). In the . term, adjusting the value of b by multiplying it by the factor (1 + Kc) is equivalent to dividing the effective diffusion coefficient in the matrix by the factor (1 + Kc)2. In the SZ transport abstraction model and the SZ Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-24 October 2004 1-D transport model, the values of effective diffusion coefficient for radionuclides subject to the Kc model of colloid-facilitated transport are adjusted according to the relationship: 2 ) 1 ( c e adjusted e K D D + = (Eq. 6-9) where De adjusted is the adjusted effective diffusion coefficient in the rock matrix [L2/T], and De is the effective diffusion coefficient in the rock matrix [L2/T]. It should be noted that this approach to adjusting the effective diffusion coefficient to account for colloid-facilitated transport in fractured media is not exact. The s term of the Sudicky and Frind analytical solution also contains the variable b and the adjustment to the effective diffusion coefficient does not scale the variable b in the same manner as in the . term. However, the variable b is a minor contributor in the expression for the s term (i.e., value of b is much smaller than the value of B, which is the half fracture spacing). In addition, the adjusted diffusion coefficient, as applied in the s term, is equivalent to increasing the value of B and a higher value of B underestimates the mass transfer to the matrix and overestimates the rate of migration of radionuclides through the SZ. The approach of adjusting the effective diffusion coefficient is thus an acceptable approximation for use in the SZ transport simulations. For colloid-facilitated radionuclide transport in which radionuclides are irreversibly attached to colloids, most of the colloids (and attached radionuclides) are delayed during transport in the SZ by a retardation factor. A small fraction of colloids with irreversibly attached radionuclides is subject to rapid transport without retardation, as described in Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.6). In fractured volcanic units, the retardation factor for the majority of colloids is applied directly in the SZ transport abstraction model input files as an input parameter. In porous media, it is not possible to directly specify a retardation factor in the SZ transport abstraction model; therefore, an effective sorption coefficient is specified that results in the sampled value of the retardation factor. In the porous medium of the alluvium, the colloid retardation factor in the alluvium units is converted to a value of effective sorption coefficient according to the relationship: b e f eff d R K . f ) 1 ( - = (Eq. 6-10) where Kd eff is the effective Kd in the porous media [L3/M]. Retardation in Fracture Zones As described in the conceptual model of transport in fractured media of the SZ (Section 6.3.1), relatively small blocks of rock matrix or rubblized material in fracture zones may participate in radionuclide transport via diffusion on a short time scale. The impact of rapid diffusion into small matrix blocks on the calculation of average linear velocity of groundwater is captured with a correspondingly larger value of flowing interval porosity for the volcanic units. In this conceptualization, the flowing interval porosity includes the fracture porosity with flowing groundwater plus it may include the matrix porosity of the small matrix blocks within the fracture zones. The possibility of small matrix blocks within fracture zones is encompassed Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-25 October 2004 within a range of uncertainty in transport behavior in fractured tuff. If this process of rapid diffusion occurs, the sorptive capacity of the small matrix blocks would also be important to the transport of sorbing radionuclides. This is handled in the following way: if the flowing interval porosity ( ff ) [-] is less than the average fracture porosity ( avg f f) [-], then groundwater flow is conceptualized to occur only in fractures, and no retardation due to sorption within small matrix blocks occurs. If the flowing interval porosity is greater than the average fracture porosity, then the portion of the flowing interval porosity in excess of the average fracture porosity corresponds to the matrix porosity of the small matrix blocks within the fracture zones. If the flowing interval porosity is greater than the average fracture porosity, then the retardation factor within the fracture domain due to sorption within small matrix blocks ( f R' ) is calculated as: m dm b f K fraction R f . ) * ( 1+ = ' (Eq. 6-11) where Kdm is the sorption coefficient in the rock matrix [L3/M], fm is the rock matrix porosity [-], and fraction is calculated as: ) ( ) ( avg f m avg f f fraction f f f f - - = (Eq. 6-12) The term fraction [-] describes the fraction of the entire rock matrix that is accessible to rapid matrix diffusion within the small matrix blocks of the fracture zone. Typically, the value of fraction would be small for the range of uncertainty in flowing interval porosity. For example, if the flowing interval porosity is 0.01 (80th percentile from Figure 6-13), the rock matrix porosity is 0.20, and the average fracture porosity is 0.001, then the value of fraction is 0.045. This means that 4.5 percent of the total rock matrix is available for direct interaction with radionuclide advection and sorption. 6.5.1.2 SZ 1-D Transport Model The SZ 1-D transport model provides simulation results for several radionuclide chains that are not simulated in the SZ transport abstraction model. The simplified decay chains considered (CRWMS M&O 2000 [DIRS 153246], Figure 3.5-5, p. F3-67) consist of the following. 1. Actinium series: Pa U Pu Am 231 235 239 243 . . . 2. Neptunium Series: Th U Np Am 229 233 237 241 . . . 3. Thorium Series: Th U Pu 232 236 240 . . Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-26 October 2004 4. Uranium Series: Ra Th U Pu U Pu 226 230 234 238 238 242 . . . . . . . The radionuclide decay chain analysis is simplified in a manner that overestimates the concentration of decay product-radionuclides by calculating secular equilibrium between the final decay products and their parents in three of these chains. 227Ac is in secular equilibrium with 231Pa in the actinium chain at the downstream end of the SZ analysis. Radium-228 is in secular equilibrium with 232Th in the thorium series. Lead-210 is in secular equilibrium with 226Ra in the uranium series. The mass of the final daughter in the neptunium series is explicitly simulated. In the model setup, radioisotopes of Am and Pu are subject to transport as irreversibly attached to colloids; and radioisotopes of Am, Pu, Th, Pa, and Cs are subject to the equilibrium colloid-facilitated transport mode. The 1-D model is set up using the Pathway Component of the Contaminant Transport Module in the GoldSim Graphical Simulation Environment. The pipe component is able to simulate advection, longitudinal dispersion, retardation, decay and ingrowth, and matrix diffusion (Figure 6-5) (Miller and Kossik 1998 [DIRS 100449]). Sources: GoldSim V7.50.100; figure from Miller and Kossik 1998 [DIRS 100449]. Figure 6-5. Transport Processes Simulated in 1-D Pipe Pathways in the GoldSim V7.50.100 Software Code Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-27 October 2004 Each pipe in the GoldSim V7.50.100 software code represents a 1-D mass transport model with uniform properties, as illustrated conceptually in Figure 6-5. The ratio of the volumetric outflow rate to the cross-sectional area of each pipe pathway represents the specific discharge in the pipe. A mass flux loading at the beginning of the first pipe is the source of the radionuclides that are transported along the connected pipes. The GoldSim V7.50.100 software code also provides a graphical container that isolates all of the model components in one compartment, to better organize the model components graphically on screen. Transport from the four source regions in the SZ is represented by four sets of connected pipes in the SZ 1-D transport model. Each set of pipes consists of three pipe segments. The first segment extends from the center of the corresponding source region beneath the repository to a distance of 5 km. The second pipe segment extends from 5 km to the contact between the volcanic aquifer and the alluvium. The third pipe segment extends from the contact between the volcanic aquifer and the alluvium to the regulatory boundary with the accessible environment. The mathematical representation of radionuclide transport in the SZ 1-D transport model is the same as that in the SZ transport abstraction model, as presented in Equation 6-2 to Equation 6-5 and Equation 6-9. There are some differences in the mathematical implementation between the models with regard to retardation in fractures, as described below. In the SZ 1-D transport model the retardation factor in fractures cannot be directly specified. The retardation in fractures for colloids with irreversibly attached radionuclides is calculated according to the retardation factor (CORVO) of the colloids using the fracture coating option in the GoldSim V7.50.100 software code. The equation for calculating the retardation factor in the fracture with the coating on the fracture surface is: ) ( 1 , , c s c c p m s m K A PT R f . f + + = (Eq. 6-13) where Rm,s is the retardation factor due to the coating [-], P is the perimeter of the fracture pathway [L], T is the thickness of the coating [L], Am is the cross-sectional area of the mobile zone [L2], p f is the porosity in the pipe (equal to 1.0 for fractures) [-], .c is the dry bulk density of the coating material [M/L3], Kc,s is the sorption coefficient of the coating [L3/M], and c f is the porosity of the coating material [-]. For a given value of Rm,s, the sorption coefficient is specified by rearranging Equation 6-13: ( ) .. . .. . - - = c s m p m c s c R PT A K f f . 1 1 , , (Eq. 6-14) It should be noted that representation of retardation in the fractures using the coating option in the GoldSim V7.50.100 software code is for mathematical convenience only. The retardation factor for colloids with irreversibly attached radionuclides is specified as an input parameter in the SZ 1-D transport model, and a corresponding value of the sorption coefficient of the fracture coating is calculated using Equation 6-14 within the parameter definitions used in the model. This does not constitute an inconsistency in the conceptual model between the SZ 1-D transport Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-28 October 2004 model and the SZ transport abstraction model. The values of the parameters T (0.0001 m) and c f (0.01) are chosen to be realistic, but are essentially irrelevant because they are only used to back-calculate the value of Kc,s. The value of the fracture perimeter is 2 m because the cross section of the pipes in the SZ 1-D transport model is specified as 1 m by 1m, and a single fracture within the pipe would have a corresponding perimeter of 2 m. There is no matrix diffusion in fractured media for colloids with irreversibly attached radionuclides. Consequently, there is no sorption in the matrix for radionuclides irreversibly attached to colloids. This is simulated by specifying an arbitrarily small value of matrix porosity (approximately 10-10) and zero sorption coefficients for these species in the volcanic matrix. The matrix diffusion coefficient for those radionuclides that do experience matrix diffusion is implemented by calculating an effective tortuosity, based on the sampled value of effective diffusion coefficient and the free water diffusion coefficient. The free water diffusion coefficient is adjusted by a factor approximately equivalent to the volcanic matrix porosity, using the parameter “Adjusted_Diffusion_Free” to match results from the 3-D SZ site-scale transport model. Values of specific discharge for segments represented by pipe pathways in the SZ 1-D transport model vary along the flow path from the repository. A plot of the particle paths in the SZ transport abstraction model indicates that the flow path length through the alluvium varies, depending on uncertainty in the SZ flow field (see Figure 6-6). This uncertainty is represented by variation in the geometry of the alluvial uncertainty zone in the SZ transport abstraction model. Specifically, the lengths of the flow paths in the volcanic units and the alluvium are functions of the western boundary of the alluvial uncertainty zone (as controlled by the FPLAW stochastic parameter). Secondarily, this variability is the result of different flow paths (i.e., width of the plume). The lengths of the flow paths are also functions of the anisotropy ratio in horizontal permeability of the volcanic units (as controlled by the HAVO stochastic parameter) (see Figure 6-6). In the 1-D radionuclide transport model, the length of the alluvium (out to an 18-km distance) is varied from 2 km to 10 km as functions of the FPLAW and HAVO parameter values and the source region beneath the repository (see Table 6-7 and supporting text). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-29 October 2004 535000 540000 545000 550000 555000 560000 UTM Easting (m) 4050000 4055000 4060000 4065000 4070000 4075000 4080000 4085000 4090000 UTM Northing (m) Source: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]). NOTE: Green lines, purple lines, blue lines, yellow lines, and red lines show simulated particle paths for horizontal anisotropy values of 0.05, 0.20, 1.0, 5.0, and 20.0, respectively. Figure 6-6. Simulated Particle Paths for Different Values of Horizontal Anisotropy in Permeability The SZ 1-D transport model represents a significant simplification of the 3-D groundwater flow system, relative to the SZ transport abstraction model. To accurately capture the 3-D characteristics of the SZ flow and transport system in this 1-D model, the SZ 1-D transport model is divided into three sets of “pipe” segments. The lengths and groundwater flow rates of these “pipe” segments are estimated from the SZ transport abstraction model. Average specific discharge along different segments of the flow path is estimated using the SZ transport abstraction model in the following way: 1,000 particles are released from a point beneath the repository (as shown in Figure 6-6) in the simulation, matrix diffusion is not used, and all porosities are assigned a value of 1.0 for the assessment of average specific discharge. The average specific discharge is calculated by dividing the flow path length by the 50th percentile of travel times among the particles, for that flow path segment. The average Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-30 October 2004 specific discharge also varies as a function of the horizontal anisotropy (parameter HAVO). The resulting values of average specific discharge, as used in the SZ 1-D transport model, are shown in Table 6-6. The values in Table 6-6 are input as a GoldSim V7.50.100 software code look-up table in the SZ 1-D transport model. Note that the values of specific discharge scale linearly with the groundwater specific discharge-scaling factor (parameter GWSPD) for the consideration of uncertainty in specific discharge. The values of specific discharge within the three pipe segments are calculated within the model by interpolating between the values of HAVO and scaling by the value of GWSPD. The volumetric flow rate is the same for all segments in the SZ 1-D transport model, and the variations in specific discharge along the flow path are incorporated by varying the cross-sectional areas of the pipe segments. Table 6-6. Average Specific Discharge in Flow Path Segments HAVO Average Specific Discharge (m/year) 0-5 km 5-13 km 13-18 km 0.05 0.312 7.50 1.936 1.00 0.536 1.824 2.357 5.00 0.722 2.694 2.793 20.00 0.870 4.465 3.183 The impacts of different climate states are implemented in the SZ 1-D transport model in a manner similar to the SZ transport abstraction model. The specific discharge within all pipe segments of the SZ 1-D transport model is scaled by the groundwater flow factors given in Table 6-5 for the monsoonal and glacial-transition climate states. Application of this scaling begins at the time of climate change. However, an important limitation of the Laplace transform solution used for radionuclide transport simulation within the pipe segments in the SZ 1-D transport model should be noted. Radionuclide mass already within a given pipe segment of the SZ 1-D transport model does not increase in velocity in response to increased specific discharge resulting from climate change. Radionuclide mass introduced after the change in specific discharge is transported at the proper, correspondingly faster rate. The impacts of this limitation to calculations of peak dose in the TSPA-LA model are not large due to the following considerations: the SZ 1-D transport model results are used only for the daughter products of the decay chains in the TSPA-LA calculations and these daughter products are only minor contributors to total simulated dose. This limitation applies only to radionuclide mass that enters a given pipe segment prior to 2,000 years, after which glacial-transition climatic conditions continue unchanged. In addition, only radionuclide mass that enters the SZ 1-D transport model prior to 600 years, at the time of change from present to monsoonal conditions, would experience this limitation to a large extent. Finally, this limitation applies only to an individual pipe segment, and the entire SZ 1-D transport model is composed of three pipe segments. This computational limitation thus applies only to a part of the total transport pathway in the SZ for any given unit of radionuclide mass. The flow path length of each pipe segment in the SZ 1-D transport model varies as a function of FPLAW, HAVO, and the source region from which the radionuclide source originates beneath the repository. The first pipe segment is 5 km in length for all cases. The second pipe segment represents that portion of the flow path from the 5-km distance to the contact between the volcanic units and the alluvium in the SZ. The third pipe segment represents the portion of the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-31 October 2004 flow path from the contact between the volcanic units and the alluvium out to the regulatory boundary to the accessible environment. The lengths of the second and third pipe segments were estimated from the particle tracking results of the 3-D SZ transport abstraction model, as shown in Figure 6-6 and as summarized in Table 6-7. The estimated pipe segment lengths are shown in Table 6-7 for differing values of HAVO and for the four source regions. Each entry in the table contains a range of values in length, where the minimum value shown for the 5-to-13-km pipe segment (second pipe segment) corresponds to FPLAW equal to 1.0 and the maximum value corresponds to FPLAW equal to 0.0. By contrast, the minimum value of length for the 13-to-18-km pipe segment (third pipe segment) corresponds to FPLAW equal to 0.0 and the maximum value corresponds to FPLAW equal to 1.0. In other words, the maximum length of the flow path in the alluvium corresponds to the maximum westerly extent of the alluvium uncertainty zone, and the minimum length of the flow path in the alluvium corresponds to the minimum westerly extent of the alluvium uncertainty zone. The values in Table 6-7 are input as a GoldSim V7.50.100 software code look-up table in the SZ 1-D transport model. Table 6-7. Flow Path Lengths of Pipe Segments Minimum and Maximum Flow Path Lengths of Pipe Segments (km) Source Region 1 Source Region 2 Source Region 3 Source Region 4 HAVO 5 – 13 km 13 – 18 km 5 – 13 km 13 – 18 km 5 – 13 km 13 – 18 km 5 – 13 km 13 – 18 km 0.05 12.0 – 14.5 7.5 – 10.0 12.0 – 14.0 7.0 – 9.0 13.0 – 16.0 3.0 – 6.0 12.5 – 15.0 3.5 – 6.0 1.00 12.0 – 14.0 5.5 – 7.5 12.0 – 14.5 4.5 – 7.0 10.0 – 13.5 2.0 – 5.5 10.0 – 12.0 3.0 – 5.0 5.00 12.5 – 14.5 3.0 – 5.0 11.5 – 14.0 3.0 – 5.5 10.5 – 14.0 1.0 – 4.5 10.5 – 12.5 2.0 – 4.0 20.00 12.5 – 14.5 2.5 – 4.5 11.5 – 14.0 3.0 – 5.5 10.5 – 14.0 1.0 – 4.5 10.5 – 12.5 2.0 – 4.0 HAVO=horizontal anisotropy 6.5.2 Base-Case Model Inputs The SZ transport abstraction model and the SZ 1-D transport model include uncertainty through stochastic simulations of uncertain parameters. Parameter uncertainties are quantified through uncertainty distributions, which numerically represent our state of knowledge about a particular parameter on a scale of the model domain. The uncertainty distribution (either cumulative distribution function (CDF) or probability density function (PDF)) of a parameter, represents what is known and what is unknown about the parameter, and reflects the current knowledge of the range and likelihood of the appropriate parameter values when used in these models (BSC 2002 [DIRS 158794], p. 45). The uncertainty distributions incorporate uncertainties associated with field or laboratory data, knowledge of how the parameter will be used in the model, and theoretical considerations. Geologic uncertainty is incorporated with regard to the location of the contact between the tuff and alluvium at the water table (see Section 6.5.2.2). In some cases, parameters are assigned constant values because radionuclide transport is relatively insensitive to the parameter, or the uncertainty is relatively small. Constant parameters are defined to vary from one hydrogeologic unit to another, but for a given hydrogeologic unit, the parameter remains constant for all realizations. The development and justification for the parameter uncertainty distributions are discussed below. See Table 6-8 for a comprehensive list of the models/analyses inputs used in the SZ transport abstraction model and the SZ 1-D transport model. The unit numbers given in Table 6-8 are defined by hydrogeologic unit Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-32 October 2004 in Table 6-9. Please note that parameter values are developed for the 19 hydrogeologic units in Table 6-9 for completeness; however, 18 units are included in the SZ site-scale flow model, the SZ site-scale transport model, and the SZ transport abstraction model. The valley-fill confining unit has a very small volume relative to other units in the model domain, and there are no occurrences of this unit along the flow path from the repository. Consequently, it is not included in the models as a separate unit. Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty KDNPVO Neptunium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 0.0 0.05 0.99 0.90 1.83 1.0 6.0 mL/g Epistemic KDNPAL Neptunium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 1.8 0.05 4.0 0.95 8.7 1.0 13.0 mL/g Epistemic KDSRVO Strontium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 20. Maximum 400. mL/g Epistemic KDSRAL Strontium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 20. Maximum 400. mL/g Epistemic KDUVO Uranium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 0.0 0.05 5.39 0.95 8.16 1.0 20.0 mL/g Epistemic KDUAL Uranium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 1.7 0.05 2.9 0.95 6.3 1.0 8.9 mL/g Epistemic KDRAVO Radium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 100. Maximum 1000. mL/g Epistemic Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-33 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty KDRAAL Radium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] Uniform: Minimum 100. Maximum 1000. mL/g Epistemic KD_Pu_Vo Plutonium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 10. 0.25 89.9 0.95 129.87 1.0 300. mL/g Epistemic KD_Pu_Al Plutonium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] Beta: Mean 100. Standard Deviation 15. Minimum 50. Maximum 300. mL/g Epistemic KD_Am_Vo Americium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. mL/g Epistemic KD_Am_Al Americium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. mL/g Epistemic KD_Cs_Vo Cesium sorption coefficient in volcanic units LA0310AM831341.002 [DIRS 165891] CDF: Probability Value 0.0 100. 0.05 3000.59 1.0 6782.92 mL/g Epistemic KD_Cs_Al Cesium sorption coefficient in alluvium LA0310AM831341.002 [DIRS 165891] Truncated Normal: Mean 728. Standard Deviation 464. Minimum 100. Maximum 1000. mL/g Epistemic FISVO Flowing interval spacing in volcanic units SN9907T0571599.001 [DIRS 122261] CDF : (Log10-transformed) Probability Value 0.0 0.087 0.05 0.588 0.25 1.00 0.50 1.29 0.75 1.58 0.95 1.90 1.0 2.62 m Epistemic Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-34 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty CORAL Colloid retardation factor in alluvium LA0303HV831352.004 [DIRS 163559] CDF : (Log10-transformed) Probability Value 0.0 0.903 0.331 0.904 0.50 1.531 1.0 3.715 N/A Epistemic CORVO Colloid retardation factor in volcanic units LA0303HV831352.002 [DIRS 163558] CDF : (Log10-transformed) Probability Value 0.0 0.778 0.15 0.779 0.25 1.010 0.50 1.415 0.80 1.778 1.0 2.903 N/A Epistemic HAVO Ratio of horizontal anisotropy in permeability SN0302T0502203.001 [DIRS 163563] CDF: Probability Value 0.0 0.05 0.0042 0.2 0.0168 0.4 0.0379 0.6 0.0674 0.8 0.10 1.0 0.60 5. 0.744 8. 0.856 11. 0.936 14. 0.984 17. 1.0 20. N/A Epistemic LDISP Longitudinal dispersivity MO0003SZFWTEEP.000 [DIRS 148744] Truncated Normal: (Log10- transformed) Mean 2.0 Standard Deviation 0.75 m Epistemic Kd_Pu_Col Plutonium sorption coefficient onto colloids SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e3 0.04 5.e3 0.12 1.e4 0.37 5.e4 0.57 1.e5 0.92 5.e5 1.0 1.e6 mL/g Epistemic Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-35 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty Kd_Am_Col Americium sorption coefficient onto colloids SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e4 0.07 5.e4 0.17 1.e5 0.40 5.e5 0.60 1.e6 0.92 5.e6 1.0 1.e7 mL/g Epistemic Kd_Cs_Col Cesium sorption coefficient onto colloids SN0306T0504103.006 [DIRS 164131] CDF: Probability Value 0.0 1.e2 0.2 5.e2 0.45 1.e3 0.95 5.e3 1.0 1.e4 mL/g Epistemic Conc_Col Groundwater concentration of colloids SN0306T0504103.005 [DIRS 164132] CDF : (Log10-transformed) Probability Value 0.0 -9.0 0.50 -7.0 0.75 -6.0 0.90 -5.0 0.98 -4.3 1.0 -3.7 g/mL Epistemic R_U_Kd Correlation coefficient for U Kd in volcanic units and alluvium LA0310AM831341.002 [DIRS 165891] 0.75 N/A N/A R_Np_Kd Correlation coefficient for Np Kd in volcanic units and alluvium LA0310AM831341.002 [DIRS 165891] 0.75 N/A N/A R_Pu_Kd Correlation coefficient for Pu Kd in volcanic units and alluvium LA0310AM831341.002 [DIRS 165891] 0.50 N/A N/A R_U_Np Correlation coefficient for U Kd and Np Kd LA0310AM831341.002 [DIRS 165891] 0.50 N/A N/A FPLAW Western boundary of alluvial uncertainty zone Internal to this report Uniform: Minimum 0.0 Maximum 1.0 N/A Epistemic FPLAN Northern boundary of alluvial uncertainty zone Internal to this report Uniform: Minimum 0.0 Maximum 1.0 N/A Epistemic Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-36 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty NVF19 Effective porosity in shallow alluvium Internal to this report Truncated Normal: Mean 0.18 Standard Deviation 0.051 Minimum 0.00 Maximum 0.30 N/A Epistemic NVF7 Effective porosity in undifferentiated valley fill Internal to this report Truncated Normal: Mean 0.18 Standard Deviation 0.051 Minimum 0.00 Maximum 0.30 N/A Epistemic FPVO Fracture porosity in volcanic units Internal to this report CDF: (Log10-transformed) Probability Value 0.0 -5.0 0.05 -4.0 0.50 -3.0 0.80 -2.0 1.0 -1.0 N/A Epistemic DCVO Effective diffusion coefficient in volcanic units Internal to this report CDF: (Log10-transformed) Probability Value 0.0 -11.3 0.08 -10.7 0.50 -10.3 0.83 -9.9 1.0 -9.3 m2/s Epistemic GWSPD Groundwater specific discharge multiplier Internal to this report CDF: (Log10-transformed) Probability Value 0.0 -1.477 0.10 -0.477 0.50 0.0 0.90 0.477 1.0 1.0 N/A Epistemic bulkdensity Bulk density of alluvium Internal to this report Normal: Mean 1910 Standard Deviation 78 kg/m3 Epistemic SRC1X SRC1Y SRC2X SRC2Y SRC3X SRC3Y SRC4X SRC4Y Source regions beneath the repository Internal to this report Uniform: Minimum 0.0 Maximum 1.0 N/A Epistemic and Aleatory Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-37 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty Alluv_xmin1 UTM minimum easting, SW corner alluvial uncertainty zone Internal to this report 548285. m N/A Alluv_xmax1 UTM maximum easting, SW corner alluvial uncertainty zone Internal to this report 546669. m N/A Alluv_ymin1 UTM minimum northing, SW corner alluvial uncertainty zone Internal to this report 4057240. m N/A Alluv_ymax1 UTM maximum northing, SW corner alluvial uncertainty zone Internal to this report 4057620. m N/A Alluv_xmin2 UTM minimum easting, SE corner alluvial uncertainty zone Internal to this report 555550. m N/A Alluv_xmax2 UTM maximum easting, SE corner alluvial uncertainty zone Internal to this report 555550. m N/A Alluv_ymin2 UTM minimum northing, SE corner alluvial uncertainty zone Internal to this report 4055400. m N/A Alluv_ymax2 UTM maximum northing, SE corner alluvial uncertainty zone Internal to this report 4055400. m N/A Alluv_xmin3 UTM minimum easting, NE corner alluvial uncertainty zone Internal to this report 557424. m N/A Alluv_xmax3 UTM maximum easting, NE corner alluvial uncertainty zone Internal to this report 557758. m N/A Alluv_ymin3 UTM minimum northing, NE corner alluvial uncertainty zone Internal to this report 4065430. m N/A Alluv_ymax3 UTM maximum northing, NE corner alluvial uncertainty zone Internal to this report 4067430. m N/A Alluv_xmin4 UTM minimum easting, NW corner alluvial uncertainty zone Internal to this report 554192. m N/A Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-38 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty Alluv_xmax4 UTM maximum easting, NW corner alluvial uncertainty zone Internal to this report 553579. m N/A Alluv_ymin4 UTM minimum northing, NW corner alluvial uncertainty zone Internal to this report 4065430. m N/A Alluv_ymax4 UTM maximum northing, NW corner alluvial uncertainty zone Internal to this report 4067430. m N/A A1_1_x UTM easting, SW corner source zone 1 Internal to this report 547570. m N/A A1_1_y UTM northing, SW corner source zone 1 Internal to this report 4078630. m N/A A1_2_x UTM easting, SE corner source zone 1 Internal to this report 548500. m N/A A1_2_y UTM northing, SE corner source zone 1 Internal to this report 4078630. m N/A A1_3_x UTM easting, NE corner source zone 1 Internal to this report 548500. m N/A A1_3_y UTM northing, NE corner source zone 1 Internal to this report 4081090. m N/A A1_4_x UTM easting, NW corner source zone 1 Internal to this report 547570. m N/A A1_4_y UTM northing, NW corner source zone 1 Internal to this report 4081090. m N/A A2_1_x UTM easting, SW corner source zone 2 Internal to this report 548500. m N/A A2_1_y UTM northing, SW corner source zone 2 Internal to this report 4078630. m N/A A2_2_x UTM easting, SE corner source zone 2 Internal to this report 549320. m N/A A2_2_y UTM northing, SE corner source zone 2 Internal to this report 4078630. m N/A A2_3_x UTM easting, NE corner source zone 2 Internal to this report 549320. m N/A Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-39 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty A2_3_y UTM northing, NE corner source zone 2 Internal to this report 4081210 m N/A A2_4_x UTM easting, NW corner source zone 2 Internal to this report 548500. m N/A A2_4_y UTM northing, NW corner source zone 2 Internal to this report 4081210. m N/A A3_1_x UTM easting, SW corner source zone 3 Internal to this report 547720. m N/A A3_1_y UTM northing, SW corner source zone 3 Internal to this report 4076170. m N/A A3_2_x UTM easting, SE corner source zone 3 Internal to this report 548500. m N/A A3_2_y UTM northing, SE corner source zone 3 Internal to this report 4076170. m N/A A3_3_x UTM easting, NE corner source zone 3 Internal to this report 548500. m N/A A3_3_y UTM northing, NE corner source zone 3 Internal to this report 4078630. m N/A A3_4_x UTM easting, NW corner source zone 3 Internal to this report 547720. m N/A A3_4_y UTM northing, NW corner source zone 3 Internal to this report 4078630. m N/A A4_1_x UTM easting, SW corner source zone 4 Internal to this report 548500. m N/A A4_1_y UTM northing, SW corner source zone 4 Internal to this report 4076170. m N/A A4_2_x UTM easting, SE corner source zone 4 Internal to this report 548890. m N/A A4_2_y UTM northing, SE corner source zone 4 Internal to this report 4076170. m N/A A4_3_x UTM easting, NE corner source zone 4 Internal to this report 548890. m N/A Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-40 October 2004 Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D Transport Model (Continued) Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty A4_3_y UTM northing, NE corner source zone 4 Internal to this report 4078630. m N/A A4_4_x UTM easting, NW corner source zone 4 Internal to this report 548500. m N/A A4_4_y UTM northing, NW corner source zone 4 Internal to this report 4078630. m N/A Max_al_por Total alluvium porosity Internal to this report 0.30 N/A N/A Fpor Average fracture porosity in volcanic units Internal to this report 0.001 N/A N/A Mpor Average matrix porosity in volcanic units Internal to this report 0.22 N/A N/A Bdens Average bulk density in volcanic units Internal to this report 1.88 g/mL N/A Matrix porosity Expected values for matrix porosity per volcanic unit SN0004T0501399.003 [DIRS 155045] Units 15- 13, 10 and 8 Units 12, 11, and 9 are internal to this report Unit 15: 0.15 Unit 14, 10, and 8: 0.25 Unit 13: 0.23 Unit 12: 0.18 Unit 11: 0.21 Unit 9: 0.21 N/A N/A Bulk Density Expected bulk density values per volcanic unit Units 15-13, 10, 8; DTN: SN0004T0501399.002 [DIRS 155046] and SN0004T0501399.003 [DIRS 155045] Units 17, 12, 11, 9, and 6-2 are internal to this report Unit 18: 2.50 Unit 17, 6, 5, and 3: 2.77 Unit 16: 2.44 Unit 15: 2.08 Unit 14, 10 and 8: 1.77 Unit 13: 1.84 Unit 12: 2.19 Unit 11: 2.11 Unit 9: 2.05 Unit 4 and 2: 2.55 Unit 1: 2.65 g/cm3 N/A Effective Porosity Expected effective porosity values for other units (see Section 6.5.2.20) Units 18-16 and 1: DTN: MO0105HCONEPOR.00 0 [DIRS 155044] Units 6-2 Internal to this report Unit 18: 0.32 Unit 17: 0.01 Unit 16: 0.08 Unit 6,5 and 3: 0.01 Unit 4: 0.18 Unit 2: 0.18 Unit 1: 0.0001 N/A N/A CDF=cumulative distribution function; UTM=Universal Transverse Mercator NOTE: Unit numbers refer to hydrogeologic units in Table 6-9 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-41 October 2004 Table 6-9. Hydrogeologic Unit Definition Hydrogeologic Unit Hydrogeologic Unit Identification Number Valley Fill 19 Valley Fill Confining Unit 18 Cenozoic Limestones 17 Lava Flows 16 Upper Volcanic Aquifer 15 Upper Volcanic Confining Unit 14 Lower Volcanic Aquifer Prow Pass 13 Lower Volcanic Aquifer Bullfrog 12 Lower Volcanic Aquifer Tram 11 Lower Volcanic Confining Unit 10 Older Volcanic Aquifer 9 Older Volcanic Confining Unit 8 Undifferentiated Valley Fill 7 Upper Carbonate Aquifer 6 Lower Carbonate Aquifer Thrust 5 Upper Clastic Confining Unit 4 Lower Carbonate Aquifer 3 Lower Clastic Confining Unit 2 Granites 1 NOTE: Hydrogeologic Units adapted from Hydrogeologic Framework Model for the Saturated-Zone Site- Scale Flow and Transport Model (BSC 2004 [DIRS 170008], Table 6-1). 6.5.2.1 Groundwater Specific Discharge Uncertainty exists in the groundwater specific discharge in the SZ along the flow path from beneath the repository to the hypothetical point of release into the biosphere. This uncertainty was quantified as a distribution of specific discharge in the volcanic aquifer near Yucca Mountain by the SZ expert elicitation (CRWMS M&O 1998 [DIRS 100353], p. 3-43). This expert elicitation was conducted in a manner consistent with Branch Technical Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program (NUREG-1563) (Kotra et al. 1996 [DIRS 100909]). Conclusions regarding the uncertainty in specific discharge by the expert elicitation panel primarily were based on single- and multi-well hydraulic testing of wells in the fractured volcanic units near Yucca Mountain. The aggregate uncertainty distribution of specific discharge in the SZ from the expert elicitation had a median value of about 0.6 m/year, with a range of values from less than 0.01 m/year to about 10 m/year (CRWMS M&O 1998 [DIRS 100353], p. 3-43). It should be noted that the experts in the SZ expert elicitation were only elicited regarding uncertainty in specific discharge within about 5 km of the repository. More recently, estimates of groundwater specific discharge in the SZ have been obtained at another location in the SZ system: from field-testing at the alluvial tracer complex (ATC) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-42 October 2004 (BSC 2004 [DIRS 170010], Section 6.5.4.3). The ATC is approximately located at the boundary of the accessible environment, as specified in regulations for the Yucca Mountain project, 10 CFR 63.302 (10 CFR 63 [DIRS 156605]). The location of the ATC is approximately 18 km from Yucca Mountain, and testing was performed in the alluvium aquifer. Estimates of groundwater specific discharge at the ATC range from 1.2 m/year to 9.4 m/year (DTN: LA0303PR831231.002, [DIRS 163561]), using alternative means of analyzing the single-well tracer testing results. The simulated average specific discharge in this region of the SZ system using the SZ transport abstraction model ranges from 1.9 m/year to 3.2 m/year for differing values of horizontal anisotropy in permeability, as shown in Table 6-6. Correspondingly, the simulated average specific discharge in the volcanic aquifer near Yucca Mountain using the SZ transport abstraction model ranges from 0.31 m/year to 0.87 m/year for differing values of horizontal anisotropy in permeability. These results show that the average groundwater specific discharge tends to increase along the flow path from beneath Yucca Mountain to the south. This increase in the specific discharge is due to convergent groundwater flow in this region of the SZ system. These results also indicate that there is general consistency between the simulated specific discharge and the median values of uncertainty ranges estimated for the volcanic aquifer and the alluvial aquifer along the flow path. The additional data from the ATC constitutes new information on the specific discharge in the SZ, and significantly reduces uncertainty in the specific discharge relative to the assessment by the expert elicitation panel. Estimates of specific discharge at the ATC range from 1.2 m/year to 9.4 m/year; the upper end of the range is 7.8 times the lower end of the range. This range of uncertainty in specific discharge is somewhat less than one order of magnitude, which is considerably less than the degree of uncertainty from the SZ expert elicitation project (CRWMS M&O 1998 [DIRS 100353]). Consequently, the uncertainty distribution for the groundwater specific discharge factor (GWSPD) is reevaluated to reflect the reduced uncertainty. From this information, a discrete CDF of uncertainty in specific discharge is constructed, in which 80 percent of the probability is between 1/3 and 3 times the best estimate of specific discharge. The lower tail of the uncertainty distribution extends to 1/30 of the expected value and 10 percent of the probability is assigned to this lower tail. The upper tail of the uncertainty distribution extends to 10 times the expected value and 10 percent of the probability is assigned to this upper tail. The lower and upper tails of the uncertainty distribution approximately correspond to the greater uncertainty reflected in the SZ expert elicitation results. The resulting wide total range of uncertainty in specific discharge implicitly includes the potential existence of undetected features in the SZ, such as fault and fracture zones that could significantly impact groundwater flow. Uncertainty in the groundwater specific discharge is incorporated into the SZ transport abstraction model using the continuously distributed GWSPD parameter. This parameter is a multiplication factor that is applied to all values of permeability and values of specified boundary fluxes in the SZ transport abstraction model to effectively scale the simulated specific discharge in the model. Note that a separate steady-state groundwater flow field is simulated for each realization of the system, using the value of GWSPD (and the value of HAVO, for horizontal anisotropy). The sampling of GWSPD is performed on the log-transformed values of the specific discharge multiplication factor, as indicated in Table 6-8. The CDF of uncertainty in the groundwater specific discharge multiplier is shown in Figure 6-7. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-43 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 1.0 Cumulative Probability Log Groundwater Specific Discharge Multiplier Output DTN: SN0310T0502103.009. Figure 6-7. CDF of Uncertainty in Groundwater Specific Discharge Multiplier 6.5.2.2 Alluvium Uncertainty Zone Uncertainty exists in the geology below the water table, along the inferred flow path from the repository at distances of approximately 10 km to 20 km downgradient of the repository. The location at which groundwater flow moves from fractured volcanic rocks to alluvium is of particular significance from the perspective of repository performance assessment. This is because of contrasts between the fractured volcanic units and the alluvium in terms of groundwater flow (fracture-dominated flow versus porous medium flow) and in terms of sorptive properties of the media for some radionuclides. The uncertainty in the northerly extent of the alluvium in the SZ of the site-scale flow and transport simulations is abstracted as a polygonal region that is assigned radionuclide transport properties representative of the valley-fill aquifer hydrogeologic unit (Table 6-9). The dimensions of the polygonal region are randomly varied in the SZ transport abstraction model for the multiple realizations. The northern boundary of the uncertainty zone is varied between the dashed lines at the northern end of the polygonal area shown in Figure 6-8. The western boundary of the uncertainty zone is varied between the dashed lines along the western side of the polygonal area shown in the figure. The uncertainty in the contact between volcanic rocks and alluvium at the water table along the northern part of the uncertainty zone is approximately bounded by the location of well UE-25 JF#3, in which the water table is below the contact between the volcanic rocks and the overlying alluvium, and by the location of well EWDP-10S, in which the water table is above the contact between the volcanic rocks and the alluvium. The uncertainty in the contact along the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-44 October 2004 western part of the uncertainty zone is defined by the locations of wells EWDP-10S, EWDP-22S, and EWDP-19D1, in which the water table is above the contact between volcanic rocks and the overlying alluvium, and outcrops of volcanic bedrock to the west. The lower boundary of the alluvium uncertainty zone varies from an elevation of 670 m in the northwestern corner of the uncertainty zone to 400 m along the southern edge of the uncertainty zone. This corresponds to a saturated alluvium thickness of approximately 50 m in the northwestern corner varying to about 300 m along the southern boundary of the uncertainty zone. The boundaries of the alluvium uncertainty zone are determined for a particular realization by the parameters FPLAW and FPLAN. These parameters have uniform distributions from 0.0 to 1.0, where a value of 0.0 corresponds to the minimum extent of the uncertainty zone and 1.0 corresponds to the maximum extent of the uncertainty zone in a westerly direction and northerly direction, respectively. A uniform distribution is appropriate for these uncertainty distributions because only the bounding values are known. A uniform distribution is the best statistically unbiased choice in this situation. These parameters are used to independently and uniformly vary the northern and western contacts of the volcanic rocks and alluvium at the water table. The maximum and minimum coordinates of the alluvium uncertainty zone, corresponding to the plot shown in Figure 6-8, are given in Table 6-8 (Alluv_xmin1 to Alluv_ymax4). 6.5.2.3 Effective Porosity of Alluvium For the TSPA Site Recommendation (SR) calculations, effective porosity in the alluvium was a truncated normal distribution with a mean of 0.18, a standard deviation of 0.051, a lower bound of 0, and an upper bound of 0.35 (CRWMS M&O 2000 [DIRS 153246], Table 3.8-3). The basis for this parameter is from Bedinger et al. (1989 [DIRS 129676], p. A18, Table 1). There were no site-specific data for effective porosity in the alluvium at the time of the TSPA-SR. Bedinger et al. (1989 [DIRS 129676]) include a study of hydraulic characteristics of alluvium within the Basin and Range Province of the Southwestern U.S. This study is relevant to the local basin fill conditions, and provides values for effective porosity as a stochastic parameter. Since the TSPA-SR, a site-specific value was determined for effective (or flow) porosity from well EWDP-19D1 at the ATC, based on a single-well pumping test (BSC 2004 [DIRS 170010], Section 6.5.4.2.4). There are also total porosity values from the same well based on borehole gravimeter surveys, which are used in developing the upper bound of the effective porosity in the alluvium uncertainty distribution. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-45 October 2004 Sources: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]); well locations are from DTNs: GS010908312332.002 [DIRS 163555]; GS030108314211.001 [DIRS 163483]. NOTE: The repository outline is shown by the solid line, and the minimum and maximum boundaries of the alluvium uncertainty zone are shown by the dashed lines. Key well locations and well numbers are shown with the cross symbols. Figure 6-8. Minimum and Maximum Extent of the Alluvium Uncertainty Zone Effective porosity is important for determining the average linear groundwater velocities used in the simulation of radionuclide transport. They are customarily calculated by dividing the specific discharge of groundwater through a model grid cell by the porosity, fe . Groundwater velocities are rendered more accurate when dead-end pores are eliminated from consideration because they do not transmit water. The effective porosity results from that elimination. As a result fe will always be less than or equal to total porosity, fT. The retardation coefficient, Rf, is also a function of porosity. Reducing total porosity to fe can erroneously raise the magnitude of this value within the model. The correction for this is detailed in the Equation 6-3 discussion in Section 6.5.1. Effective porosity is treated as an uncertain parameter for the two alluvium units (19 and 7) of the nineteen SZ model hydrogeologic units. Uncertain, in this sense, means that fe will be constant spatially for each unit for any particular model realization, but that value will vary from Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-46 October 2004 one realization to the next. In comparison, constant parameters are constant spatially and do not change from realization to realization. The parameter input sources used in this analysis are described in Table 4-1, and corroborative data are discussed in this section. The uncertainty distribution used for the analysis is the distribution used for TSPA-SR, with a change to the upper bound. The effective porosity uncertainty distribution is shown in Figure 6-9. Figure 6-9 compares the distribution of Bedinger et al. (1989 [DIRS 129676]) (DTN: MO0105HCONEPOR.000 [DIRS 155044]) to distributions, ranges, and values from the other sources that were considered to develop the uncertainty distribution. The site-specific effective porosity data point of 0.1 from well EWDP-19D1 (BSC 2004 [DIRS 170010], Section 6.5) is shown on Figure 6-9. This is considered a corroborative data point, and falls within the uncertainty distribution. The upper bound of the uncertainty distribution for effective porosity is re-evaluated because of new site-specific data obtained after TSPA-SR. The new upper bound is based on the total porosity values from well EWDP-19D1 and the average of the total porosity values from the Cambric study (Burbey and Wheatcraft 1986 [DIRS 129679], pp. 23 and 24) within the NTS but several kilometers to the east, in Frenchman Flat; and total porosity shown in Tables 8-1 and 8-2 of Regional Groundwater Flow and Tritium Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, Nevada (DOE 1997 [DIRS 103021], pp. 8-5 and 8-6, see Table 6-10). The computed total porosity values from EWDP-19D1 are shown in Table 6-11, and have an average value of 0.24. The average of the total porosity values in Table 6-10 and the average of the site-specific data from well EWDP-19D1 were used to develop the upper bound of the effective porosity uncertainty distribution. Although there is considerable variability in measured total porosity within alluvial strata (see Table 6-11), an average value to define the upper bound of the uncertainty distribution is appropriate because of scaling considerations. The grid cells in the SZ site-scale transport model are 500 m by 500 m and smaller scale variations in total porosity would be averaged over this large volume of alluvium. The average total porosity value of 0.35 and the average value from EWDP-19D1 of 0.24 result in a mean of 0.30. Figure 6-10 shows the truncated normal distribution developed in this analysis for effective porosity in the alluvium (parameter NVF19 and NVF7) with a mean of 0.18, standard deviation of 0.051, a lower bound of 0, and an upper bound of 0.30. Note that parameter NVF7 has the same distribution as NVF19, and is sampled independently. The hydrogeologic units corresponding to the parameters NVF19 and NVF7 (Units 19 and 7) developed at different geologic times and under potentially differing tectonic conditions. Consequently, they may have different characteristics with regard to effective porosity and the parameters are not correlated in the sampling process. The resulting range of uncertainty in effective porosity of the alluvium implicitly accounts for the potential existence of undetected stratigraphic and sedimentological features, such as fine-grained, low-permeability facies, that could exclude groundwater flow through the alluvium aquifer. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-47 October 2004 0 1 2 3 4 5 6 7 8 9 10 0 0.1 0.2 0.3 0.4 0.5 0.6 Porosity (effective or 'total') Frequency Sources: DTN: MO0003SZFWTEEP.000 [DIRS 148744]; BSC 2004 [DIRS 170010], Section 6.5; Burbey and Wheatcraft 1986 [DIRS 129679], pp. 23 to 24; DOE 1997 [DIRS 103021], Table 8-1, p. 8-5, and Table 8-2, p. 8-6. NOTE: The dashed black line is Neuman (MO0003SZFWTEEP.000 [DIRS 148744]); the solid heavy blue line is DTN: MO0105HCONEPOR.000 [DIRS 155044]; the solid pink line is Gelhar (DTN: MO0003SZFWTEEP.000 [DIRS 148744]); the solid blue block is the effective porosity value calculated from EWDP-19D1 (BSC 2004 [DIRS 170010], Section 6.5). The single value data points do not have a y-scale value, but do correspond to the x-axis. These points are shown for comparison purposes only. The solid black triangle is DOE 1997 [DIRS 103021], Table 8-1, mean matrix porosity; the diamond outlined shapes are Burbey and Wheatcraft 1986 [DIRS 129679] total porosity; the X is DOE 1997 [DIRS 103021], Table 8-2, total porosity; and the square outlined shape is DOE 1997 [DIRS 103021], Table 8-1, mean bulk porosity. Figure 6-9. Effective Porosity Distributions and Values for Alluvium Compared Table 6-10. Total Porosity Summary ( fT) for Alluvium Reference Total Porosity Comments DOE 1997 [DIRS 103021], Table 8-1, p. 8-5 0.36 Mean bulk porosity DOE 1997 [DIRS 103021], Table 8-2, p. 8-6 0.35 Total porosity Burbey and Wheatcraft 1986 [DIRS 129679], pp. 23 to 24 0.34 Average of porosity values from Table 3 of that study Average of above 0.35 N/A Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-48 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 Cumulative Probability Effective Porosity in Alluvium Output DTN: SN0310T0502103.009. Figure 6-10. CDF of Uncertainty in Effective Porosity in Alluvium 6.5.2.4 Flowing Interval Spacing The flowing interval spacing is a key parameter in the dual porosity model that is included in the SZ transport abstraction model. A flowing interval is defined as a fractured zone that transmits fluid in the SZ, as identified through borehole flow meter surveys (see Figure 6-11). This figure shows a borehole that is intersected by multiple, irregularly spaced fractures. The figure also shows several black bands, labeled as flowing intervals, in which a flow meter survey has detected groundwater flow into (or out of) the borehole. The analysis uses the term “flowing interval spacing” as opposed to “fracture spacing,” which is typically used in the literature. Fracture spacing was not used because field data identified zones (or flowing intervals) that contain fluid-conducting fractures but do not distinguish how many or which fractures comprise the flowing interval. These data also indicate that numerous fractures between flowing intervals do not transmit significant amounts of groundwater. The flowing interval spacing is the distance between the midpoints of each flowing interval. The flowing interval approach and the resulting uncertainty distribution implicitly accounts for the potential existence of undetected features, such as fracture zones through which groundwater flow is channeled, in the fractured volcanic units of the SZ. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-49 October 2004 Source: BSC 2004 [DIRS 170014], Figure 6-1. Figure 6-11. Example of Flowing Interval Spacing for a Typical Borehole There is considerable uncertainty regarding the flowing interval spacing parameter due to the limited number of data points available. The data set used for the analysis consisted of borehole flow meter survey data. This analysis is described in detail in Probability Distributions for Flowing Interval Spacing (BSC 2004 [DIRS 170014]). There are no new data available to reevaluate the uncertainty distribution for this parameter; therefore, a CDF based on the lognormal distribution (BSC 2004 [DIRS 170014], Section 7) that was used in TSPA-SR is used as input to the TSPA-LA model, and is shown in Figure 6-12. The flowing interval spacing parameter is specified for a particular realization by the parameter FISVO. See Table 6-8 for the associated probabilities for the flowing interval spacing CDF. 6.5.2.5 Flowing Interval Porosity The flowing interval porosity is defined as the volume of the pore space through which significant groundwater flow occurs, relative to the total volume. At Yucca Mountain, rather than attempt to define the porosity within all fractures, a flowing interval is defined as the region in which significant groundwater flow occurs at a well. The fracture porosity then characterizes these flowing intervals rather than all fractures. The advantage to this definition of fracture porosity is that in situ well data may be used to characterize the parameter. The flowing interval porosity may also include the matrix porosity of small matrix blocks within fracture zones that potentially experience rapid matrix diffusion. Flowing Interval Spacing Flowing interval Borehole Fractures Fracture Spacing Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-50 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 Cumulative Probability Log Flowing Interval Spacing (m) Output DTN: SN0310T0502103.009. Figure 6-12. CDF of Uncertainty in Flowing Interval Spacing For the TSPA-SR calculations, the flowing interval (fracture) porosity probability distribution was a uniform distribution with an upper bound of log10 (flowing interval porosity) of -1.0 and a lower bound of log10 (flowing interval porosity) of -5.0 (CRWMS M&O 2000 [DIRS 147972], Section 6.7). The basis for this uncertainty distribution includes estimates of fracture porosity in intact cores of volcanic rock, and the results of pumping tests and tracer tests in the Bullfrog Tuff at the C-wells complex (CRWMS M&O 2000 [DIRS 147972], Section 6.7). The TSPA-SR probability distribution for the flowing interval porosity has been modified based on new sources of information pertaining to flowing interval porosity. New information has been derived from tests in unsaturated tuff in the Exploratory Studies Facility (ESF). Fracture porosity has been estimated in unsaturated volcanic tuff in the ESF for the middle nonlithophysal welded tuff (UZ model layer tsw34) using gas tracer testing. The assumptions used in obtaining the fracture porosity from gas tracer tests are that the diffusion of gas into the rock matrix is negligible compared to the flow through the fractures, that the fracture network is well connected, and that the gas flow is approximately radial toward the pumped borehole. This calculation of fracture porosity is documented in the Analysis of Hydrologic Properties Data report (BSC 2004 [DIRS 170038], Section 6.1.3) and estimates of fracture porosity in other volcanic subunits have been based on these testing results. The estimated average value of fracture porosity is on the order of 0.01. Fracture porosity has also been estimated using the residence time of conservative tracers during cross-hole tracer tests at the C-wells complex (CRWMS M&O 1997 [DIRS 100328], pp. 2 to 4; BSC 2004 [DIRS 170010]). This method assumes that the mean tracer arrival time is equal to the time required to drain a homogenous, fractured cylinder of rock with a radius equal to the distance between the pumping well and the tracer-injection well. A large range in estimated Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-51 October 2004 fracture porosity for the saturated Bullfrog Tuff resulted from this method because the tracers were interpreted to have traveled along two paths with different travel times. The path with the longer travel time resulted in a larger estimate of fracture porosity. The resulting lower and upper bounds of fracture porosity were 0.003 and 0.10, respectively (DTNs: LA0303PR831231.005 [DIRS 166259] and GS031008312315.002 [DIRS 166261]). The Department of Energy Nevada Site Office Underground Test Area Project (DOE 1997 [DIRS 103021]) evaluated the fracture spacing and apertures in seven cores from wells in volcanic rocks at Pahute Mesa. The estimated open fracture porosities based on the assumption of parallel plates range from 2.6 × 10-6 to 4.7 × 10-4 in these cores (DOE 1997 [DIRS 103021], p. 5-14). Information compiled for Total-System Performance Assessment for Yucca Mountain – SNL Second Iteration (TSPA-1993) (Wilson et al. 1994 [DIRS 100191], Volume 1, Chapter 7, Table 7-19, p. 7-30) indicates expected values of fracture porosities ranging from 8.1 × 10-5 to 2.8 × 10-3 in core from USW G-1, USW GU-3, USW G-4, and UE25a#1, when parallel plate fracture geometry is assumed. This information generally corroborates the estimates of fracture porosity from DOE (1997 [DIRS 103021]). There is large uncertainty in the flowing interval porosity parameter. Given the estimates of this parameter from values based on theoretical models, pumping tests, and tracer data, the parameter uncertainty ranges over four orders of magnitude. To estimate the lower bound of flowing interval porosity, the estimates of fracture porosity of intact cores of volcanic rock were used. The upper bound of uncertainty in the flowing interval porosity is based on interpretations of pumping test and tracer data. The new data from the ESF provide an estimate of flowing interval porosity that falls in the upper half of the distribution used for this parameter (CRWMS M&O 2000 [DIRS 147972], Section 6.7) in the TSPA-SR. For the TSPA-LA calculations, a cumulative distribution with a lower bound of log10 (flowing interval porosity) equal to -5.0, and an upper bound of log10 (flowing interval porosity) equalt to -1.0 is selected for this parameter, as shown in Figure 6-13. This distribution places more weight in the middle of the distribution range in comparison to the TSPA-SR uniform distribution (CRWMS M&O 2000 [DIRS 147972], Section 6.7) that results in equal probabilities for the given range. The 0.5 probability value of -3.0 is representative of the smallest values of fracture porosity estimated from the new data from the ESF and previous field tests. See Table 6-8 for the associated probabilities for the flowing interval porosity CDF. The flowing interval porosity parameter is specified for a particular realization by the parameter FPVO. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-52 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -5 -4 -3 -2 -1 Cumulative Probability Log Flowing Interval Porosity in Volcanic Units Output DTN: SN0310T0502103.009. Figure 6-13. CDF of Uncertainty in Flowing Interval Porosity 6.5.2.6 Effective Diffusion Coefficient Matrix diffusion is a process in which diffusing particles move, via Brownian motion, through both mobile and immobile fluids. Diffusion is a Fickian process; that is, diffusing species move from high to low concentrations. It is dependent on the free water molecular diffusion coefficient for individual constituents and the characteristics of the flow path in which the diffusing species passes. Because diffusion through porous media is less than free water molecular diffusion, it is quantitatively defined as the effective diffusion coefficient, De. Matrix diffusion has been demonstrated to occur in the volcanic rocks within the vicinity of Yucca Mountain (Reimus et al. 2002 [DIRS 162956]; Reimus et al. 2002 [DIRS 163008]). Thus, it is modeled in the volcanic units of the SZ transport abstraction model and the SZ 1-D transport model for TSPA-LA. It is the transport mechanism that occurs in the rock matrix portion of the volcanic units. Consequently, it can be an important process that physically retards net radionuclide transport in fractured media. The variability in De in saturated media is caused by the variability in: 1. The individual constituents’ size (atom, ion, or molecule) and charge 2. Fluid temperature 3. The unique properties of a porous media’s lithology at a microscopic scale. The contribution of these uncertainties and variabilities to deriving a value of De is evaluated in the following subsections. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-53 October 2004 Variability between Lithologic Units There are several derived ‘lumped’ parameters, used as adjustments to the free water molecular diffusion, to account for the impact of lithology on molecular diffusion. Tortuosity, formation, and constrictivity factors are common adjustment parameters. These lumped parameters are based on various linear regression models, fit to field and laboratory experimental results and measured properties of the host rock, such as porosity, permeability, and formation electrical resistivity (from geophysical logs). Diffusion cell experiments have demonstrated that De is affected more by the structural properties of the porous medium, such as permeability, porosity, pore size distribution, and pore geometry, than by the mineralogy or geochemistry (Skagius and Neretnieks 1986 [DIRS 156862], pp. 389 to 398). Specific to Yucca Mountain, diffusion cell experiments documented in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section E.2) on dilute bromide solutions diffusing through Yucca Mountain tuff samples demonstrated De was directly proportional to the variability in permeability. Buchholtz ten Brink et al. (1991 [DIRS 162954]) found De for 238U on various Yucca Mountain tuff samples to be dependent on the pore size distribution of the hydrostratigraphic units. Many mathematical models have been formulated to derive a value of De. Most, if not all, rely on porosity, with some adding other “lumped” parameters. For example, Dynamics of Fluids in Porous Media (Bear 1972 [DIRS 156269], Sections 4.8.2 and 4.8.3) relates effective matrix diffusion to porosity, formation factor (derived from geophysical logs), and the free water molecular diffusion coefficient as follows: F D De f 0 = (Eq. 6-15) where De is the effective diffusion coefficient in a porous medium [L2/T], 0 D is the diffusion coefficient in water [L2/T], and F is the formation factor [-]. The formation factor is defined by the electrical resistivity of the porous medium saturated with electrolyte divided by the resistivity of the electrolyte. This method has limitations, in that it relies on formation factor measurements. Domenico and Schwartz (1990 [DIRS 100569], p. 368) document the relationship between porosity and effective diffusion with the following: 0 ) / ( D Dm t f = (Eq. 6-16) where t (= Le/L) is the tortuosity [-], Le is the length of the channel for the fluid particle [L], and L is the length of the porous media channel [L]. This method has limitations, in that it relies on multiple diffusion cell measurements on a wide variety of rock samples to derive a global value for t. Domenico and Schwartz (1990 [DIRS 100569], p. 368) define a range for Dm with the following empirical equation: Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-54 October 2004 Dm = 2 0 Df to 2 0 2 . .. . . .. . - f f D (Eq. 6-17) Bound 1 Bound 2 This relationship captures the uncertainty and range of Dm in a heterogeneous system. It is dependent only on porosity and, because there are many matrix porosity measurements on Yucca Mountain tuffs, site-specific data can be used as input. Using Equation 6-17 and site-specific porosity data, a range in the effective diffusion coefficient in the volcanic rock matrix (De) can be calculated. Mean porosity values were calculated using the relative-humidity porosities found in DTN: MO0109HYMXPROP.001 [DIRS 155989] for the SZ hydrostratigraphic units defined in Characterization of Hydrogeologic Units Using Matrix Properties, Yucca Mountain, Nevada (Flint 1998 [DIRS 100033]) as input. Relativehumidity porosity is measured by drying the sample in an oven for 48 hours at 60°C and 65 percent relative humidity. (Note: Flint’s hydrostratigraphic units are subunits of the SZ hydrogeologic framework models (HFM) units adopted in TSPA-LA.) Using Flint’s hydrostratigraphic units to represent a mean porosity is appropriate for this exercise because Flint’s basis for categorizing the units is heavily based on matrix rather than fracture properties, and it is the matrix properties that are important to diffusion in the SZ. Using relative-humidity porosity values in DTN: MO0109HYMXPROP.001 [DIRS 155989], the minimum average porosity is 0.042, and is located in the Calico Hills-vitric unit (a subunit of the SZ’s Upper Volcanic Confining, Unit 14); the maximum average is 0.321, and is located in unit TC (Tiva Canyon Tuff, a subunit of the SZ Upper Volcanic Aquifer, Unit 15). For this exercise, 0 D is that of 3HHO (tritiated water), 2.44 × 10–5 cm2/s. The resulting range in De is between 3.92 × 10-6 and 1.12 × 10-8 cm2/s when the largest porosity is used as input in bound 1, and the smallest porosity is used as input to bound 2. The variability in De is a factor of: 350 / 10 12 . 1 / 10 3.92 2 8 2 6 = × × - - s cm s cm (Eq. 6-18) Reimus et al. (2002 [DIRS 163008]) have developed an empirical relationship between De and porosity and permeability measurements based on diffusion cell experiments on rock samples from the Yucca Mountain area. Diffusing species used in the experiments are 99Tc (as TcO4 -), 14C (as HCO3 -) and 3HHO, as well as Br- and I -. Rock samples used were taken from within the vicinity of Yucca Mountain, under Pahute Mesa and Area 25 of the NTS. Based on these experiments, Reimus et al. (2002 [DIRS 163008]) describe three different approaches to deriving De. Two are dependent on linear regression relationships fitting the experimental results to diffusion cell measurements for: 1. Both matrix porosity and permeability 2. Only matrix porosity measurements. The third approach is simply compiling a CDF based on their numerous diffusion cell results. Reimus et al. (2002 [DIRS 163008], Section 4) found that differences in rock type account for Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-55 October 2004 the largest variability in the effective diffusion coefficients, rather than variability between diffusing species, size, and charge. The highest predictability in determining a value of De occurs when both matrix porosity and log permeability are known, with log permeability the most important predictive variable. The following equation defines their linear regression relationship based on porosity and permeability values and diffusion cell results (Reimus et al. 2002 [DIRS 163008], p. 2.25): )(log 165 . 0 38 . 1 49 . 3 ) ( log 10 10 m m e k D + + - = f (Eq. 6-19) where e D is in units of cm2/s and m k is matrix permeability [L2] in units of m2. Again, using matrix properties based on Flint’s hydrostratigraphic subdivisions (denoted as hydrogeologic units in this report), the variability in De can be calculated using Equation 6-19 and the following inputs: • Find the maximum and minimum geometric mean permeability in DTN: MO0109HYMXPROP.001 [DIRS 155989] within the Flint-defined set of hydrostratigraphic units (listed as hydraulic conductivities in DTN: MO0109HYMXPROP.001 [DIRS 155989], then converted to permeability). • Determine the maximum and minimum average porosity within the Flint-defined set of hydrostratigraphic units (listed as relative-humidity porosities in DTN: MO0109HYMXPROP.001 [DIRS 155989]). The highest mean log permeability is -13.25, and is located in the Calico Hill-vitric unit (a subunit of the SZ HFM Unit 14), the lowest mean log permeability is -19.39, and is located in unit TLL (a subunit of SZ HFM Unit 15). The largest porosity, 0.321, is located in the Calico Hill-vitric unit; the smallest porosity, 0.042, is located in unit TC (Tiva Canyon Tuff). The variation in De, using Equation 6-19 and average maximum and minimum permeabilities and porosities values, expressed as a ratio of maximum to minimum estimated De, is as: 25 / 10 34 . 2 / 10 84 . 5 2 7 2 6 = × × - - s cm s cm (Eq. 6-20) Variability from Ionic Radius and Charge Empirical correlations exist in the literature to adjust free diffusion coefficients dependent on species size and charge. For this analysis, general guidance provided by Newman (1973 [DIRS 148719], Table 75-1, p. 230), which lists diffusion coefficients for ions and cations of varying charges and size, is adopted in the scaling of radionuclide diffusion coefficients. Diffusion coefficients listed for the simple monovalent ions Br- and I - are the largest values listed by Newman. Consequently, diffusion coefficient scaling factors for all other ions and Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-56 October 2004 cations are relative to those listed for Br- and I -. The rationale for specific scaling factors is given below. 1. Simple monovalent cations tend to be more hydrated than anions, resulting in larger effective radii than anions, and concomitantly, diffusion coefficients are about 0.90 and 0.95 times that of simple monovalent anions such as Br- and I -. PuO2 + and NpO2 + would fall into this category, since they both have relatively low charge-to-mass ratios and should not be highly hydrated. 2. Cations, such as Na+ and Li+, with high charge-to-mass ratios have a diffusion coefficient between 0.65 and 0.5 times that of Br- and I -. 3. Multivalent anions (which are generally multiatom species) tend to have diffusion coefficients of 0.4 to 0.6 times that of Br- and I -. 4. Multivalent cations have diffusion coefficients between 0.3 to 0.4 times that of Br- and I -. 5. Diffusion coefficients of organic molecules can be considered reasonable lower bounds for diffusion coefficients of large anionic radionuclide complexes. An example is the large monovalent anions, such as pentafluorobenzoate, which have diffusion coefficients about 0.33 times that of Br- and I - (Callahan et al. 2000 [DIRS 156648], Tables 5 and 6, p. 3553). 6. Cations with charges of +3 typically hydrolyze or form complexes in solution, resulting in a lower charge and higher mass species (e.g., hydroxyl or carbonate complexes). Consequently, the multivalent and complexed species could diffuse between 0.3 and 0.25 times that of Br- and I -. Concluding from the above, the variation between the diffusion coefficients for simple and relatively small monovalent ions and the larger multivalent complexed cations can be as much as: 0 . 4 25 . 0 1 = (Eq. 6-21) The variability in De due to ionic charge and species size can be as much as a factor of 4.0. Variability from Temperature The uncertainty and variability in diffusion due solely to temperature variations (over space and time) will affect all contaminants equally. Hence, the uncertainty in temperature will not affect the decision to use a single diffusion coefficient. The Stokes-Einstein relationship can be used to approximate the molecular diffusion of ions in water with concentrations of ions as high as seawater and with temperatures ranging from 0°C to 100°C (Li and Gregory 1974 [DIRS 129827], p. 704; (Simpson and Carr 1958 [DIRS 139449], p. 1201). Using the Stokes-Einstein relationship, the molecular diffusion coefficient for a given temperature can be Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-57 October 2004 estimated as a function of the diffusion coefficient at a reference absolute temperature ( 0 T ) and the relative change in temperature and water viscosity, ( .) [M/(LT)] (Li and Gregory 1974 [DIRS 129827], p. 704): ) ( ) ( 0 0 1 0 0 1 1 0 T D T T T D . . = (Eq. 6-22) Given the maximum potential range in temperature for the Yucca Mountain groundwater along the transport pathway of 20°C to 50°C (293.15 K to 323.15 K), based on the ambient geothermal gradient and range in depth to the shallow SZ and the viscosity of water at those temperatures (Viswanath and Natarajan 1989 [DIRS 129867], p. 714), Equation 6-22 can be rewritten and solved as follows: 15 . 2 / 516 . 0 / 007 . 1 15 . 293 15 . 323 ) ( ) ( 2 2 1 0 0 1 0 0 1 0 = = = m Ns m Ns K K T T T D T D . . (Eq. 6-23) Thus, 0 D can vary by a factor of about 2.2 due to changes in water temperature. Effective Diffusion Coefficients for Yucca Mountain Volcanic Units Given the above arguments, it is demonstrated that the largest variability in De is due to differences in lithology. The variability in De using Equation 6-19 is not as high as that derived using Equation 6-17. However, Equation 6-19 will be adopted in deriving the uncertainty distribution of De for the following reasons: 1. Because Equation 6-19 is derived based on site-specific data, it is more appropriate in determining the range of De due to lithology specific to Yucca Mountain. 2. A large number of permeability and porosity measurements are taken from the SZ hydrogeologic units where flow is expected to take place. Averages of these measurements can be used as input to Equation 6-19. 3. Using maximum and minimum averages from matrix porosity and permeability as input yields a range in De that approaches that of the few laboratory-derived De measurements specific to Yucca Mountain tuffs for TcO4 - (1.0 × 10-7 to 2.0 × 10-6) and HTO- (1.2 × 10-7 to 3.5 × 10-6) (see Triay et al. 1993 [DIRS 145123]); Rundberg et al. 1987 [DIRS 106481]) as indicated on the “Flint_Reim_TrRnd” spreadsheet in the EXCEL workbook Eff_MtrxDif_11.xls file (DTN: SN0306T0502103.006). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-58 October 2004 The CDF for uncertainty in the effective diffusion coefficient used in this analysis is derived as follows: 1. Mean porosity and permeability values (calculated from values found in DTN: MO0109HYMXPROP.001 [DIRS 155989]) were calculated for the volcanic hydrostratigraphic units TC, TR, TUL, TMN, TLL, TM2, TM1, CHV, CHZ, PP4, PP3, PP2, PP1, BF3, and BF2, defined by Flint (1998 [DIRS 100033]). These are subunits of the more broadly defined SZ HFM Units 11, 12, 13, 14, and 15, and are units where flow and transport are expected to take place. Mean porosity and permeability values are given on the spreadsheets “LVA (12 &11)”, “LVA (13)”, “UVC (14)”, and “UVA (15)” in the EXCEL file Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 2. A CDF for De was calculated with Equation 6-19, using the mean permeability and porosity values for the above hydrostratigraphic units as input. These values are given on the spreadsheet “drns_all_straight”, (Column AG, Rows 34 through 49) in the EXCEL file Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 3. The derived CDF was then scaled down to account for the variability in De (to account for ionic charge and size). The scaling factors used are: 1) 0.9, to represent diffusion of simple monovalent cations, 2) 0.65 and 0.50, to represent cations with a high charge-to-mass ratios, 3) 0.3, to represent large monovalent anions, and 4) 0.25, to represent multivalent and complexed cations (Figure 6-14). Note the rationale for the above scaling factors is discussed in the subsection “Variability from Ionic Radius and Charge”. These values are given on the spreadsheet “drns_all_straight” in the EXCEL file Eff_MtrxDf_11.xls (Column AG, Rows 50 through 109) (DTN: SN0306T0502103.006). The resulting CDF yields a distribution given in Figure 6-14, with a range in log space of –5.3 to –7.12 cm2/s. The range captures laboratory 3HHO and TcO4 - measured values of De on Yucca Mountain tuffs reported by Triay et al. (1993 [DIRS 145123]) and Rundberg et al. (1987 [DIRS 106481]) and 3HHO, TcO4, and 14C De reported by Reimus et al. (2002 [DIRS 163008]) and Reimus et al. (2003 [DIRS 162950]). Additionally, this range incorporates the interpreted diffusion coefficients (6.0 × 10-6 cm2/s and 1.3 × 10-7 cm2/s) derived from field tests using Br-, PFBA (a fluorinated organic acid) as the diffusing species (Reimus et al. 2003 [DIRS 162950]). The distribution for the derived values of effective diffusion coefficient using Equation 6-19 is about half an order of magnitude lower than the distribution of values from laboratory and field results. This is because the derived distribution scales the effective diffusion coefficient to take into account species not measured in laboratory or field experiments, as described in step 3, above. The lowest values of effective diffusion coefficient are those for hydrolyzed or complexed ions having a low charge and high mass, which would have diffusion coefficients about 0.25 times the values for Br- and I- ions. To account for uncertainties in De at the lower end, the uncertainty range is expanded to span a full 2 orders of magnitude (log De –5.3 to –7.3 with De in units of cm2/s), with the 50-percentile Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-59 October 2004 log De set at –6.3. When converted to m2/s, it results in a log De (m2/s) range of –9.3 to –11.3, with the 50-percentile log De set at –10.3 (see Figure 6-15). The effective matrix diffusion coefficient is determined for a particular realization by the parameter DCVO. See Table 6-8 for the associated probabilities for the effective matrix diffusion coefficient CDF. 0.00 0.20 0.40 0.60 0.80 1.00 -7.50 -7.00 -6.50 -6.00 -5.50 -5.00 -4.50 Log Effective Diffusion Coefficient (cm2/sec) Cumulative Probability TcO4 labmatrix diffusion - red dots (Rundberg et al. 1987 [106481] and Triay 1993 [145126]) 3HHO lab matrix diffusion - green squares (Rundberg et al. 1987 [106481] and Triay 1993 [145126]) Output DTN: SN0306T0502103.006. NOTE: The CDF to the left represents values of effective diffusion coefficient derived using Equation 6-19 (black asterisks). Included in the plot are laboratory measurements of effective diffusion coefficient from Triay 1993 [DIRS 145123] and Rundberg et al. 1987 [DIRS 106481] to demonstrate the reasonableness of the derived values of effective diffusion coefficient. The CDF to the right represents laboratory and field-derived values. Yellow Triangles – 14C laboratory values; Blue Squares – 3HHO laboratory values; Red Diamonds – TcO4 laboratory values; Purple Circles – Br- and PFBA field values (Reimus et al. 2002 [DIRS 163008]; Reimus et al. 2003 [DIRS 162950]). Figure 6-14. CDFs of Data Used in the Assessment of Uncertainty in Effective Diffusion Coefficient Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-60 October 2004 Output DTN: SN0310T0502103.009. Figure 6-15. CDF of Uncertainty in Effective Diffusion Coefficient 6.5.2.7 Bulk Density of Alluvium For the TSPA-SR, the dry bulk density was considered to be a constant, and set to 1.27 g/cm3 (CRWMS M&O 2000 [DIRS 147972], Section 6.9). The basis for this parameter value is a set of tests performed on four five-foot alluvial intervals from each of the EWDP Boreholes 2D, 9S, and 3S, at depths of 395 to 415 feet, 145 to 165 feet, and 60 to 80 feet, respectively (DTN: LA0002JC831341.001 [DIRS 147081]). These samples were drill cuttings and thus highly disturbed from their condition in the aquifer. The range of the dry bulk density values in laboratory columns packed with alluvium from these wells was 1.2 to 1.3 g/cm3. The data are presented in Unsaturated Zone and Saturated Zone Transport Properties (U0100) (CRWMS M&O 2000 [DIRS 152773], p. 86) with a note stating that densities were measured in the laboratory and do not represent in situ conditions. The values used in the TSPA-SR were low compared to dry bulk densities measured in alluvium at Frenchman Flat and the NTS near Yucca Mountain (Howard 1985 [DIRS 153266], Table 3, p. 31, and Table A-1, p. 38). Similarly, a comparison to the range of dry bulk densities of alluvial material in general (Manger 1963 [DIRS 154474], pp. E41 to E42) led to the conclusion that the values used in the TSPA-SR were likely an underestimate of the true bulk density. Consequently, bulk density in the alluvium and its uncertainty has been reevaluated using data from the Yucca Mountain area that have been measured at a larger, more representative scale. The dry bulk density of the alluvium is used in the computation of the retardation of sorbing radionuclides. The dry bulk density is related to the matrix retardation coefficient as indicated in Equation 6-2. Borehole gravimeter surveys were conducted by EDCON (2000 [DIRS 154704], pp. 1 to 23) at well EWDP-19D1 directly south of Yucca Mountain near U.S. Highway 95. A total of 36 values of saturated bulk density were estimated, based on the geophysical measurements taken from this Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-61 October 2004 well (EDCON 2000 [DIRS 154704], p. 3). Seventeen measurements were taken from a depth corresponding to the inferred depth of the flow path through the alluvium near Yucca Mountain (401.5 to 776 feet). The wet bulk density computed from gravimeter measurements is presented in Table 6-11, and also includes the porosity and dry bulk density computed from Freeze and Cherry (1979 [DIRS 101173], p. 337): grain w grain sat . . . . f - - = T (Eq. 6-24) ( ) T f. . - = 1 grain b (Eq. 6-25) where .sat is the saturated bulk density [M/L3], .grain is the average grain density for these samples [M/L3] (2.52 g/cm3), and .w is the density of water (1.0 g/cm3). The average grain density was computed to be 2.52 g/cm3 (2520 kg/m3) from alluvial samples from other boreholes in the vicinity of Yucca Mountain (USGS n.d. [DIRS 154495], pp. 3 to 4). The grain density varied little (2.49 to 2.55 g/cm3), and so the average was used in the computation of the porosity and dry bulk density. The mean dry bulk density for this set of measurements was 1.91 g/cm3 (1910 kg/m3). This value is close to dry bulk density values previously measured at Frenchman Flat and the NTS in similar material at similar depth (Howard 1985 [DIRS 153266], Table 3, p. 31, and Table A-1, p. 38), and it is the value used as the mean in the uncertainty distribution. The computed standard deviation for these measurements is 0.078 g/cm3. A normal distribution was selected to characterize the uncertainty in the dry bulk density based on the frequency plot shown in Figure 6-16. The relatively large volume of the medium interrogated by the borehole gravimeter method suggests that the variability observed is appropriate for the uncertainty in this parameter at the scale of individual grid cells in the SZ transport abstraction model. The CDF of uncertainty in bulk density of the alluvium is shown in Figure 6-17. The bulk density in the alluvium is specified for a particular realization by the parameter bulk density. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-62 October 2004 Table 6-11. Measured Saturated Density, Computed Porosity, and Computed Dry Bulk Density for Depths from 402 to 776 Feet Below the Surface at the Nye County Well EWDP-19D1 Sample Depth (ft) Drift-Corrected Saturated Bulk Density, .sat (g/cm3) Computed Total Porosity, T f Computed Dry Bulk Density, .b (g/cm3) 402 2.231 0.190 2.04 422 2.156 0.239 1.92 442 2.180 0.224 1.96 485 2.163 0.235 1.93 505 2.174 0.228 1.95 525 2.214 0.201 2.01 569.95 2.148 0.245 1.90 589.9 2.142 0.249 1.89 610 2.105 0.273 1.83 630 2.079 0.290 1.79 649.95 2.077 0.291 1.79 669.95 2.133 0.255 1.88 690 2.121 0.262 1.86 715.95 2.158 0.238 1.92 736 2.143 0.248 1.90 756 2.105 0.273 1.83 776 2.239 0.185 2.05 Source: DTN: MO0105GPLOG19D.000 [DIRS 163480]. 1.6 1.7 1.8 1.9 2 2.1 2.2 Dry BulkDensity (g/cm3) 0 1 2 3 4 5 Frequency NOTE: Normal distribution fit to the data shown with the dashed line. Figure 6-16. Histogram of Dry Bulk Density from Borehole Gravimeter Data Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-63 October 2004 Output DTN: SN0310T0502103.009. Figure 6-17. CDF of Uncertainty in Bulk Density of Alluvium 6.5.2.8 Sorption Coefficients Sorption, or adsorption, is the process by which dissolved radionuclides temporarily adhere or bond to rock and alluvial substrate along a transport path. Sorption occurs because of the electrochemical affinity between the dissolved species and the substrate. The significance of sorption to the SZ transport abstraction model and the SZ 1-D transport model is that sorption results in a retardation of the radionuclide because part of the radionuclide transport time is spent on an immobile surface. A linear, equilibrium, sorption coefficient, Kd, is considered appropriate for the radionuclides that exhibit sorption during transport because of experimental observations that establish the adequacy of this approach. The Kd model also depends on chemical equilibrium between the aqueous phase and sorbed phase of a given species. The Kd relationship is defined as follows (Domenico and Schwartz 1990 [DIRS 100569], p. 441): C K S d = (Eq. 6-26) where S [moles/M] is the mass sorbed on the surface of the substrate, and C [moles/L3] is the concentration of the dissolved mass. The Kd model determines transport retardation as described earlier per Equation 6-2. A detailed discussion of the uncertainty distributions for sorption coefficients used in the SZ transport abstraction model and the SZ 1-D transport model is given in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix A). The documentation provided by Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix A) includes the technical bases Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-64 October 2004 for the values of sorption coefficient for the relevant radionuclides in volcanic units and alluvium at Yucca Mountain. 6.5.2.9 Dispersivity Longitudinal dispersion is the mixing of a solute in groundwater that occurs along the direction of flow. This mixing is a function of many factors, including the relative concentrations of the solute, the velocity pattern within the flow field, and the host rock properties. An important component of this dispersion is the dispersivity, a coarse measure of solute (mechanical) spreading properties of the rock. The dispersion process causes spreading of the solute in directions transverse to the flow path, as well as in the longitudinal flow direction (Freeze and Cherry 1979 [DIRS 101173], p. 394). Longitudinal dispersivity will be important only at the leading edge of the advancing plume; transverse dispersivity (horizontal transverse and vertical transverse) is the strongest control on plume spreading and possible dilution for the Yucca Mountain repository (CRWMS M&O 1998 [DIRS 100353], p. LG-12). Temporal changes in the groundwater flow field can significantly increase the apparent dispersivity displayed by a contaminant plume, particularly with regard to transverse dispersion. However, observations of water levels in wells at Yucca Mountain have not indicated large or consistent variations (Luckey et al. 1996 [DIRS 100465], pp. 29 to 32), suggesting that transience in the SZ flow system would not lead to much greater dispersion. The thick UZ in the area of Yucca Mountain likely dampens the response of the SZ flow system to seasonal variations or transience in infiltration on time scales of less than centuries. These dispersivities (longitudinal, vertical transverse, and horizontal transverse) are used in the advection-dispersion equation governing solute transport, and are implemented into the SZ transport abstraction model as stochastic parameters. Recommendations from the SZ expert elicitation were used as the basis for determining the distribution for longitudinal and transverse dispersivity. This expert elicitation was conducted in a manner consistent with Branch Technical Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program (Kotra et al. 1996 [DIRS 100909]). As part of the expert elicitation, Dr. Lynn Gelhar provided statistical distributions for longitudinal dispersivity at 5 km and 30 km (CRWMS M&O 1998 [DIRS 100353], p. 3-21). These distributions for longitudinal dispersivity are consistent with his previous work (Gelhar 1986 [DIRS 101131], pp. 135s to 145s). Modeling Sub Gridblock Scale Dispersion in Three-Dimensional Heterogeneous Fractured Media (CRWMS M&O 2000 [DIRS 152259], p. 53) provided estimates of the transverse and longitudinal dispersion that can occur at the subgridblock scale within the SZ site-scale model. The estimation of dispersivity using subgridblock scale modeling is also described by McKenna et al. (2003 [DIRS 163578]). The results from the subgridblock scale modeling (CRWMS M&O 2000 [DIRS 152259], p. 55) are in general agreement with the estimates by the expert elicitation panel (CRWMS M&O 1998 [DIRS 100353], p. 3-21). However, there is a significant difference in the spatial scale at which the analyses in Modeling Sub Gridblock Scale Dispersion in Three-Dimensional Heterogeneous Fractured Media (CRWMS M&O 2000 [DIRS 152259]) were conducted (500 m) and the scales at which the expert elicitation (CRWMS M&O 1998 [DIRS 100353]) estimates were made (5 km and 30 km). Nonetheless, both sources of information on dispersivity are mutually supportive. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-65 October 2004 In the SZ transport abstraction model, the longitudinal dispersivity parameter is sampled as a log-transformed parameter, and the transverse dispersivities are then calculated as indicated by Saturated Zone Flow and Transport Expert Elicitation Project (CRWMS M&O 1998 [DIRS 100353], p. 3-21), according to the following relationships: 200 L h a a = (Eq. 6-27) 20000 L v a a = (Eq. 6-28) where L a is the longitudinal dispersivity [L], h a is the transverse horizontal dispersivity [L], and v a is transverse vertical dispersivity [L]. The longitudinal dispersivity is specified for a particular realization by the parameter LDISP. The statistical distribution is a lognormal distribution: E[log10( L a )]: 2.0 and S.D.[log10( L a )]: 0.75. The CDF of uncertainty in longitudinal dispersivity is shown in Figure 6-18. 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -2 -1 0 1 2 3 4 5 6 Cumulative Probability Log Longitudinal Dispersivity (m) Output DTN: SN0310T0502103.009. Figure 6-18. CDF of Uncertainty in Longitudinal Dispersivity Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-66 October 2004 Effective Longitudinal Dispersivity in the SZ Transport Abstraction Model Longitudinal dispersivity for radionuclide transport simulations in the SZ transport abstraction model is specified as a transport parameter. The dispersion process is simulated by the random-walk displacement algorithm on the local scale for each time step in the transport simulation. In addition, the spatial distribution of hydrogeologic units of contrasting permeability within the model imparts additional dispersion to the simulated transport of particles as the flow paths diverge to adjacent grid cells of contrasting permeability during transport. The effective longitudinal dispersivity simulated by the SZ transport abstraction model can be significantly larger than the specified value due to the additive effects of these two processes. The effective longitudinal dispersivity in the SZ transport abstraction model is analyzed for a range of values of specified longitudinal dispersivity to evaluate this effect. A point source beneath the repository is used for the analysis. Neither sorption nor matrix diffusion is included in the simulations. Effective longitudinal dispersivity is estimated using the relationship from Kreft and Zuber (1978 [DIRS 107306]): 2 2 . .. . . .. . = t t f L m L s a (Eq. 6-29) where Lf is the flow path length [L], st is the standard deviation in travel time [T], and mt is the mean travel time [T]. The standard deviation is estimated from the particle mass breakthrough curve at an 18-km distance by taking the difference in time between the arrival of 0.159 fraction of the mass (the mean minus one standard deviation for a Gaussian distribution) and the arrival of 0.841 fraction of the mass (the mean plus one standard deviation for a Gaussian distribution), and dividing by 2. The mean travel time is estimated using the arrival time of 0.500 fraction of the mass. The results of this analysis are shown in Figure 6-19, with the plotted open circles. The effective simulated longitudinal dispersivity is consistently about one order of magnitude higher (bold red dashed line) than the specified longitudinal dispersivity (for values of specified longitudinal dispersivity of less than 1,000 m). These results indicate that the heterogeneous distribution of permeability in the SZ transport abstraction model in the region along the flow path is contributing approximately one order of magnitude of dispersivity relative to the specified value. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-67 October 2004 1 10 100 1000 10000 100000 Specified Longitudinal Dispersivity (m) 1 10 100 1000 10000 100000 Effective Simulated Longitudinal Dispersivity (m) Figure 6-19. Effective Simulated Longitudinal Dispersivity Versus the Specified Longitudinal Dispersivity in the SZ Transport Abstraction Model These results indicate that the effective longitudinal dispersivity in the SZ transport abstraction model is significantly higher than the value input to the model. In order to avoid the excessive effective dispersion in the SZ transport abstraction model, the input value of longitudinal dispersivity can be reduced. Based on these results, the value of specified longitudinal dispersivity used in the SZ transport abstraction model for the TSPA-LA abstraction simulations is adjusted to yield the correct value of effective simulated longitudinal dispersivity. This is accomplished by scaling the input value of longitudinal dispersivity down by one order of magnitude (i.e., dividing the longitudinal dispersivity by 10) in the input files for each realization. 6.5.2.10 Horizontal Anisotropy in Permeability Although a detailed description of the analysis and derivation of the distribution of anisotropy ratio in the SZ near the C-wells complex is presented in the Saturated Zone In Situ Testing report (BSC 2004 [DIRS 170010], Section 6.2.6), some background information and a short summary are presented here. Interpretation of well test data with analytical solutions consists of inferring the hydraulic properties of the system from its measured responses, based on an assumed flow geometry (i.e., radial). The problem becomes more complicated, however, when the system geometry cannot be specified with reasonable certainty. In a layered sedimentary system lacking extreme heterogeneity, flow might reasonably be expected to be radial during a hydraulic test. When hydraulic tests are conducted at some arbitrary point within a 3-D fractured rock mass, however, the flow geometry is complex. Radial flow would occur only if the test were performed in a single uniform fracture of effectively infinite extent, or within a network of fractures confined to a planar body in which the fractures were so densely interconnected that the network behaves like an equivalent porous medium. More likely, flow in fractured tuff is Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-68 October 2004 nonradial and variable, as fracture terminations and additional fracture intersections were reached. Therefore, it must be emphasized that assumptions required in the analytical treatment of anisotropy may not be strictly consistent with site geology. Through the fractured tuff and alluvium near Yucca Mountain, there is significant heterogeneity in hydraulic properties, which not only vary spatially, but also differ depending upon the direction in which they are measured (both horizontally and vertically). In the fractured volcanic units near Yucca Mountain, preferential orientation of open fractures and/or faults can possibly impart significant anisotropy in horizontal permeability to the groundwater flow system. The uncertainty in horizontal anisotropy in permeability implicitly accounts for potential undetected features, such as fault and fracture zones, that impart preferential directional flow to groundwater. In this analysis, transmissivity and storativity are the hydrologic parameters required to calculate and define large-scale anisotropy, and their measured values reflect the heterogeneity of the media. The concept of anisotropy is typically associated with a homogeneous medium—a criterion not met here. Nevertheless, there are clearly spatial and directional variations in transmissivity, and the notion remains that, over a large enough representative elementary volume, there exists a preferential flow direction that can be termed anisotropy. Data from the long-term pumping test conducted from May 8, 1996, to November 12, 1997, were used to evaluate the anisotropy in the vicinity of the C-wells complex in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6). After filtering the drawdown data in response to pumping at UE-25 c#3, transmissivity and storativity were calculated at four distant wells (USW H-4, UE-25 ONC1, UE-25 wt#3, and UE-25 wt#14). A distribution of anisotropies must be specified so that an anisotropy ratio can be selected for each of the 200 stochastic model realizations used as input to the SZ transport abstraction model. Because the current version of the FEHM V2.20 software code [DIRS 161725] can only implement anisotropy oriented in alignment with the grid direction, principal directions discussed above are not directly applicable in the model. The net result of being unable to specify a principal direction is that uncertainty in the anisotropy ratio increases. For example, the analytical result for anisotropy using the Cooper-Jacob (1946 [DIRS 150245]) method is a ratio of 3.3 in a direction 15º east of north. A projection that orients the principal direction north-south (0º) results in a new anisotropy ratio of 2.5. In fact, this line of reasoning suggests that it is possible for the projected north-south anisotropy ratio to be significantly less than one. Based on consultations with USGS staff and with the YMP Parameters Team, and on scientific judgment and results from the analytical anisotropy analyses, Figure 6-20a represents the best estimate of the PDF for the anisotropy ratio (north-south / east-west) in the SZ near the C-wells complex. Figure 6-20b is the corresponding CDF. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-69 October 2004 Source: DTN: SN0302T0502203.001 [DIRS 163563]. Figure 6-20. Probability Density Function (a) and Corresponding CDF (b) for the Uncertainty in North-South/East-West Anisotropy Ratio There are several noteworthy points based on three distinct regions of the anisotropy ratio distribution (DTN: SN0302T0502203.001 [DIRS 163563]). • Anisotropy ratio between 5 and 20. The maximum anisotropy ratio of 20:1 is based upon the highest calculated anisotropy ratio of 17:1 reported by Ferrill et al. (1999 [DIRS 118941], p. 7). The maximum reported value of 17:1 was rounded to 20:1 and set as the upper limit for horizontal anisotropy. Furthermore, although features such as high transmissivity zones and fractures can yield very large anisotropy ratios locally, globally, their effects are attenuated, and 20 is a reasonable maximum. The 5.5 anisotropy ratio calculated by the second approach of the modified Papadopulos-PEST method (see Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6)) lies in this range, near its highest probability point. Therefore, between 5 and 20, a triangular distribution of anisotropy ratio is constructed that decreases to zero probability at 20. A 40-percent probability is assigned to this portion of the probability density function. • Anisotropy ratio between 0.05 and 1. Discussions among Sandia National Laboratories (SNL) and USGS staff established that, although it is likely the SZ is anisotropic with a principal direction approximately northeast, it is possible the media could be isotropic, as well as a small probability that the principal direction could be significantly different from north-northeast. Correspondingly, an anisotropy ratio of less than one is possible, and the minimum anisotropy ratio is set equal to the inverse of the maximum, 1:20, with a triangular distribution of 10 percent probability decreasing to zero at a ratio of 0.05. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-70 October 2004 An additional Papadopulos solution yielding an anisotropy ratio of 3.5 at 79° west of north (BSC 2004 [DIRS 170010], Section 6.2.6) falls in this range. • Anisotropy ratio between 1 and 5. A uniformly distributed 50 percent probability is assigned to the range of anisotropy ratio between 1 and 5. This interval comprises the more likely values of anisotropy ratios, with no specific value more likely than any other. It should be noted that in a previous model of the SZ near Yucca Mountain (CRWMS M&O 2000 [DIRS 153246], Section 3.8.1.3), anisotropy was binomially distributed with a 50 percent probability of isotropy (1:1) and a 50 percent probability of a 5:1 ratio. It is assumed that the potential anisotropy of permeability in the horizontal direction is adequately represented by a permeability tensor that is oriented in the north-south and east-west directions. This approach is carried forward from the Saturated Zone In-Situ Testing scientific analysis report (BSC 2004 [DIRS 170010], Section 6.2.6). The numerical grid in the SZ site-scale flow and transport model is aligned in the north-south and east-west directions, and values of permeability may only be specified in directions parallel to the grid. Analysis of the probable direction of horizontal anisotropy shows that the direction of maximum transmissivity may be about N 15° E, indicating that the anisotropy applied on the SZ transport abstraction model grid is within approximately 15° of the inferred anisotropy. Figure 6-20(a) and Figure 6-20(b) are the best estimates for the PDF and the CDF, respectively, of north-south anisotropy ratios in the SZ to be modeled with the FEHM V2.20 software code [DIRS 161725] in the SZ transport abstraction model. Horizontal anisotropy in permeability is determined for a particular realization by the parameter HAVO. 6.5.2.11 Retardation of Colloids with Irreversibly Sorbed Radionuclides For TSPA-LA, colloid-facilitated transport of radionuclides in the SZ is simulated to occur by two basic modes. In the first mode, radionuclides that are irreversibly attached to colloids are transported at the same rate as the colloids, which are themselves retarded by interaction with the aquifer material. In the second mode, radionuclides that are reversibly attached to colloids are in equilibrium with the aqueous phase and the aquifer material. In this mode of transport, the effective retardation of these radionuclides during transport in the SZ is dependent on the sorption coefficient of the radionuclide onto colloids, the concentration of colloids, and the sorption coefficient of the radionuclide onto the aquifer material. This section deals with the first mode of colloid-facilitated transport; Section 6.5.2.12 addresses the second mode. The SZ transport simulations of radionuclides that are irreversibly attached to colloids are conducted for radioisotopes of Pu and Am. The retardation of colloids with irreversibly attached radionuclides is a kinetically controlled process, which approaches equilibrium behavior for long transport times. For transport of colloids through the SZ, equilibrium behavior is nearly achieved. However, nonequilibrium behavior results in unimpeded migration of some of the colloids. Consequently, a small fraction of these colloids is transported through the SZ with no retardation, whereas the larger fraction is delayed by a retardation factor. For the SZ transport simulations, a small fraction of the radionuclide mass irreversibly attached to colloids is transported without retardation, and the remaining fraction of the radionuclide mass is retarded. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-71 October 2004 A discussion of the fraction of colloids transported with no retardation is in Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.6). The fraction of irreversibly sorbed to reversibly sorbed radionuclides is determined in the waste-form component of TSPA-LA, and is used as input to the SZ transport abstraction model and the SZ 1-D transport model. The processes important to the transport of irreversible colloids in the volcanic units of the SZ are as follows: advection and dispersion of colloids in the fracture water, exclusion of the colloids from the matrix waters, and chemical filtration or adsorption of the colloids onto the fracture surfaces. Modeling of the advective/dispersive processes is handled as if the colloids were solute in the SZ transport abstraction model and the SZ 1-D transport model. Matrix exclusion (i.e., colloid transport only in the fractures) in the volcanic units is considered to be appropriate because of the large size and small diffusivities of the colloids compared to the solute, plus the possibility of similar electrostatic charge of the colloids and the tuff matrix. Matrix exclusion is implemented by reducing the values of the effective diffusion coefficients for radionuclides (see Section 6.5.2.6 for a discussion of the solute diffusion coefficient) by 10 orders of magnitude, thus preventing essentially all matrix diffusion. Chemical (i.e., reversible) filtration of irreversible colloids is modeled by applying a retardation factor to the transport in the fractures. The implementation of the retardation factor in the SZ transport abstraction model is described in Section 6.5.1. Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.4) describes the development of colloid retardation factors for fractured tuff from field and experimental data. Figure 6-21 shows the CDF used for retardation factors in the volcanic units for the SZ transport abstraction model and Table 6-8 provides the associated probabilities. This CDF is based on the uncertainty distribution developed in Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Table 6-2). A log cumulative probability distribution is used because the retardation factors span slightly more than two orders of magnitude. Retardation of colloids with irreversibly sorbed radionuclides in the volcanic units is specified for a particular realization by the parameter CORVO. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-72 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 Cumulative Probability Log Colloid Retardation Factor in Volcanic Units Source: DTN: LA0303HV831352.002 [DIRS 163558]. Figure 6-21. CDF of Uncertainty in Colloid Retardation Factor in Volcanic Units The processes modeled for irreversible colloids in the alluvium are the same as those modeled for irreversible colloids in the volcanic units, with the exception of matrix exclusion, because the alluvium is modeled as a single porous medium. Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.5) describes the development of colloid retardation parameters for the alluvium using experimental data specific to colloid transport in alluvial material from Yucca Mountain, as well as bacteriophage field studies in alluvial material, which are thought to be good analogues for colloid transport because of their colloidal size and passive transport characteristics. As with irreversible colloids in the volcanic units, filtration in the alluvium is modeled by applying a retardation factor to transport in the porous medium. Figure 6-22 shows the CDF used for retardation factors in the alluvium for the SZ transport abstraction model, and Table 6-8 provides the associated probabilities. This CDF is based on the uncertainty distribution developed in Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Table 6-3). A log cumulative probability distribution is used because the retardation factors span slightly more than three orders of magnitude. The implementation of the retardation factor in the SZ transport abstraction model is described in Section 6.5.1. Retardation of colloids with irreversibly sorbed radionuclides in the alluvium is specified for a particular realization by the parameter CORAL. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-73 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 1.0 2.0 3.0 4.0 Cumulative Probability Log Colloid Retardation Factor in Alluvium Source: DTN: LA0303HV831352.004 [DIRS 163559]. Figure 6-22. CDF of Uncertainty in Colloid Retardation Factor in Alluvium 6.5.2.12 Transport of Radionuclides Reversibly Sorbed on Colloids Radionuclides that are reversibly sorbed onto colloids are modeled to be temporarily attached to the surface of colloids. Thus, these radionuclides are available for dissolution in the aqueous phase, and their transport characteristics are a combination of the transport characteristics of solute and colloids. The SZ transport simulations of radionuclides that are reversibly attached to colloids are conducted for radioisotopes of Pu, Am, Th, Pa, and Cs, which is consistent with the radionuclides selected for reversible sorption (BSC 2004 [DIRS 170025], 6.3.3.1). For these transport simulations, radioisotopes of Pu are transported as one group, radioisotopes of Am, Th, and Pa are transported as a second group, and Cs is transported as a third species. Americium and plutonium can also be transported as irreversibly sorbed onto colloids; see Section 6.5.2.11. The Kc parameter is a distribution coefficient that represents the equilibrium partitioning of radionuclides between the aqueous phase and the colloidal phase, as given in Equation 6-4. The Kc is a function of only radionuclide sorption properties, colloid substrate properties, and colloid mass concentration, and not any properties of the immobile media through which transport occurs; thus, the same Kc applies to transport of a radionuclide in both the volcanic units and the alluvium. For TSPA-LA, the coll d K uncertainty distributions for Pu, Am, Th, Pa, and Cs were developed in Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary (BSC 2004 [DIRS 170025], Table 6-6). Figures 6-23 to 6-25 show the uncertainty distributions input to the SZ transport abstraction model for sorption coefficients onto colloids. The Ccol uncertainty distribution was also developed in Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary (BSC 2004 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-74 October 2004 [DIRS 170025], Table 6-4) (see Figure 6-26). Retardation of colloids with reversibly sorbed radionuclides is determined for a particular realization by the following uncertain parameters: • Conc_Col for groundwater colloid concentrations • Kd_Cs_Col for cesium sorption coefficient onto colloids; • Kd_Am_Col for americium, thorium, and protactinium sorption coefficients onto colloids • Kd_Pu_Col for plutonium sorption coefficient onto colloids. Implementation of the Kc model in the SZ transport abstraction model is discussed in Section 6.5.1. Note that the values given for the parameter vectors of Kd_Pu_Col, Kd_Am_Col, and Kd_Cs_Col in Appendix A are the log10-transformed values. 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 2.0e05 4.0e05 6.0e05 8.0e05 1.0e06 Cumulative Probability Plutonium Sorption Coefficient onto Colloids ml/g) Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. Figure 6-23. CDF of Uncertainty in Plutonium Sorption Coefficient onto Colloids (mL/g) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-75 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 2.0e06 4.0e06 6.0e06 8.0e06 1.0e07 Cumulative Probability Americium Sorption Coefficient onto Colloids ml/g) Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. Figure 6-24. CDF of Uncertainty in Americium Sorption Coefficient onto Colloids 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 1.0e03 2.0e03 3.0e03 4.0e03 5.0e03 6.0e03 7.0e03 8.0e03 9.0e03 1.0e04 Cumulative Probability Cesium Sorption Coefficient onto Colloids (ml/g) Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. Figure 6-25. CDF of Uncertainty in Cesium Sorption Coefficient onto Colloids (mL/g) (mL/g) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-76 October 2004 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -9 -8 -7 -6 -5 -4 -3 Cumulative Probability Log Groundwater Colloid Concentrations (g/ml) Source: DTN: SN0306T0504103.005 [DIRS 164132], Table 3. Figure 6-26. CDF of Uncertainty in Groundwater Colloid Concentrations Accompanying the Kc model is the partitioning of radionuclides between the aqueous phase and the sorbed phase onto the tuff matrix and the alluvium, as described by Kd for the radionuclide onto the aquifer material. The Kd uncertainty distributions for americium, plutonium, and cesium are described in Table 6-8 (DTN: LA0310AM831341.002, [DIRS 165891]). 6.5.2.13 Source Regions Variations in radionuclide transport pathways and travel times in the SZ from various locations beneath the repository are considered by defining four radionuclide source regions at the water table. For any particular TSPA-LA realization, a point source of radionuclides is defined within each of the four regions for simulation of radionuclide transport in the SZ transport abstraction model. A point source of radionuclides in the SZ is appropriate for a single leaking waste package or for highly focused groundwater flow along a fault or single fracture in the UZ. Whereas a more diffuse source of radionuclides at the water table may be more physically realistic for later times when numerous leaking waste packages occur, use of a point source in the SZ is an approach that overestimates the concentration of radionuclides near the source. The SZ source region locations are based on the extent of the repository design and on the general pattern of groundwater flow in the UZ as simulated by the UZ site-scale flow and transport model. Variations in the pattern of groundwater flow from the repository to the water table exist among infiltration models, ACMs, and climate states for the UZ site-scale model (BSC 2004 [DIRS 169861], Section 6.6). The UZ flow and transport simulations indicate varying degrees of lateral diversion of groundwater to the east of the repository, and downward redirection by interception of flow at major faults. The SZ source region locations are defined to accommodate the general range in UZ transport pathways simulated by the suite of UZ site-scale flow model simulations. (g/mL) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-77 October 2004 The four SZ radionuclide source regions are shown in Figure 6-27. Note that the CORPSCON software code (CORPSCON V5.11.08, STN: 10547-5.11.08-00 [DIRS 155082]) was used to convert the coordinates of the repository design (given in state plane coordinates, in meters) to Universal Transverse Mercator (UTM) coordinates. The coordinates of the corners of the source regions are given in Table 6-8. Source regions 1, 3, and part of 2 are located directly below the repository to capture radionuclide transport that occurs vertically downward in the UZ site-scale flow and transport model. In addition, regions 1, 2, and 3 are appropriate source locations for radionuclides arriving at the water table in the human intrusion scenario (see Total System Performance Assessment for the Site Recommendation (CRWMS M&O 2000 [DIRS 153246], Section 4.4)), in which a hypothetical borehole penetrates the repository and extends to the SZ. Source regions 2 and 4 are located to the east of the repository to capture radionuclide transport that is subject to lateral diversion of groundwater to the east along dipping volcanic strata in the UZ. Also note, that the northern part of source region 2 underlies a northeasterly extension of the repository. The random locations of the radionuclide source term for each realization are defined by eight stochastic parameters. The parameters SRC1X, SRC1Y, SRC2X, SRC2Y, SRC3X, SRC3Y, SRC4X, and SRC4Y determine the x coordinate and y coordinate for the source location within regions 1 to 4, respectively. These parameter values are drawn from independent, uniform distributions from 0.0 to 1.0. The result is a randomly located point source within each of the four source regions for each realization of the SZ transport abstraction model. 6.5.2.14 Maximum Alluvial Porosity The value of maximum or total alluvial porosity is used to calculate the adjusted (or new) Kd value in the effective porosity conceptualization of transport in the alluvium (see Equation 6-3). The average total porosity of alluvium from corroborative data given in Table 6-10 is 0.35. The calculated value of average total porosity in alluvium from the borehole gravimeter data from well EWDP-19D1 is significantly lower, as shown in Table 6-11. The approximate average value of maximum alluvial porosity from these two sources is 0.30. The uncertainty distribution in effective porosity of alluvium is truncated at a maximum value of 0.30 (Figure 6-10). 6.5.2.15 Average Fracture Porosity The value of average fracture porosity of volcanic rocks is used to calculate the retardation factor of sorbing radionuclides in the rubblized material of fracture zones. This retardation factor in the fracture zones only applies when the flowing interval porosity exceeds the average fracture porosity. The average fracture porosity is conceptualized to be the total fracture porosity of the volcanic units, not including any matrix porosity in the rubblized material of fracture zones. The average fracture porosity is taken as the median of the uncertainty distribution assigned to the flowing interval porosity (FPVO) (see Table 6-8), which is equal to 0.001. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-78 October 2004 Sources: Repository outline from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]) and 800-IED-WIS0- 00101-000-00A (BSC 2004 [DIRS 164519]). NOTE: Repository outline is shown by the solid blue line and the four source regions are shown by the dashed red lines. Figure 6-27. Source Regions for Radionuclide Release in the SZ Transport Abstraction Model 6.5.2.16 Average Matrix Porosity The value of average matrix porosity of volcanic rocks is used to calculate the retardation factor of sorbing radionuclides in the SZ 1-D transport model and in the rubblized material of fracture zones. This retardation factor in the fracture zones only applies when the flowing interval porosity exceeds the average fracture porosity. The average matrix porosity of volcanic rocks is calculated as the average of matrix porosity in hydrogeologic Units 11 through 14, as given in Table 6-12. The calculated average matrix porosity is 0.22. 6.5.2.17 Average Bulk Density of the Volcanic Matrix The value of average bulk density of the matrix in volcanic rocks is used to calculate the retardation factor of sorbing radionuclides in the SZ 1-D transport model and in the rubblized material of fracture zones. This retardation factor in the fracture zones only applies when the flowing interval porosity exceeds the average fracture porosity. The average bulk density of the volcanic matrix is calculated as the weighted average of bulk density in hydrogeologic Units 13 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-79 October 2004 through 15, as given in Table 6-13, with double weighting given to Unit 13 because of its prominence in the flow path beneath the repository. The calculated average bulk density is 1.88 g/cm3. 6.5.2.18 Matrix Porosity of Volcanic Units (Constant) Matrix porosity ( fm) is treated as a constant parameter for eight units of the nineteen SZ model hydrogeologic units. Constant, in this sense, means that fm will vary from one unit to another but, given a particular unit, the porosity is constant for all realizations. The porosity also remains spatially constant for each unit. The parameter values and input source(s) are shown in Section 4, Table 4-1, and discussed below. The following discussion covers data sources used in constant porosity inputs for the affected hydrogeologic units. The volcanic Units 11 through 15 do lie in the expected flow paths per the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.6.2). All of the remaining units lie outside of any expected SZ model transport paths because they do not exist in this area of the model or they occur deeper than the expected flow paths. Thus, the values of matrix porosity assigned to the remaining units have no impact on the transport simulations. However, the model requires values for fm for all units, regardless of whether they play a role in transport simulations; therefore, values as representative as possible were used. For the case of Units 15-13, the matrix porosity is based on the values from DTN: SN0004T0501399.003. The matrix porosity value for Units 12 and 11 were derived from matrix porosity data from the boreholes: UE-25P#1, USW H-3, SD7, USW G-3, USW H-1, USW G-4, USW H-5, and USW H-6 (DTNs: SN0004T0501399.003 [DIRS 155045], MO0109HYMXPROP.001 [DIRS 155989], MO0010CPORGLOG.002 [DIRS 155229]). Simple averages of the wells described above were calculated from the data for Units 12 and 11, as shown in spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006). Units 10 and 8 are both volcanic confining units. The value of fm for these units was obtained from the value for Unit 14, which is a volcanic confining unit for which there are site-specific data. The fm value for Unit 9 (volcanic unit) was obtained by averaging the values for the three overlying Crater Flat group units (Units 11 - 13). These averages were used as the matrix porosity inputs to the SZ site-scale model for their respective units, as shown in Table 6-12. 6.5.2.19 Bulk Density of the Volcanic Matrix Bulk density ( .b ) is defined by Freeze and Cherry (1979 [DIRS 101173], p. 337) as the “oven-dried mass of the sample divided by its field volume.” It is a factor in Equation 6-2, used to determine retardation of a solute due to chemical adsorption in groundwater. That equation is employed in the SZ site-scale flow and transport model as part of the FEHM code (Zyvoloski et al. 1997 [DIRS 110491], p. 42). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-80 October 2004 Table 6-12. Values of Matrix Porosity ( fm) for Several Units of the SZ Model SZ Unit Name SZ Unit Number Matrix Porosity ( fm) Upper Volcanic Aquifer (Topopah) 15 0.15 Upper Volcanic Confining Unit (Calico Hills) 14 0.25 Lower Volcanic Aquifer, Prow Pass 13 0.23 Lower Volcanic Aquifer, Bullfrog 12 0.18 Lower Volcanic Aquifer, Tram 11 0.21 Lower Volcanic Confining Unit 10 0.25 Older Volcanic Aquifer 9 0.21 Older Volcanic Confining Unit 8 0.25 Output DTN: SN0310T0502103.010. Bulk density is treated as a constant parameter for seventeen of the nineteen units of the SZ model hydrogeologic units. Constant, in this sense, means that .b varies from one unit to another but, given a particular unit, the bulk density stays the same for all realizations. The bulk density also remains spatially constant for each unit. Bulk density in hydrogeologic Units 19 and 7 is treated as an uncertain parameter, and is discussed in Section 6.5.2.7. The parameter values and input source(s) are described in Section 4. This section contains a discussion of the analyses used to develop the values. The volcanic Units 11 through 15 do lie in the expected flow paths per the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.6.2). All of the remaining units lie outside of any expected SZ model transport paths, because they do not exist in this area of the model or they occur deeper than the expected flow paths. Thus, the values of bulk density assigned to the remaining units have no impact on the transport simulations. Estimates for bulk density were either based on the use of an analogous unit, or a calculation was required, as discussed below. For some units, including part of the volcanic units and the carbonate units, the calculation involved averaging a group of referenced bulk density values. Some of the volcanic units required the use of a referenced graph to calculate bulk density as a certain function of matrix porosity (for which values had already been determined). Finally, two units (granite and lava flows) required the use of a general equation that relates bulk density to porosity. Many of the calculations required referencing either the matrix porosities or the effective porosities that were tabulated in Table 6-12 and Table 6-14, respectively. The estimated bulk densities are summarized in Table 6-13, and the methods used to obtain these values are summarized in the discussion below. Table 6-13. Values of Bulk Density ( .b) for All Units of the SZ Site-Scale Model SZ Unit Name SZ Unit Number Bulk Density (.b) (g/cm3) Valley Fill Confining Unit 18 2.50 Cenozoic Limestone 17 2.77 Lava Flows 16 2.44 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-81 October 2004 Table 6-13. Values of Bulk Density ( .b) for All Units of the SZ Site-Scale Model (Continued) SZ Unit Name SZ Unit Number Bulk Density (.b) (g/cm3) Upper Volcanic Aquifer (Topopah) 15 2.08 Upper Volcanic Confining Unit (Calico Hills) 14 1.77 Lower Volcanic Aquifer, Prow Pass 13 1.84 Lower Volcanic Aquifer, Bullfrog 12 2.19 Lower Volcanic Aquifer, Tram 11 2.11 Lower Volcanic Confining Unit 10 1.77 Older Volcanic Aquifer 9 2.05 Older Volcanic Confining Unit 8 1.77 Upper Carbonate Aquifer 6 2.77 Lower Carbonate Aquifer Thrust 5 2.77 Upper Clastic Confining Unit 4 2.55 Lower Carbonate Aquifer 3 2.77 Lower Clastic Confining Unit 2 2.55 Granites 1 2.65 NOTE: Units 19 and 7 are treated as uncertain parameters, and are discussed in Section 6.5.2.7. Carbonates Units 3, 5, 6, and 17 – Bulk density for Units 3, 5, 6, and 17 is determined from an average of a series of bulk density values from the Roberts Mountain Formation and the Lone Mountain Formation of Borehole UE-25p#1 (DTN: MO0010CPORGLOG.002 [DIRS 155229]). A simple average was calculated using these values (see spreadsheet bulkd_matr_eff_La.xls [DTN: SN0306T0502103.006]). Clastic Units 2, 4, and 18 – Bulk density values for Unit 4 are determined from an average of a series of sedimentary deposit formation bulk densities from Borehole UE-25P#1 (DTN: MO0010CPORGLOG.002 [DIRS 155229]). There are no bulk density data available for the Clastics hydrogeologic units. A simple average was calculated using these values (see spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). The bulk density assigned to Unit 4 was used as an analogous value for Unit 2, because Unit 2 is also a clastic confining unit. Unit 4 is also used as an analogous unit for Unit 18 because data do not exist for this unit, and the value was rounded to 2.5. Volcanic Units 8, 10, 13, 14, and 15 - The rock properties model (BSC 2004 [DIRS 170032]) contains a graph (Figure 6.4-21) that relates point values of .b to fm in volcanic tuff. The graph demonstrates a strong linear correlation between the two parameters. The equation for the straight-line fit to the scatterplot is shown below (DTN: SN0004T0501399.002 [DIRS 155046]) m b f . · - = 8924 . 2 5019 . 2 (Eq. 6-30) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-82 October 2004 Table 6-8 lists the values of fm for the units (Units 13 - 15) that were used to calculate .b . Hydrogeologic Units 8 and 10 are volcanic confining units. The value of .b for these units was obtained from the value for Unit 14, which is a volcanic confining unit for which we have site-specific data. Volcanic Units 11 and 12 – Bulk density for Units 11 and 12 is determined from values of the so-called “middle volcanic aquifer,” which is equivalent to SZ Units 11 and 12 (DTNs: MO0109HYMXPROP.001 [DIRS 155989] and MO0010CPORGLOG.002 [DIRS 155229]). The bulk density values come from Boreholes SD7, USW H-1, UE-25b#1, J-13, UE-25a#1, USW GU-3, USW G-3, USW G-4, UE-25p#1, and USW G-1. A simple average was calculated from those values (see spreadsheet bulkd_matr_eff_La.xls [DTN: SN0306T0502103.006]). Volcanic Unit 9 – Unit 9 is a “volcanic aquifer.” Its value was obtained by averaging the values for the three overlying volcanic Crater Flat group units (Units 11 - 13) and Unit 15. Lava Flows (Unit 16) and Granites (Unit 1) – The values of bulk density for these units are calculated from Equation 6-25. A representative value that is appropriate for .grain is 2.65g/cm3 (Hillel 1980 [DIRS 101134], p. 9). As both of these units are not in the transport model path, it is suitable to use the particle density value and effective porosity to calculate bulk density (Equation 6-31) (see spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). The effective porosity values were used for Equation 6-31 because the effective porosity is very similar to the total porosity for the lava flow and granite units. The porosity values were taken from Table 6-12. The lava flow unit has an effective porosity of 0.08, and the granite unit has a porosity of 0.0001. Therefore, the bulk densities assigned for those units are 2.44 and 2.65 g/cm3, respectively. 6.5.2.20 Effective Porosity Effective porosity ( fe ) is treated as a constant parameter for nine of the nineteen SZ model hydrogeologic units. Constant, in this sense, means that fe varies from one unit to another but, given a particular unit, the porosity is the same for all realizations. The effective porosity is also homogeneous within each unit. The input source(s) are described in Section 4, Table 4-1. The nine hydrogeologic units discussed in this section do not occur within the flow path from beneath the repository; therefore, these values do not impact the simulated transport of radionuclides. However, representative values are used. The Bedinger et al. report (1989 [DIRS 129676], Table 1, p. A18) includes hydrogeologic data for the Basin and Range Province of the Southwestern U.S. The Bedinger et al. report covers a region that extends into eight states and includes the Yucca Mountain site. The Bedinger et al. report was used as the source for data on the Valley Fill Confining Unit (18), the Cenozoic Limestone Unit (17), Lava Flow Unit (16), Upper Carbonate Aquifer Unit (6), Lower Carbonate Aquifer Thrust Unit (5), Upper Clastic Confining Unit (4), Lower Carbonate Aquifer Unit (3), Lower Clastic Confining Unit (2) and the Granites Unit (1). All of the carbonate units were assigned the same value. The effective porosity values (Bedinger et al. 1989 [DIRS 129676], Table 1, page A18; DTN: MO0105HCONEPOR.000 [DIRS 155044]) are used for all of the hydrogeologic units Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-83 October 2004 described in this paragraph. The upper carbonate aquifer, the lower carbonate aquifer, the lower carbonate thrust aquifer, and the Cenozoic limestone units (designated as Units 6, 3, 5, and 17 respectively) use the mean value of Carbonate Rocks. The Cenozoic Limestone Unit is assigned the same value as the carbonate units because it is a similar rock type to the carbonate rocks. The value for granites (Unit 1) is set equal to the estimate for metamorphic rock with a depth more than 300 m. Unit 16 is assigned the average of the Lava Flows, fractured and moderately dense, from the DTN: MO0105HCONEPOR.000 [DIRS 155044] source. Units 4 and 2 utilize the mean value from the Clastic Sedimentary Units. Unit 18 utilizes the Basin fill mean value for fine-grained clay and silt cited by Bedinger et al. (1989 [DIRS 129676], Table 1). This information is summarized in the spreadsheet geonames.xls (DTN: SN0306T0502103.006). Table 6-14 lists the constant values used for each unit, for the SZ transport abstraction model for TSPA-LA. Table 6-14. Values of Effective Porosity ( fe) for Several Units of the SZ Transport Abstraction Model SZ Unit Name SZ Unit Number Effective Porosity ( fe) Valley Fill Confining Unit 18 0.32 Cenozoic Limestone 17 0.01 Lava Flows 16 0.08 Upper Carbonate Aquifer 6 0.01 Lower Carbonate Aquifer Thrust 5 0.01 Upper Clastic Confining Unit 4 0.18 Lower Carbonate Aquifer 3 0.01 Lower Clastic Confining Unit 2 0.18 Granites 1 0.0001 Output DTN: SN0310T0502103.009. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-84 October 2004 6.5.3 Summary of Computational Models Both the SZ transport abstraction model and the SZ 1-D transport model are intended for use in the analyses for TSPA-LA. The results of the multiple realizations of SZ transport with the SZ transport abstraction model, in the form of multiple breakthrough curves, are coupled with the TSPA-LA simulations using the convolution integral method. The SZ 1-D transport model is intended for direct incorporation into the TSPA-LA model. The SZ 1-D transport model is developed independently of the TSPA-LA model, but contains the elements necessary for implementation within the TSPA-LA model. The results of the SZ transport abstraction model and the SZ 1-D transport model are combined for calculating dose for comparison to the individual protection standard in the following way: the mass arriving at the accessible environment of the following radionuclides is simulated, using the SZ transport abstraction model: 14C, 90Sr, 99Tc, 129I, 135Cs, 137Cs, 232U, 243Am, 241Am, 240Pu, 242Pu, 239Pu, 237Np, 236U, 238U, 238Pu, and 234U. Note, transport of the actinides listed above (with the exception of 232U) is also simulated with the SZ 1-D transport model, but only the subsequent daughter products in the four decay chains are taken as output from the SZ 1-D transport model. The mass arriving at the accessible environment of the following radionuclides is simulated with the SZ 1-D transport model (or assumed to be in secular equilibrium with their respective parents): 235U, 233U, 232Th, 231Pa, 229Th, 229Ra, 230Th, and 226Ra. 6.5.3.1 SZ Transport Abstraction Model The groups of radioelements for simulated transport in the SZ transport abstraction model are summarized in Table 6-15. There are 10 groupings of radionuclides noted in the first column of Table 6-15. The modes of radionuclide transport are: 1. As solute, 2. As colloid-facilitated transport of radionuclides reversibly attached to colloids, and 3. As colloid-facilitated transport of radionuclides irreversibly attached to colloids. As indicated in Table 6-15, the nonsorbing radionuclides of carbon, technetium, and iodine are grouped together because their migration is identical. Americium, thorium, and protactinium reversibly attached to colloids are grouped together because of their similar sorption characteristics. Note that plutonium and americium may be transported both reversibly and irreversibly attached to colloids. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-85 October 2004 Table 6-15. Radioelements Transported in the SZ Transport Abstraction Model Radionuclide Number Transport Mode Radioelements 1 Solute Carbon, Technetium, Iodine 2 Colloid-Facilitated (Reversible) Americium, Thorium, Protactinium 3 Colloid-Facilitated (Reversible) Cesium 4 Colloid-Facilitated (Reversible) Plutonium 5 Solute Neptunium 6 Colloid-Facilitated (Irreversible) Plutonium, Americium 7 Solute Radium 8 Solute Strontium 9 Solute Uranium 10 Colloid-Facilitated (Fast Fraction of Irreversible) Plutonium, Americium Output DTNs: SN0310T0502103.010 and SN0310T0502103.012. The radionuclide breakthrough curves from the SZ transport abstraction model for the 200 Monte Carlo realizations of SZ flow and transport are generated as follows: a steady-state groundwater flow field is produced for each of the 200 realizations prior to transport simulations. Variations in the groundwater specific discharge are included by scaling all values of permeability in the base-case SZ site-scale flow model (BSC 2004 [DIRS 170037]) and the values of specified recharge, using the value of the GWSPD parameter. Variations in horizontal anisotropy in permeability are included by scaling the values of north-south and east-west permeability within the zone of volcanic rocks influenced by anisotropy, using the value of the HAVO parameter. Each steady-state groundwater flow solution is stored to be used as the initial conditions in the radionuclide transport simulations. The SZ_Pre V2.0 software code (STN: 10914-2.0-00, SNL 2003 [DIRS 163281]) is a preprocessor that is used to prepare the FEHM V2.20 software code [DIRS 161725] input files for each of the 200 realizations. The preprocessor reads the values of the parameters from an input file containing a table of values for all 200 realizations, performs relevant parameter transformations, and writes the appropriate values to the various FEHM V2.20 software code [DIRS 161725] input files. A total of 7,200 individual simulations (200 realizations × 9 radioelement groups × 4 source regions) of SZ transport are conducted, and the particle tracking output files are saved. The particle tracking simulations of matrix diffusion use the type curves of the analytical solution for matrix diffusion in DTN: LA0302RP831228.001 [DIRS 163557]. The SZ_Post V3.0 software code (STN: 10915-3.0-00, SNL 2003 [DIRS 163571]) is a post-processor that is used to extract the breakthrough curves from the FEHM V2.20 software code [DIRS 161725] output files, and concatenate all 200 realizations into a single file for input to the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]), for use in the TSPA-LA. For implementation of the SZ transport abstraction model in the TSPA-LA model, the specific radionuclides and the timing of climate change events must be specified in the control file for the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). The Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-86 October 2004 radionuclides for each radioelement and their corresponding values of half-life are specified in order for the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]) to calculate the decay of these radionuclides during simulated transport in the SZ. The number of climate states and the times at which climate changes occur during the TSPA-LA model simulation are also specified in the control file for the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). The multiplier of groundwater flow rate in the SZ (relative to present conditions) for each climate state is also specified for the TSPA-LA simulation. The values for this factor are given in Table 6-5. 6.5.3.2 SZ 1-D Transport Model Implementation of the SZ 1-D transport model in the TSPA-LA model requires that the “stand-alone” version of the model developed in this report be correctly integrated into the TSPA-LA model. The SZ 1-D transport model was developed in anticipation of integration into the TSPA-LA model, but the following aspects of the integration are required for implementation in the TSPA-LA model: The radionuclide flux into and out of the SZ 1-D transport model must be properly linked to the other components of the TSPA-LA model. The radionuclide decay and ingrowth chains and the corresponding half-life values of radionuclides must be consistent with the other components of the TSPA-LA model. The parameter values for the 200 realizations of the SZ transport abstraction model are stored as a table in the TSPA-LA model, and the SZ 1-D transport model must be correctly linked with this table of values to ensure consistency with the SZ transport abstraction model on a realization-by-realization basis. The parameter vectors used in the SZ transport abstraction model that need to be incorporated into the table values used by the SZ 1-D transport model are contained in Appendix A of this report and in DTN: SN0310T0502103.009. The variable controlling changes in climate state in the TSPA-LA model must be correctly linked with the SZ 1-D transport model. 6.6 BASE-CASE MODEL RESULTS Base-case model results from the SZ transport abstraction model consist of radionuclide mass breakthrough curves at the accessible environment of the biosphere, approximately 18 km downgradient from the repository. A suite of breakthrough curves is generated for each species or class of radionuclides based on multiple realizations of the model. Variability in the results among these multiple realizations reflects uncertainty in groundwater flow and radionuclide transport behavior in the SZ. Variations in transport behavior among the species are also represented in these results. 6.6.1 Overview The results of the 200 SZ transport abstraction model realizations are shown in Figures 6-28 to 6-36. Each figure shows the relative mass arriving at the accessible environment as a function of time and a histogram of median transport times, for a given category of radionuclides from Table 6-15. Note that the breakthrough curves and transport times shown in these figures are for Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-87 October 2004 a continuous, steady source at the water table below the repository (source region 1), initiated at time equal to zero. Transport simulation results for source region 1 are representative of results for all of the source regions; there are no dramatic variations among the source regions in simulated radionuclide transport times for any given realization. Note that the breakthrough curves shown in these figures are for present climatic conditions, and do not include the effects of radioactive decay. Recall that the process of radioactive decay is implemented in the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). Although individual breakthrough curves can be difficult to discern in some of the figures, both the timing and the shapes of the breakthrough curves vary among the realizations. Variability in the timing of the breakthrough is reflected in the histograms of median transport time, for the bulk of the radionuclide mass arrival at the accessible environment. Variability in the shapes of the breakthrough curves is a function of differences in matrix diffusion and dispersivity among the realizations. The results differ from the results presented in SZ Flow and Transport Model Abstraction (BSC 2003 [DIRS 164870], Section 6.6) for neptunium, plutonium reversibly attached to colloid, cesium reversibly attached to colloids, and uranium. However, the results presented here for the breakthrough curves do not differ significantly from the results in SZ Flow and Transport Model Abstraction (BSC 2003 [DIRS 164870]) for transport times of less than 100,000 years, given the overall uncertainty among the 200 realizations. In addition, simulated breakthrough curves for the fast fraction of plutonium and americium irreversibly attached to colloids are developed for this report, as shown in Figure 6-37. Transport of these radionuclides in the SZ is simulated to occur with no retardation of colloids in the volcanic units or alluvium, and with no matrix diffusion in the volcanic units. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-88 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-28. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Carbon, Technetium, and Iodine at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-89 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-29. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Americium, Thorium, and Protactinium on Reversible Colloids at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-90 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-30. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Cesium on Reversible Colloids at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-91 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-31. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Plutonium on Reversible Colloids at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-92 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-32. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Neptunium at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-93 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-33. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Plutonium and Americium on Irreversible Colloids at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-94 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-34. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Radium at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-95 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-35. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Strontium at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-96 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.010. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-36. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Uranium at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-97 October 2004 1 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass 1 10 100 1000 10000 100000 Time (years) 0 10 20 30 Frequency Output DTN: SN0310T0502103.012. NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include radionuclide decay. Results shown for 200 realizations from source region 1. Figure 6-37. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for the Fast Fraction of Plutonium and Americium on Irreversible Colloids at 18-km Distance Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-98 October 2004 6.6.2 Summary of Results SZ transport simulation results with the SZ transport abstraction model for the nonsorbing radionuclides of carbon, technetium, and iodine indicate that variability in simulated median transport times to the boundary of the accessible environment ranges from a few tens of years to 100,000 years. The bulk of the realizations show transport times ranging from a few hundred years to a few thousand years for nonsorbing species, and a median transport time among all of the realizations of about 640 years. Approximately 97 percent of the realizations of americium, protactinium, and thorium transported as reversibly sorbed onto colloids have simulated transport times of greater than 100,000 years. Approximately 99 percent of the realizations of cesium transported as reversibly sorbed onto colloids have simulated transport times of greater than 100,000 years. Simulated median transport times for plutonium reversibly sorbed on colloids range from a few thousand years to greater than 100,000 years, with a majority of the realizations indicating transport times of greater than 100,000 years. The simulated breakthrough curves for neptunium range from less than 100 years to greater than 100,000 years, with a median transport time among the realizations of about 18,000 years. Simulated median transport times for plutonium and americium irreversibly attached to colloids range from a few hundred years to greater than 100,000 years, with a median among the realizations of about 18,000 years. About 99 percent of the realizations of radium transport have simulated transport times of greater than 100,000 years. Greater than 99 percent of the realizations of strontium transport have simulated transport times of greater than 10,000 years, with the majority of the realizations having median transport times of greater than 100,000 years. Simulated median transport times for uranium range from somewhat less than 1,000 years to greater than 100,000 years, with a median transport time among the realizations of about 24,000 years. Simulated median transport times for plutonium and americium irreversibly attached to the fast fraction of colloids (i.e., with no retardation) range from a few tens of years to greater than 10,000 years, with a median among the realizations of about 300 years. 6.7 DESCRIPTION OF BARRIER CAPABILITY The SZ forms a barrier to the migration of radionuclides and to the exposure of the potential receptor population to these radionuclides in two ways. Delay in the release of radionuclides to the accessible environment during transport in the SZ allows radioactive decay to diminish the mass of radionuclides that are ultimately released. Dilution of radionuclide concentrations in groundwater used by the potential receptor population occurs during transport in the SZ and in the process of producing groundwater from wells. Further discussion of the SZ flow system as a barrier to radionuclide migration at Yucca Mountain is found in a report by Eddebbarh et al. (2003 [DIRS 163577]). 6.7.1 Analyses of Barrier Capability The simulated transport times of radionuclides in the SZ give a direct indication of the barrier capability of the SZ with regard to the delay in the release of radionuclides to the accessible environment. Uncertainty in the radionuclide transport times in the SZ is represented in the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-99 October 2004 multiple realizations of the SZ system with the SZ transport abstraction model and shown in the breakthrough curves for various radionuclides in Figures 6-28 to 6-36. As shown by these figures, the effectiveness of the SZ as a barrier to transport varies significantly among the classes of radionuclides included in the analyses. The ranges of median transport times and the median transport times from all realizations for the various radionuclides are summarized in Table 6-16. Variations in the radionuclide transport time among the realizations shown in Figures 6-28 to 6-36 reflect the aggregate uncertainty in the underlying input parameters to the SZ transport abstraction model. Although formal sensitivity analyses have not been applied to these results, sensitivity analyses have been performed on similar previous SZ transport modeling results (Arnold et al. 2003 [DIRS 163857]). The SZ transport abstraction model has not been significantly changed and the parameter uncertainty distributions have not been dramatically changed in the present modeling, relative to the modeling analyzed in Arnold et al. (2003 [DIRS 163857]). Consequently, the general conclusions from the study are expected to apply to the current modeling. The analyses in Arnold et al. (2003 [DIRS 163857]) indicate that uncertainties in groundwater specific discharge, sorption coefficients, and retardation of colloids are major factors in the simulated uncertainty in radionuclide transport times. Parameters related to matrix diffusion and geologic uncertainty have significant, but secondary importance with regard to the uncertainty in radionuclide transport times. For nonsorbing species, such as carbon, technetium, and iodine, the delay afforded by the SZ can be less than 100 years to as much as 100,000 years, within the range of uncertainty indicated by the simulation results shown in Figure 6-28. The median transport time for nonsorbing species among all realizations is about 620 years. For the moderately sorbing species of neptunium, simulated median transport times range from about 200 years to greater than 100,000 years, with a median transport time among all realizations of 17,100 years (see Table 6-16). For the strongly sorbing species of radium, simulated median transport times range from 80,200 to greater than 100,000 years, with a median transport time among all realizations of greater than 100,000 years (see Table 6-16). Analyses with the SZ transport abstraction model indicate that there is considerable uncertainty in the delay to release of radionuclides to the accessible environment for all radionuclides. The upper bounds of uncertainty in the transport times are greater than 100,000 years (the upper limit of time in the transport simulations) for all radionuclides, with the exception of the fast fraction of plutonium and americium irreversibly attached to colloids. The lower bounds of the uncertainty in transport times are indicated by the ranges given in Table 6-16. It should be noted that the summary of simulated transport times presented in Table 6-16 is given for SZ groundwater flow under present climatic conditions. Under glacial-transition climatic conditions that are expected to occur within the next 10,000 years, the groundwater flow rate would be significantly higher. Groundwater flow rates in the SZ are estimated to be 3.9 times higher under glacial-transition climate conditions (see Section 6.5.1) corresponding to transport times of approximately 3.9 shorter than those presented in Table 6-16. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-100 October 2004 Table 6-16. Summary of Simulated Transport Times in the SZ Under Present Climatic Conditions Species Range of Median Transport Time (years) Median Transport Time Among All Realizations (years) Carbon Technetium Iodine 20 - >100,000 620 Reversible Colloids: Americium Thorium Protactinium 25,000 - >100,000 >100,000 Reversible Colloids: Cesium 80,000 - >100,000 >100,000 Reversible Colloids: Plutonium 5,000 - >100,000 >100,000 Neptunium 200 - >100,000 17,100 Irreversible Colloids: Plutonium Americium 200 - >100,000 19,400 Radium 80,200 - >100,000 >100,000 Strontium 3,300 - >100,000 >100,000 Uranium 600 - >100,000 23,300 Fast Fraction of Irreversible Colloids: Plutonium Americium 20 – 32,620 310 6.7.2 Summary of Barrier Capability Taken as a whole, these analyses indicate that the SZ is expected to be a significant barrier to the transport of radionuclides to the accessible environment within the 10,000-year period of regulatory concern for the repository at Yucca Mountain. The expected behavior of the SZ system is to delay the transport of sorbing radionuclides and radionuclides associated with colloids for many thousands of years, even under future wetter climatic conditions. Nonsorbing radionuclides are expected to be delayed for hundreds of years during transport in the SZ. However, analyses of uncertainty in radionuclide transport in the SZ indicate that delays in the release of nonsorbing radionuclides could be as small as tens of years. The transport times in the SZ of neptunium, uranium, and of plutonium and americium irreversibly attached to colloids could be as small as hundreds of years, based on the analyses of uncertainty conducted with the SZ transport abstraction model. It is important to note that ranges of uncertainty based on analyses with 200 Monte Carlo realizations extend to relatively low probability (approximately 0.5 percent probability) and thus include relatively unlikely results. Nonetheless, lower values in the ranges of transport time are possible, given the degree of uncertainty included in the model. The radioactive decay of radionuclides during transport in the SZ enhances the barrier capability of the SZ by reducing the mass of radionuclides ultimately released to the accessible environment. The effectiveness of the decay process in attenuating releases from the SZ is related to the delay in the SZ and the half-life of the radionuclide. For radionuclides with longer Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-101 October 2004 transport times in the SZ and relatively short half-lives, this process renders the SZ an extremely effective barrier. Strontium-90 and 137Cs transport times would exceed several thousand half-lives, i.e., greater than 100,000 years, based on the median transport time among the realizations (Table 6-16). For comparison, the reduction in radioactivity after 20 half-lives is more than six orders of magnitude. For some radionuclides, a modest reduction in radionuclide mass would occur during transport in the SZ. Plutonium-239 that is irreversibly attached to colloids would be expected to experience about 0.8 half-lives, based on the median transport time among all realizations (Table 6-16). Several radionuclides would experience little attenuation due to radioactive decay during transport in the SZ. Technetium-99, 129I, and 237Np would have only very small reductions in mass during the delay in release afforded by the SZ, due to their long half-lives (2.13 × 105 years for 99Tc to 1.59 × 107 years for 129I). The dilution of radionuclides in the SZ and during pumping from wells by the future hypothetical community in which the RMEI resides is not quantitatively assessed with the transport modeling approach used in the SZ transport abstraction model. The relatively low values of transverse dispersivity in the uncertainty distribution for this parameter suggest that a large amount of dilution in radionuclide concentration during transport from beneath the repository to the accessible environment in the SZ is not expected. It is likely that the amount of dilution implicit in averaging the concentration of radionuclides in 3,000 acre-ft/year of the representative volume of groundwater would be greater than the dilution during transport in the SZ. 6.8 GROSS ALPHA CONCENTRATION Regulations in 10 CFR 63.331 (10 CFR 63 [DIRS 156605]) limit the gross alpha concentration and 226Ra and 228Ra concentration in groundwater. These groundwater protection standards apply to the accessible environment in the Yucca Mountain region and potential impacts of the repository must be compared to them. One aspect of the analysis is an assessment of the natural background concentrations in groundwater near the site because the standards for both gross alpha activity and combined 226Ra and 228Ra activity concentrations (respectively 15 pCi/L and 5 pCi/L (picocuries per liter (pCi/L)), 10 CFR 63 [DIRS 156605], Section 63.331, Table 1) are inclusive of natural background concentrations. 6.8.1 Gross Alpha Activity Data A testing program to measure ambient radiation levels in groundwater was conducted in FY 1998. This work was performed under the YMP QA program. Groundwater samples were collected in June, July, and September of 1998 from each of six wells and two springs. The details and findings of this evaluation were reported in Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420]). The data of interest for this study are the reported gross alpha concentrations (picocuries per liter (pCi/L)) (CRWMS M&O 1999 [DIRS 150420], Section 3.2.1, Table 3) and submitted, with gross beta measurements, to the Total Management Data System as DTN: MO9904RWSJJS98.000 [DIRS 165866]. In Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420], p. 9) it was stated that, when gross alpha Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-102 October 2004 concentrations in groundwater exceed 5 pCi/L, calculation of average combined 226Ra and 228Ra concentration was required. However, Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420], Section 3.2.1) demonstrates the mean gross alpha concentration at each sample location was below 5 pCi/L in FY 1998, and continues by stating that in such cases, it was not necessary to calculate combined 226Ra and 228Ra concentration. As a consequence, data concerning 226Ra and 228Ra concentrations were not presented. 6.8.2 Counting Statistics and Error Prediction Because of the random nature of radioactive decay and the relatively low concentrations of alpha emitting radionuclides in natural groundwater, it is necessary to understand the statistical fluctuations of the analytical method in relation to uncertainty. 6.8.2.1 Counting Statistics and Uncertainty The following discussions on the statistics of radioactive decay measurements are taken from Radiation Detection and Measurement (Knoll 1989 [DIRS 161052], Chapter 3). When a counter is used to detect the number of radioactive decays in a given period of time, the counts from multiple trials have a Poisson distribution. If a single measurement is taken of n counts, then the estimate of the actual average number of counts ( n ) in that period is n (Knoll 1989 [DIRS 161052], p. 84). Furthermore, the sample variance (s2) is also n, implying that the standard deviation (s) is n0.5 (Knoll 1989 [DIRS 161052], p. 85). For large values of n, the Poisson distribution can be approximated by a normal (i.e., Gaussian) distribution, thereby allowing confidence limits for the true mean ( n ) to be established. Measurements involving radioactive decay are generally conducted for sufficient time to establish conditions for this approximation to be valid. One example given by Knoll 1989 [DIRS 161052], Table 3-6, is for a measurement of n = 100, then there is a 90 percent probability that the true mean ( n ) is in the interval s ± 64 . 1 n , or 83.6 to 116.4. The symmetry of the normal distribution indicates that in this example, that there is a 5 percent chance of the true mean being below 83.6 and a 5 percent chance of it being above 116.4. 6.8.2.2 Uncertainty Propagation Measurements involving the counting of radioactive decay events are subject to spurious counts from natural background radiation. The effect of this natural background on the desired results can be negated to a certain extent by performing the measurement twice, once with the sample to be quantified and once without the sample. The former measurement gives a count of the desired signal plus unwanted background noise, while the latter provides an estimate of the background noise. If the counting times for both trials are equal, then the net counts from the sample to be characterized is then the difference between the two measured counts. Following the approach presented by Knoll (1989 [DIRS 161052], p. 88), if there were two counts taken the first x being associated with the sample and background noise and the second y corresponding to the background noise, then the net counts attributable to the sample being Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-103 October 2004 assessed is the difference between x and y. The variance (s2) associated with the net value is the sum of the variances of the two measurements: 2 2 2 y x net s + s = s (Eq. 6-31) Because of the stochastic nature of both radioactive decay and background radiation, it is possible for a sample of low activity to give rise to a total count that is lower than the independently measured background count. These cases produce a negative estimate for the net sample activity. If these measurements to quantify a small level of activity were to be repeated several times, then the stochastic nature of the processes will result in a range of net activity estimates. Some of these results would underestimate the true activity while others would overestimate the true value. Combining the data sets allows the random fluctuations observed in single measurements to be averaged over multiple measurements and thereby reduce statistical variations. This approach is adopted here. If there are n measurements of a variable x, where measurement i is denoted by xi having a variance of 2 i s (number of counts) then the average ( x ) is given by: . = n i x n x 1 1 (Eq. 6-32) Knoll (1989 [DIRS 161052], Equations 3-38 and 3-40) provides an estimate of the standard deviation ( x s ) in x as: .s = s n i x n 1 2 1 (Eq. 6-33) 6.8.3 Applicable Sample Locations Gross alpha concentration data in groundwater from eight locations in the vicinity of the receptor were collected in Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420]). Six of these locations were identified as being in the subbasin (Alkali Flat-Furnace Creek Subbasin) that contains Yucca Mountain, as shown in the first column of Table 6-17 (DTN: MO9904RWSJJS98.000 [DIRS 165866]). The data from these six locations were selected to be the basis of estimating the groundwater gross alpha concentration at the receptor’s location. The data from the Cherry Patch Well and Fairbanks Spring were not used, as these locations are not in the groundwater subbasin containing the repository. It was appreciated that other weighting schemes to obtain a mean activity level from these data were available. Weights could be based on some function of distance of the sampled wells from the receptor location or on the uncertainties of the individual measurements. In the interests of keeping the analysis simple without having to provide justification from any particular scheme, it was elected to use simple averaging. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-104 October 2004 6.8.4 Data Analysis The calculation of the mean activity values and the estimated standard deviation is shown in Table 6-17. It should be noted that the measurements of gross alpha concentrations on these groundwater samples are for all alpha emitters, whereas the regulations in 10 CFR 63.331 (10 CFR 63 [DIRS 156605]) exclude radon and uranium from the standard for gross alpha activity. Consequently, the measurements shown in Table 6-17 overestimate the gross alpha activity exclusionary of radon and uranium. Table 6-17. Data Table Showing Calculation of Mean and Standard Deviation of Gross Alpha Concentration Gross Alpha (xi) Uncertaintya ± Sigma (si) si 2 Location Date (pCi/L) (pCi/L) (pCi/L) (pCi/L)2 NDOT Well 24-Jun-98 -0.08 1.56 0.78 0.608 29-Jul-98 0.32 1.1 0.55 0.303 23-Sep-98 -1.40 0.79 0.40 0.156 Gilgan's South Well 24-Jun-98 -0.63 0.86 0.43 0.185 29-Jul-98 0.64 0.86 0.43 0.185 23-Sep-98 -0.74 0.69 0.35 0.119 UE-25 J-12 23-Jun-98 0.06 0.96 0.48 0.230 28-Jul-98 0.27 0.72 0.36 0.130 22-Sep-98 0.27 0.8 0.40 0.160 UE-25 J-13 23-Jun-98 0.05 0.94 0.47 0.221 28-Jul-98 0.50 0.73 0.37 0.133 22-Sep-98 -0.18 1.2 0.60 0.360 UE-25 c#2 23-Jun-98 1.20 1.33 0.67 0.442 28-Jul-98 1.49 0.94 0.47 0.221 22-Sep-98 0.73 1.67 0.84 0.697 Crystal Pool 22-Jun-98 1.04 1.27 0.64 0.403 27-Jul-98 1.75 1.64 0.82 0.672 25-Sep-98 -0.85 1.21 0.61 0.366 Sxi = 4.44 Ssi 2 = 5.59 Mean Gross Alpha x = 0.25 x s = 0.13 Source: DTN: MO9904RWSJJS98.000 [DIRS 165866]. a Uncertainty is defined as being two standard deviations (sigma) (CRWMS M&O 1999 [DIRS 150420], Section 3.2.1, Note to Table 3 given on p. 9). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-105 October 2004 6.8.5 Results From the discussion in Section 6.8.2 from Knoll (1989 [DIRS 161052], p. 86), there is a 90 percent chance that the true mean of a parameter (µ) will fall in the interval of x x s ± 64 .1 and that in only 5 percent of the cases will the true value exceed x x s + 64 . 1 . From the values presented in Table 6-17 to two decimal places, the best estimate for the mean gross alpha concentration in groundwater is 0.25 pCi/L with a 95 percent confidence that the concentration will not exceed 0.46 pCi/L. The overall uncertainty in the mean gross alpha concentration has a physically defined lower bound of 0.0 pCi/L. The upper bound of the uncertainty in the gross alpha concentration can be reasonably defined using a value that is 3 times the standard deviation above the expected value, which can be calculated as 0.64 pCi/L. A value that is 3 times the standard deviation above the expected value corresponds approximately to the 99.9th percentile in a normal distribution. The overall uncertainty distribution of the mean gross alpha concentration can thus be defined as a truncated normal distribution with a mean of 0.25 pCi/L, a standard deviation of 0.13 pCi/L, a lower bound of 0.0 pCi/L, and an upper bound of 0.64 pCi/L. In the absence of data on the combined concentrations of 226Ra and 228Ra, it should be conservatively assumed for the standards involving these radionuclides that they are responsible for all gross alpha activity. For 226Ra and 228Ra, the mean concentration is 0.25 pCi/L with a 95 percent confidence that the concentration will not exceed 0.46 pCi/L. These results are summarized in Table 6-18. Table 6-18. Summary of Alpha Concentration Results in Amargosa Valley Groundwater Parameter Expected Value pCi/L Upper (95%) Limit pCi/L Gross Alpha Concentration 0.25 0.46 Combined Concentration of 226Ra and 228Ra 0.25 0.46 6.8.6 Corroborative Data Two reports were identified that provided measurements (non-QA) of gross alpha and radium concentrations in groundwater in the vicinity of the receptor that could be used to corroborate the concentrations derived to demonstrate compliance with the groundwater protection standards. These data are discussed below. In Yucca Mountain Site Characterization Project Radiological Programs, Radioactivity in FY 1997 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1998 [DIRS 104963]) the closest measurement site to the location of the receptor is the NDOT well near the intersection of highways US 95 and Route 373. At this location, the annual average gross alpha activity concentration in groundwater during FY 1997 was reported as –0.54 ± 1.20 pCi/L (CRWMS M&O 1998 [DIRS 104963], Table 5). The format is the mean value of 4 quarterly measurements ± two standard deviations. Table 4 of Yucca Mountain Site Characterization Project Radiological Programs, Radioactivity in FY 1997 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1998 [DIRS 104963]) gives, for the same location and year, an average combined 226Ra and 228Ra concentrations in Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-106 October 2004 groundwater of 0.32 ± 0.33 pCi/L. Both these measurements of activity concentrations are consistent with the values provided in Table 6-18. Some additional project data of gross alpha and radium activity concentrations in groundwater are reported in Yucca Mountain Site Characterization Project Radiological Programs White Paper: Radioactivity in Groundwater in the Vicinity of Yucca Mountain (CRWMS M&O 1997 [DIRS 147759], Table 4). These data were based on samples taken during the first and second quarters of 1997. At each location of interest discussed in Section 6.8.3, gross alpha concentrations were reported to be below the detection limit, a limit that was not defined in the report. The combined 226Ra and 228Ra activity concentration (rounded here to two significant figures) ranged from a low value of 0.29 ± 0.27 pCi/L at the NDOT well to a high value of 0.70 ± 0.47 pCi/L at Crystal Pool. These values are consistent with those reported in Section 6.8.5. In Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 [DIRS 156604], p. 8-1), the preamble to Section 8, Groundwater Monitoring, identifies that for the calendar year covered by the report (CY 2000), some results for radioactivity analysis were somewhat higher than historical data. It was also mentioned that the (unidentified) organization providing oversight of groundwater monitoring activities had also experienced similar difficulty in obtaining accurate analytical data. Because, there was no indication as to whether this caveat applied to specific data sets or to all data, it must be assumed that all data based on radioactivity analysis were systematically biased to higher values. The measurement site in Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 [DIRS 156604], Figure 8.3) that is closest to the point of compliance is the Amargosa Valley RV Park, which is shown to be near the intersection of highways US 95 and Route 373 (i.e., close to the NDOT well of CRWMS M&O (1998 [DIRS 104963])). The samples for this site were taken on November 14, 2000, and reported concentrations were based on a single measurement. In Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 [DIRS 156604]) the gross alpha concentration in groundwater was reported to be 0.78 ± 0.50 pCi/L (Table 8.3), the 226Ra concentration was 0.59 ± 0.40 pCi/L (Table 8.6), and the 228Ra concentration was 0.43 ± 0.79 pCi/L (Table 8.7). By combining the two Ra measurements as discussed in Radiation Detection and Measurement (Knoll 1989 [DIRS 161052] Equation 3-38, p. 88), the combined concentration of 226Ra and 228Ra is 1.02 ± 0.89 pCi/L. Given that for a normal distribution the 95 percent confidence limits are at the mean value ± 2 standard deviations, the following statements can be made for the concentrations reported in Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 [DIRS 156604]). Gross alpha: 0.28 pCi/L < actual concentration < 1.28 pCi/L 226Ra and 228Ra: 0.13 pCi/L < actual concentration < 1.91 pCi/L Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-107 October 2004 As the data reported by Townsend (2001 [DIRS 156604]) are stated to have systematically overestimated the concentrations, the above concentration ranges are not inconsistent with those in Table 6-18. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 6-108 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-1 October 2004 7. VALIDATION This section of the report documents the validation of the SZ transport abstraction model and the SZ 1-D transport model. For the SZ transport abstraction model, a comparison is made between the abstraction model and the underlying process model, which is discussed in the report Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036]). This comparison tests the appropriateness and accuracy of the convolution integral method used in the SZ transport abstraction model. Similarly, the validation of the SZ 1-D transport model consists of a qualitative comparison between the abstraction model and the site-scale process model mentioned above (BSC 2004 [DIRS 170036]). In all cases, the validations of these models are performed for a range of behavior that is representative of the uncertainties being evaluated for the TSPA-LA analyses. In addition, this section documents corrections to the SZ 1-D transport model and evaluates the impacts of these corrections (see Section 7.5). 7.1 VALIDATION PROCEDURES As discussed above, validation of both the SZ transport abstraction model and the SZ 1-D transport model involves comparison with the underlying process model (BSC 2004 [DIRS 170036]). In making these comparisons, three cases for radionuclide transport are defined for implementation: median case, fast case, and slow case. The median case uses median values from uncertainty distributions for the relevant flow and transport parameters. The fast case uses parameter values set at the 90th percentile or the 10th percentile, depending on the parameter, that result in more rapid transport of radionuclides through the SZ. For example, the flowing interval spacing is set to its 90th percentile value, and the sorption coefficient is set to its 10th percentile value for transport of neptunium in the fast case. The slow case uses parameter values set at the 90th percentile or 10th percentile that result in less rapid transport of radionuclides through the SZ. These three cases approximately span the range of uncertainty in results of the SZ transport abstraction model with regard to radionuclide transport in the SZ, as shown in Figures 6-28 and 6-32. The parameter values used in the median, fast, and slow cases are summarized in Table 7-1. The SZ site-scale transport model (BSC 2004 [DIRS 170036]) was run for each of the three model validation cases by varying the input parameters to conform to the values given in Table 7-1. The steady-state groundwater flow solution for each case was first established by running the flow model (BSC 2004 [DIRS 170037]) to equilibrium with the specified values of the parameters GWSPD and HAVO. The particle-tracking algorithm in the FEHM V2.20 software code [DIRS 161725] was then used to obtain the simulated mass breakthrough curves with the SZ site-scale transport model at the regulatory boundary of the accessible environment. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-2 October 2004 Table 7-1. Parameter Values in the Three Cases for SZ Transport Model Validation Parameter Name Parameter Description Median Case Fast Case Slow Case FISVO Flowing interval spacing in volcanic units 1.29 (19.5 m) 1.82 (66.1 m) 0.67 (4.68 m) HAVO Ratio of horizontal anisotropy in permeability 4.2 16.25 1.0 LDISP Longitudinal dispersivity 2.0 (100 m) 2.96 (920 m) 1.03 (10.9 m) FPLAW Western boundary of the alluvial uncertainty zone 0.5 0.1 0.9 FPLAN Northern boundary of the alluvial uncertainty zone 0.5 0.1 0.9 NVF19 Effective porosity in shallow alluvium 0.18 0.114 0.245 NVF7 Effective porosity in undifferentiated valley fill 0.18 0.114 0.245 FPVO Fracture porosity in volcanic units -3.0 (10-3) -3.89 (1.29 × 10-4) -1.50 (0.0316) DCVO Effective diffusion coefficient in volcanic units -10.3 (5.0 × 10-11 m2/s) -10.68 (2.08 × 10-11 m2/s) -9.65 (2.22 × 10-10 m2/s) GWSPD Groundwater specific discharge multiplier 0.0 (1.0) 0.477 (3.0) -0.477 (0.333) bulkdensity Bulk density of alluvium 1910 kg/m3 1810 kg/m3 2010 kg/m3 KDNPVO Neptunium sorption coefficient in volcanic units 1.3 mL/g 1.04 mL/g 1.6 mL/g KDNPAL Neptunium sorption coefficient in alluvium 6.35 mL/g 4.26 mL/g 8.44 mL/g NOTE: Values in parentheses are the parameter values from log-transformed uncertainty distributions. 7.1.1 SZ Transport Abstraction Model Validation of the SZ transport abstraction model is accomplished by running this model using the breakthrough curves for the three validation cases from the SZ site-scale transport model (BSC 2004 [DIRS 170036]). The SZ transport abstraction model uses the convolution integral method as implemented by the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]) to produce the radionuclide mass breakthrough to the accessible environment, given the time-varying input of mass at the water table below the repository for the TSPA-LA. Note that model validation tests were performed with the SZ_Convolute V2.2 software code (STN: 10207-2.2-00, SNL 2003 [DIRS 163344]). For the first validation test, a constant input of 1 g/year from the UZ is applied at the water table beneath the repository in the SZ transport abstraction model. This is essentially the same transport boundary condition used in the SZ site-scale transport model (BSC 2004 [DIRS 170036]) to derive the SZ breakthrough curves for input to the abstraction model. Consequently, the output of the SZ transport abstraction model should reproduce the breakthrough curve used as the input in the validation test. This validation test is conducted for both a nonsorbing species and for neptunium. The validation test is also run for the three Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-3 October 2004 validation cases described in the previous section. To facilitate comparison of the results, the transport simulations in both the SZ site-scale transport model and the SZ transport abstraction model are performed without radioactive decay. As a second validation test, the mass balance of radionuclides transported in the SZ transport abstraction model is checked. This check is performed by setting the upstream boundary condition equal to 1 g/year for time up to 1,000 years and reducing this to 0 g/year for the remainder of the simulation. Thus, the total radionuclide mass input to the SZ transport abstraction model is 1,000 grams. Since radioactive decay is not included in this validation test, the cumulative output of the model over a long simulation time should also be 1,000 grams. This second validation test is also run for the three validation cases described in the previous section (Table 7-1). It should be noted that several additional test cases for the SZ_Convolute V2.2 software code (SZ_Convolute V2.2, STN: 10207-2.2-00, [DIRS 163344]) have been conducted for the purposes of software verification (BSC 2003, [DIRS 163587]). These tests verify the ability of the convolution integral method, as implemented by the SZ_Convolute V2.2 software code (STN: 10207-2.2-00, SNL 2003 [DIRS 163344]), to simulate accurately radionuclide transport with variable input boundary conditions, radioactive decay, and variations in groundwater flux with climate change. Although not directly applied to the radionuclide transport results of the SZ transport abstraction model presented in this report, the numerical testing of the software code used in this model provides additional confidence in the validity of the model. 7.1.2 SZ 1-D Transport Model Validation of the SZ 1-D transport model is conducted by running this model and comparing the results to the output of the SZ site-scale transport model (BSC 2004 [DIRS 170036] and DTN: LA0306SK831231.001 [DIRS 164362]). The SZ 1-D transport model is implemented using the GoldSim V7.50.100 software code. Ultimately, the SZ 1-D transport model is fully integrated into the TSPA-LA model; however, for the purposes of model development and validation, a stand-alone version of this model is used. For the validation test, a constant input of 1 g/year from the UZ is applied at the upstream boundary of the SZ 1-D transport model. This is the same radionuclide mass boundary condition used in the SZ site-scale transport model (BSC 2004 [DIRS 170036]). The breakthrough curves from the SZ 1-D model should approximately match the output of the site-scale transport model. This validation test is conducted for both a nonsorbing species and for neptunium, and is run for the three validation cases described in the previous section. To facilitate comparison of the results, the transport simulations in both the SZ site-scale transport model and the SZ 1-D transport model are performed without radioactive decay. It should be noted that several additional test cases for the GoldSim V7.50.100-00 software code have been conducted for the purposes of software verification (BSC 2002 (BSC 2002 [DIRS 163962]). These tests verify the ability of the GoldSim V7.50.100-00 software code to accurately simulate radioactive decay and ingrowth. Although not directly applied to the radionuclide transport results of the SZ 1-D transport model presented in this report, the numerical testing of the software code used in this model provides additional confidence in the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-4 October 2004 validity of the model. It should also be noted that a problem in the GoldSim V7.50.100-00 software code with regard to parameter sampling was identified subsequent to the validation testing documented in this report and this problem is reported in CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009). The parameter-sampling component of the GoldSim V7.50.100-00 software code was not used in the validation testing of the SZ 1-D transport model and the problem reported in CR 2222 is thus not relevant to the validation testing conducted for this report. Groundwater flow rates and flow-path lengths derived from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) were used in the development of the SZ 1-D transport model. However, both the approximate nature of the equivalency between the two models and the reduction in dimensionality in the 1-D transport model limit the ability of the 1-D model to match the results of the site-scale transport model. Among the realizations of SZ transport in the TSPA-LA analyses, the source locations within each of the four source regions beneath the repository are varied in the SZ transport abstraction model. However, the impact of this variability on flow paths and flow-path lengths is not captured in the SZ 1-D transport model. This limitation of the SZ 1-D transport model results in some differences in simulation results between the SZ transport abstraction model and the SZ 1-D transport model for any given realization in the TSPA-LA analyses. These differences are evaluated for a sampling of realizations and the results are also documented in Section 7.3.2. The results of this evaluation indicate acceptable agreement between the SZ 1-D transport model and the SZ site-scale transport model, from which it was abstracted. 7.2 VALIDATION CRITERIA The current Technical Work Plan For: Natural System – Saturated Zone Analysis and Model Report Integration (BSC 2004 [DIRS 171421], Section 2.2.1.1) states that model validation was completed following criteria in the previous version of the technical work plan (TWP). Model validation presented in Section 7 of this report follows the Technical Work Plan for: Saturated Zone Flow and Transport Modeling and Testing (BSC 2003 [DIRS 166034], Section 2.5). The previous TWP (BSC 2003 [DIRS 166034], Section 2.5) states that Level-II validation will be achieved through confidence building activities during model development and by implementing one post-development validation method. In the cases of the SZ transport abstraction model and the SZ 1-D transport model, the post-development method was chosen to be the corroboration of the abstraction model results to the results of the validated process model from which the abstraction was derived (BSC 2003 [DIRS 166034], Section 2.5). This is the most appropriate method of model validation because the underlying process model (the SZ site-scale transport model) has undergone validation independently, and the SZ transport abstraction model and the SZ 1-D transport model are derived directly from this process model. In addition, the TWP validation plan for the SZ Flow and transport abstraction model includes a check of output for mass balance. The acceptance criterion for validation of both the SZ transport abstraction model and the SZ 1-D transport model is a favorable qualitative comparison between the simulated SZ breakthrough curves from these two models and the breakthrough curve from the SZ site-scale transport model conducted by visual examination of graphs made of the breakthrough curves (BSC 2004 [DIRS 170036] and DTN: LA0306SK831231.001 [DIRS 164362]). The Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-5 October 2004 breakthrough curves are compared at 10 percent, 50 percent, and 90 percent mass breakthrough in the evaluation of this criterion. Breakthrough curves are compared for a nonsorbing species and for neptunium. Breakthrough curves for the median, fast, and slow cases outlined above are compared. An additional acceptance criterion for the validation of the SZ transport abstraction model is a check of the radionuclide mass balance in the model. The mass input to the model should equal the mass output from the model over long time periods. Discrepancies of a few percent are acceptable due to both less-than-complete discharge of radionuclide mass from the model and numerical (truncation) errors in the computer software implementing the numerical integration used in the convolution integral method. These acceptance criteria reflect the essential functions of the SZ system with regard to the transport time and radionuclide mass delivery to the accessible environment. 7.2.1 Confidence Building During Model Development to Establish Scientific Basis and Accuracy for Intended Use For Level II validation, the development of the models should be documented in accordance with the requirements of Section 5.3.2(b) of AP-SIII.10Q. The development of the SZ transport abstraction model and the SZ 1-D transport model has been conducted in accordance with these criteria, as follows: 1. Selection of input parameters and/or input data, and a discussion of how the selection process builds confidence in the model. [AP-SIII.10 Q 5.3.2(b) (1) and AP-2.27Q Attachment 3 Level I (a)] The inputs to the SZ transport abstraction model and the SZ 1-D transport model have all been obtained from controlled sources (see Tables 4-1, 4-2, and 4-3), including discussion about selection of input and design parameters (Section 4.1). The SZ transport abstraction model takes the SZ site-scale transport model, which has been independently validated (BSC 2004 [DIRS 170036]), as a direct input. Model assumptions have been described in Section 5. Detailed discussion about model concepts can be found in Section 6.3. Section 6.5.2 contains detailed discussion and analyses of data sources and parameter uncertainty, leading to increased confidence in the parameters that are used in the models presented in this report. Thus, this requirement is considered satisfied. 2. Description of calibration activities, and/or initial boundary condition runs, and/or run convergences, simulation conditions set up to span the range of intended use and avoid inconsistent outputs, and a discussion of how the activity or activities build confidence in the model. Inclusion of a discussion of impacts of any non-convergence runs [(AP-SIII.10Q 5.3.2(b)(2) and AP-2.27Q Attachment 3 Level I (e)]. The SZ transport abstraction model and the SZ 1-D transport model use the SZ sitescale transport model (BSC 2004 [DIRS 170036]), which is itself based on the calibrated SZ site-scale flow model (BSC 2004 [DIRS 170037]), as a starting point. The SZ transport abstraction model generates breakthrough curves for a unit point Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-6 October 2004 source, hence initial and boundary conditions for radionuclide mass transport are established through linkage to the UZ transport model in TSPA-LA model simulations. The SZ 1-D transport model obtains boundary conditions for radionuclide mass from the UZ in the TSPA-LA model. Section 6.3.3 discusses the source term for the models. Section 6.6 provides detailed discussion of model results. Discussion about nonconvergence runs is not relevant for this model report. Thus, this requirement is considered satisfied. 3. Discussion of the impacts of uncertainties to the model results including how the model results represent the range of possible outcomes consistent with important uncertainties.[(AP-SIII.10 Q 5.3.2(b)(3) and AP-2.27Q Attachment 3 Level 1 (d) and (f)]. Results of 200 realizations of the SZ transport abstraction model are presented in Section 6.6. These results constitute an assessment of the impacts of uncertainty in model parameters and provide this information as a direct feed to the probabilistic analyses of the TSPA-LA model. 4. Formulation of defensible assumptions and simplifications. [AP-2.27Q Attachment 3 Level I (b)]. Discussion of assumptions and simplifications are provided in Section 5 and Section 6.3. The conceptual model of transport in the SZ and the components of the model are discussed in Section 6.3. Justification of assumptions and discussion of their implications for the models are also provided. 5. Consistency with physical principles, such as conservation of mass, energy, and momentum. [AP-2.27Q Attachment 3 Level I (c)] Consistency with physical principles is demonstrated by the conceptual and mathematical formulation of the SZ transport abstraction model and the SZ 1-D transport model in Sections 6.3 and 6.5.1, and the selection and use of the FEHM and GoldSim software codes in Section 3. Thus, this requirement is considered satisfied. 7.2.2 Confidence Building After Model Development to Support the Scientific Basis of the Model Model validation requires mathematical models be validated by one or more of several methods given in Section 5.3.2(c and d) of AP-SIII.10Q. Validation of the SZ transport abstraction model and the SZ 1-D transport model is documented in Section 7 of this report and is related to the procedural requirements as follows: 1. AP-SIII.10 Q 5.3.2(c), Method 6: Corroboration of abstraction model results to the results of the validated mathematical model from which the abstraction model is derived. The SZ transport abstraction model and the SZ 1-D transport model are validated by comparing results from these models with the SZ site-scale transport model, which is Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-7 October 2004 the underlying validated mathematical (process) model from which they are derived. The validation criteria, testing, and results are described in detail in Section 7 of this report. 2. AP-SIII.10 Q 5.3.2(d): Technical review through publication in a refereed professional journal. The SZ transport abstraction model and its results are described in the refereed professional publication of Arnold et al. (2003 [DIRS 163857]). This publication demonstrates additional confidence in the model, when taken in conjunction with the model validation activity described in item 1 above. 7.3 RESULTS OF VALIDATION ACTIVITIES The numerical results of the model validation activities described above are presented primarily as a series of plots of simulated breakthrough curves. A quantitative comparison of models with regard to radionuclide mass balance is also presented for the SZ transport abstraction model. 7.3.1 SZ Transport Abstraction Model Validation Results Results of the SZ transport abstraction model and the SZ site-scale transport model (BSC 2004 [DIRS 170036]) for a nonsorbing species are shown as simulated breakthrough curves in Figure 7-1. This figure shows results for the median, fast and slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. The simulated breakthrough curves from the SZ site-scale transport model are shown with the solid and dashed lines for the three cases. The results from the SZ transport abstraction model are shown as the open symbols that are superimposed on the breakthrough curves from the site-scale model. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-8 October 2004 10 100 1000 10000 100000 1000000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case (solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ transport abstraction model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). Breakthrough curves do not include radioactive decay. Figure 7-1. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction Model and the SZ Site-Scale Transport Model for a Nonsorbing Radionuclide Visual comparison of the open symbols and the lines in Figure 7-1 indicates agreement within a few percent of relative mass in the results from the SZ transport abstraction model and the SZ site-scale transport model for all three cases of SZ transport. The one exception is the first point in the results of the SZ transport abstraction model for the fast case, which is lower than the corresponding breakthrough curve from the SZ site-scale transport model. It should be noted that the time step used in the abstraction model is 20 years, which differs from the 10-year time step used in the site-scale model for the fast case. This difference in time-step size accounts for the small discrepancy between the models at the first time step. Results of the SZ transport abstraction model and the SZ site-scale transport model (BSC 2004 [DIRS 170036] and DTN: LA0306SK831231.001 [DIRS 164362]) for neptunium are shown as simulated breakthrough curves in Figure 7-2. This figure shows results for the median, fast, and slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. The simulated breakthrough curves from the SZ site-scale transport model are shown with the solid and dashed lines for the three cases. The results from the SZ transport abstraction model are shown as the open symbols that are superimposed on the breakthrough curves from the site-scale model. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-9 October 2004 10 100 1000 10000 100000 1000000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case (solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ transport abstraction model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). Breakthrough curves do not include radioactive decay. Figure 7-2. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction Model and the SZ Site-Scale Transport Model for Neptunium Visual comparison of the open symbols and the lines in Figure 7-2 indicates agreement within a few percent of relative mass in the results from the SZ transport abstraction model and the SZ site-scale transport model for all three cases of SZ transport of neptunium. Figure 7-3 shows the simulated breakthrough curve from the SZ transport abstraction model of a nonsorbing species for the median case. This simulation applies a radionuclide mass influx boundary condition of 1 g/year for the first 1,000 years of the simulation, which results in a total mass input of 1,000 grams. The mass balance in the SZ transport abstraction model is checked by summing the total mass output from the simulated breakthrough curve shown in Figure 7-3 over the 100,000 years of the simulation. The output sum is 981 grams, which is 98.1 percent of the input mass. Examination of the simulated breakthrough curve from the SZ site-scale transport model for the median case indicates that 98 percent of the mass has reached the accessible environment within 100,000 years. Consequently, the discrepancy between total input mass and total output mass can be explained as the radionuclide mass retained in the SZ system after 100,000 years. The total output mass from the SZ transport abstraction model for the fast case and the slow case is 99.8 percent and 99.5 percent of the input mass, respectively. Mass breakthrough for the median case has a longer “tail” than the slow and fast cases due to matrix diffusion. Consequently, the total mass output is somewhat lower for the median case than the slow and fast cases in this validation test. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-10 October 2004 10 100 1000 10000 100000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass NOTE: Results from the SZ transport abstraction model are shown for the median case. The breakthrough curve does not include radioactive decay. Figure 7-3. Simulated Breakthrough Curve for a Nonsorbing Radionuclide from a 1000-Year-Duration Source 7.3.2 SZ 1-D Transport Model Validation Results Results of the SZ 1-D transport model and the SZ site-scale transport model for a nonsorbing species are shown as simulated breakthrough curves in Figure 7-4. This figure shows results for the median, fast, and slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. The simulated breakthrough curves from the SZ site-scale transport model are shown with the solid and dashed lines for the three cases. The results from the SZ 1-D transport model are shown as the open symbols superimposed on the breakthrough curves from the SZ site-scale transport model. Visual comparison of the open symbols and the lines in Figure 7-4 indicates close agreement in the results for a nonsorbing species from the SZ 1-D transport model and the SZ site-scale transport model for the median case of SZ transport. There is generally close comparison in the overall shapes of the breakthrough curves from the SZ 1-D transport model and the SZ site-scale transport model, as indicated by the times of 10 percent, 50 percent, and 90 percent of mass breakthrough, with somewhat greater deviation for the upper tails of the breakthrough curves. Results of the SZ 1-D transport model and the SZ site-scale transport model for neptunium are shown as simulated breakthrough curves in Figure 7-5. This figure shows results for the median, fast and slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. The simulated breakthrough curves from the SZ site-scale transport model are shown with the solid and dashed lines for the three cases. The results from the SZ 1-D transport Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-11 October 2004 model are shown as the open symbols superimposed on the breakthrough curves from the SZ site-scale transport model. Visual comparison of the open symbols and the lines in Figure 7-5 indicates close agreement in the results for neptunium from the SZ 1-D transport model and the SZ site-scale transport model for the median case of SZ transport. The comparison is slightly less close for the fast case and slow case. There is generally close comparison in the overall shapes of the breakthrough curves from the SZ 1-D transport model and the SZ site-scale transport model. Results of the SZ 1-D transport model and the SZ transport abstraction model for a nonsorbing species and neptunium are shown and compared in Figure 7-6. These results are for a single realization (above) and for the average of 15 realizations (below). Comparison between the simulated breakthrough curves for the SZ 1-D transport model and the SZ transport abstraction model for a single realization shows differences between the simulated results, particularly for neptunium transport in this realization. However, there are small differences between the simulated breakthrough curves when the results are averaged over 15 realizations of the models, as shown in the lower plot in Figure 7-6. For the case of nonsorbing species, the average of the SZ 1-D transport model simulations shows somewhat earlier breakthrough for the tail of the breakthrough curve, relative to the SZ transport abstraction model. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-12 October 2004 10 100 1000 10000 100000 1000000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass Output DTN: SN0306T0502103.005. NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case (solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D transport model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). Breakthrough curves do not include radioactive decay. Figure 7-4. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and the SZ Site-Scale Transport Model for a Nonsorbing Radionuclide Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-13 October 2004 10 100 1000 10000 100000 1000000 Time (years) 0 0.2 0.4 0.6 0.8 1 Relative Mass Output DTN: SN0306T0502103.005. NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case (solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D transport model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). Breakthrough curves do not include radioactive decay. Figure 7-5 Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and the SZ Site-Scale Transport Model for Neptunium Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-14 October 2004 Figure 7-6. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model (1D) and the SZ Transport Abstraction Model (3D) for a Nonsorbing Radionuclide (I129) and Neptunium (Np237) for a Single Realization (Above) and for the Average of 15 Realizations (Below) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-15 October 2004 7.4 CONCLUSIONS 7.4.1 SZ Transport Abstraction Model Validation Validation testing of the SZ transport abstraction model indicates good agreement with the SZ site-scale transport model (BSC 2004 [DIRS 170036]). Acceptance criteria established for the model validation regarding the qualitative comparison of simulated breakthrough curves and the quantitative evaluation of radionuclide mass balance are met. Results of the validation testing indicate that the SZ transport abstraction model is valid for the approximate range of uncertainty incorporated into the model through parameter uncertainty distributions. Results also indicate that the SZ transport abstraction model is valid for both nonsorbing and sorbing radionuclide species for its intended use. It should be noted that the SZ is more effective as a barrier for highly sorbing, short-lived radionuclides such as 90Sr and 137Cs, relative to neptunium, as used in this validation testing. The validation testing does not demonstrate the delay afforded by the SZ in the migration of these radionuclides; nor does it demonstrate the impact of radionuclide decay. However, the importance of the SZ as a barrier to 90Sr and 137Cs transport, with regard to both delay and decay, is discussed in Section 6.7. The small deviation from the SZ site-scale transport model results at early times for the fast case is a result of the time-step size used in the simulation. Such deviations in the abstraction model for realizations with very fast transport in the SZ would not be significant within the context of the TSPA-LA analyses using this model. The discrepancy in radionuclide mass balance identified in the validation testing is a small percentage and is readily understood with regard to long-term mass retention in the SZ due to the matrix diffusion process. No future activities are needed to complete this model validation for its intended use. 7.4.2 SZ 1-D Transport Model Validation Validation testing of the SZ 1-D transport model indicates acceptable agreement with the SZ site-scale transport model (BSC 2004 [DIRS 170036]). Qualitative acceptance criteria regarding the comparison of the simulated breakthrough curves with the results of the SZ site-scale transport model are met. Results of the validation testing indicate that the SZ 1-D transport model is valid for the approximate range of uncertainty incorporated into the model through parameter uncertainty distributions. Results also indicate that the SZ 1-D transport model is valid for both nonsorbing and sorbing radionuclide species for its intended use. It is relevant to consider the purpose and use of the SZ 1-D transport model in the evaluation of validation testing results. This model is used for the purpose of simulating radioactive decay and ingrowth for four decay chains. This simplified model is required because the SZ transport abstraction model is not capable of simulating ingrowth by radioactive decay. It is not anticipated that the decay products in these decay chains would be significant contributors to total radiological dose; however, groundwater protection regulations require assessment of groundwater concentrations for some of these decay products. The results of the SZ 1-D transport model are used only for the decay products in these decay chains within the TSPA-LA analyses. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-16 October 2004 It must also be considered that there are fundamental differences between the SZ 1-D transport model and the SZ site-scale transport model that limit the degree of consistency that can be expected between these two models. Groundwater flow and radionuclide transport simulation in the SZ site-scale transport model occur in three dimensions with a relatively complex representation of geological heterogeneity from the hydrogeologic framework model. Radionuclide transport in the SZ 1-D transport model is simulated in a significantly simplified representation of the SZ system consisting of three pipe segments. Each pipe segment has properties that represent the average characteristics in that area of the SZ site-scale transport model. There are also variations in the source location within the four source regions beneath the repository simulated by the SZ transport abstraction model that are not incorporated in the SZ 1-D transport model on a realization-by-realization basis, as discussed in Section 7.1.2. Another difference between the SZ 1-D transport model and the SZ transport abstraction model is the way in which changes in groundwater flux related to climate change are handled. A fundamental limitation to the Laplace transform solution used by the GoldSim software code to simulate radionuclide transport in the “pipe” module is that radionuclide mass in transit through a particular pipe segment does not change in response to changes in specified groundwater flow rate. Consequently, radionuclide mass that has entered a pipe segment in the SZ 1-D transport model before increased flow rates are imposed at 600 and 2,000 years for the monsoonal and glacial-transition climate states in the TSPA-LA model, would not be instantaneously accelerated, as it is in the SZ transport abstraction model. Because peak releases of radionuclides to the SZ are not expected to occur within the first 2,000 years of the TSPA-LA simulations, this limitation to the SZ 1-D transport model is unlikely to have a significant impact on the simulation results. Comparison of simulation results from the SZ 1-D transport model and the SZ transport abstraction model shows that there are differences for individual realizations, as used in the TSPA-LA analyses. However, when results are averaged over several realizations the ensemble behavior of the SZ 1-D transport model is very similar to the SZ transport abstraction model. This indicates that there is no consistent bias in the simulation results from the SZ 1-D transport model relative to the SZ transport abstraction model. Given this finding and the intended use of the SZ 1-D transport model for the simulation of decay chain products only, differences in the results with the SZ transport abstraction model for individual realizations are acceptable. Considering these factors, the SZ 1-D transport model provides a good approximation of simulated radionuclide transport in the 3-D system of the SZ. No future activities are needed to complete this model validation for its intended use. 7.4.3 Validation Summary The SZ transport abstraction model and the SZ 1-D transport model have been validated by applying acceptance criteria based on an evaluation of the models’ relative importance to the potential performance of the repository system. All relevant validation requirements have been fulfilled, including corroboration of model results with comparison to the model from which they were derived and publication in a refereed professional journal. Activities requirements for confidence building during model development have also been satisfied. The model development activities and post-development validation activities described establish the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-17 October 2004 scientific bases for the SZ transport abstraction model and the SZ 1-D transport model. Based on this, the SZ transport abstraction model and the SZ 1-D transport model used in this report are considered to be sufficiently accurate and adequate for the intended purpose and to the level of confidence required by the models’ relative importance to the potential performance of the repository system. 7.5 CORRECTION TO THE SZ 1-D TRANSPORT MODEL Reevaluation of the SZ 1-D transport model has indicated two corrections to the model relative to the model file contained in output DTN: SN0306T0502103.005. This section of the report describes those corrections and evaluates their impact with regard to radionuclide transport simulation results in the SZ 1-D transport model. The first correction is for the value of average matrix porosity of the volcanic units used to divide the free water diffusion coefficient. The value used in the original model file is 0.20, but it should be 0.21 to be consistent with the value used in the pipe segments to analyze matrix diffusion. The second correction is to the effective value of the flowing interval spacing used in the pipe segments to simulate matrix diffusion. In the original model file the value of flowing interval spacing (FISVO) was converted from the log-transformed value to the actual value and divided by 4. The corrected calculation is to divide the value by 2. The impact of these corrections is evaluated by comparing the original results with the corrected results for the average breakthrough curves of a nonsorbing species and of neptunium with the SZ 1-D transport model. The model results for this comparison are shown in Figure 7-7. Examination of these results indicates that the agreement between the average breakthrough curves for the SZ 1-D transport model and the SZ transport abstraction model is better for the corrected SZ 1-D transport model than for the original SZ 1-D transport model. This is particularly true for the transport of nonsorbing radionuclides; the differences between the original and corrected versions of the SZ 1-D transport model are minimal for the transport of neptunium. Based on these results it is concluded that the impacts of the corrections to the SZ 1-D transport model are small with regard to validation of the SZ 1-D transport model. Further more, for the 15 realizations used in the impact analysis, the original SZ 1-D transport model overpredicts the rate of migration of nonsorbing species in the tail of the average breakthrough curve, relative to the SZ transport abstraction model. Overprediction of the rate of migration of radionuclides results in higher simulated dose in the TSPA-LA model. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 7-18 October 2004 Figure 7-7. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D transport model (1D) and the SZ Transport Abstraction Model (3D) for a Nonsorbing Radionuclide (I129) and Neptunium (Np237) for the Average of 15 Realizations for the Original (Above) and Corrected SZ 1-D Transport Model (Below) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-1 October 2004 8. CONCLUSIONS 8.1 SUMMARY OF MODELING ACTIVITY The SZ transport abstraction model and the SZ 1-D transport model are developed for use in the TSPA-LA analyses. In addition, analyses of uncertainty in input parameters for these models are conducted, and the results are documented as uncertainty distributions. Values of uncertain parameters are sampled for 200 realizations of the SZ flow and transport system. Simulations using the SZ transport abstraction model are conducted for these 200 realizations, and the results are documented in this report. Analyses of parameter uncertainty and of multiple realizations of the SZ system, using the SZ transport abstraction model, constitute an assessment of uncertainty in the SZ system that is useful for direct implementation in the TSPA-LA model. The simulated radionuclide mass breakthrough curves from the SZ transport abstraction model are coupled to the TSPA-LA analyses using the convolution integral method (via the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180])). In addition, the SZ 1-D transport model is developed for direct implementation, in conjunction with the GoldSim V7.50.100 software code, in the TSPA-LA. The uncertain input parameters defined for the SZ transport abstraction model are used in the SZ 1-D transport model, to provide consistency between the two models when they are used in the probabilistic analyses of the TSPA-LA. The SZ transport abstraction model and the SZ 1-D transport model are validated, and the results of these validation activities are documented in this report. Validation of the SZ transport abstraction model indicates very close agreement with the underlying SZ site-scale transport model when the convolution integral method is used. Although the SZ 1-D transport model is much simpler than the 3-D SZ transport abstraction model, validation of the SZ 1-D transport model indicates there is close agreement, over a broad range of uncertainty, between the 1-D and 3-D models with respect to each model’s assessment of transport behavior of representative radionuclides. The technical bases of FEPs included in the models are presented in this report, and are provided to clarify the parameters and components of the SZ transport abstraction model and the SZ 1-D transport model. The role of the SZ as a natural barrier to the transport of radionuclides is assessed in relation to the results of the SZ transport abstraction model. In addition, the model development and analyses presented in this report address those YMRP acceptance criteria (NRC 2003 [DIRS 163274]) that are listed in Section 4.2 of this report. Information on the correlation between distribution coefficients (Kds) used in the sampling of uncertain parameters for the SZ transport abstraction model and for the SZ 1-D transport model is provided in Table 4-3 and Table 6-8. Positive correlation between the distribution coefficient for uranium in volcanic units and alluvium is specified, based on potentially similar hydrochemical conditions in the two aquifers. Positive correlation between the distribution coefficient for neptunium in volcanic units and alluvium is specified, based on potentially similar hydrochemical conditions in the two aquifers. Positive correlation between the distribution Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-2 October 2004 coefficient for plutonium in volcanic units and alluvium is specified, based on potentially similar hydrochemical conditions in the two aquifers. Positive correlation between the distribution coefficients for uranium and neptunium is specified, based on similarities in the chemical behavior of these radioelements. The technical bases for correlations between distribution coefficients (or the lack thereof) are documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Section C1.2.1). Evaluation of uncertainty in horizontal anisotropy in permeability is summarized in Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is given in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010]), Section 6.2.6. Results of this evaluation indicate that there is a greater probability of enhanced permeability in the north-south direction, but a small probability of greater permeability in the east-west direction. Implementation of uncertainty in horizontal anisotropy in the SZ transport abstraction model and in the SZ 1-D transport model is discussed in Section 6.5.3.1 and Section 6.5.1.2, respectively. The impacts of spatial variability of parameters affecting radionuclide transport in the alluvium are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. Uncertainties in individual parameters affecting radionuclide transport, as influenced by spatial variability, are combined in the probabilistic analyses with the SZ transport abstraction model. The technical bases for uncertainty in distribution coefficients are documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Attachment A). Information on geological uncertainty in the location of the contact between tuff and alluvium, and the consequent uncertainty in flow-path lengths in the alluvium, is presented in Section 6.5.2.2. This evaluation of uncertainty includes information from the Nye County drilling program. Reevaluation of the uncertainty in the northern and western extent of the alluvium resulted in significant reduction in this uncertainty, in comparison to the previous evaluation (CRWMS M&O 2000 [DIRS 147972], Section 6.2). The sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in the assessment of ACMs in Section 6.4. The results of this sensitivity analysis indicate that a minimal matrix diffusion ACM is captured within the range of uncertainty used in the SZ transport abstraction model. 8.2 MODEL OUTPUTS 8.2.1 Developed Output The technical output from this report is given in seven DTNs; these DTNs are summarized in Table 8-1. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-3 October 2004 Table 8-1. Summary of Developed Output Output DTN Description SN0310T0502103.009 Uncertainty distributions for parameters used in the SZ transport abstraction model. Sampling output of uncertain parameters for 200 realizations is also included (see Appendix I). This DTN also includes a description of each uncertain parameter. SN0310T0502103.010 Input and output files for the SZ transport abstraction model. This DTN also contains the output breakthrough curves for use in the TSPA-LA analyses. SN0306T0502103.005 Input and output files for the SZ 1-D transport model. SN0306T0502103.006 Data spreadsheets to support data uncertainty development. SN0310T0502103.012 Input and output files for the SZ transport abstraction model for the fast fraction of radionuclides irreversibly attached to colloids. This DTN also contains the output breakthrough curves for use in the TSPA-LA analyses. SN0407T0502103.013 Input and output files for the SZ transport abstraction model with re-sampling of input parameters to address CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009). This DTN also contains the output breakthrough curves for use in the TSPA-LA analyses. MO0310SPANGRAC.000 Results of the background gross alpha concentration analysis. Results of the parameter uncertainty analyses from this report are given in DTN: SN0310T0502103.009. These results include the uncertainty distributions for parameters that were developed in this analysis or incorporated from other analyses and the input file for the GoldSim V7.50.100 software code for sampling 200 realizations from these uncertainty distributions. DTN:SN0310T0502103.009 also contains the output file from the GoldSim V7.50.100 software code, which includes the parameter vectors to be used in the SZ transport abstraction model. Results of the SZ transport abstraction model from this report are given in DTN: SN0310T0502103.010. These results consist of the input and output files from the FEHM V2.20 software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code (STN: 10914-2.0-00), and the SZ_Post V3.0 software code (STN: 10915-3.0-00) used in the analyses. The results that form a direct input to the TSPA-LA model are the files that contain the breakthrough curves (from the SZ transport abstraction model) from the 200 realizations of radionuclide transport. The breakthrough curves used in the TSPA-LA model (i.e., the breakthrough curves at the regulatory boundary of the accessible environment) are defined in the output files in the first column (“time”) and the third column (“relative mass”). The input and output files for the SZ 1-D transport model are given in DTN: SN0306T0502103.005. The input file of the SZ 1-D transport model for the GoldSim V7.50.100 software code is intended for incorporation into the TSPA-LA model. Output pertaining to parameter values for use in the SZ 1-D transport model is also found in Section 6.5.1.2 of this report. Estimates of groundwater specific discharge for the three pipe segments (in the SZ 1-D transport model) taken from the SZ transport abstraction model are given in Table 6-6, as a function of horizontal anisotropy in permeability. Estimates of the minimum and maximum pipe lengths for the second and third pipe segments in the SZ 1-D transport model are given in Table 6-7 as a function of source region and horizontal anisotropy in permeability. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-4 October 2004 The data spreadsheets in DTN: SN0306T0502103.006 have the data used in the analyses of parameter uncertainty summarized in this report and in DTN: SN0310T0502103.009. The spreadsheets mentioned by filename in this report are included in DTN: SN0306T0502103.006. Results of the SZ transport abstraction model that used re-sampling of the input parameters from Appendix B of this report are given in DTN: SN0407T0502103.013. These results were generated primarily to address CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009) with respect to evaluation of the impact of the sampling difference in the GoldSim V7.50.100 software code. These radionuclide transport simulation results are also appropriate for use as input to the TSPA-LA for purposes of evaluating the impacts of the problem identified in CR 2222 at the total-system level, if necessary. These results consist of the input and output files from the following codes used in the analyses: the FEHM V2.20 software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code (STN: 10914-2.0-00), and the SZ_Post V3.0 software code (STN: 10915-3.0-00). The breakthrough curves accepted for use in the TSPA-LA model (i.e., the breakthrough curves at the regulatory boundary of the accessible environment) are defined in the output files, in the first column (“time”) and the third column (“relative mass”). This report’s results of the SZ transport abstraction model for the fast fraction of radionuclides irreversibly attached to colloids are given in DTN: SN0310T0502103.012. These results consist of the input and output files from the following codes used in the analyses: the FEHM V2.20 software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code (STN: 10914-2.0-00), and the SZ_Post V3.0 software code (STN: 10915-3.0-00). The results that form a direct input to the TSPA-LA model are the files that contain the breakthrough curves (from the SZ transport abstraction model) used for the 200 realizations of radionuclide transport. The breakthrough curves accepted for use in the TSPA-LA model (i.e., the breakthrough curves at the regulatory boundary of the accessible environment) are defined in the output files, in the first column (“time”) and the third column (“relative mass”). The results of the background gross alpha concentration analysis (as documented in Section 6.8) are given in DTN: MO0310SPANGRAC.000. 8.2.2 Output Uncertainties and Limitations The assessment of uncertainty in model parameters and model outputs is an integral part of the performed analyses in this report. Uncertainty in model parameters is quantitatively represented by the statistical distributions developed and given in DTN: SN0310T0502103.009. Uncertainty in radionuclide transport in the SZ transport abstraction model is embodied in the breakthrough curves for the 200 realizations given in DTN: SN0310T0502103.010. The SZ 1-D transport model is intended for direct incorporation into the TSPA-LA model, with which uncertainty will be assessed using Monte Carlo probabilistic analyses. All relevant uncertainties in data and model parameters, with respect to their affect upon groundwater flow and radionuclide transport, have been included in both the SZ transport abstraction model and the SZ 1-D transport model. Uncertainties have been propagated through the results of the SZ transport abstraction model (i.e., the radionuclide breakthrough curves for multiple realizations) documented in this report. These output uncertainties address the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-5 October 2004 requirements of acceptance criterion 3 of the YMRP (NRC 2003 [DIRS 163274]) for the propagation of data uncertainty through model abstraction for flow paths in the SZ and for radionuclide transport in the SZ. Use of the SZ transport abstraction model and the SZ 1-D transport model is subject to the limitations and restrictions imposed by the assumptions listed in Sections 5, 6.3, and 6.5 of this report. Limitations in knowledge of specific parameter values are addressed in this report in the analysis of parameter uncertainties. The radionuclide breakthrough curves generated for the SZ Transport Abstraction model are limited to 100,000 years duration for present climatic conditions; this limits the time period that can be simulated with the TSPA-LA model when using these breakthrough curves for the SZ. Because the SZ breakthrough curves are scaled for higher groundwater flow rates under future climatic conditions, the time period that can be simulated with the TSPA-LA model would be significantly less than 100,000 years. If the glacial-transition climate state is applied for most of the simulation period in the TSPA-LA model, the SZ breakthrough curves would be scaled by a factor of approximately four, thereby limiting the TSPA-LA model simulation time to about 25,000 years. 8.3 YUCCA MOUNTAIN REVIEW PLAN ACCEPTANCE CRITERIA The following information describes how this analysis addresses the acceptance criteria in the Yucca Mountain Review Plan (NRC 2003 [DIRS 163274], Sections 2.2.1.3.8.3 and 2.2.1.3.9.3). Only those acceptance criteria that are applicable to this report (see Section 4.2) are discussed. In most cases, the applicable acceptance criteria are not addressed solely by this report; rather, the acceptance criteria are fully addressed when this report is considered in conjunction with other analysis and model reports that describe flow and transport in the saturated zone. Where a subcriterion includes several components, only some of those components may be addressed. How these components are addressed is summarized below. Acceptance Criteria from Section 2.2.1.3.8.3 Flow Paths in the Saturated Zone Acceptance Criterion 1: System Description and Model Integration Are Adequate Subcriterion (1): Total system performance assessment adequately incorporates important design features, physical phenomena, and couplings, and uses consistent and appropriate assumptions, throughout the flow paths in the saturated zone abstraction process; Important physical phenomena and couplings are incorporated into the SZ flow and transport model abstraction through application of the best relevant, qualified data from the Yucca Mountain site and region (Sections 4.1.1 and 4.1.2). Consistent and appropriate assumptions noted in Sections 5 and 6.3 are used throughout this abstraction report and other abstractions, model reports, and analysis reports related to flow paths in the SZ. Integration of the SZ abstraction models for the TSPA-LA is described in Sections 6.3.3 and 6.5.3. Subcriterion (2): The description of the aspects of hydrology, geology, geochemistry, design features, physical phenomena, and couplings that affect flow paths in the saturated zone, is adequate. Conditions and assumptions in the Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-6 October 2004 abstraction of flow paths in the saturated zone are readily identified, and consistent with the body of data presented in the description; This abstraction provides fully adequate descriptions of the aspects of hydrology, geology, geochemistry, physical phenomena, and couplings that may affect flow paths in the saturated zone through reference to supporting analysis and model reports in Table 4-1, discussion of incorporated features, events, and processes in Table 6-1, and detailed discussions of base-case conceptual model and inputs in Sections 6.3 and 6.5.2. Additional and more detailed descriptions of these aspects of the system are provided in supporting documents, particularly Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]) and BSC 2004 [DIRS 170036]. Conditions and assumptions in the abstraction of flow paths in the saturated zone are readily identified in Sections 5 and 6.3, and they are consistent with the body of data presented in the descriptions (Sections 4.1, 6.2, 6.3, and 6.5). Subcriterion (3): The abstraction of flow paths in the saturated zone uses assumptions, technical bases, data, and models that are appropriate and consistent with other related U.S. Department of Energy abstractions. For example, the assumptions used for flow paths in the saturated zone are consistent with the total system performance assessment abstraction of representative volume (Section 2.2.1.3.12 of the Yucca Mountain Review Plan). The descriptions and technical bases provide transparent and traceable support for the abstraction of flow paths in the saturated zone; Assumptions, described in Section 5, are consistent with those used in other model and analysis reports. For example, two of the six assumptions are carried forward directly from the Saturated Zone Colloid Transport scientific analysis report (BSC 2004 [DIRS 170006], Section 6.3). Technical bases, data, models, and local modeling assumptions are described in Section 6.3. Transparent and traceable support for the abstraction of flow paths in the SZ is provided for the SZ transport abstraction and the SZ 1-D transport model. For example, estimates of the variation in groundwater specific discharge and flow-path lengths in the SZ 1-D transport model are explained and illustrated in Section 6.5.1.2. Subcriterion (4): Boundary and initial conditions used in the total system performance assessment abstraction of flow paths in the saturated zone are propagated throughout its abstraction approaches. For example, abstractions are based on initial and boundary conditions consistent with site-scale modeling and regional models of the Death Valley ground water flow system; Boundary conditions used in the TSPA-LA abstraction of flow paths in the SZ are taken from the SZ site-scale flow model, as described in Section 6.5. These boundary conditions are based on analyses that use the regional model of the Death Valley groundwater flow system, as described in Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]). The effects of these boundary conditions are implicitly propagated to the SZ 1-D transport model through estimates of flow rates and pipe-segment lengths, as described in Section 6.5.1.2. Initial conditions are not used in the abstraction of flow paths because steady-state conditions are assumed. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-7 October 2004 Subcriterion (5): Sufficient data and technical bases to assess the degree to which features, events, and processes have been included in this abstraction are provided; FEPs addressed in this model report are documented in Section 6.2. Table 6-1 summarizes those SZ FEPs for which the technical bases are provided in this report, and includes the location within this report of the information providing sufficient data and bases. Subcriterion (7): Long-term climate change, based on known patterns of climatic cycles during the Quaternary period, particularly the last 500,000 years, and other paleoclimate data, are adequately evaluated; The patterns of climatic cycles used for modeling were provided in the USGS Report Future Climate Analysis (USGS 2003 [DIRS 167961]), and were adequately evaluated for impacts on groundwater flow paths and flow rates in the SZ. The USGS analyzed known patterns of climatic cycles covering the last 500,000 years and correlated them with relevant paleoclimate data to produce the climate projections incorporated in this report. The application of climate information in modeling is described in Section 6.5. Subcriterion (9): The impact of the expected water table rise on potentiometric heads and flow directions, and consequently on repository performance, is adequately considered; The impact of expected water table rise has been adequately considered in Section 5 of this report by conservatively scaling transport rates in the SZ. Water table rise directly beneath the repository would place flow in hydrogeologic units with lower values of permeability (Section 5, item 6). This approximation of climate change with unaltered SZ flow paths is shown to underestimate radionuclide transport times in sensitivity studies documented in Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Attachment E). Subcriterion (10): Guidance in NUREG–1297 and NUREG–1298 (Altman, et al., 1988a, b), or other acceptable approaches for peer review and data qualification is followed. This report was developed in accordance with the Quality Assurance Requirements and Description (QARD) (DOE 2004 [DIRS 171539]), which commits to NUREGs 1297 and 1298. Moreover, compliance with the DOE procedures, which are designed to ensure compliance with the QARD, is verified by audits by QA and other oversight activities. Accordingly, the guidance in NUREGs 1297 and 1298 has been followed as appropriate. Acceptance Criterion 2: Data Are Sufficient for Model Justification Subcriterion (1): Geological, hydrological, and geochemical values used in the license application to evaluate flow paths in the saturated zone are adequately justified. Adequate descriptions of how the data were used, interpreted, and appropriately synthesized into the parameters are provided; Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-8 October 2004 Section 6.5.2 of this report provides thorough explanations that adequately justify the use of geological, hydrological, and geochemical values in the evaluation of flow paths. Section 6.5.2 also adequately describes the interpretation of data and development of parameter values and distributions. Additional and more detailed descriptions of these aspects of the analysis are provided in supporting documents, particularly, Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]) and BSC 2004 [DIRS 170036]. Subcriterion (3): Data on the geology, hydrology, and geochemistry of the saturated zone used in the total system performance assessment abstraction are based on appropriate techniques. These techniques may include laboratory experiments, site-specific field measurements, natural analog research, and process-level modeling studies. As appropriate, sensitivity or uncertainty analyses used to support the U.S. Department of Energy total system performance assessment abstraction are adequate to determine the possible need for additional data; Section 6.5.2 of this report describes the sources of data that were used in the development of modeling parameters in the TSPA-LA abstraction, the techniques used to evaluate these data, and the sufficiency of the data; the section also shows these techniques were appropriate. Table 6-8 includes the sources of input data, and associated uncertainty types. Acceptance Criterion 3: Data Uncertainty Is Characterized and Propagated Through the Model Abstraction Subcriterion (1): Models use parameter values, assumed ranges, probability distributions, and bounding assumptions that are technically defensible, reasonably account for uncertainties and variabilities, and do not result in an under-representation of the risk estimate; The development of parameter values, bounding values, and probability distributions is described in Section 6.5.2. The development was conducted in a technically defensible manner that reasonably accounts for uncertainty and variability. Two bounding assumptions are also described in Section 5, and model-specific assumptions are discussed in Section 6.3. Table 6-8 shows probability distributions associated with the parameters, and Section 6.5.2 explains the sources of uncertainties in the parameters. The conservative simplifications and assumptions used for the abstraction models reasonably account for uncertainties and variabilities, and do not result in an under-representation of the risk estimate (Sections 5 and 6.3). Subcriterion (2): Uncertainty is appropriately incorporated in model abstractions of hydrologic effects of climate change, based on a reasonably complete search of paleoclimate data; The treatment of climate change and associated changes in infiltration are explained in Section 6.5 and Table 6-5. Applicable paleoclimate data was incorporated in the development of the climate phases adopted through the USGS Report Future Climate Analysis (USGS 2003 [167961]). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-9 October 2004 Subcriterion (3): Uncertainty is adequately represented in parameter development for conceptual models, process-level models, and alternative conceptual models considered in developing the abstraction of flow paths in the saturated zone. This may be done either through sensitivity analyses or use of conservative limits. For example, sensitivity analyses and/or similar analyses are sufficient to identify saturated zone flow parameters that are expected to significantly affect the abstraction model outcome; Section 6.5.2 includes detailed explanations of parameter representations and uncertainty sources of parameters that were used in the development of flow paths. Alternative conceptual models and associated sensitivity analyses used to address uncertainty are discussed in Section 6.4. Subcriterion (4): Where sufficient data do not exist, the definition of parameter values and conceptual models is based on appropriate use of expert elicitation, conducted in accordance with NUREG–1563 (Kotra, et al., 1996). If other approaches are used, the U.S. Department of Energy adequately justifies their uses. Expert elicitation was used in the determination of groundwater specific discharge in the SZ. The expert elicitation process was conducted in accordance with DOE procedures that conform to NUREG-1563, and use of these results in quantifying uncertainty in specific discharge is described, with references, in Section 6.5.2.1. Acceptance Criterion 4: Model Uncertainty Is Characterized and Propagated Through the Model Abstraction Subcriterion (1): Alternative modeling approaches of features, events, and processes are considered and are consistent with available data and current scientific understanding, and the results and limitations are appropriately considered in the abstraction; The process of minimal matrix diffusion and the feature of horizontal anisotropy in permeability are considered in alternative conceptual models, as described in Section 6.4 and Table 6-4. The models are shown to be consistent with available data and current scientific knowledge and are considered appropriately in the abstraction through the ranges of parameter uncertainties in the base-case model. Subcriterion (2): Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed. For example, uncertainty in data interpretations is considered by analyzing reasonable conceptual flow models that are supported by site data, or by demonstrating through sensitivity studies that the uncertainties have little impact on repository performance; Alternative conceptual models are discussed in Section 6.4. ACMs are also listed in Table 6-4, which includes key assumptions and bases for screening decisions. A sensitivity analysis was used to determine the impact of these alternatives on repository performance. Additional Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-10 October 2004 descriptions of ACMs of the SZ flow system are provided in the supporting document, Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]). Subcriterion (3): Consideration of conceptual model uncertainty is consistent with available site characterization data, laboratory experiments, field measurements, natural analog information and process-level modeling studies; and the treatment of conceptual model uncertainty does not result in an under-representation of the risk estimate. The parameters and parameter uncertainty related to groundwater flow from external sources used directly in the modeling documented in this report are shown in Table 4-3. Spatial variability in rock properties is encompassed within uncertainty distributions for key parameters (Tables 6-1 and 6-8). The uncertainty distributions incorporate uncertainties associated with Yucca Mountain field or laboratory data, knowledge of how the parameter will be used in the model, and theoretical considerations (Section 6.5.2). The probabilistic analysis of uncertainty in groundwater flow is implemented through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA simulations (Section 6.3). Variability in the results of multiple radionuclide breakthrough curves reflects the uncertainty in groundwater flow and radionuclide transport behavior in the SZ (Section 6.6). These results are intended for direct incorporation into the TSPA-LA model (Section 8.2.2), and as such, do not contribute to an under-representation of the risk estimate as determined in the TSPA-LA. Subcriterion (4): Appropriate alternative modeling approaches are consistent with available data and current scientific knowledge, and appropriately consider their results and limitations, using tests and analyses that are sensitive to the processes modeled. The process, bases, and results for alternative modeling approaches are discussed in Section 6.4. Results obtained by use of an ACM are also shown in Figure 6-3. Additional descriptions of ACMs of the SZ flow system are provided in the supporting document, Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]). An example is an alternative model based on different interpretations of pump test results in the fractured volcanic units. Acceptance Criterion 5: Model Abstraction Output Is Supported by Objective Comparisons Subcriterion (1): The models implemented in this total system performance assessment abstraction provide results consistent with output from detailed process-level models and/or empirical observations (laboratory and field testings and/or natural analogs); Results of TSPA-LA abstraction modeling are compared with results of detailed process-level models in Section 7. Graphical representations of these comparisons between the results of the SZ transport abstraction model and the SZ site-scale transport model, and between the results of the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 7-4, and 7-5. These figures show consistent results between the abstraction models and detailed process-level models. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-11 October 2004 Subcriterion (2): Outputs of flow paths in the saturated zone abstractions reasonably produce or bound the results of corresponding process-level models, empirical observations, or both; Model outputs, in the form of breakthrough curves, are presented in Section 6.6. In Section 7, results are compared with those of process models. The analysis abstracting the flow-path lengths from the SZ site-scale transport model, for use in the SZ 1-D transport model, is described in Section 6.5.1.2. Subcriterion (3): Well-documented procedures that have been accepted by the scientific community to construct and test the mathematical and numerical models are used to simulate flow paths in the saturated zone; and Section 7.2 documents the procedures that were followed in the testing and validation of the abstraction models developed in this model report. Approved QA procedures identified in the TWP (BSC 2004 [DIRS 171421], Section 4) have been used to conduct and document the activities described in this model report. Section 7.2 documents the procedures accepted by the scientific community that were followed in the testing and validation of the abstraction models developed in this model report. Subcriterion (4): Sensitivity analyses or bounding analyses are provided to support the abstraction of flow paths in the saturated zone, that cover ranges consistent with site data, field or laboratory experiments and tests, and natural analog research. Bounding analyses consistent with Yucca Mountain field and laboratory data were conducted to support the TSPA abstraction of flow paths in the saturated zone. These analyses considered uncertainties in the parameter that characterizes horizontal anisotropy. In addition, analyses were completed to bound the effects of uncertainty in the geometry of the alluvial uncertainty zone (Section 6.5.1.2) and the flow paths represented therein. Acceptance Criteria from Section 2.2.1.3.9, Radionuclide Transport in the Saturated Zone Acceptance Criterion 1: System Description and Model Integration Are Adequate Subcriterion (1): Total system performance assessment adequately incorporates important design features, physical phenomena, and couplings, and uses consistent and appropriate assumptions, throughout the radionuclide transport in the saturated zone abstraction process; Important physical phenomena and couplings are incorporated into the SZ flow and transport model abstraction through application of the best relevant, qualified data from the Yucca Mountain site and region (Sections 4.1.1 and 4.1.2). Consistent and appropriate assumptions noted in Sections 5 and 6.3 are used throughout this abstraction report and other abstractions, model reports, and analysis reports related to radionuclide transport in the SZ. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-12 October 2004 Subcriterion (2): The description of the aspects of hydrology, geology, geochemistry, design features, physical phenomena, and couplings that may affect radionuclide transport in the saturated zone, is adequate. For example, the description includes changes into transport properties in the saturated zone, from water-rock interaction. Conditions and assumptions in the abstraction of radionuclide transport in the saturated zone are readily identified, and consistent with the body of data presented in the description; The abstraction in Section 6.3 of this report adequately describes the physical phenomena for the base-case conceptual model because it includes the aspects of hydrology, geology, geochemistry, physical phenomena, and couplings that may affect radionuclide transport in the saturated zone through reference to supporting analysis and model reports in Table 4-1, discussion of incorporated features, events, and processes in Table 6-1, and detailed discussions of important model considerations and inputs in Sections 6.3 and 6.5.2. Additional and more detailed descriptions of these aspects of the system are provided in supporting documents, particularly, Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]) and BSC 2004 [DIRS 170036]. Conditions and assumptions in the abstraction of radionuclide transport in the saturated zone are readily identified in Sections 5, 6.3, and 6.5, and they are consistent with the body of data presented in the descriptions (Sections 4.1, 6.2, 6.3, and 6.5). Subcriterion (3): The abstraction of radionuclide transport in the saturated zone uses assumptions, technical bases, data, and models that are appropriate and consistent with other, related U.S. Department of Energy abstractions. For example, assumptions used for radionuclide transport in the saturated zone are consistent with the total system performance assessment abstractions of radionuclide release rates and solubility limits, and flow paths in the saturated zone (Sections 2.2.1.3.4 and 2.2.1.3.8 of the Yucca Mountain Review Plan, respectively). The descriptions and technical bases provide transparent and traceable support for the abstraction of radionuclide transport in the saturated zone; Assumptions, described in Section 5, are consistent with those used in other model and analysis reports. For example, two of the six assumptions are carried forward directly from the Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [DIRS 170006], Section 6.3). Section 6.3.3 addresses the issue of consistency with interfacing UZ and biosphere models. Technical bases, data, models, and local modeling assumptions are described in Section 6.3. Transparent and traceable support for the abstraction of radionuclide transport in the SZ is provided for the SZ transport abstraction and the SZ 1-D transport model. For example, estimates of the variation in groundwater-specific discharge and flow-path lengths in the SZ 1-D transport model are explained and illustrated in Section 6.5.1.2. Subcriterion (4): Boundary and initial conditions used in the abstraction of radionuclide transport in the saturated zone are propagated throughout its abstraction approaches. For example, the conditions and assumptions used to generate transport parameter values are consistent with other geological, hydrological, and geochemical conditions in the total system performance assessment abstraction of the saturated zone; Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-13 October 2004 Section 6.5 discusses boundary and initial conditions used in transport modeling. The groundwater flow boundary conditions for the SZ site-scale flow model, the SZ site-scale transport model, and the SZ transport abstraction model are specified head at the lateral boundaries and specified groundwater flux for recharge at the upper boundary. These boundary conditions are described in detail in Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037], Section 6.3.2). Subcriterion (5): Sufficient data and technical bases for the inclusion of features, events, and processes related to radionuclide transport in the saturated zone in the total system performance assessment abstraction are provided; and FEPs addressed in this model report are documented in Section 6.2. Table 6-1 summarizes those SZ FEPs for which the technical bases are provided in this report, and includes the location within this report of the technical information. Subcriterion (6): Guidance in NUREG–1297 and NUREG–1298 (Altman, et al., 1988a, b), or other acceptable approaches for peer review and data qualification is followed. This report was developed in accordance with the QARD (DOE 2004 [DIRS 171539]), which commits to NUREGs 1297 and 1298. Moreover, compliance with the DOE procedures, which are designed to ensure compliance with the QARD, is verified by audits by QA and other oversight activities. Accordingly, the guidance in NUREGs 1297 and 1298 has been followed as appropriate. Acceptance Criterion 2: Data Are Sufficient for Model Justification Subcriterion (1): Geological, hydrological, and geochemical values used in the license application are adequately justified (e.g., flow path lengths, sorption coefficients, retardation factors, colloid concentrations, etc.). Adequate descriptions of how the data were used, interpreted, and appropriately synthesized into the parameters are provided; Section 6.5.2 of this report provides adequate and thorough explanations of the use of geological, hydrological, and geochemical values in evaluating flow, sorption, and colloid retardation. Section 6.5.2 also documents the interpretation of data, and the development of parameter values and uncertainty distributions. Subcriterion (2): Sufficient data have been collected on the characteristics of the natural system to establish initial and boundary conditions for the total system performance assessment abstraction of radionuclide transport in the saturated zone; The boundary conditions and interfaces between radionuclide transport in the SZ and the UZ and the biosphere are described in Section 6.3.3. An analysis of background gross alpha concentrations in groundwater, which represent the initial conditions of the system with regard to groundwater protection standards, is presented in Section 6.8. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-14 October 2004 Acceptance Criterion 3: Data Uncertainty Is Characterized and Propagated Through the Model Abstraction Subcriterion (1): Models use parameter values, assumed ranges, probability distributions, and bounding assumptions that are technically defensible, reasonably account for uncertainties and variabilities, and do not result in an under-representation of the risk estimate; The development of parameter values, bounding values, and probability distributions is described in Section 6.5.2. The development was conducted in a technically defensible manner that reasonably accounts for uncertainty and variability. Two bounding assumptions are also described in Section 5. Table 6-8 shows probability distributions associated with the parameters, and Section 6.5.2 explains the sources of uncertainties in the parameters. The probabilistic analysis of uncertainty is implemented through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA simulations (Section 6.3). Subcriterion (4): Parameter values for processes, such as matrix diffusion, dispersion, and ground water mixing, are based on reasonable assumptions about climate, aquifer properties, and ground water volumetric fluxes (Section 2.2.1.3.8 of the Yucca Mountain Review Plan); The conceptual model descriptions of processes such as advection, dispersion, and matrix diffusion are found in Section 6.3. Section 6.5.2 includes detailed explanations of the development of parameters used in these SZ flow processes, including discussions on the assumptions (e.g., climate changes, aquifer properties, and colloid transport properties) and bases upon which the parameter values are developed. Subcriterion (5): Uncertainty is adequately represented in parameter development for conceptual models, process-level models, and alternative conceptual models considered in developing the abstraction of radionuclide transport in the saturated zone. This may be done either through sensitivity analyses or use of conservative limits; Uncertainty in parameter values is adequately represented in Sections 6.3 and 6.4 of this report, in the context of conceptual models and alternative conceptual models. Parameter uncertainty at the process and abstraction level is discussed in detail in Sections 6.5.1 and 6.5.2. A probabilistic analysis of uncertainty in key model parameters is implemented through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA simulations. Subcriterion (6): Where sufficient data do not exist, the definition of parameter values and conceptual models is based on appropriate use of other sources, such as expert elicitation conducted in accordance with NUREG–1563 (Kotra, et al., 1996). If other approaches are used, the U.S. Department of Energy adequately justifies their use. Expert elicitation was used in the determination of dispersivity in the SZ. The expert elicitation process was conducted in accordance with DOE procedures that conform to NUREG-1563, and Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-15 October 2004 use of these results in quantifying uncertainty in dispersivity is described, with references, in Section 6.5.2.9. Acceptance Criterion 4: Model Uncertainty Is Characterized and Propagated Through the Model Abstraction Subcriterion (1): Alternative modeling approaches of features, events, and processes are considered, and are consistent with available data and current scientific understanding, and the results and limitations are appropriately considered in the abstraction; The process of minimal matrix diffusion and the feature of horizontal anisotropy in permeability are considered in alternative conceptual models, as described in Section 6.4 and Table 6-4. The models are shown to be consistent with available Data and current scientific knowledge and are considered appropriately in the abstraction through the ranges of parameter uncertainties in the base-case model. Subcriterion (2): Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed; Conceptual model uncertainties are adequately defined and documented in Sections 6.3 and 6.5 of this report. The effects of the uncertainties on conclusions regarding performance of the conceptual model are discussed and shown in curves presented in Section 6.6 figures. Subcriterion (3): Consideration of conceptual model uncertainty is consistent with available site characterization data, laboratory experiments, field measurements, natural analog information and process-level modeling studies; and the treatment of conceptual model uncertainty does not result in an under-representation of the risk estimate; and The parameters and parameter uncertainty from external sources used directly in the modeling documented in this report are shown in Table 4-3. Spatial variability in rock properties is encompassed within uncertainty distributions for key parameters (Tables 6-1 and 6-8). The uncertainty distributions incorporate uncertainties associated with Yucca Mountain field or laboratory data, knowledge of how the parameter will be used in the model, and theoretical considerations (Section 6.5.2). The probabilistic analysis of uncertainty is implemented through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA simulations (Section 6.3). Variability in the results of multiple radionuclide breakthrough curves reflects the uncertainty in groundwater flow and radionuclide transport behavior in the SZ (Section 6.6). These results are intended for direct incorporation into the TSPA-LA model (Section 8.2.2), and as such, do not contribute to an under-representation of the risk estimate as determined in the TSPA-LA. Subcriterion (4): Appropriate alternative modeling approaches are consistent with available data and current scientific knowledge, and appropriately consider their results and limitations, using tests and analyses that are sensitive to the processes modeled. For example, for radionuclide transport through fractures, the U.S. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-16 October 2004 Department of Energy adequately considers alternative modeling approaches to develop its understanding of fracture distributions and ranges of fracture flow and transport properties in the saturated zone. Alternative model approaches discussed in Section 6.4 are consistent with alternative interpretations of available data. Alternative conceptual models are also listed in Table 6-4, which includes key assumptions and bases for screening decisions. Alternative modeling approaches of fracture distributions and ranges of fracture flow and transport properties in the SZ are incorporated in upstream model reports. The conclusion of sensitivity analyses with regard to matrix diffusion in fractured media is that the alternative model of essentially no matrix diffusion is incorporated in the range of parameter uncertainties in the SZ transport abstraction model, as described in Section 6.4. Acceptance Criterion 5: Model Abstraction Output Is Supported by Objective Comparisons Subcriterion (1): The models implemented in this total system performance assessment abstraction provide results consistent with output from detailed process-level models and/or empirical observations (laboratory and field testings and/or natural analogs); Results of TSPA-LA abstraction modeling are compared with results of detailed process-level models in Section 7. Graphical representations of these comparisons between the results of the SZ transport abstraction model and the SZ site-scale transport model, and between the results of the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 7-4, and 7-5. These figures show consistent results between the abstraction models and detailed process-level models. Subcriterion (2): Outputs of radionuclide transport in the saturated zone abstractions reasonably produce or bound the results of corresponding process-level models, empirical observations, or both. The U.S. Department of Energy-abstracted models for radionuclide transport in the saturated zone are based on the same hydrological, geological, and geochemical assumptions and approximations shown to be appropriate for closely analogous natural systems or laboratory experimental systems; Results of TSPA abstraction modeling are compared with results of detailed process-level models in Section 7. Graphical representations of these comparisons between the results of the SZ transport abstraction model and the SZ site-scale transport model, and between the results of the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 7-4, and 7-5. These figures show consistent results between the abstraction models and detailed process-level models. Subcriterion (3): Well-documented procedures that have been accepted by the scientific community to construct and test the mathematical and numerical models are used to simulate radionuclide transport through the saturated zone; and Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-17 October 2004 Section 7.2 documents the procedures accepted by the scientific community that were followed in the testing and validation of the abstraction models developed in this model report. Approved QA procedures identified in the TWP (BSC 2004 [DIRS 171421], Section 4) have been used to conduct and document the activities described in this model report. Section 7.2 documents the procedures that were followed in the testing and validation of the abstraction models developed in this report. Subcriterion (4): Sensitivity analyses or bounding analyses are provided to support the total system performance assessment abstraction of radionuclide transport in the saturated zone, that cover ranges consistent with site data, field or laboratory experiments and tests, and natural analog research). Sensitivity analyses consistent with Yucca Mountain field and laboratory data were conducted to support the TSPA abstraction of radionuclide transport in the saturated zone. In particular, a sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in the assessment of alternative conceptual models in Section 6.4. This analysis used the SZ transport abstraction model to show that the minimal matrix diffusion alternate model is included within the range of parameter uncertainties considered. Sensitivity analyses have also been performed on previous SZ transport modeling results (Arnold et al. 2003 [DIRS 163857]) (Section 6.7). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 8-18 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-1 October 2004 9. INPUTS AND REFERENCES The following is a list of the references cited in this document. Column 2 represents the unique six digit numerical identifier (the Document Input Reference System number), which is placed in the text following the reference callout (e.g., BSC 2004 [DIRS 170014]). The purpose of these numbers is to assist in locating a specific reference. Within the reference list, multiple sources by the same author (e.g., BSC 2004) are sorted alphabetically by title. 9.1 DOCUMENTS CITED Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Qualification of Existing Data for High-Level Nuclear Waste Repositories: Generic Technical Position. NUREG-1298. Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 200652. 103750 Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Peer Review for High-Level Nuclear Waste Repositories: Generic Technical Position. NUREG-1297. Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 200651. 103597 Arnold, B.W.; Kuzio, S.P.; and Robinson, B.A. 2003. “Radionuclide Transport Simulation and Uncertainty Analyses with the Saturated-Zone Site-Scale Model at Yucca Mountain, Nevada.” Journal of Contaminant Hydrology, 62-63, 401-419. New York, New York: Elsevier. TIC: 254205. 163857 Bear, J. 1972. Dynamics of Fluids in Porous Media. Environmental Science Series. Biswas, A.K., ed. New York, New York: Elsevier. TIC: 217356. 156269 Bedinger, M.S.; Sargent, K.A.; Langer, W.H.; Sherman, F.B.; Reed, J.E.; and Brady, B.T. 1989. Studies of Geology and Hydrology in the Basin and Range Province, Southwestern United States, for Isolation of High-Level Radioactive Waste—Basis of Characterization and Evaluation. U.S. Geological Survey Professional Paper 1370-A. Washington, D.C.: U.S. Government Printing Office. ACC: NNA.19910524.0125. 129676 Bower, K.M.; Gable, C.W.; and Zyvoloski, G.A. 2000. Effect of Grid Resolution on Control Volume Finite Element Groundwater Modeling of Realistic Geology. LA-UR-001870. Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 248256. 149161 BSC (Bechtel SAIC Company) 2001. Data Qualification Report: Calculated Porosity and Porosity-Derived Values for Lithostratigraphic Units for Use on the Yucca Mountain Project. TDR-NBS-GS-000020 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010531.0193. 163479 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-2 October 2004 BSC 2001. Data Qualification Report: Matrix Hydrologic Properties and Alcove 1 Infiltration Rate Data for Use on the Yucca Mountain Project. TDR-NBS-HS- 000014 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010924.0268. 163566 BSC 2002. Guidelines for Developing and Documenting Alternative Conceptual Models, Model Abstractions, and Parameter Uncertainty in the Total System Performance Assessment for the License Application. TDR-WIS-PA-000008 REV 00, ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20020904.0002. 158794 BSC 2002. Validation Test Report, GoldSim Version 7.50.100. SDN: 10344-VTR- 7.50.100-00. Las Vegas, Nevada: BSC (Bechtel SAIC Company). ACC: MOL.20030312.0227. 163962 BSC 2003. Saturated Zone Flow and Transport Model Abstraction. MDL-NBSHS- 000021 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040128.0001. 167651 BSC 2003. SZ Flow and Transport Model Abstraction. MDL-NBS-HS-000021 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030818.0007. 164870 BSC 2003. Technical Work Plan for: Saturated Zone Flow and Transport Modeling and Testing. TWP-NBS-MD-000002 REV 01 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20031203.0002. 166034 BSC 2003. Validation Test Report, SZ_Convolute Version 2.2. SDN: 10207-VTR- 2.2-00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20021202.0341. 163587 BSC 2004. Analysis of Hydrologic Properties Data. ANL-NBS-HS-000042, Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 170038 BSC 2004. D&E / PA/C IED Subsurface Facilities. 800-IED-WIS0-00101-000- 00A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: ENG.20040309.0026. 164519 BSC 2004. Features, Events, and Processes in SZ Flow and Transport. ANL-NBSMD- 000002, Rev. 03. Las Vegas, Nevada: Bechtel SAIC Company. 170013 BSC (Bechtel SAIC Company) 2004. Future Climate Analysis. ANL-NBS-GS- 000008 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040908.0005. 170002 BSC 2004. Hydrogeologic Framework Model for the Saturated Zone Site Scale Flow and Transport Model. MDL-NBS-HS-000024, Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 170008 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-3 October 2004 BSC 2004. Probability Distribution for Flowing Interval Spacing. ANL-NBS-MD- 000003, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 170014 BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: ENG.20040721.0007. 168361 BSC 2004. Recharge and Lateral Groundwater Flow Boundary Conditions for the Saturated Zone Site-Scale Flow and Transport Model. ANL-NBS-MD-000010 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20041008.0004. 170015 BSC 2004. Rock Properties Model. MDL-NBS-GS-000004, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 170032 BSC 2004. Saturated Zone Colloid Transport. ANL-NBS-HS-000031, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 170006 BSC 2004. Saturated Zone In-Situ Testing. ANL-NBS-HS-000039, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 170010 BSC 2004. Saturated Zone Site-Scale Flow Model. MDL-NBS-HS-000011, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 170037 BSC 2004. Site-Scale Saturated Zone Transport. MDL-NBS-HS-000010, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 170036 BSC 2004. Technical Work Plan for: Natural System - Saturated Zone Analysis and Model Report Integration. TWP-NBS-MD-000002 REV 02 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040818.0004. 171421 BSC 2004. Total System Performance Assessment (TSPA) Model/Analysis for the License Application. MDL-WIS-PA-000004, Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 168504 BSC 2004. UZ Flow Models and Submodels. MDL-NBS-HS-000006, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 169861 BSC 2004. Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary. MDL-EBS-PA-000004, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 170025 BSC 2004. Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model. ANL-NBS-HS-000034, Rev. 02. Las Vegas, Nevada: Bechtel SAIC Company. 170009 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-4 October 2004 Buchholtz ten Brink, M.; Phinney, D.L.; and Smith, D.K. 1991. “Actinide Transport in Topopah Spring Tuff: Pore Size, Particle Size and Diffusion.” Scientific Basis for Nuclear Waste Management XIV, Symposium held November 26-29, 1990, Boston, Massachusetts. Abrajano, T.A., Jr. and Johnson, L.H., eds. 212, 641-648. Pittsburgh, Pennsylvania: Materials Research Society. TIC: 203656. 162954 Buesch, D.C.; Spengler, R.W.; Moyer, T.C.; and Geslin, J.K. 1996. Proposed Stratigraphic Nomenclature and Macroscopic Identification of Lithostratigraphic Units of the Paintbrush Group Exposed at Yucca Mountain, Nevada. Open-File Report 94-469. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970205.0061. 100106 Burbey, T.J. and Wheatcraft, S.W. 1986. Tritium and Chlorine-36 Migration from a Nuclear Explosion Cavity. DOE/NV/10384-09. Reno, Nevada: University of Nevada, Desert Research Institute, Water Resources Center. TIC: 201927. 129679 Callahan, T.J.; Reimus, P.W.; Bowman, R.S.; and Haga, M.J. 2000. “Using Multiple Experimental Methods to Determine Fracture/Matrix Interactions and Dispersion of Nonreactive Solutes in Saturated Volcanic Tuff. “Water Resources Research, 36, (12), 3547-3558. Washington, D.C.: American Geophysical Union. TIC: 250760. 156648 Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. TERMGR- MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20031222.0006. 166275 Cooper, H.H., Jr. and Jacob, C.E. 1946. “A Generalized Graphical Method for Evaluating Formation Constants and Summarizing Well-Field History.” Transactions, American Geophysical Union, 27, (IV), 526-534. Washington, D.C.: American Geophysical Union. TIC: 225279. 150245 CRWMS (Civilian Radioactive Waste Management System) M&O (Management & Operating Contractor) 1997. Report of Results of Hydraulic and Tracer Tests at the C-Holes Complex. Deliverable SP23APM3. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19971024.0074. 100328 CRWMS M&O 1997. The Site-Scale Unsaturated Zone Transport Model of Yucca Mountain. Milestone SP25BM3, Rev. 1. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19980224.0314. 124052 CRWMS M&O 1997. Yucca Mountain Site Characterization Project Radiological Programs White Paper: Radioactivity in Groundwater in the Vicinity of Yucca Mountain. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19971215.0904. 147759 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-5 October 2004 CRWMS M&O 1998. “Saturated Zone Flow and Transport.” Chapter 8 of Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis Document. B00000000-01717-4301-00008 REV 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19981008.0008. 100365 CRWMS M&O 1998. Saturated Zone Flow and Transport Expert Elicitation Project. Deliverable SL5X4AM3. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19980825.0008. 100353 CRWMS M&O 1998. Yucca Mountain Site Characterization Project Radiological Programs, Radioactivity in FY 1997 Groundwater Samples from Wells and Springs Near Yucca Mountain. Rev. 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990218.0213. 104963 CRWMS M&O 1999. Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca Mountain. BA0000000-01717-5705-00029 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990622.0219. 150420 CRWMS M&O 2000. Modeling Sub Gridblock Scale Dispersion in Three- Dimensional Heterogeneous Fractured Media (S0015). ANL-NBS-HS-000022 REV 00 ICN 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20001107.0376. 152259 CRWMS M&O 2000. Total System Performance Assessment for the Site Recommendation. TDR-WIS-PA-000001 REV 00 ICN 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20001220.0045. 153246 CRWMS M&O 2000. Uncertainty Distribution for Stochastic Parameters. ANL-NBS-MD-000011 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000526.0328. 147972 CRWMS M&O 2000. Unsaturated Zone and Saturated Zone Transport Properties (U0100). ANL-NBS-HS-000019 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20000829.0006. 152773 D'Agnese, F.A.; O'Brien, G.M.; Faunt, C.C.; and San Juan, C.A. 1999. Simulated Effects of Climate Change on the Death Valley Regional Ground-Water Flow System, Nevada and California. Water-Resources Investigations Report 98-4041. Denver, Colorado: U.S. Geological Survey. TIC: 243555. 120425 DOE (U.S. Department of Energy) 1997. Regional Groundwater Flow and Tritium Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, Nevada. DOE/NV-477. Las Vegas, Nevada: U.S. Department of Energy. ACC: MOL.20010731.0303. 103021 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-6 October 2004 DOE 2003. Design Document for: SZ_CONVOLUTE Version 3.0. 10207-DD-3.0- 00. Las Vegas, Nevada: U.S. Department of Energy, Office of Repository Development. ACC: MOL.20030717.0479. 167588 DOE 2004. Quality Assurance Requirements and Description. DOE/RW-0333P, Rev. 16. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20040907.0002. Replacement for 171386 171539 Domenico, P.A. and Schwartz, F.W. 1990. Physical and Chemical Hydrogeology. New York, New York: John Wiley & Sons. TIC: 234782. 100569 EDCON. 2000. Report for the Borehole Gravity Survey in the NC-EWDP-19D Well in Nye County, Nevada on Behalf of TRW Corp. EDCON Job# 00011. Denver, Colorado: EDCON. TIC: 249823. 154704 Eddebbarh, A.A.; Zyvoloski, G.A.; Robinson, B.A.; Kwicklis, E.M.; Reimus, P.W.; Arnold, B.W.; Corbet, T.; Kuzio, S.P.; and Faunt, C. 2003. “The Saturated Zone at Yucca Mountain: An Overview of the Characterization and Assessment of the Saturated Zone as a Barrier to Potential Radionuclide Migration.” Journal of Contaminant Hydrology, 62-63, 477-493. New York, New York: Elsevier. TIC: 254205. 163577 Ferrill, D.A.; Winterle, J.; Wittmeyer, G.; Sims, D.; Colton, S.; Armstrong, A.; and Morris, A.P. 1999. “Stressed Rock Strains Groundwater at Yucca Mountain, Nevada.” GSA Today, 9, (5), 1-8. Boulder, Colorado: Geological Society of America. TIC: 246229. 118941 Flint, L.E. 1998. Characterization of Hydrogeologic Units Using Matrix Properties, Yucca Mountain, Nevada. Water-Resources Investigations Report 97-4243. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980429.0512. 100033 Freeze, R.A. and Cherry, J.A. 1979. Groundwater. Englewood Cliffs, New Jersey: Prentice-Hall. TIC: 217571. 101173 Gelhar, L.W. 1986. “Stochastic Subsurface Hydrology from Theory to Applications.” Water Resources Research, 22, (9), 135S-145S. Washington, D.C.: American Geophysical Union. TIC: 240749. 101131 Hillel, D. 1980. Fundamentals of Soil Physics. New York, New York: Academic Press. TIC: 215655. 101134 Howard, N.W. 1985. Variation in Properties of Nuclear Test Areas and Media at the Nevada Test Site. UCRL-53721. Livermore, California: Lawrence Livermore National Laboratory. TIC: 229690. 153266 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-7 October 2004 Jury, W.A.; Sposito, G.; and White, R.E. 1986. “A Transfer Function Model of Solute Transport Through Soil. 1. Fundamental Concepts.” Water Resources Research, 22, (2), 243-247. Washington, D.C.: American Geophysical Union. TIC: 254552. 164314 Knoll, G.F. 1989. Radiation Detection and Measurement. 2nd Edition. New York, New York: John Wiley & Sons. TIC: 233703. 161052 Kreft, A. and Zuber, A. 1978. “On the Physical Meaning of the Dispersion Equation and Its Solutions for Different Initial and Boundary Conditions.” Chemical Engineering Science, 33, (11), 1471-1480. New York, New York: Pergamon Press. TIC: 245365. 107306 Li, Y-H. and Gregory, S. 1974. “Diffusion of Ions in Sea Water and Deep-Sea Sediments.” Geochimica et Cosmochimica Acta, 38, (5), 703-714. New York, New York: Pergamon Press. TIC: 246823. 129827 Luckey, R.R.; Tucci, P.; Faunt, C.C.; Ervin, E.M.; Steinkampf, W.C.; D'Agnese, F.A.; and Patterson, G.L. 1996. Status of Understanding of the Saturated-Zone Ground-Water Flow System at Yucca Mountain, Nevada, as of 1995. Water- Resources Investigations Report 96-4077. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19970513.0209. 100465 Manger, G.E. 1963. Porosity and Bulk Density of Sedimentary Rocks. Geological Survey Bulletin 1144-E. Washington, D.C.: U.S. Government Printing Office. TIC: 249699. 154474 McKenna, S.A.; Walker, D.D.; and Arnold, B. 2003. “Modeling Dispersion in Three-Dimensional Heterogeneous Fractured Media at Yucca Mountain.” Journal of Contaminant Hydrology, 62-63, 577-594. New York, New York: Elsevier. TIC: 254205. 163578 Miller, I. and Kossik, R. 1998. Repository Integration Program RIP Integrated Probabilistic Simulator for Environmental Systems Theory Manual and User’s Guide. Redmond, Washington: Golder Associates. ACC: MOL.19980526.0374. 100449 Moyer, T.C. and Geslin, J.K. 1995. Lithostratigraphy of the Calico Hills Formation and Prow Pass Tuff (Crater Flat Group) at Yucca Mountain, Nevada. Open-File Report 94-460. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19941208.0003. 101269 Newman, J. 1973. Electrochemical Systems. Englewood Cliffs, New Jersey: Prentice-Hall. TIC: 210201. 148719 NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review Plan, Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory Commission, Office of Nuclear Material Safety and Safeguards. TIC: 254568. 163274 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-8 October 2004 Reimus, P.W.; Haga, M.J.; Adams, A.I.; Callahan, T.J.; Turin, H.J.; and Counce, D.A. 2003. “Testing and Parameterizing a Conceptual Solute Transport Model in Saturated Fractured Tuff Using Sorbing and Nonsorbing Tracers in Cross-Hole Tracer Tests.” Journal of Contaminant Hydrology, 62-63, 613-636. New York, New York: Elsevier. TIC: 254205. 162950 Reimus, P.W.; Haga, M.J.; Humphrey, A.R.; Counce, D.A.; Callahan, T.J.; and Ware, S.D. 2002. Diffusion Cell and Fracture Transport Experiments to Support Interpretations of the BULLION Forced-Gradient Experiment. LA-UR-02-6884. Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 253859. 162956 Reimus, P.W.; Ware, S.D.; Benedict, F.C.; Warren, R.G.; Humphrey, A.; Adams, A.; Wilson, B.; and Gonzales, D. 2002. Diffusive and Advective Transport of 3H, 14C, and 99Tc in Saturated, Fractured Volcanic Rocks from Pahute Mesa, Nevada. LA-13891-MS. Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 253905. 163008 Rundberg, R.S.; Partom, I.; Ott, M.A.; Mitchell, A.J.; and Birdsell, K. 1987. Diffusion of Nonsorbing Tracers in Yucca Mountain Tuff. Milestone R524. Los Alamos, New Mexico: Los Alamos National Laboratory. ACC: NNA.19930405.0074. 106481 Simpson, J.H and Carr, H.Y. 1958. “Diffusion and Nuclear Spin Relaxation in Water. “The Physical Review, Second Series, 111, (5), 1201-1202. New York, New York: American Physical Society. TIC: 246907. 139449 Skagius, K. and Neretnieks, I. 1986. “Porosities and Diffusivities of Some Nonsorbing Species in Crystalline Rocks. “Water Resources Research, 22, (3), 389-398. Washington, D.C.: American Geophysical Union. TIC: 225291. 156862 Sudicky, E.A. and Frind, E.O. 1982. “Contaminant Transport in Fractured Porous Media: Analytical Solutions for a System of Parallel Fractures. “Water Resources Research, 18, (6), 1634-1642. Washington, D.C.: American Geophysical Union. TIC: 217475. 105043 Townsend, Y.E. and Grossman, R.F., eds. 2001. Nevada Test Site Annual Site Environmental Report for Calendar Year 2000. DOE/NV/11718-605. Las Vegas, Nevada: U.S. Department of Energy, Nevada Operations Office. TIC: 251545. 156604 Triay, I.R.; Birdsell, K.H.; Mitchell, A.J.; and Ott, M.A. 1993. “Diffusion of Sorbing and Non-Sorbing Radionuclides. “High Level Radioactive Waste Management, Proceedings of the Fourth Annual International Conference, Las Vegas, Nevada, April 26-30, 1993. 2, 1527-1532. La Grange Park, Illinois: American Nuclear Society. TIC: 208542. 145123 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-9 October 2004 USGS (U.S. Geological Survey) 2003. Future Climate Analysis. ANL-NBS-GS- 000008 REV 00 ICN 01 Errata 001. Denver, Colorado: U.S. Geological Survey. ACC: MOL.20011107.0004; DOC.20031015.0003. 167961 USGS 2001. Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model. ANL-NBS-HS-000034 REV 01. Denver, Colorado: U.S. Geological Survey. ACC: MOL.20020209.0058. 157611 USGS n.d. Bulk Density. Denver, Colorado: U.S. Geological Survey. ACC: NNA.19940406.0076. 154495 Viswanath, D.S. and Natarajan, G. 1989. Data Book on the Viscosity of Liquids. 714-715. New York, New York: Hemisphere Publishing Corporation. TIC: 247513. 129867 Wilson, M.L.; Gauthier, J.H.; Barnard, R.W.; Barr, G.E.; Dockery, H.A.; Dunn, E.; Eaton, R.R.; Guerin, D.C.; Lu, N.; Martinez, M.J.; Nilson, R.; Rautman, C.A.; Robey, T.H.; Ross, B.; Ryder, E.E.; Schenker, A.R.; Shannon, S.A.; Skinner, L.H.; Halsey, W.G.; Gansemer, J.D.; Lewis, L.C.; Lamont, A.D.; Triay, I.R.; Meijer, A.; and Morris, D.E. 1994. Total-System Performance Assessment for Yucca Mountain – SNL Second Iteration (TSPA-1993). SAND93-2675. Executive Summary and two volumes. Albuquerque, New Mexico: Sandia National Laboratories. ACC: NNA.19940112.0123. 100191 Zyvoloski, G.; Kwicklis, E.; Eddebbarh, A.A.; Arnold, B.; Faunt, C.; and Robinson, B.A. 2003. “The Site-Scale Saturated Zone Flow Model for Yucca Mountain: Calibration of Different Conceptual Models and their Impact on Flow Paths.” Journal of Contaminant Hydrology, 62-63, 731-750. New York, New York: Elsevier. TIC: 254340. 163341 Zyvoloski, G.A.; Robinson, B.A.; Dash, Z.V.; and Trease, L.L. 1997. Summary of the Models and Methods for the FEHM Application—A Finite-Element Heat-and Mass-Transfer Code. LA-13307-MS. Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 235587. 110491 9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic Repository at Yucca Mountain, Nevada. 156605 AP-2.22Q, Rev. 1, ICN 1. Classification Analyses and Maintenance of the Q-List. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20040714.0002. AP-AC.1Q, Rev. 0, ICN 2. Expert Elicitation. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20020416.0050. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-10 October 2004 AP-SIII.10Q, Rev. 2, ICN 7. Models. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20040920.0002. LP-SI.11Q-BSC, Rev. 0, ICN 1. Software Management. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20041005.0008. 9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER GS010908312332.002. Borehole Data from Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model. Submittal date: 10/02/2001. 163555 GS030108314211.001. Interpretation of the Lithostratigraphy in Deep Boreholes NC-EWDP-18P, NC-EWDP-22SA, NC-EWDP-10SA, NC-EWDP-23P, NCEWDP- 19IM1A, and NC-EWDP-19IM2A, Nye County Early Warning Drilling Program, Phase III. Submittal date: 02/11/2003. 163483 GS031008312315.002. Transport Parameters from Analysis of Conservative (Non- Sorbing) Tracer Tests Conducted in the Fractured Tuff at the C-Hole Complex from 1996 to 1999. Submittal date: 10/09/2003. 166261 LA0002JC831341.001. Depth Intervals and Bulk Densities of Alluviums. Submittal date: 03/08/2000. 147081 LA0302RP831228.001. Type Curve Data for FEHM Macro “SPTR” Based on Sudicky and Frind Solution. Submittal date: 02/11/2003. 163557 LA0303HV831352.002. Colloid Retardation Factors for the Saturated Zone Fractured Volcanics. Submittal date: 03/31/2003. 163558 LA0303HV831352.004. Colloid Retardation Factors for the Saturated Zone Alluvium. Submittal date: 03/31/2003. 163559 LA0303PR831231.002. Estimation of Groundwater Drift Velocity from Tracer Responses in Single-Well Tracer Tests at Alluvium Testing Complex. Submittal date: 03/18/2003. 163561 LA0303PR831231.005. Simple Calculations for SZ In-Situ Testing AMR. Submittal date: 03/19/2003. 166259 LA0306SK831231.001. SZ Site-Scale Transport Model, FEHM Files for Base Case. Submittal date: 06/25/2003. 164362 LA0310AM831341.002. Saturated Zone Distribution Coefficients (Kds) for U, Np, Pu, Cs, Am, Pa, SR, Th, Ra, C, Tc, and I. Submittal date: 10/21/2003. 165891 LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed from Field Data. Submittal date: 05/14/2002. 159525 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-11 October 2004 LB03023DSSCP9I.001. 3-D Site Scale UZ Flow Field Simulations for 9 Infiltration Scenarios. Submittal date: 02/28/2003. 163044 MO0003SZFWTEEP.000. Data Resulting from the Saturated Zone Flow and Transport Expert Elicitation Project. Submittal date: 03/06/2000. 148744 MO0010CPORGLOG.002. Calculated Porosity from Geophysical Logs Data from “Old 40” Boreholes. Submittal date: 10/16/2000. 155229 MO0105GPLOG19D.000. Geophysical Log Data from Borehole NC EWDP 19D. Submittal date: 05/31/2001. 163480 MO0105HCONEPOR.000. Hydraulic Conductivity and Effective Porosity for the Basin and Range Province, Southwestern United States. Submittal date: 05/02/2001. 155044 MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. Submittal date: 09/17/2001. 155989 MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760 MO9904RWSJJS98.000. Radioanalytical Water Data for Samples Collected in June, July, and September 1998. Submittal date: 04/08/1999. 165866 SN0004T0501399.002. Correlation of RH (Relative Humidity) Porosity and Bulk Density. Submittal date: 04/13/2000. 155046 SN0004T0501399.003. Statistical Summary of Porosity Data. Submittal date: 04/13/2000. 155045 SN0302T0502203.001. Saturated Zone Anisotropy Distribution Near the C-Wells. Submittal date: 02/26/2003. 163563 SN0306T0504103.005. Revised Groundwater Colloid Mass Concentration Parameters for TSPA (Total System Performance Assessment). Submittal date: 06/30/2003. 164132 SN0306T0504103.006. Revised Sorption Partition Coefficients (Kd Values) for Selected Radionuclides Modeled in the TSPA (Total System Performance Assessment). Submittal date: 06/30/2003. 164131 SN9907T0571599.001. Probability Distribution of Flowing Interval Spacing. Submittal date: 07/15/1999. 122261 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 9-12 October 2004 9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER MO0310SPANGRAC.000. Natural Gross Alpha Concentration In Amargosa Valley Groundwater. Submittal date: 10/23/2003. SN0306T0502103.005. SZ (SZ) 1-D Transport Model. Submittal date: 06/05/2003. SN0306T0502103.006. Data Spreadsheets To Support Parameter Uncertainty Development. Submittal date: 06/05/2003. SN0310T0502103.009. Revised Sz Transport Abstraction Model Uncertain Inputs. Submittal date: 10/09/2003. SN0310T0502103.010. Revised Sz Flow And Transport Model Abstraction Inputs And Results. Submittal date: 10/09/2003. SN0310T0502103.012. SZ Flow And Transport Model Abstraction Inputs And Results For Fast Fraction Of Irreversible Colloids. Submittal date: 10/24/2003. SN0407T0502103.013. Re-Sampled Sz Flow And Transport Model Abstraction Inputs And Results. Submittal date: 7/13/2004. 9.5 SOFTWARE CODES BSC (Bechtel SAIC Company) 2003. Software Code: GoldSim. V7.50.100. PC. 10344-7.50.100-00. 161572 BSC 2004. Software Code: GoldSim. V8.01 Service Pack 4. PC, Windows 2000. 10344-8.01SP4-00. 169695 LANL (Los Alamos National Laboratory) 2001. Software Code: CORPSCON. V5.11.08. 10547-5.11.08-00. 155082 LANL 2003. Software Code: FEHM. V2.20. SUN, PC. 10086-2.20-00. 161725 SNL (Sandia National Laboratories) 2003. Software Code: SZ_Convolute. V2.2. PC, Windows 2000. 10207-2.2-00. 163344 SNL 2003. Software Code: SZ_Convolute. V3.0. PC, Windows 2000. 10207-3.0- 00. 164180 SNL 2003. Software Code: SZ_Post. V3.0. Sun, SunO.S. 5.7. 10915-3.0-00. 163571 SNL 2003. Software Code: SZ_Pre. V2.0. Sun, Solaris 7. 10914-2.0-00. 163281 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 October 2004 APPENDIX A STOCHASTIC PARAMETER VALUES Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 October 2004 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 A-1 October 2004 This appendix contains a table listing the stochastic parameter values sampled for the SZ transport abstraction model and the SZ 1-D transport model. These parameter vectors for 200 realizations were sampled using the uncertainty distributions described in Section 6.5.2. The base-case model results described in Section 6.6 correspond to the input parameter values tabulated in Table A-1. MDL-NBS-HS-000021 REV 02 A-2 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 1 0.70451 0.028309 0.15851 0.11373 1.3862 -3.7026 -10.092 1.7762 6.3364 268.07 259.27 2 0.61702 0.70184 0.11408 0.081329 0.84234 -3.0161 -10.116 1.2311 4.8505 258.99 113.51 3 0.35217 0.61633 0.083152 0.20585 1.0234 -3.3666 -10.146 1.09 4.2112 113.11 290.67 4 0.43734 0.35304 0.20587 0.19441 0.83422 -3.8921 -10.539 1.3057 7.6552 290.9 159.82 5 0.3726 0.4368 0.19441 0.16058 0.92304 -4.461 -10.042 1.5285 6.1118 160.14 199.68 6 0.38137 0.37493 0.16033 0.17169 1.4084 -2.3306 -10.426 1.1931 6.4302 200.28 240.98 7 0.96095 0.38323 0.17133 0.16309 0.81193 -2.6095 -10.325 1.556 5.7365 240.86 85.61 8 0.96721 0.96199 0.1631 0.16459 1.1285 -3.3333 -10.197 1.2925 7.73 86.233 122.88 9 0.063508 0.96547 0.16442 0.26596 1.3996 -3.1397 -10.612 1.1273 4.6382 122.69 82.931 10 0.39763 0.063782 0.26525 0.26907 1.2126 -3.2812 -10.518 1.2363 7.7179 83.165 99.983 11 0.12641 0.39708 0.26845 0.1011 0.63908 -3.2658 -10.619 1.2345 6.2902 100.11 249.1 12 0.83363 0.12855 0.10207 0.16643 1.5206 -1.199 -10.572 1.8288 7.5701 248.31 79.438 13 0.82638 0.83084 0.16658 0.12153 1.3272 -1.15 -10.174 1.2777 6.451 79.842 156.96 14 0.46725 0.82571 0.12117 0.22766 0.62506 -3.976 -10.626 1.22 4.9316 156.83 245.64 15 0.11482 0.46679 0.2272 0.22709 1.6764 -3.2319 -10.431 1.4189 6.8839 244.94 185.29 16 0.24233 0.11166 0.22688 0.17505 1.0682 -3.8285 -10.185 1.5742 7.3231 183.88 46.974 17 0.8055 0.24472 0.17513 0.11746 1.2021 -1.8383 -10.366 1.6247 7.8869 47.598 285.48 18 0.1329 0.80984 0.11813 0.14376 1.0712 -1.8602 -10.758 1.2913 5.1106 284.54 222.27 19 0.73058 0.13299 0.14387 0.22266 1.4018 -3.0689 -10.059 1.7072 5.8951 223.16 46.513 20 0.34072 0.73141 0.22261 0.12312 1.3451 -3.856 -10.26 1.7658 8.6697 45.328 329.38 21 0.048591 0.34315 0.12247 0.21023 1.0043 -3.5674 -10.801 1.5571 7.4175 327.85 136.96 22 0.74837 0.048613 0.21035 0.15875 1.4574 -1.9719 -9.921 1.6685 7.7301 137.24 181.17 23 0.93881 0.74785 0.15923 0.093691 1.2402 -3.8166 -10.485 1.5587 6.4626 180.92 138.35 24 0.55458 0.93563 0.09379 0.21283 1.1247 -2.2296 -10.372 1.0925 1.9633 139.62 247.14 25 0.79283 0.55378 0.21273 0.25453 1.668 -3.3458 -10.476 1.7332 6.3834 246.15 228.25 26 0.37734 0.79098 0.25543 0.18598 1.816 -4.0395 -10.185 5.906 7.6101 227.35 115.13 MDL-NBS-HS-000021 REV 02 A-3 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 27 0.67108 0.37594 0.18625 0.2203 0.94555 -2.1743 -10.24 1.5551 7.8466 116.36 264.39 28 0.65266 0.67222 0.22046 0.16351 1.6175 -1.3137 -10.538 0.83687 6.7485 264.74 194.12 29 0.62918 0.65188 0.1638 0.20193 1.5918 -2.8203 -10.13 1.6876 10.779 194.18 155.64 30 0.24883 0.62618 0.20225 0.199 1.3545 -2.032 -10.341 1.135 2.4415 156.36 325.19 31 0.71164 0.2459 0.19922 0.19577 0.76344 -3.2677 -10.437 1.3511 6.4552 325.42 362 32 0.36584 0.7122 0.1961 0.14524 2.4058 -2.4327 -9.9314 1.5141 6.5489 361.97 105.28 33 0.47113 0.36787 0.14464 0.20748 1.2638 -2.4921 -9.6565 1.5069 6.2446 103.82 313.97 34 0.58157 0.47388 0.20749 0.16199 1.8275 -2.5698 -10.565 1.0319 5.3839 313.5 308.63 35 0.17154 0.58391 0.16242 0.17587 1.381 -3.5586 -9.9702 1.1229 4.5499 307.59 232.62 36 0.27276 0.17077 0.17593 0.19016 1.7866 -2.2884 -9.9878 1.2241 6.5466 230.98 72.64 37 0.16841 0.2727 0.18985 0.13151 1.3153 -3.2946 -10.231 1.4754 5.7734 71.65 395.34 38 0.21269 0.16757 0.13141 0.14914 1.5424 -3.0598 -10.645 1.0729 4.3751 395.81 200.88 39 0.60151 0.21358 0.14881 0.13017 1.6877 -2.7243 -9.3455 1.1663 4.6523 201.21 362.94 40 0.15729 0.60256 0.13036 0.13857 1.4451 -3.7297 -10.322 1.2935 5.863 363.36 239.29 41 0.3647 0.15605 0.13923 0.19281 1.2456 -3.5069 -9.6366 1.402 7.3494 238.67 353.32 42 0.59284 0.36398 0.19225 0.12862 1.5022 -3.7412 -10.208 1.1224 6.6715 353.63 219.29 43 0.43429 0.59413 0.1289 0.16172 1.0933 -3.6399 -9.7391 1.7931 4.4304 218.86 293.52 44 0.074964 0.43453 0.1616 0.1909 1.3933 -2.6663 -10.274 1.2546 6.7603 293.54 329.87 45 0.69768 0.072714 0.19154 0.17113 1.7338 -3.7591 -10.037 1.0482 4.24 329.95 260.63 46 0.53002 0.69555 0.17083 0.10469 0.60159 -3.3102 -9.9122 5.9484 12.998 260.58 195.92 47 0.066897 0.53497 0.10634 0.20539 1.5563 -2.6836 -10.14 1.3471 6.3144 195.81 278.81 48 0.81253 0.067039 0.20548 0.18333 1.629 -3.1487 -10.338 1.7807 8.2368 279.26 147.09 49 0.307 0.81175 0.18364 0.10332 1.1917 -3.954 -10.079 1.1421 5.1387 146.39 242.3 50 0.42421 0.30885 0.10441 0.2239 1.6554 -2.3446 -10.461 5.8964 12.116 242.61 342.55 51 0.31471 0.42162 0.22428 0.15377 1.015 -2.8939 -10.193 1.7596 7.6537 342.37 42.645 52 0.59783 0.31468 0.15362 0.16942 1.0887 -3.9623 -9.8347 1.3367 6.3723 41.049 296.42 53 0.54881 0.59673 0.16958 0.15458 0.92816 -1.937 -10.881 1.826 5.3289 296.98 317.67 54 0.25186 0.54916 0.15499 0.19171 1.3722 -3.4313 -10.022 2.9922 10.605 316.68 177.7 55 0.64107 0.25325 0.19159 0.18521 0.58809 -3.1758 -9.9578 1.4494 6.9642 177.84 322.55 56 0.45988 0.64197 0.18541 0.14594 0.70644 -3.4213 -10.38 1.3908 5.5995 322.77 120.09 57 0.35868 0.45653 0.14567 0.19779 1.1816 -2.6824 -9.9416 1.8202 8.3781 119.49 144.75 MDL-NBS-HS-000021 REV 02 A-4 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 58 0.80213 0.35725 0.19771 0.17377 1.8448 -2.8405 -10.526 1.4432 8.2585 144.07 102.59 59 0.89925 0.80492 0.17397 0.16094 1.8056 -3.5446 -10.465 1.7504 8.3775 102.46 238.09 60 0.22248 0.89986 0.16077 0.22181 0.8828 -2.5185 -10.569 2.0366 7.6319 238.24 40.481 61 0.77121 0.22433 0.22181 0.24279 1.776 -3.0919 -10.209 4.6391 8.5555 39.125 60.504 62 0.75746 0.77304 0.24181 0.14055 1.4833 -3.3141 -10.914 1.3779 5.6484 61.745 174.98 63 0.55579 0.75953 0.14106 0.21688 0.29449 -1.9893 -10.676 1.5845 6.0788 175.27 368.07 64 0.13508 0.5581 0.2173 0.2146 0.97023 -1.5186 -10.388 1.6112 7.9421 368.85 358.4 65 0.9875 0.13511 0.21415 0.18662 0.67711 -3.6141 -9.5831 1.4423 7.3588 358.6 93.383 66 0.47965 0.98618 0.18644 0.12437 1.0221 -2.0912 -9.6872 1.6498 6.3947 93.089 351.55 67 0.90123 0.47822 0.12407 0.28381 1.3397 -2.146 -10.594 1.4092 4.8544 350.82 273.61 68 0.57866 0.90303 0.28224 0.17637 1.1865 -2.81 -9.7422 1.5295 7.097 272.91 29.222 69 0.87669 0.57844 0.17686 0.24362 1.3222 -3.8028 -10.099 1.7656 8.2015 29.194 109.73 70 0.52246 0.87687 0.24338 0.18948 1.4151 -1.0566 -11.127 1.689 7.9085 110.4 55.672 71 0.71788 0.52221 0.18946 0.23674 1.8942 -3.0485 -10.55 1.5342 7.2882 54.464 122.53 72 0.81847 0.71882 0.23781 0.182 1.7624 -1.4862 -10.686 1.0478 4.0931 122.07 225.24 73 0.63474 0.81922 0.18229 0.20867 0.738 -2.7404 -10.522 1.3844 5.8392 225.84 177.4 74 0.46117 0.63266 0.20818 0.22519 1.7318 -1.6079 -10.25 1.1146 5.563 177.5 220.21 75 0.68208 0.46283 0.22459 0.19667 1.533 -2.9264 -10.382 1.4729 4.6409 220.36 251.38 76 0.33346 0.68422 0.19617 0.1746 1.7237 -2.2736 -10.267 3.8397 5.4484 250.42 379.89 77 0.58661 0.33143 0.17454 0.2033 2.5288 -1.9123 -10.169 1.108 5.8758 379.91 348.05 78 0.84781 0.58957 0.20353 0.15752 0.18779 -2.5558 -9.4799 3.6575 8.1698 347.72 65.785 79 0.055061 0.84838 0.15727 0.1908 1.4319 -3.0857 -9.7859 1.7059 8.3184 65.77 340.28 80 0.72545 0.059548 0.19074 0.23065 0.65772 -2.3987 -10.66 1.0474 6.9709 340.32 288.61 81 0.78233 0.72652 0.23023 0.09896 1.0081 -3.3729 -9.8592 4.7524 7.3093 288.29 337.65 82 0.41537 0.78383 0.10033 0.21009 1.5687 -2.7055 -10.051 1.3448 4.2383 338.42 396.46 83 0.79615 0.4153 0.21009 0.21848 0.1867 -1.7701 -9.868 1.116 4.5096 396.97 24.361 84 0.26279 0.79769 0.21877 0.169 1.8692 -3.9839 -9.3285 1.3663 6.2532 24.087 256.82 85 0.32585 0.26149 0.16913 0.22126 1.0848 -2.2475 -11.197 3.2666 8.0548 257.05 51.292 86 0.21935 0.32771 0.22133 0.14731 0.43697 -2.0638 -10.149 1.2834 6.8038 50.403 118.69 87 0.57287 0.21868 0.14692 0.15714 1.0417 -3.1822 -10.698 1.1281 5.642 117.57 303.07 88 0.05408 0.5743 0.15668 0.14015 0.69929 -2.0111 -10.532 1.5478 6.9799 302.88 23.539 MDL-NBS-HS-000021 REV 02 A-5 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 89 0.10576 0.054487 0.13962 0.18832 1.2717 -3.5333 -10.005 1.6866 5.067 22.372 375.01 90 0.40754 0.10529 0.18845 0.096424 1.6977 -3.3872 -11.258 2.6858 8.1054 374.3 142.05 91 0.91603 0.40782 0.098203 0.11647 0.90599 -3.6232 -9.5364 1.2958 7.3349 143.11 32.802 92 0.89135 0.91567 0.11686 0.16758 1.7454 -2.7577 -10.47 1.7117 6.3243 33.088 128.36 93 0.19019 0.89023 0.16751 0.24842 0.46766 -3.9928 -11.072 1.5973 5.532 129.99 59.201 94 0.87315 0.19372 0.24868 0.24104 1.2729 -3.8725 -10.503 1.4454 8.2211 58.595 204.12 95 0.66517 0.87134 0.24128 0.13522 1.7668 -3.2063 -10.678 1.3136 6.3196 203.25 333.28 96 0.024123 0.66764 0.13509 0.2357 0.79926 -1.415 -10.318 1.3962 5.1403 333.2 96.423 97 0.23899 0.022985 0.23591 0.20122 0.78641 -1.5294 -9.9071 1.6784 10.47 96.617 343.73 98 0.093079 0.23563 0.20126 0.079449 0.50753 -3.6823 -10.585 1.5156 6.2799 344.24 33.838 99 0.26953 0.090888 0.078007 0.14284 1.6105 -1.6374 -9.8223 2.0086 12.343 33.832 205.03 100 0.54079 0.26698 0.14297 0.1121 0.7266 -2.4384 -11.023 1.3193 4.8847 205.87 348.78 101 0.41165 0.54048 0.11173 0.14771 1.2905 -4.5523 -10.31 1.114 5.4429 349.62 77.497 102 0.52854 0.41152 0.14803 0.18493 1.053 -3.5782 -9.7593 5.3252 7.4087 77.534 76.842 103 0.60808 0.52661 0.18474 0.16809 1.8672 -3.9083 -10.633 1.6194 5.0404 76.359 36.081 104 0.94548 0.60856 0.1683 0.18302 1.8887 -3.5167 -10.633 1.0013 4.9632 36.121 311.98 105 0.86326 0.94988 0.18294 0.19313 1.9802 -2.8632 -10.973 1.2785 5.8423 312.49 63.968 106 0.12173 0.86184 0.19307 0.25889 2.2252 -3.196 -9.9776 1.5042 8.3694 64.993 210.78 107 0.84161 0.12403 0.259 0.23369 0.81543 -2.9144 -10.666 1.0022 4.0211 210.19 132.5 108 0.70681 0.84374 0.23391 0.12085 1.0518 -2.6365 -10.296 1.6652 8.0432 133.56 371.99 109 0.83677 0.70737 0.12071 0.22943 1.0756 -1.2562 -10.492 1.404 7.1784 372.31 378.64 110 0.99128 0.83905 0.22953 0.20708 1.0619 -1.6871 -9.5526 1.8088 6.2277 377.8 384.4 111 0.010519 0.99171 0.20724 0.2288 1.1152 -3.8399 -9.5112 1.5117 8.0958 383.78 389.32 112 0.62269 0.011542 0.22836 0.28924 1.5627 -1.7758 -9.4549 0.46893 2.0554 388.62 81.669 113 0.084204 0.62223 0.29036 0.067107 1.1593 -2.3046 -9.3949 1.3874 5.0674 81.049 131.2 114 0.25597 0.083179 0.063538 0.19537 1.7925 -1.8199 -10.623 1.0262 4.8538 131.47 141.54 115 0.74132 0.25944 0.19539 0.10837 1.8399 -1.0372 -10.499 1.4555 4.3711 140.73 134.5 116 0.007434 0.74115 0.10822 0.14618 1.3104 -4.793 -10.473 1.4463 4.6318 135.74 152.57 117 0.93236 0.008269 0.14655 0.21192 1.0318 -2.5914 -10.486 1.2589 4.8102 151.56 300.09 118 0.32035 0.93043 0.21235 0.049913 0.25923 -3.925 -10.447 1.6972 8.4928 299.64 166.3 119 0.030233 0.32271 0.054478 0.25292 1.8314 -3.5417 -10.015 1.3911 6.5942 167.99 355.78 MDL-NBS-HS-000021 REV 02 A-6 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 120 0.28508 0.034057 0.25215 0.15635 1.6384 -2.197 -10.408 1.0517 4.3142 355.96 366.8 121 0.10144 0.28681 0.15579 0.084439 1.4232 -4.8885 -9.7061 4.1216 8.6042 365.99 216.81 122 0.48434 0.10353 0.087276 0.15092 1.2272 -1.3375 -9.6162 1.7822 10.632 216.07 125.11 123 0.82334 0.4826 0.15078 0.11532 1.2217 -3.394 -10.28 1.1916 6.8495 126.33 25.85 124 0.20394 0.82124 0.1155 0.17726 1.8577 -4.3628 -10.513 0.55633 5.2954 25.77 364.38 125 0.8532 0.20325 0.1773 0.2256 0.64581 -3.4685 -11.163 0.60824 5.5611 364.43 319.08 126 0.037624 0.85435 0.22552 0.13752 2.2805 -3.8812 -9.6208 1.6654 8.6597 318.59 252.72 127 0.48593 0.038573 0.1374 0.23209 1.8027 -3.0395 -9.9522 1.1375 4.852 253.06 189.7 128 0.86876 0.48711 0.2322 0.090398 1.4724 -1.8783 -10.167 1.5864 7.4125 189.11 188.25 129 0.1544 0.86639 0.087853 0.17752 0.8727 -3.6625 -10.349 1.2554 6.6315 189 371.09 130 0.14816 0.15141 0.17766 0.23528 1.4626 -1.7361 -10.354 1.7691 6.1952 371.34 48.507 131 0.043598 0.14898 0.2347 0.12704 0.8525 -4.2851 -9.5649 0.57225 6.1647 49.552 391 132 0.76846 0.043645 0.12788 0.12639 1.9175 -3.0322 -10.707 1.5393 8.5753 392.36 358.05 133 0.11602 0.76916 0.12658 0.091042 0.77682 -1.663 -9.3758 1.5539 6.1291 357.09 270.33 134 0.50019 0.11576 0.091188 0.21608 1.5858 -3.7717 -9.697 1.4248 5.1128 268.94 91.21 135 0.29848 0.50385 0.21619 0.11938 0.66707 -3.782 -10.108 1.7533 7.8604 91.012 266.13 136 0.92706 0.29908 0.11876 0.1795 0.9665 -4.1659 -10.598 1.3229 6.3067 266.24 87.774 137 0.94102 0.92914 0.17972 0.15236 1.6015 -2.1023 -10.123 1.4054 4.568 87.49 381.85 138 0.95563 0.94338 0.1525 0.25203 1.0371 -3.8468 -10.607 1.3532 6.9416 382.11 73.304 139 0.97152 0.95988 0.25117 0.25751 1.4984 -2.9884 -9.4764 1.4846 7.5599 75.05 305.76 140 0.16243 0.97467 0.25758 0.26263 1.3352 -3.4489 -10.64 1.4352 6.1782 306.58 52.742 141 0.29141 0.16433 0.26227 0.27269 1.3693 -1.3574 -9.9925 1.0025 4.2885 52.555 108.71 142 0.31613 0.29468 0.27054 0.12983 0.90791 -1.2856 -10.691 1.304 5.0186 107.51 310.21 143 0.30444 0.31977 0.12929 0.1517 1.1741 -1.2235 -10.553 1.2773 6.5328 309.31 127.74 144 0.34719 0.30198 0.15141 0.15513 2.5485 -1.1431 -9.9839 1.6238 4.665 126.78 278.2 145 0.73918 0.34993 0.15548 0.15306 1.2035 -3.7544 -10.508 1.5304 6.9865 278.09 224.01 146 0.38633 0.73982 0.15327 0.15945 0.94859 -3.4626 -10.086 1.7279 6.2592 223.97 234.71 147 0.88281 0.38841 0.15936 0.21123 1.7483 -3.4067 -10.258 1.4001 7.0045 235.6 98.655 148 0.91034 0.88286 0.21103 0.16498 1.5123 -3.4429 -10.217 0.9905 2.7287 98.884 173.85 149 0.51841 0.91188 0.16505 0.2382 0.12866 -3.3353 -10.578 0.96945 3.0842 172.58 398.45 150 0.27749 0.51972 0.23803 0.24697 1.4763 -2.2129 -10.391 1.8137 7.36 399.04 182.7 MDL-NBS-HS-000021 REV 02 A-7 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 151 0.018691 0.27629 0.2464 0.18134 1.6242 -3.245 -9.3007 1.6874 6.8565 182.75 106.24 152 0.90977 0.017058 0.18162 0.14925 0.88989 -1.5786 -10.367 1.6278 7.3442 106.39 346.76 153 0.78691 0.90918 0.14972 0.071036 1.1644 -1.444 -10.56 1.7089 8.5463 345.34 282.36 154 0.61273 0.78833 0.073847 0.24478 1.5462 -2.9437 -9.806 1.532 4.5883 283.74 20.174 155 0.44835 0.61154 0.24491 0.21959 1.509 -3.4983 -10.066 1.644 6.1311 20.054 272.36 156 0.44417 0.44562 0.21926 0.19385 2.3672 -4.6266 -11.292 1.578 7.6511 270.96 316.33 157 0.92465 0.44049 0.19402 0.17247 1.2376 -1.4517 -10.102 1.5821 7.0916 315.47 94.793 158 0.076609 0.92395 0.17275 0.17226 1.297 -2.0342 -9.9661 1.036 4.1036 95.841 169.24 159 0.97647 0.077995 0.17184 0.25011 1.2888 -2.622 -10.589 1.8158 6.7876 169.73 294.38 160 0.88672 0.97946 0.24939 0.10731 1.3071 -3.1179 -10.4 1.4875 6.203 294.14 280.49 161 0.65647 0.88508 0.10708 0.27559 1.3647 -3.1224 -10.027 1.4853 7.3059 281.47 392.49 162 0.18665 0.65755 0.2747 0.2403 1.4503 -1.3913 -10.072 1.3696 4.7212 392.92 192.19 163 0.64606 0.18543 0.23956 0.19953 0.86176 -3.9385 -9.369 5.6796 11.544 192.4 212.7 164 0.17568 0.6463 0.19972 0.13401 1.2833 -1.1169 -10.347 1.0218 5.7699 212.65 209.44 165 0.95061 0.17555 0.13472 0.19829 1.1026 -1.5522 -10.29 3.2702 12.928 209.18 215.42 166 0.14335 0.95267 0.19855 0.13239 0.68419 -2.4821 -10.302 1.1476 4.9715 215.41 233.45 167 0.75389 0.14211 0.13248 0.26065 0.35455 -3.6937 -10.285 1.4987 6.0234 233.3 262.83 168 0.088815 0.75375 0.26063 0.12567 1.5235 -2.5044 -10.222 1.7817 7.7213 262.21 88.429 169 0.23232 0.08869 0.12491 0.21379 1.4276 -3.7156 -10.133 1.1922 5.8916 89.341 207.49 170 0.76434 0.23274 0.21353 0.11061 1.1196 -1.2367 -10.602 1.0342 6.3693 207.28 148.16 171 0.28202 0.7616 0.11071 0.14232 1.2168 -3.7935 -10.308 1.3828 7.5455 147.76 56.742 172 0.67838 0.28377 0.1421 0.21493 1.1411 -2.1576 -10.453 1.0248 4.8431 56.111 30.192 173 0.53511 0.67815 0.2155 0.15048 1.1566 -3.9196 -10.686 1.3506 7.8087 30.992 286.7 174 0.56885 0.53997 0.15046 0.20288 2.0937 -3.5938 -11.111 5.5651 10.593 286.98 254.82 175 0.20533 0.5681 0.20264 0.18426 2.1634 -2.1331 -10.054 5.0921 12.993 254.19 153.59 176 0.40471 0.20916 0.18434 0.18769 0.61684 -3.4847 -10.156 1.0081 2.0458 153.92 185.52 177 0.9995 0.40055 0.18774 0.13838 1.1696 -2.4075 -10.442 1.5078 6.559 186.74 162.09 178 0.42544 0.99674 0.13813 0.1669 0.74682 -2.8729 -10.359 1.76 6.093 160.92 166.26 179 0.22637 0.42607 0.16701 0.29202 1.7114 -2.7766 -10.421 1.8183 8.4675 165.99 386.06 180 0.85993 0.22959 0.29861 0.17001 1.7077 -3.649 -10.414 0.37838 4.25 385.73 387.44 181 0.69081 0.85616 0.17039 0.14118 1.2552 -3.218 -9.4402 1.5396 6.3219 388.13 42.922 MDL-NBS-HS-000021 REV 02 A-8 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 182 0.000316 0.69391 0.14143 0.23223 0.71843 -1.0082 -9.4219 1.6811 7.6176 44.051 170.83 183 0.66425 0.000898 0.23224 0.20456 0.98249 -3.165 -10.84 0.82101 1.8184 170.21 68.282 184 0.77963 0.6644 0.20481 0.02251 1.6687 -3.6051 -10.4 1.2373 4.7156 67.757 336.51 185 0.19856 0.77701 0.026558 0.20066 0.75819 -1.714 -10.656 1.4965 5.9137 336.43 333.76 186 0.39325 0.19937 0.2007 0.21764 1.5619 -2.3599 -9.8929 1.3319 6.6568 334.86 197.72 187 0.72376 0.39066 0.21781 0.13599 1.1067 -4.9164 -9.9021 4.4429 10.666 197.9 62.435 188 0.68892 0.7222 0.13594 0.16567 0.55484 -2.4516 -10.331 1.063 4.4061 61.878 112.56 189 0.98274 0.6877 0.1656 0.2091 1.5759 -2.0718 -10.67 4.0276 8.2587 112.62 326.39 190 0.45275 0.98273 0.20896 0.20396 1.8807 -3.6752 -10.546 1.699 8.1244 326.54 71.187 191 0.50526 0.45272 0.20412 0.28052 1.3502 -3.2414 -9.9247 1.3218 7.4539 70.071 298.21 192 0.49598 0.50781 0.27675 0.17357 1.6501 -2.2593 -10.652 1.4167 6.163 298.79 151.05 193 0.51183 0.49782 0.17314 0.18015 1.1476 -2.3726 -10.017 1.5236 4.1231 150.2 38.786 194 0.56134 0.51179 0.18047 0.17902 1.4929 -1.0761 -10.45 0.036671 6.0078 38.545 304.18 195 0.63937 0.56322 0.17911 0.18073 1.469 -3.1087 -10.948 1.5217 5.8151 303.54 376.34 196 0.18288 0.63794 0.18074 0.18708 1.4386 -2.9756 -9.9997 1.0782 4.5618 376.21 230.27 197 0.49279 0.18439 0.18748 0.19706 0.99788 -3.0038 -9.5125 1.2419 5.6844 229.91 321.71 198 0.33957 0.49261 0.19742 0.13392 1.5377 -2.9649 -10.239 1.2661 7.7128 321.32 162.65 199 0.097933 0.33587 0.13394 0.17855 1.1373 -2.7936 -9.9428 1.1672 5.5324 163.61 275.46 200 0.02951 0.098121 0.17837 0.15841 1.2559 -2.5445 -10.415 0.37655 1.9883 274.65 268.56 MDL-NBS-HS-000021 REV 02 A-9 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 1 6.3929 4.0476 0.8181 1791.7 1.0875 1.0042 0.39801 0.12912 0.82832 0.11435 0.46636 2 5.4235 4.3547 -0.85495 1889.7 3.5582 1.6714 0.12714 0.83286 0.46792 0.2438 0.11184 3 6.091 4.121 -0.1215 1820.9 3.5695 1.1986 0.83439 0.82826 0.11009 0.80568 0.24456 4 6.0964 4.1487 -0.44224 1984.5 0.90319 1.3675 0.82819 0.4672 0.24114 0.13093 0.80542 5 7.4704 6.9729 0.39432 1983.7 1.1434 1.5138 0.46584 0.11053 0.80879 0.73468 0.13052 6 7.5767 7.1394 0.3885 1904.1 0.90338 0.83369 0.11165 0.24447 0.13119 0.34017 0.73259 7 6.7357 2.9464 -0.03684 1815.2 2.9725 1.0459 0.24061 0.80742 0.73112 0.046301 0.34463 8 6.9733 4.2057 -0.46085 1855.7 2.9604 0.81838 0.80897 0.13118 0.34463 0.7483 0.04631 9 5.4813 3.1882 -0.30786 1978.3 1.4071 0.91882 0.13468 0.73388 0.04603 0.93663 0.74671 10 6.1144 5.8512 0.36448 1823.5 0.90334 1.5367 0.73421 0.34146 0.74618 0.55383 0.93928 11 8.0149 5.8404 -0.43612 1957.8 0.90373 0.79926 0.34235 0.045831 0.93877 0.79495 0.55274 12 7.3052 4.4718 0.27522 1878.4 2.8768 1.1894 0.049235 0.74967 0.55011 0.37712 0.79438 13 5.7365 3.13 -0.19072 1777.8 0.9034 1.5267 0.74852 0.93563 0.79164 0.67425 0.37882 14 6.3898 3.6295 -0.97733 1961.7 2.5538 1.3075 0.93625 0.55419 0.37553 0.65406 0.67351 15 8.0955 5.7631 0.29233 2028.3 0.94105 0.77849 0.55335 0.79368 0.67241 0.62614 0.65251 16 5.418 3.2064 0.66404 1920 0.90314 1.6522 0.79004 0.37616 0.65068 0.24578 0.62768 17 7.2363 5.4719 0.059967 1973.9 2.6065 1.4544 0.37912 0.67379 0.62866 0.7112 0.24627 18 6.297 3.9963 0.3514 1885.7 3.4344 0.77844 0.67485 0.65038 0.24892 0.3687 0.71087 19 6.1532 2.8633 -0.14488 1944.9 1.7505 1.8446 0.65415 0.62701 0.711 0.47078 0.36665 20 6.3443 5.5418 0.20717 1940.3 2.8112 1.0993 0.62895 0.24539 0.36569 0.58084 0.47477 21 7.247 6.249 0.18479 1935.4 1.0695 1.288 0.24752 0.71071 0.47397 0.17007 0.5826 22 6.6527 4.799 0.15118 1856.8 2.2828 1.1135 0.71398 0.36774 0.58472 0.27474 0.1718 23 7.1839 5.711 -0.30353 1953.7 2.2025 1.5333 0.36813 0.47456 0.17021 0.1663 0.27316 24 6.3895 4.1293 0.25181 1883.7 2.0793 1.4721 0.47446 0.58489 0.27248 0.21154 0.16614 25 6.9776 5.251 -0.15875 1904.5 0.90375 1.0179 0.58135 0.17051 0.16512 0.60233 0.21337 26 14.466 5.1801 -0.03341 1925.9 2.4697 1.5852 0.17104 0.27259 0.21288 0.15556 0.60328 27 5.7245 5.0737 0.099475 1836.3 1.04 1.3493 0.27161 0.1696 0.60274 0.36263 0.15521 28 5.4412 3.6421 -0.38882 1862.7 1.4328 1.1809 0.16813 0.2111 0.15655 0.59017 0.36338 MDL-NBS-HS-000021 REV 02 A-10 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 29 7.345 5.3989 -0.27169 1834.9 1.8884 1.7837 0.21312 0.60029 0.36028 0.43416 0.59491 30 6.6146 4.1024 -0.39819 1847.3 0.90353 2.3132 0.60039 0.15621 0.59053 0.070562 0.43237 31 6.4572 4.4969 -0.34483 1930.7 0.90382 0.94597 0.15578 0.36256 0.43289 0.69568 0.072704 32 6.7446 4.9141 0.11944 1831.2 0.90351 1.7452 0.36078 0.59297 0.074871 0.53396 0.69861 33 6.5102 3.3664 -0.41112 1882.9 0.90364 1.7258 0.59401 0.43237 0.69566 0.066305 0.53255 34 6.3393 3.7497 -0.16609 1928.7 1.9686 1.4833 0.43426 0.073074 0.53246 0.81035 0.069985 35 5.9997 3.344 0.10967 1896.5 0.90348 0.77891 0.073323 0.6975 0.067696 0.30531 0.81321 36 5.9559 3.508 -0.07847 1796.8 1.0186 2.8271 0.6963 0.53488 0.81113 0.42313 0.30702 37 7.7597 4.9963 -0.76296 1950.8 1.9415 1.3809 0.53406 0.06581 0.30994 0.3125 0.42397 38 5.4215 3.3073 0.23755 1916.7 1.2853 2.3632 0.065321 0.81078 0.4221 0.59713 0.31337 39 7.5782 4.0865 0.037959 1792.3 0.90322 1.5062 0.81429 0.30812 0.31475 0.54755 0.59695 40 6.8481 4.9427 -0.81314 1978.7 2.3987 2.2149 0.30883 0.42455 0.59518 0.25434 0.54791 41 6.4336 4.348 0.37313 1870.6 1.6641 1.4434 0.42078 0.31241 0.54998 0.64335 0.25415 42 5.9679 2.9858 -0.23107 1894.9 0.9032 1.6805 0.31042 0.59809 0.25497 0.45955 0.64074 43 7.6914 5.3518 -0.08994 1872.4 2.8904 1.8892 0.59966 0.549 0.64079 0.35531 0.45927 44 6.5365 4.7282 -0.2259 1929.2 0.90393 1.5782 0.54701 0.25493 0.45549 0.80303 0.35881 45 3.8988 2.9717 0.11488 1919 1.2471 1.3553 0.25287 0.64012 0.35869 0.89767 0.8011 46 7.76 5.7864 0.054703 1857.7 0.90394 1.634 0.64341 0.45504 0.80265 0.22022 0.89575 47 6.9593 3.8645 -0.29576 1938.4 1.9461 1.1435 0.45681 0.35554 0.89736 0.77279 0.22201 48 6.3023 4.2993 0.16765 1902 1.729 1.5204 0.35767 0.8033 0.22106 0.75653 0.7745 49 7.1005 3.8948 -0.05232 1881.8 0.90376 2.0395 0.80219 0.8976 0.77391 0.55844 0.75595 50 7.2944 4.9688 -0.17085 1976.9 2.1536 0.77839 0.89527 0.22021 0.75624 0.13669 0.55693 51 6.9967 4.7739 0.35802 2009.1 1.3766 1.6906 0.22262 0.77394 0.55501 0.98761 0.13778 52 6.1107 3.6678 0.4722 1850.2 1.0029 1.7566 0.77311 0.75559 0.136 0.47673 0.98982 53 5.5058 5.1336 -0.32842 1968.2 2.8598 1.2814 0.75897 0.55733 0.98911 0.90165 0.47795 54 8.0283 4.4488 0.3249 1965 3.2589 1.7758 0.55928 0.13643 0.47798 0.57992 0.9017 55 7.1634 4.0579 0.30516 1921.4 0.90367 1.0305 0.13924 0.9852 0.90361 0.87597 0.57623 56 7.7182 5.7363 0.069194 1824.4 2.7248 1.1388 0.98859 0.47716 0.57516 0.52119 0.8799 57 16.934 6.1005 -0.43183 2082 2.6468 0.93337 0.47781 0.9021 0.87838 0.71927 0.52202 58 6.3677 3.5446 0.92526 1905.5 1.7898 1.5033 0.90019 0.57664 0.52429 0.81645 0.71732 MDL-NBS-HS-000021 REV 02 A-11 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 59 8.0137 5.6306 -0.02427 2011 0.90342 0.77833 0.57734 0.87993 0.7155 0.63189 0.8157 60 7.5803 5.5676 0.47755 1925.5 3.6555 0.77871 0.87726 0.52225 0.81696 0.46085 0.63455 61 7.8045 4.8121 0.093825 2000.3 1.4533 1.2651 0.52405 0.71818 0.63403 0.6836 0.4645 62 6.8065 3.2399 0.44786 1914.8 3.2957 2.4448 0.71743 0.81913 0.46208 0.33488 0.68352 63 7.8024 8.2148 0.027231 1955.4 1.8794 2.2914 0.81684 0.63478 0.68113 0.58819 0.33071 64 6.3658 4.5135 0.26113 1979.9 3.1858 0.87284 0.63336 0.46033 0.33102 0.84547 0.58869 65 6.6401 6.1286 0.38063 1936 1.6237 2.1973 0.46483 0.68187 0.58955 0.056247 0.84656 66 8.0802 4.8948 0.15618 1902.7 2.4911 1.6189 0.68036 0.33279 0.84721 0.72827 0.058062 67 7.5176 6.0288 -0.04535 1947.4 2.9073 0.77816 0.33359 0.58683 0.055556 0.78499 0.72763 68 6.292 4.6899 0.21756 1876.5 2.1063 0.98331 0.5888 0.84941 0.72882 0.41564 0.78044 69 7.9056 5.4261 -0.19898 1927.3 1.3901 0.77861 0.84696 0.057968 0.78458 0.79874 0.41834 70 7.6321 5.7935 0.10325 1990.4 2.3218 1.0352 0.059202 0.72741 0.41612 0.26343 0.79713 71 7.3797 5.1016 0.41512 1786.2 0.91759 1.4684 0.72908 0.783 0.79694 0.32595 0.26112 72 6.5261 4.4622 -0.90291 1957.5 1.9062 1.2751 0.78309 0.41711 0.26183 0.21814 0.32885 73 7.6682 5.2846 0.2696 1971.2 3.0586 1.4506 0.41849 0.79753 0.3285 0.57109 0.21954 74 5.9958 3.9643 0.33449 1893.6 0.90317 1.5424 0.79539 0.26215 0.21556 0.051789 0.57407 75 6.3393 4.9391 -0.0988 1974.5 2.5336 2.6217 0.26288 0.32672 0.57298 0.10611 0.052027 76 7.6319 5.9195 0.3558 1860.1 2.769 2.1371 0.32568 0.21746 0.053163 0.40591 0.10719 77 5.7279 2.9262 -0.2854 1874.8 1.2181 0.7788 0.21624 0.57483 0.10741 0.91972 0.40777 78 7.3452 5.4588 -0.20391 1849.7 2.8383 2.0286 0.57311 0.052277 0.40829 0.8908 0.91655 79 7.8172 5.6723 -0.33597 1924.3 0.90379 1.6683 0.05449 0.10898 0.91926 0.19459 0.89262 80 7.2748 4.293 0.088795 1785.3 0.90398 1.9847 0.10825 0.4085 0.89123 0.87371 0.19373 81 13.835 5.7162 -0.95629 1813.8 0.90365 2.8559 0.40932 0.91507 0.19271 0.66865 0.87036 82 6.9084 3.6944 -0.46886 1891.7 1.847 0.77807 0.91592 0.89045 0.87402 0.022481 0.66851 83 6.2653 3.9482 -0.11054 2018.2 0.90316 1.5616 0.89293 0.19045 0.66901 0.23693 0.024774 84 5.4962 3.5414 0.57263 2006.8 0.90333 0.77854 0.19004 0.87062 0.023309 0.091047 0.2352 85 7.7176 4.87 0.47059 1842.7 1.1819 1.0206 0.87302 0.66938 0.2368 0.26906 0.091802 86 5.916 2.9113 -0.3659 1998.4 3.3469 1.7082 0.6656 0.024152 0.090667 0.54398 0.26823 87 5.885 3.1148 0.44164 1944.2 3.2399 0.77803 0.023333 0.23528 0.26661 0.41455 0.54303 88 6.5153 4.2502 0.19729 1751.8 0.90358 2.5253 0.23803 0.090919 0.54429 0.52672 0.41381 MDL-NBS-HS-000021 REV 02 A-12 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 89 18.883 6.1699 -1.2709 1853.8 3.1498 1.1287 0.093541 0.26709 0.4112 0.6066 0.52874 90 7.4636 6.0913 -0.31499 1806.3 2.2535 0.77822 0.26696 0.54419 0.52817 0.94606 0.60614 91 5.5562 3.4321 -0.57236 1861.2 0.90307 1.0671 0.54172 0.41108 0.60997 0.86265 0.94816 92 15.126 6.0081 -0.27432 1917.9 0.90372 0.77868 0.41491 0.52686 0.94891 0.12263 0.86301 93 7.5253 5.2247 0.050354 1892.7 0.90328 1.3907 0.52942 0.60533 0.86005 0.84008 0.12295 94 6.0635 2.2972 -0.10337 1915.2 0.9038 1.9143 0.60947 0.9471 0.12418 0.70779 0.84136 95 6.1259 3.6118 0.032758 1931.1 1.7069 0.90439 0.94625 0.86346 0.84482 0.83642 0.70974 96 6.019 3.0688 0.13087 2035.9 1.2067 2.0823 0.86403 0.12324 0.70673 0.9929 0.83838 97 6.7596 3.7298 0.73013 1995.7 1.6498 0.77824 0.12021 0.84037 0.83719 0.014448 0.9937 98 6.65 4.7642 0.43066 1819 1.9956 1.3968 0.84499 0.70858 0.99258 0.62177 0.010011 99 7.1823 4.2707 -0.45167 1988.1 3.4882 2.1656 0.70993 0.83907 0.011816 0.080484 0.62177 100 6.451 4.6949 0.40649 1952.6 3.1045 0.7812 0.83656 0.99291 0.62029 0.25668 0.084052 101 7.4039 4.9982 0.24501 1986.7 0.90337 0.77897 0.99369 0.011109 0.084139 0.74363 0.25783 102 7.4767 6.296 0.40263 2096.8 3.03 0.77829 0.012139 0.6206 0.25558 0.008536 0.74421 103 7.0457 5.9683 0.9646 1736.1 2.4303 1.7389 0.62312 0.083331 0.74082 0.93232 0.008844 104 5.7161 3.1765 -1.3741 1934.3 2.9977 0.77877 0.082851 0.25726 0.005755 0.32377 0.93333 105 5.9557 5.8845 0.14663 1800.5 3.6849 1.4182 0.25651 0.74433 0.93264 0.031595 0.32274 106 6.9747 5.3933 -0.65556 1859.7 0.90304 1.0833 0.74383 0.008921 0.32254 0.28928 0.032629 107 8.938 5.8838 -0.29014 1960.3 2.0719 2.503 0.007082 0.93162 0.032139 0.10235 0.28732 108 11.561 8.4623 0.28677 1711.5 0.90325 2.5914 0.9343 0.32226 0.28774 0.48315 0.10135 109 6.12 1.9755 -1.4049 2027.8 0.90377 2.6724 0.32398 0.033875 0.10227 0.82137 0.48128 110 6.9574 5.0698 0.65206 1874.1 2.5889 2.7358 0.034804 0.28617 0.48419 0.20142 0.82385 111 5.7228 3.0312 -0.2145 1765.8 0.90302 0.8074 0.28713 0.10452 0.82206 0.85408 0.20133 112 5.5625 3.6783 -1.1351 1866.8 3.4201 1.0809 0.10321 0.48255 0.20087 0.03713 0.85191 113 7.3147 5.5068 -0.25443 1811.7 0.90397 1.1169 0.48009 0.82013 0.85325 0.48798 0.038156 114 6.3164 1.9046 -0.47282 1906.2 0.9031 1.0955 0.82478 0.20143 0.036873 0.86745 0.48608 115 7.5921 6.2268 -0.02221 1981.5 0.90386 1.1662 0.20399 0.85208 0.48667 0.15011 0.86707 116 5.6012 3.9339 0.38733 1845.1 0.90331 1.7033 0.85464 0.036304 0.86896 0.14649 0.15383 117 1.2364 2.4753 -0.35313 1991.5 1.4715 1.2305 0.038431 0.48549 0.15269 0.041893 0.14705 118 6.6036 3.7894 0.42255 1773.4 2.934 2.2435 0.4888 0.86597 0.1496 0.76799 0.042585 MDL-NBS-HS-000021 REV 02 A-13 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 119 5.6675 3.1009 -1.0969 1907.4 0.90361 2.4104 0.86947 0.1505 0.041331 0.11687 0.76983 120 8.0168 4.5391 -0.01547 1997.7 3.0755 1.434 0.15471 0.14696 0.76917 0.50225 0.11804 121 7.805 5.8264 0.4368 1830.6 0.90311 1.0568 0.1482 0.041927 0.11919 0.29972 0.50172 122 7.3702 3.4667 -0.41438 1827.8 1.4778 0.77813 0.043749 0.76965 0.50249 0.92993 0.29938 123 6.7213 5.929 -0.41778 1776.7 3.1256 2.3797 0.76795 0.11768 0.29931 0.94398 0.92995 124 4.3306 2.6339 -1.0303 1966.5 0.90346 1.7621 0.11763 0.50186 0.92988 0.9591 0.94279 125 6.2064 4.5436 0.31744 1818.1 0.90345 1.5484 0.50125 0.29969 0.9417 0.9723 0.95904 126 7.6523 5.9877 -0.45746 1910.2 0.90312 1.3264 0.29829 0.92712 0.95959 0.16336 0.9735 127 5.563 3.2852 0.001514 1868.8 2.6949 1.3193 0.92626 0.94495 0.97011 0.29355 0.16075 128 6.1336 3.2702 -0.24028 2024.4 0.90336 2.4598 0.94317 0.95688 0.16089 0.31924 0.29198 129 6.3297 2.6876 0.63084 2032.1 1.5522 0.77853 0.95718 0.97024 0.29356 0.30068 0.31688 130 8.0247 5.6069 0.70954 2044.3 0.9039 2.7802 0.97338 0.16089 0.31924 0.34894 0.30226 131 5.8546 3.1558 0.77432 2060.7 3.4028 2.2586 0.16471 0.29112 0.30169 0.73742 0.34723 132 6.8369 4.6179 0.8669 1834 3.4585 1.6053 0.2919 0.31659 0.34685 0.38542 0.73879 133 7.0371 3.8323 -0.40523 1867.7 3.5324 0.86487 0.31639 0.30034 0.7382 0.8844 0.38707 134 8.0813 6.22 -0.24736 1873.1 3.5873 1.5948 0.30114 0.34737 0.38911 0.91417 0.88103 135 7.7775 6.2657 -0.21795 1869.7 0.9035 0.84208 0.34709 0.7389 0.8827 0.51527 0.91491 136 8.0432 6.5706 -0.23599 1879.7 0.90388 2.6439 0.73959 0.38723 0.91191 0.27739 0.51637 137 7.1933 7.4878 -0.18222 1959.9 0.90395 0.77896 0.3856 0.88123 0.51821 0.01555 0.27512 138 5.4294 3.3293 0.28472 1888.1 0.90392 1.721 0.8846 0.91276 0.27884 0.90859 0.015142 139 7.4959 3.8249 -0.13344 2003.3 0.96295 0.77857 0.91058 0.51807 0.019829 0.78559 0.9075 140 7.0592 3.9127 0.45875 2015.8 2.5618 0.96496 0.51863 0.27877 0.90669 0.61248 0.78753 141 5.8007 3.847 0.55231 1913.2 1.1215 1.7325 0.27928 0.018004 0.78506 0.44553 0.6123 142 6.8881 4.0184 0.022971 1864.3 3.212 1.0603 0.017035 0.90513 0.61484 0.44206 0.44827 143 7.4777 5.5041 -0.26788 1747.7 3.339 1.6273 0.90617 0.7874 0.44935 0.92037 0.44137 144 7.7513 4.1826 -1.319 2012.9 1.6067 1.4599 0.78778 0.61244 0.44289 0.077399 0.92211 145 7.312 6.0396 0.51974 1971.7 0.90383 1.4942 0.61002 0.44738 0.92177 0.9795 0.075209 146 14.261 6.1585 0.34072 1931.8 0.90305 0.9128 0.44868 0.44026 0.078919 0.88632 0.9771 147 6.8555 4.6736 0.13291 1900.1 3.3213 1.2546 0.44447 0.92422 0.97874 0.65608 0.88741 148 6.0243 3.7619 -0.06401 1898.7 2.7905 2.8905 0.92373 0.077673 0.88803 0.18793 0.65881 MDL-NBS-HS-000021 REV 02 A-14 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 149 5.5135 2.0896 -0.07036 2019.6 2.0286 1.2974 0.076063 0.97623 0.65712 0.646 0.1872 150 10.004 6.1315 0.60144 1800.4 1.3319 0.95621 0.977 0.88897 0.18621 0.17963 0.6468 151 7.2786 5.6864 -0.70644 2065.3 1.3096 2.1114 0.88659 0.65894 0.64638 0.9533 0.17576 152 7.0625 5.0306 0.88838 2004.3 3.3771 1.6455 0.65842 0.18734 0.17977 0.14185 0.9527 153 7.3807 4.394 0.46244 1941.7 0.90323 0.77801 0.18664 0.64891 0.95287 0.75049 0.14379 154 5.5048 4.3793 0.1871 1840.8 3.6119 1.6096 0.64507 0.17691 0.14233 0.086316 0.75248 155 7.5409 6.1992 -0.37093 1939.2 3.2128 1.7536 0.17711 0.95118 0.75482 0.23203 0.087912 156 6.3404 2.9992 0.17419 1838.4 2.2216 0.88998 0.95059 0.14242 0.086579 0.7641 0.23087 157 6.1266 7.8565 -0.38192 2039.2 0.90356 1.2436 0.14252 0.75409 0.23232 0.28118 0.76162 158 6.9607 6.0621 0.75051 1826.1 2.1818 1.6866 0.75153 0.088803 0.76344 0.67984 0.28492 159 8.1312 5.1999 -0.42699 1963.6 0.90353 1.6433 0.08683 0.2337 0.28051 0.53945 0.67884 160 5.6327 3.4208 0.29815 1803.9 3.5015 2.797 0.23407 0.76141 0.67786 0.56739 0.53767 161 7.5186 5.1585 -0.61352 1852.5 0.90344 1.3361 0.76128 0.2824 0.53504 0.20679 0.5676 162 7.238 3.3742 -0.3168 1966.2 2.6324 1.4226 0.28348 0.67679 0.56754 0.4036 0.20555 163 8.0541 6.3283 0.31264 1864.5 0.90326 1.4115 0.6774 0.5359 0.20907 0.99995 0.40382 164 1.2445 3.2461 -0.26077 1945.8 0.9037 1.4326 0.53853 0.56976 0.40303 0.42927 0.99514 165 7.6782 5.5608 0.21202 1917.8 2.6793 1.4902 0.56716 0.20581 0.99747 0.22505 0.42972 166 4.29 3.0393 0.042953 1923.5 0.90386 1.5815 0.20914 0.40267 0.42578 0.85881 0.22675 167 7.0772 3.5934 0.082558 1846.9 2.304 0.85035 0.40148 0.99633 0.22882 0.69465 0.85692 168 8.1091 5.5989 -0.3463 1890.8 1.6854 1.4043 0.99946 0.429 0.85968 0.002816 0.69442 169 6.5584 3.7778 -0.11436 2150 1.8197 1.1554 0.42931 0.22809 0.69398 0.66467 0.004499 170 7.6312 5.2625 0.9848 1896.2 0.90363 0.77864 0.22617 0.85547 0.000323 0.77513 0.66304 171 6.7437 4.737 -0.08534 1851.6 1.1755 0.77818 0.85851 0.69354 0.66257 0.19757 0.77725 172 5.6544 4.8472 -0.32558 1992.9 3.6966 1.6616 0.69111 0.003257 0.77945 0.39292 0.19571 173 6.0848 3.487 0.42615 1949.6 1.2557 1.5596 0.003656 0.66345 0.19765 0.72304 0.3905 174 10.67 4.2364 0.23043 1675.6 0.90369 1.1742 0.66204 0.77506 0.39062 0.68608 0.72139 175 19.991 8.772 -1.4274 1942.6 3.1009 1.3104 0.77547 0.19838 0.72232 0.98368 0.68895 176 5.7069 4.3221 0.1918 1969.8 2.3748 1.2113 0.19977 0.39453 0.68752 0.45485 0.98231 177 5.8428 3.5686 0.32826 1844.1 0.903 1.2221 0.39164 0.72283 0.98031 0.50929 0.45473 178 14.033 5.9529 -0.36243 1888.8 2.2491 2.6986 0.72173 0.68745 0.45427 0.49792 0.50512 MDL-NBS-HS-000021 REV 02 A-15 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDE NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 179 6.969 5.3194 -0.1308 1955.7 2.7377 2.7263 0.68811 0.98268 0.5089 0.51067 0.49559 180 4.8706 1.7248 0.26453 1948.5 0.90359 0.77843 0.98291 0.45113 0.49716 0.56127 0.51465 181 7.2743 5.2177 0.22384 2076 1.14 1.249 0.45143 0.50761 0.51411 0.63635 0.56495 182 14.003 5.6477 0.90461 1900.3 2.4991 0.77886 0.50641 0.4978 0.56414 0.18298 0.63987 183 5.5135 3.4549 -0.05683 1911.2 2.3608 1.9716 0.49998 0.51184 0.63908 0.49347 0.18035 184 7.4711 4.1951 0.010673 1909.7 3.6328 1.9303 0.51124 0.56314 0.18468 0.33757 0.49318 185 6.7534 5.4358 -0.00257 1912.2 1.3576 1.3653 0.56096 0.63868 0.49378 0.095147 0.339 186 7.6828 5.3098 0.015309 1922.2 1.5741 0.77876 0.63832 0.18425 0.33664 0.02893 0.098947 187 8.1434 7.9127 0.072474 1937 1.5171 0.98742 0.18035 0.4943 0.0968 0.70491 0.029299 188 6.7702 4.4289 0.16452 1839.5 1.5859 1.8086 0.49056 0.33741 0.026781 0.61604 0.70419 189 7.4674 4.637 -0.37947 1909 1.7945 0.77888 0.33874 0.096534 0.70431 0.35289 0.61966 190 6.9612 4.5943 -0.00717 1877.3 2.1272 1.6963 0.096831 0.029759 0.61591 0.43939 0.35146 191 6.5706 4.6492 -0.19088 1809 0.90355 1.1569 0.028917 0.70069 0.35311 0.37338 0.43794 192 6.4819 4.8274 -0.50508 1763.2 1.5065 0.77832 0.70456 0.6185 0.43943 0.38091 0.37255 193 6.2727 5.1259 -1.2166 1951.2 0.921 1.7169 0.61513 0.35035 0.37237 0.96251 0.38203 194 2.3318 3.4099 0.23869 1933.3 0.9033 2.5605 0.35362 0.43951 0.38267 0.96816 0.96337 195 6.6827 4.5729 0.13794 1880 0.90309 1.4774 0.43658 0.37213 0.96475 0.063027 0.96716 196 6.4829 3.9869 -0.176 1897.5 2.4068 1.766 0.37128 0.38098 0.96775 0.39953 0.061097 197 5.7686 3.0866 -0.07449 1884.9 2.0457 1.2188 0.38369 0.964 0.061914 0.1285 0.3971 198 6.1081 2.3548 -0.15273 1887.1 0.98501 1.6249 0.96476 0.96823 0.39947 0.83442 0.12711 199 6.5657 5.3679 -0.14182 2047.7 1.3082 1.601 0.96697 0.061409 0.12965 0.82773 0.83158 200 6.7453 5.0355 0.79534 2055 1.0649 1.5667 0.061482 0.39772 0.83314 0.46639 0.82855 MDL-NBS-HS-000021 REV 02 A-16 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 1 0.83233 0.24005 0.80624 14.221 1.9903 812.85 440.3 109.47 108.87 4.8775 2 0.82718 0.80526 0.13308 4.609 1.6863 438.05 704.33 129.6 92.939 5.0531 3 0.46566 0.13442 0.73247 9.336 1.0289 707.27 688.4 38.71 77.02 4.2620 4 0.11361 0.73275 0.34383 3.211 0.54985 688.19 663.39 79.503 109.71 4.5371 5 0.24003 0.34009 0.049709 6.490 2.4022 663.62 323.7 93.181 124.51 4.2375 6 0.80576 0.046205 0.7459 6.106 2.2194 321.01 742.97 102.03 100.9 4.3941 7 0.13452 0.74864 0.93901 5.590 1.7185 741.48 430.16 101.08 112.08 5.1399 8 0.73186 0.93694 0.55457 2.180 1.8825 429.34 525.79 96.651 94.367 4.2041 9 0.34145 0.55106 0.79371 7.319 1.7536 526.19 626.36 116.43 106.1 4.6918 10 0.047266 0.79274 0.37606 3.153 1.7716 626.1 256.08 94.687 105.03 5.1004 11 0.74875 0.37598 0.67186 3.965 3.3158 255.36 346.45 94.86 104.08 4.8134 12 0.9384 0.67431 0.65349 4.865 3.4105 344.48 252.75 107.78 89.193 3.8495 13 0.55426 0.65427 0.62915 1.599 0.85794 250.6 293.32 122.12 107.76 5.3892 14 0.79285 0.62833 0.24857 2.380 1.8079 289.57 644.32 104.11 93.974 4.9578 15 0.37977 0.24591 0.71151 1.533 1.1538 644.32 240.83 58.263 97.825 3.8205 16 0.67304 0.71226 0.36864 1.911 2.7247 241.27 425.57 112.1 102.21 5.5740 17 0.65016 0.36852 0.47149 5.094 2.7109 426.26 632.99 96.424 85.471 4.6028 18 0.62547 0.47303 0.58007 1.476 1.9399 631.8 489.65 114.56 90.109 4.8036 19 0.24894 0.58477 0.17326 3.117 1.099 489.47 166.43 98.307 85.408 4.6142 20 0.71268 0.17148 0.2719 4.941 1.4758 166.72 727.65 109.97 87.421 5.1106 21 0.36671 0.27358 0.16723 3.642 2.6485 726.02 580.16 67.302 102.9 4.9749 22 0.47389 0.16561 0.2131 0.834 1.1613 578.39 161.12 123.13 84.683 4.4990 23 0.58452 0.21367 0.60303 7.035 2.4699 159.62 829.77 91.467 93.664 5.2601 24 0.17185 0.60264 0.15762 4.458 1.6923 830.57 376.18 96.067 102.68 4.8586 25 0.27162 0.15986 0.36181 0.809 0.73272 375.4 481.98 91.381 96.375 4.6846 26 0.16981 0.36202 0.59096 9.867 2.4972 479.18 381.72 96.797 79.051 5.5658 27 0.21102 0.59494 0.43437 2.680 3.1595 381.7 638.55 129.53 107.22 5.6739 28 0.60015 0.43132 0.070798 3.579 2.1024 638.67 590.61 90.95 100.17 4.4166 29 0.15677 0.070876 0.69583 2.681 2.615 593.85 328.84 112.58 78.996 5.5237 MDL-NBS-HS-000021 REV 02 A-17 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 30 0.36158 0.69708 0.53266 5.000 1.7618 326.95 678.7 108.37 113.21 5.4983 31 0.59138 0.53117 0.065333 4.581 2.3314 677.42 509.58 94.841 91.582 4.9849 32 0.43049 0.068262 0.81193 2.210 2.2912 511.98 422.18 90.197 96.013 4.1083 33 0.074454 0.81122 0.30876 5.930 2.2459 422.1 820.66 58.974 91.679 5.9685 34 0.6978 0.3088 0.42281 3.841 1.4862 822.12 909.44 110.04 102.71 4.8878 35 0.53021 0.42103 0.3129 3.077 2.4162 909.46 300.12 126.65 100.7 5.6821 36 0.068291 0.31034 0.59624 9.575 1.7497 298.61 796.55 93.625 89.246 5.0253 37 0.81435 0.59788 0.5451 12.473 1.9504 794.22 779.79 103.89 104.64 5.6522 38 0.30796 0.54611 0.25403 1.983 2.1609 779.57 599.93 120.88 97.323 4.9442 39 0.42208 0.25262 0.64219 8.726 1.2938 599.68 224.14 73.613 93.554 5.4314 40 0.31087 0.64499 0.45689 8.364 1.5451 222.51 987.6 191.27 112.55 5.5843 41 0.59771 0.45948 0.35958 4.645 1.2728 987.07 529.6 124.49 119.63 5.2355 42 0.54692 0.35889 0.80226 1.284 1.4037 530.28 914.05 93.929 87.977 4.8650 43 0.2541 0.80481 0.89657 17.394 2.1923 910.33 620.16 179.01 110.89 5.3636 44 0.64387 0.89955 0.2211 4.001 1.2504 620.04 891.15 124.42 110 4.6416 45 0.45648 0.22056 0.77458 12.785 1.7351 891.41 571.89 54.883 101.28 5.0719 46 0.35594 0.77106 0.75751 4.813 2.1801 571.12 746.07 106.71 83.562 5.6180 47 0.8044 0.75705 0.55876 11.844 1.8744 747.9 837.75 111.76 135.96 3.7922 48 0.89716 0.55861 0.13615 4.372 0.91376 835.64 667.68 91.97 98.093 5.4487 49 0.22083 0.1361 0.98634 7.493 2.3907 670.09 514.51 98.776 120.19 5.5328 50 0.7728 0.98683 0.4783 9.902 2.0576 514.64 715.01 126.99 102.03 4.7887 51 0.75745 0.47635 0.90182 5.705 0.88603 712.87 399.44 83.962 118.01 5.5539 52 0.5575 0.90124 0.57823 3.901 2.6678 399.58 628.62 112.43 99.752 4.5138 53 0.13948 0.57826 0.87579 6.717 1.6269 627.55 864.64 126.74 107.99 4.6338 54 0.9886 0.87902 0.52465 2.859 1.849 864.15 150.75 258.23 113.65 4.4139 55 0.47636 0.52426 0.71777 4.903 1.6384 151.12 756.56 118.39 104.29 5.0128 56 0.90226 0.71853 0.81891 10.737 2.1894 754.26 803.41 127.89 97.509 3.7624 57 0.57565 0.81586 0.63343 0.739 2.0898 806.44 474.02 128.39 106.51 3.9613 58 0.87726 0.63481 0.46333 7.676 1.5057 476.79 818.8 83.831 92.659 4.7692 59 0.52271 0.46349 0.68074 9.049 2.2752 818.62 336.85 88.254 102.42 5.6955 60 0.71539 0.68244 0.33489 3.526 1.9216 336.49 394.56 122.77 115.57 5.6712 MDL-NBS-HS-000021 REV 02 A-18 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 61 0.81858 0.33278 0.58895 9.446 1.7264 394.68 294.57 81.37 78.053 4.3374 62 0.63424 0.58517 0.84543 2.290 2.6399 296.99 615.74 100.52 108.66 5.6464 63 0.46136 0.84982 0.056311 2.831 2.956 613.08 148.46 121.59 111.49 5.3243 64 0.68066 0.057841 0.72978 1.928 1.426 145.92 195.85 75.673 95.797 3.5267 65 0.33153 0.72969 0.78261 4.799 2.5599 198.3 467.99 108.21 112.44 4.4555 66 0.58726 0.78325 0.4167 0.690 2.5179 465.66 924.72 96.256 89.718 3.9177 67 0.84941 0.41653 0.79797 1.040 2.1075 926.22 903.86 105.75 92.376 4.5297 68 0.058578 0.79803 0.26066 3.457 1.1735 903.5 273.95 102.44 87.717 4.9694 69 0.728 0.26347 0.32972 13.311 3.6979 272.15 883.85 45.587 101.83 4.7835 70 0.78038 0.32548 0.21687 12.414 1.9618 885.32 702.03 43.519 77.264 4.9502 71 0.41596 0.21798 0.57346 1.751 2.9809 700.89 121.54 105.41 81.802 5.1614 72 0.79808 0.57228 0.054074 11.625 2.1481 119.34 314.87 94.86 95.495 5.8209 73 0.26002 0.052024 0.10657 6.408 2.8736 311.66 183.97 108.3 121.95 5.6385 74 0.32626 0.10795 0.40776 0.436 2.039 183.08 339.8 114.71 119.24 4.0269 75 0.21674 0.40841 0.91631 2.097 2.4268 339.18 589.62 63.997 86.459 5.6138 76 0.57425 0.91592 0.89188 0.955 2.6786 588.04 473.21 128.28 117.71 5.4099 77 0.053163 0.89356 0.19002 2.324 2.2583 471.84 575.22 84.112 105.81 5.6053 78 0.10825 0.19055 0.87486 4.521 1.933 572.68 648.88 112.64 73.738 5.9754 79 0.40749 0.87385 0.66564 3.502 2.361 646.51 950.64 76.018 88.667 3.3825 80 0.91533 0.66936 0.024592 4.407 1.6742 952.86 877.79 15.936 80.824 5.1987 81 0.89182 0.024802 0.238 5.160 2.1683 877.91 212.04 90.958 89.887 3.8823 82 0.19247 0.23768 0.092733 14.707 2.7659 208.9 860.23 125.16 100.63 4.5064 83 0.8716 0.093798 0.2697 11.234 0.82441 860.11 736.5 93.682 95.705 5.4698 84 0.66663 0.26782 0.54484 1.175 2.4578 738.68 855.93 123.3 100.03 3.2578 85 0.022039 0.54487 0.41286 10.610 2.5864 854.64 993.11 113.89 103.17 5.7672 86 0.23834 0.41297 0.5255 7.247 1.8464 994.47 110.54 118.18 126.14 4.6235 87 0.09303 0.52693 0.60617 10.538 2.6304 110.62 659.13 299.8 116.81 3.6374 88 0.26994 0.6098 0.94768 18.734 1.5209 658.39 174.16 120.3 82.794 4.5614 89 0.54397 0.94692 0.8623 0.348 1.6666 172.55 331.74 120.44 115.37 3.9564 90 0.41441 0.86116 0.12201 5.461 1.4188 329.82 767.45 106.38 107.69 4.8941 91 0.52656 0.12189 0.84487 0.899 2.1415 766.83 108.83 104.64 115.02 5.5922 MDL-NBS-HS-000021 REV 02 A-19 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 92 0.60929 0.84095 0.70556 2.267 0.76916 108.02 939.97 177.71 139.22 4.3696 93 0.94947 0.70568 0.83988 7.963 1.062 937.88 389.58 100.55 71.507 5.6284 94 0.8607 0.83864 0.99131 0.244 1.8277 388.79 129.98 92.897 103.93 3.6732 95 0.12496 0.99254 0.012151 13.874 3.0474 127.83 358.17 113.61 80.093 4.8986 96 0.84424 0.014322 0.6206 2.779 2.9291 359.12 191.36 125.2 89.546 5.6454 97 0.70863 0.62212 0.081579 0.537 1.3502 192.1 534.33 123.97 109.3 4.1823 98 0.83814 0.081611 0.25537 2.518 2.8488 534.89 840.2 69.572 68.715 4.1468 99 0.99153 0.25963 0.74219 1.040 2.3268 841.52 281.38 118.18 124.07 3.7073 100 0.01084 0.74266 0.00638 4.070 0.4986 282.1 868.25 94.204 92.211 5.5092 101 0.6226 0.008537 0.9333 10.121 1.4611 866.27 135.17 33.92 74.655 3.9941 102 0.082755 0.93024 0.32214 1.816 1.0042 131.91 540.77 81.289 90.751 4.9205 103 0.25772 0.32134 0.031583 10.910 1.5392 539 882.9 17.356 81.538 4.5873 104 0.74379 0.031874 0.28828 0.588 2.0766 880.48 236.85 95.217 98.315 5.7497 105 0.0066 0.28693 0.10244 4.092 1.833 238.35 232.4 121.57 113.88 5.8007 106 0.9304 0.10181 0.48385 11.375 2.0524 232.95 136.31 34.896 86.943 5.8716 107 0.32214 0.48365 0.82219 1.424 2.2089 139.73 790.5 109.12 116.02 5.9238 108 0.034931 0.82127 0.20133 1.361 3.2142 789.56 205.25 16.508 75.807 4.2303 109 0.28848 0.20343 0.85064 0.647 2.8115 204.97 554.05 83.719 98.454 4.5744 110 0.10153 0.85494 0.037852 8.580 1.131 552.51 367.97 106.86 117.35 4.6150 111 0.48488 0.039425 0.48927 1.134 2.7541 369.82 936.25 54.043 84.514 4.5945 112 0.82181 0.48703 0.86816 4.212 2.4064 935.32 947.4 101.16 84.306 4.6692 113 0.20309 0.86964 0.15423 2.581 2.735 949.48 963.04 98.817 76.071 5.4624 114 0.85318 0.15153 0.14775 13.639 3.9162 960.13 975.53 126.69 110.59 4.7348 115 0.037029 0.14723 0.043615 14.307 0.28545 973.13 244.95 80.878 82.558 5.6580 116 0.48919 0.044629 0.76977 15.467 2.2311 247.87 362.6 120.8 98.991 5.6920 117 0.86816 0.76877 0.11639 16.361 0.96482 361.16 385.18 93.073 91.229 4.9390 118 0.15324 0.11722 0.50208 1.506 1.5153 386.4 373.33 121.41 123.17 4.5446 119 0.14901 0.50107 0.29533 2.556 2.4838 370.58 412.47 115.09 124.87 3.4129 120 0.042737 0.29727 0.92996 2.757 0.24038 414.2 765.76 96.594 127.87 5.6875 121 0.76893 0.92623 0.94325 2.617 3.1079 763.07 449.47 204.67 130.96 5.5441 122 0.11682 0.94167 0.9558 2.972 1.6573 450.84 893.8 98.19 85.118 5.1761 MDL-NBS-HS-000021 REV 02 A-20 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 123 0.50185 0.95667 0.97337 7.856 0.63252 896.39 919.94 90.724 90.898 4.8374 124 0.29877 0.97469 0.16451 3.297 1.5766 920.24 564.89 81.361 92.057 4.8294 125 0.9262 0.16335 0.29046 12.053 1.0562 566.15 347.78 105.17 91.285 5.7118 126 0.94249 0.29347 0.31994 13.073 1.963 349.81 116.51 94.688 93.119 3.8728 127 0.95651 0.31629 0.30057 4.359 2.6953 115.03 915.08 98.763 109.14 5.9370 128 0.97227 0.30062 0.34665 2.407 1.3783 917.36 808.56 120.32 94.609 5.6665 129 0.16375 0.34816 0.73806 0.396 2.7931 807.17 653.26 56.345 118.5 5.3010 130 0.2908 0.73514 0.38982 12.887 0.64424 650.78 504.69 122.96 121.56 4.3202 131 0.31825 0.38902 0.88375 9.230 1.9739 502.29 497.53 96.43 99.609 5.2718 132 0.30346 0.8811 0.91445 5.287 2.8316 497.26 928.08 109.77 90.397 4.2901 133 0.34536 0.91351 0.51775 3.793 1.2279 932.09 167.74 96.177 71.682 5.8432 134 0.73979 0.51891 0.27618 3.753 1.2149 170.49 978.15 63.713 120.69 4.1248 135 0.38918 0.27944 0.017364 13.549 0.71527 981.81 900.52 33.543 111.8 5.4871 136 0.88142 0.018064 0.90692 0.871 2.5438 899.31 692.85 106.49 103.46 3.9044 137 0.91369 0.90812 0.78832 16.548 1.1016 691.49 268.16 89.996 96.932 4.4487 138 0.51854 0.78574 0.61055 12.129 2.0081 266.74 684.08 122.92 96.697 5.5024 139 0.27967 0.61066 0.44885 6.175 1.6021 682.82 261.21 108.67 122.43 4.5558 140 0.018437 0.44944 0.44473 1.681 3.1047 259.8 957.8 62.316 79.558 5.3464 141 0.90992 0.44492 0.92486 6.018 3.1925 959.02 228.62 117.29 132.79 4.9658 142 0.78977 0.92496 0.077725 1.626 3.2736 228.36 778.38 115.04 118.79 4.9995 143 0.61162 0.077621 0.97922 14.966 3.4137 776.75 180.78 105.11 105.23 4.3784 144 0.44672 0.97709 0.88689 1.355 1.2599 177.45 308.05 97.168 86.269 4.7661 145 0.44483 0.88694 0.65537 8.294 1.5851 307.83 787.18 29.899 104.91 5.9886 146 0.92381 0.65965 0.18644 0.932 1.6389 788.47 355.4 94.639 85.829 4.8111 147 0.077437 0.18566 0.64725 2.079 1.6102 354.67 709.36 126.18 127.33 4.4372 148 0.97688 0.64518 0.17796 8.446 1.7018 710.03 584.97 112.95 83.89 5.6345 149 0.88764 0.17513 0.95462 2.479 2.4779 585.05 611.31 110.25 109.74 5.3747 150 0.65902 0.95013 0.14251 6.661 1.7862 610.1 285.37 52.359 80.593 3.1110 151 0.18671 0.14065 0.75367 4.480 2.8909 285.78 461.67 21.46 88.309 5.3096 152 0.64903 0.75082 0.085452 4.723 3.0224 462.78 999.51 114.38 110.43 5.5276 153 0.17695 0.087076 0.23365 1.871 2.0351 999.67 483.77 93.823 90.563 4.3465 MDL-NBS-HS-000021 REV 02 A-21 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 154 0.9512 0.23467 0.76487 3.420 1.5586 484.97 306.89 113.63 106.18 4.7466 155 0.14091 0.76127 0.2801 19.238 0.38107 306.1 872.4 127.4 100.45 5.4393 156 0.75336 0.28179 0.67652 3.611 3.0035 871.12 725.39 116.87 101.58 5.3692 157 0.08953 0.67582 0.53817 2.021 2.5998 721.14 103.99 72.216 87.341 5.9484 158 0.23059 0.53548 0.56945 11.103 2.2116 101.08 695.4 40.23 95.224 4.8526 159 0.7646 0.56552 0.20822 6.888 1.8999 698.34 798.89 108.46 148.17 4.9279 160 0.28497 0.20529 0.40255 0.176 1.8931 798.55 277.25 197.34 96.195 4.9132 161 0.67504 0.40101 0.99992 6.311 3.0661 275.58 455.23 102.95 88.301 4.9346 162 0.53552 0.99938 0.42575 8.932 0.9365 455.05 748.2 111.1 116.45 4.9929 163 0.56653 0.42685 0.22858 1.774 3.5397 751.7 720.14 63.445 106.92 5.2455 164 0.20863 0.22935 0.85861 3.334 2.9012 718.67 983.76 123.47 63.959 4.3054 165 0.40195 0.85843 0.69288 7.557 2.3059 984.15 509.34 118.65 105.54 4.9098 166 0.99884 0.69375 0.001538 6.803 1.3307 505.59 556.96 116.61 111.26 4.6501 167 0.4295 0.00151 0.66146 16.959 2.2877 556.95 548.66 68.395 86.894 3.9386 168 0.22599 0.66498 0.77751 3.825 1.3026 547.43 562.63 110.89 94.915 3.5547 169 0.8586 0.77867 0.19755 4.276 3.2398 561.48 608.45 100.01 108.24 5.4048 170 0.69437 0.1954 0.39244 4.192 1.1982 608.46 671.99 99.386 106.64 5.1931 171 0.001231 0.39299 0.72459 4.305 2.514 671.82 265.99 231.89 134.49 4.6748 172 0.6606 0.72016 0.68846 4.690 0.97624 262.5 541.5 120.61 97.076 4.8286 173 0.77628 0.68789 0.98023 5.795 1.4467 545.05 402.29 113.14 99.164 4.7081 174 0.19637 0.98146 0.45478 1.678 2.5403 403.25 185.89 54.005 98.867 4.7295 175 0.39311 0.45483 0.50829 4.127 1.5639 189.74 125.45 122.69 99.409 5.8882 176 0.72453 0.50536 0.49776 2.894 2.3457 124.24 734.44 100.24 101.46 5.9004 177 0.68917 0.49845 0.51009 0.990 2.0682 731.22 654.92 95.999 104.55 3.8036 178 0.98396 0.51107 0.56335 0.488 2.1292 653.57 416.24 116.28 86.075 4.7517 179 0.45418 0.56394 0.63905 7.186 1.394 416.08 492.31 103.99 98.647 4.0583 180 0.50686 0.6384 0.18176 5.367 1.8196 493.18 435.53 118.77 92.833 5.6042 181 0.49959 0.18351 0.49236 3.002 4.0513 437.08 445.56 34.207 81.084 5.5955 182 0.51036 0.49117 0.33981 3.713 1.862 446.28 964.34 104.91 74.407 4.8724 183 0.56418 0.33823 0.098419 3.186 1.4389 965.64 970.23 124.85 107.46 3.9848 184 0.63522 0.098359 0.029148 3.280 2.8066 970.12 157.45 94.654 103.63 4.4748 MDL-NBS-HS-000021 REV 02 A-22 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 185 0.18001 0.028657 0.7049 15.790 2.3825 155.45 458.25 63.226 93.339 5.5682 186 0.49328 0.70242 0.61821 15.872 -0.00165 458.27 216.04 106.68 96.562 4.0889 187 0.33932 0.6174 0.35471 0.779 2.3105 213.33 848.03 116.92 94.132 5.4564 188 0.095855 0.35206 0.43994 3.371 2.5777 848.42 845.9 129.27 94.576 4.6564 189 0.025006 0.43563 0.37403 1.236 1.3627 843.72 521.17 120.76 129.18 3.7290 190 0.70291 0.37478 0.38384 10.428 1.7917 519.67 200.06 120.91 130.24 5.4786 191 0.61896 0.38398 0.96484 10.269 2.4475 199.43 316.94 103.58 78.41 5.7810 192 0.35329 0.96202 0.96738 3.958 2.3695 320.09 827.3 114.03 95.042 4.9796 193 0.43628 0.9654 0.062055 1.092 3.5458 826.09 219 85.037 83.247 5.5478 194 0.37169 0.061335 0.39868 2.121 1.9109 218.91 760.81 93.183 114.66 4.7098 195 0.38195 0.39667 0.12538 9.702 2.0123 761.17 408.2 93.174 114.11 5.3385 196 0.96264 0.12797 0.83326 1.247 1.9917 406.69 142.25 106.22 97.678 5.2878 197 0.96574 0.8321 0.82688 7.725 2.0208 144.67 773.83 28.908 82.048 5.2122 198 0.063634 0.82798 0.46962 2.930 2.1217 772.31 943.72 93.594 88.773 4.4856 199 0.39766 0.46669 0.11218 0.664 2.2674 943.38 595.47 114.98 113.09 5.4216 200 0.12612 0.1129 0.24114 8.080 1.3256 596.34 813.08 109.78 83.544 4.6979 MDL-NBS-HS-000021 REV 02 A-23 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 1 6488.6 5700.9 5.6503 4168 178.08 3.4892 -4.4407 2 7769.2 6721 5.8331 2766.9 799.65 2.9211 -4.4107 3 5702.4 5037 5.9814 5772.4 945 3.0682 -8.7573 4 6712.4 6161.5 5.0086 6542.1 653.54 3.3114 -7.4077 5 5039.6 6078.9 5.4456 5006.4 833.8 2.6497 -8.4926 6 6166.2 5984.6 4.9920 5951.3 521.65 2.8072 -5.4465 7 6096 4478.6 5.2380 4312.3 744.24 2.6360 -5.476 8 5984.4 6343.7 6.0000 5475.1 729.51 2.7197 -7.1382 9 4483.4 4998.1 4.9762 5389.5 710.35 3.3486 -8.5426 10 6347.6 5398.5 5.6375 5296.6 405.6 2.6160 -8.0268 11 5003.5 5816.1 5.9903 3786 773.96 2.9143 -5.6308 12 5395.8 4080.1 5.7619 5640.9 512.41 3.3299 -8.4685 13 5804 4586.6 4.7149 4258.3 596.07 2.9856 -6.0663 14 4084.8 4056 6.3464 4687.9 676.07 2.3959 -7.6293 15 4591.2 4298.1 5.9175 5127.8 330.43 3.4717 -8.8063 16 4071.1 5882.9 4.6899 3493.9 431.82 3.2197 -6.018 17 4312.5 3986.6 6.5623 3882.3 328.73 2.3635 -4.6686 18 5887.7 4981.3 5.5315 3471 371.58 3.5901 -6.7922 19 3997.5 5842.8 5.7451 3656.9 692.74 2.8522 -5.715 20 4964.8 5254.5 5.5465 5206.8 318.51 2.9747 -7.4927 21 5841.3 3352.8 5.9978 3424.7 509.22 2.8589 -6.3092 22 5249.8 6267.7 5.9360 4246.1 684.76 3.3399 -6.3854 23 3350.7 5629.4 5.3838 5164.9 563.37 3.2550 -6.4937 24 6266.9 3265 6.1931 4532.5 211.99 2.7812 -8.015 25 5614 6838 5.8089 3093.9 761.1 3.4056 -6.1406 26 3268.8 4754.3 5.6274 5569 639.2 3.0266 -7.5392 27 6830 5203.4 6.5441 4917.6 203.9 2.9089 -7.1142 28 4752.1 4769.3 6.6739 3067.4 847.86 3.5824 -6.6703 29 5208.6 5863.3 5.2765 6042 461.44 3.6609 -8.3015 30 4760.6 5676.8 6.5011 4035.3 556.39 2.7344 -7.9093 31 5868 4504.5 6.4728 4490.8 466.35 3.5520 -8.3327 MDL-NBS-HS-000021 REV 02 A-24 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 32 5686.4 6049.8 5.9494 4039.5 688.99 3.5412 -8.1408 33 4496.5 5340.1 4.9233 5173.5 651.93 3.2668 -6.5819 34 6054.1 4946 6.9605 4978.7 411.96 2.5760 -8.3777 35 5335.9 6784.5 5.8382 3800 720.52 3.9447 -7.556 36 4954.1 7395.9 6.6776 5350.2 582.95 3.0918 -6.6373 37 6768.2 4367.7 5.9759 4628 502.03 3.6629 -7.2777 38 7399.6 6606.1 6.6522 4233 839.43 3.3045 -8.7023 39 4349 6544.1 5.9085 5999.7 916.61 3.6457 -6.2199 40 6613.4 5717.4 6.3962 6377.4 383.48 3.2028 -6.8793 41 6556 3873.3 6.5717 3691.6 818.98 3.4953 -8.7381 42 5719.5 8732.1 6.1461 5871.8 808.27 3.5966 -5.5862 43 3858.1 5413.4 5.8195 5824.7 660.06 3.3930 -7.7721 44 8721.8 7419.7 6.3075 5026.1 294.01 3.0345 -7.3063 45 5413.9 5800.7 5.5809 3349.8 991.22 3.4557 -7.745 46 7437.8 7226.2 5.9859 6739.4 598.1 2.8849 -6.6174 47 5796.5 5589.3 6.6128 4704.9 919.06 3.3241 -6.8126 48 7243.6 6357.7 4.6388 6398.1 672.8 3.6195 -7.9985 49 5589.2 6861.8 6.4183 5104.8 899.64 2.3345 -6.4285 50 6364.8 6003.9 6.5159 6302.1 634.71 3.5066 -7.1708 51 6866 5353.2 5.7348 4883.7 777.9 3.5638 -7.5752 52 6008.3 6205.2 6.5366 5656.5 852.87 2.9709 -5.6643 53 5358 4858.7 5.4150 6057.5 712.71 3.5795 -5.0276 54 6218.9 5834.7 5.5775 5310.3 586.49 2.7970 -8.1064 55 4843 7046.9 5.2695 4642.6 750.31 2.8776 -5.8657 56 5831.9 3132.8 5.9717 5519.3 484.63 2.7310 -5.9515 57 7035.9 6410 4.6104 4131 681.99 3.2964 -6.7658 58 3173.9 6675 4.8343 5133.9 873.87 2.3122 -8.4411 59 6397.3 5193.9 5.7110 6175.2 194.82 2.4968 -4.1002 60 6670.5 6733.1 6.6972 3036.4 784.86 2.9609 -7.0941 61 5191.2 4558.9 6.6712 5688.1 825.8 3.6766 -4.9691 62 6755 4836.8 5.1367 5911.1 550.47 3.6582 -6.6998 MDL-NBS-HS-000021 REV 02 A-25 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 63 4559.2 4322.6 6.6454 4468.5 836.11 2.6876 -5.161 64 4826 5767.5 6.2577 5976.8 421.28 3.6429 -6.9188 65 4342.6 3093.2 4.3501 3837.3 477.44 3.4355 -6.1259 66 5774 3650.4 5.3404 4101.5 378.03 2.1519 -5.5367 67 3112.8 5143.1 4.7901 3677.3 668.9 2.7602 -6.4733 68 3652.9 7554.3 5.4249 5088.1 186.91 2.4561 -7.1524 69 5141.2 7336 5.9355 3018.3 260.88 2.8035 -6.2729 70 7565.7 4199.1 5.7202 3230.6 545.33 3.2382 -7.6777 71 7361.4 7210.9 5.9101 4422.1 931.75 2.9685 -6.6509 72 4211.5 6137.8 6.0374 6460.7 911.36 3.2124 -5.3511 73 7212.3 2536.1 6.8306 6348.8 351.33 3.3517 -8.7724 74 6144.2 4428.3 6.6335 3560.8 896.71 3.6989 -6.0952 75 2583 3502.6 4.8833 6283.9 739.45 3.6343 -5.7992 76 4435.6 4576.3 6.6053 5466.5 142.3 2.5393 -7.3313 77 3519.2 5666.3 6.3674 1332.8 399.64 3.6162 -5.6828 78 4580.1 5162 6.5966 3743.7 241.47 3.4880 -7.9519 79 5656.1 5596.2 6.9741 3163.1 426.23 3.6116 -7.6875 80 5172.4 5914 4.2386 3858.5 647.46 3.9614 -8.1309 81 5609.8 7944.5 6.1038 4957.3 550.07 2.0951 -6.7135 82 5912.4 7132.6 4.7531 4448.8 634.96 3.3796 -8.7844 83 7914.7 3773.6 5.4065 4893.1 697.02 2.4256 -8.5657 84 7132.3 7012.5 6.4456 5219 955.7 2.7860 -7.3649 85 3753.5 6324.4 4.1847 6566.3 885.57 3.5229 -4.8334 86 6986.5 6980.9 6.7505 6234.4 276.95 2.0594 -5.0489 87 6306.8 8979.8 5.5658 3296 872.71 3.6879 -8.2303 88 6979.8 2198.1 4.4545 6153.4 769.22 2.8735 -5.1937 89 9020.7 5962.9 5.4814 5609.9 868.01 2.2234 -6.3262 90 2223.7 3419.5 4.8231 6129.4 995.38 2.8308 -8.9159 91 5959.5 4534.1 5.8457 6760.5 122.28 2.4814 -8.049 92 3435.1 6465.6 6.5752 698.84 707.86 3.1066 -8.6293 93 4518.4 1938.8 5.1959 5287.2 226.24 3.6012 -7.9308 MDL-NBS-HS-000021 REV 02 A-26 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 94 6479.5 7749.4 6.6201 3126.2 418.09 2.7010 -6.8351 95 1944.9 4815.2 4.4834 3829.2 794.98 3.6242 -7.3558 96 7738.3 2757.9 5.8567 5762.7 116.33 2.2479 -6.8801 97 4813.7 4650.8 6.6405 669.12 943.93 3.1094 -6.5674 98 2752.3 3626 4.9596 6518.4 474.28 3.6371 -4.579 99 4668.5 5430.8 4.9532 4078.5 156.07 2.6025 -5.2514 100 3590.2 6886.2 4.5261 2047.5 445.26 2.5987 -8.5003 101 5437.2 4246.3 6.4871 3955.1 253.85 2.2623 -5.3798 102 6878.3 7050 4.8636 3207.5 602.23 3.5479 -6.1694 103 4242.2 2836.9 5.8808 4724.6 855.89 2.5293 -5.4229 104 7071.8 5458.1 5.5038 6071.5 365.43 3.1555 -3.9017 105 2849 7165.5 6.7372 3615.2 879.29 2.8449 -8.9485 106 5452 3968.1 6.8082 6203.8 161.11 3.6822 -6.5045 107 7180.6 3947.5 6.8733 2313.5 607.45 3.6947 -8.6754 108 3975.9 2963 6.9243 4750.4 889.84 3.7506 -7.9714 109 3949.9 6585 4.9802 6255.2 310.82 3.8465 -6.0296 110 2961.6 3722.4 5.4942 3405.5 306.56 2.6266 -8.9706 111 6583.9 5508.2 5.5563 3396.5 167.18 2.8365 -4.7113 112 3744.8 4713.2 5.5211 2566.2 815.33 2.8642 -7.7037 113 5502.7 7651.4 5.6117 5859.1 271.76 2.8499 -8.8791 114 4707.5 7827.8 6.4298 3276 619.25 2.9020 -7.8504 115 7668.2 8061.2 5.6812 4801.1 451.04 3.5209 -8.5921 116 7875.1 8371.1 6.6551 3985.2 937.03 2.9405 -7.0702 117 8054.6 4033.3 6.6920 6498.8 952.66 3.6481 -5.5235 118 8382.8 4674.7 5.9025 6550.2 965.4 3.6725 -8.1812 119 4032.2 4794.8 5.4548 6613.1 975.16 3.1876 -5.3301 120 4682.7 4727.1 4.3159 6665.6 320.43 2.8162 -8.8483 121 4789.7 4923.1 6.6857 3448.6 446.62 2.1361 -7.0482 122 4733.6 6446.1 6.5263 3960.9 470.86 3.6683 -5.226 123 4918.3 5066.3 6.0719 4064.5 456.71 3.5702 -8.3913 124 6457.4 7265.2 5.7917 4014.1 493.65 3.3600 -8.4006 MDL-NBS-HS-000021 REV 02 A-27 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 125 5073.8 7501.7 5.7853 4190.3 792.72 2.9976 -8.8265 126 7269 5566.2 6.7024 5728.5 527.66 2.9937 -5.8902 127 7503.6 4620.7 4.7329 4350.1 902.78 3.6804 -8.5362 128 5573.1 2382.2 6.9325 6325 928.67 2.4095 -6.9813 129 4622.1 7497.1 6.6599 6426.1 629.98 3.8979 -7.8073 130 2420.4 6694.9 6.2405 4867.7 435.71 3.6530 -4.7451 131 7457.5 5934.5 5.1173 3908.3 127.29 3.4250 -4.6212 132 6679.9 5310 6.1987 995.09 924.13 2.6807 -4.4973 133 5936.4 5289 5.0374 6414.2 830.59 3.4087 -4.3664 134 5304.7 7600.3 6.8506 5940.5 698.01 2.6538 -8.3547 135 5285.5 3394.1 4.9341 5233.1 575.88 3.7269 -7.8364 136 7609.5 8528.2 6.4669 4588 572.62 2.5810 -7.7319 137 3398.2 7310.8 4.7676 4566.4 934.01 3.5342 -7.7884 138 8495.8 6104.3 5.3160 6480.9 220.56 2.4374 -7.6139 139 7329.9 4160.2 6.4786 3100.4 981.25 2.7538 -6.0479 140 6102.7 6062.9 5.4698 6693 907.73 3.5430 -7.4548 141 4166.5 4117.4 6.2900 6337.7 733.62 2.8222 -5.1313 142 6062 7991.4 5.9253 5422.8 349.23 3.4512 -4.9116 143 4131.1 3906.2 5.9633 3546.9 726.94 3.2263 -6.9204 144 8021.9 6524.3 5.2175 5384.1 336.27 3.2910 -7.891 145 3903.4 3468.8 5.7076 3509.5 960.78 2.7132 -8.9265 146 6511.8 4418.7 6.9969 6586.2 300.53 2.9582 -4.9539 147 3457.3 6579.8 5.7505 3359.8 803.03 3.9972 -5.7348 148 4404.6 4630.4 5.2945 5803.8 232.94 2.9797 -6.5489 149 6571.7 6183.3 6.6243 3147.6 394.75 2.7420 -7.2133 150 4650.1 5637.9 6.3304 3734.3 809.21 3.6309 -7.225 151 6185.5 5757.9 4.0403 5840.2 439.43 3.4709 -4.7824 152 5645.3 4276.8 6.2553 3929.5 747.16 2.0382 -8.6861 153 5748.4 5137.6 6.5065 5492.1 644.24 3.4298 -4.3303 154 4277.4 9300.6 5.1614 4944.8 668.14 3.5591 -5.0869 155 5131 5222.6 5.6857 5055.9 369.36 2.6922 -6.3617 MDL-NBS-HS-000021 REV 02 A-28 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 156 9534.9 4376.2 6.3997 3628.1 540.59 2.9465 -8.2544 157 5223.8 7111.8 6.3160 4397.9 998.61 3.5045 -6.4036 158 4371.9 6245.4 6.9528 6778.5 559.62 3.4647 -8.2975 159 7107.4 1511.6 5.8035 4506.4 387.34 3.9291 -4.5372 160 6262.1 6123.3 5.8876 3710.1 884.11 3.0123 -8.4216 161 1345 6652.3 5.8745 6222 759.54 3.1609 -5.9679 162 6117.2 4216 5.8954 5553.8 106.16 3.1339 -8.6561 163 6648.8 5090.8 5.9552 133.63 737.64 3.1759 -8.0717 164 4235.5 6390.9 6.1584 5437.7 821.88 3.2811 -5.909 165 5089.3 6227.3 5.0969 5895.3 357.82 3.3966 -7.878 166 6385.7 8608 5.8603 3585.5 532.58 2.6703 -6.2949 167 6223.2 5321.4 5.5933 4356.9 781.14 3.1305 -6.8452 168 8546.8 5534.4 4.8125 5669.7 755.11 2.8881 -6.7339 169 5319.2 5483.1 4.4143 5538.5 983.03 2.4729 -8.1665 170 5521.6 5542.5 6.3617 6717.7 580.56 2.1921 -7.3829 171 5495.8 5731.1 6.0755 4608.6 622.03 3.4794 -3.6765 172 5549.6 6033.4 5.6232 4816.2 613.79 3.3727 -7.2856 173 5727.9 4140 5.7782 4782.9 623.75 2.9066 -8.0952 174 6023.7 5477.9 5.6590 4843.3 664.5 2.9908 -5.2724 175 4148.4 4872.6 5.6693 5042 719.54 2.9265 -6.2288 176 5479.6 3549.9 6.8814 5344 343.37 2.9380 -8.9859 177 4879.1 2624.6 6.9058 3534 608.71 3.8063 -6.3475 178 3562.2 6292.3 4.6491 4764.2 488.67 3.8289 -5.8284 179 2691.1 5944.7 5.6981 4144.2 248.32 2.3548 -8.2179 180 6293.7 4927.5 4.8968 3190.7 150.62 2.9539 -7.4396 181 5941.6 5265.2 6.5944 1697.7 766.1 2.5494 -6.1073 182 4940.1 5004.8 6.5843 5606.2 701.74 3.6094 -6.2584 183 5261.6 5043.6 5.8215 5251.5 497.44 3.6051 -4.1654 184 5020.3 8191.8 4.8495 4209.5 568.89 3.0603 -7.1812 185 5060.4 8242.6 5.3579 4551.7 517.51 2.5082 -6.9617 186 8136.4 3206.1 6.5563 4293.2 522.73 2.7668 -7.0139 MDL-NBS-HS-000021 REV 02 A-29 October 2004 Saturated Zone Flow and Transport Model Abstraction Table A-1. Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 187 8289.8 5112.5 4.9119 4326.7 967.88 3.5857 -6.9487 188 3212.5 3783.9 6.4232 6625 972.79 2.5597 -6.7548 189 5101.7 6943.9 5.6010 6654.5 199 3.5129 -6.4514 190 3797.2 6920.3 4.5707 3041.1 535.96 2.8922 -8.267 191 6929.3 5377.6 6.4533 4377.2 283.4 2.2913 -7.0285 192 6916.6 3672.1 6.7846 3319.1 863.42 3.5281 -7.651 193 5384 4451.3 5.9450 6111.5 861.69 3.6906 -8.615 194 3694.1 6790.8 6.5366 6096.6 590.15 3.2638 -8.8951 195 4459 3827.5 5.6646 4668.2 262.72 3.5723 -6.1974 196 6789.6 6419 6.2765 3248.5 403.04 2.9325 -6.5318 197 3839.3 4891.3 6.2175 3762.3 844.46 3.4436 -7.5985 198 6419.4 3017.7 6.1335 6014.8 285.99 3.4185 -7.2599 199 4889 6501.1 5.3766 3329.5 788.24 3.3858 -7.5095 200 3037 7780.9 6.3784 5721.1 489.71 2.7745 -7.4663 Source: DTN: SN0310T0502103.009 [DIRS 168763]. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 A-30 October 2004 INTENTIONALLY LEFT BLANK Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 October 2004 APPENDIX B RE-SAMPLED STOCHASTIC PARAMETER VALUES Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 October 2004 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-1 October 2004 This appendix documents the results of the SZ transport abstraction model using a re-sampling of the uncertain input parameters. The re-sampling uses the same uncertainty distributions described in Section 6.5 of this model report, but utilizes a different sampling algorithm implemented in an updated version of the GoldSim software code. The version of the GoldSim software code ([DIRS 161572]) used to sample the uncertain parameter vectors for the SZ transport abstraction model for the simulations presented in Section 6.6 contained a dfference in the sampling routine relative to Latin Hypercube Sampling. This difference was reported in CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009), and the problem was corrected in subsequent versions of the GoldSim software. Appendix B documents the impact analysis of this sampling difference on the SZ transport simulation results, as indicated by the plan in CR 2222. The inputs and outputs from the SZ transport abstraction model for the analysis documented in this appendix are contained in DTN: SN0407T0502103.013. The impact analysis for SZ radionuclide transport results consists of the following steps. The uncertain parameter inputs to the SZ transport abstraction model are re-sampled using GoldSim V8.01 SP4 (STN: 10344-8.01SP4-00, BSC 2004 [DIRS 169695]), in which the sampling difference has been corrected. The re-sampled values of the stochastic parameters are given in Table B-1. The full suite of radionuclide transport simulations is conducted using the re-sampled parameter vectors. Among the 200 realizations for the 10 groups of radionuclides, the median transport times are extracted and ranked to determine the fifth percentile, median, and 95 percentile values out of the 200 realizations. The values of median transport time for these three levels of cumulative probability are then compared to the comparable values from the base-case results (as presented in Section 6.6). The comparison of median simulated transport times at these three levels of cumulative probability is presented in Table B-2. The impact analysis plan in CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of ANL-EBS-PA-000009) gives a criterion of 10 percent difference between the base case SZ transport simulation results and the re-sampled parameter case for the impacts of the sampling difference in GoldSim to be considered significant. The results shown in Table B-2 indicate that this criterion for significant impact is exceeded for several of the radionuclide groups and for each of the levels of cumulative probability. In contrast, a graphical comparison of the CDFs for the median simulated transport times of nonsorbing species for the base case and the re-sampled parameters suggests little difference in the overall uncertainty distributions for the modeling results (see Figure B-1). Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-2 October 2004 Table B-1. Resampled Stochastic Parameter Values real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 1 0.15451 0.61331 0.17939 0.24512 0.82056 -3.8248 -11.253 1.7437 6.1641 102.77 160.47 2 0.47702 0.13684 0.11408 0.11487 1.2012 -2.1908 -10.542 1.1902 4.6904 127.89 398.51 3 0.56717 0.97133 0.18689 0.20301 1.1162 -1.0748 -10.369 1.2517 4.7706 230.91 100.67 4 0.10734 0.95304 0.15792 0.21281 2.1091 -4.0288 -10.449 1.4754 8.214 89.503 239.62 5 0.4026 0.3768 0.21127 0.083927 0.99514 -3.2734 -9.9334 1.1209 4.4149 329.24 382.08 6 0.84137 0.72993 0.14731 0.21163 1.1126 -3.0427 -10.626 0.75688 5.2304 261.08 41.482 7 0.31095 0.11323 0.10118 0.16575 1.1435 -3.1508 -9.5171 1.8229 7.0925 368.16 85.61 8 0.61721 0.30199 0.26624 0.10631 1.1633 -3.9555 -10.391 1.514 8.4012 86.233 246.38 9 0.64351 0.54047 0.22131 0.21951 1.33 -3.8841 -10.355 1.2195 5.0232 295.59 348.93 10 0.017634 0.69878 0.24485 0.09997 1.3982 -2.0052 -10.148 1.2513 7.772 366.26 232.98 11 0.36141 0.69208 0.16297 0.16612 1.7877 -3.4103 -9.8462 1.2362 6.2984 79.21 300.4 12 0.66863 0.51855 0.16177 0.17671 1.6181 -2.7493 -9.6179 1.8261 7.555 50.712 237.14 13 0.93638 0.86084 0.17432 0.18663 1.4548 -2.8833 -9.9251 1.7219 8.2876 39.942 221.56 14 0.54225 0.74071 0.12117 0.20404 1.0209 -2.114 -10.469 1.3192 5.3529 97.935 25.237 15 0.079818 0.14179 0.21335 0.19217 0.92842 -1.2718 -10.2 1.3252 6.4525 121.44 187.19 16 0.22733 0.53666 0.23757 0.22169 1.0914 -3.7174 -10.51 1.815 8.3339 153.48 35.574 17 0.9105 0.78472 0.1764 0.15444 1.4341 -2.8256 -10.457 1.7151 8.2226 87.498 154.38 18 0.7729 0.084835 0.14338 0.087999 1.1292 -3.9712 -10.267 1.5264 6.1475 339.64 53.169 19 0.22058 0.092993 0.16874 0.12009 1.8222 -1.1551 -9.3046 5.3108 7.0649 293.46 293.51 20 0.63572 0.22141 0.19893 0.18049 1.2755 -3.6338 -10.606 1.7728 8.6851 355.03 61.475 21 0.46859 0.15315 0.23131 0.07532 1.7139 -2.7178 -10.28 1.405 6.7432 248.05 306.06 22 0.55837 0.73861 0.14775 0.17517 1.8189 -2.5646 -10.364 1.6164 7.5053 188.54 285.67 23 0.93381 0.16285 0.20725 0.1593 1.4084 -1.4373 -11.221 1.1998 4.8646 393.72 71.854 24 0.27958 0.19563 0.18585 0.16883 1.5481 -2.2463 -10.472 1.0035 1.8242 71.215 171.14 25 0.67783 0.82878 0.19173 0.26284 1.2494 -4.7125 -10.179 1.8117 6.8152 213.85 129.45 26 0.14234 0.90098 0.15347 0.17201 2.1518 -3.2488 -10.428 5.9266 7.6134 331.85 113.23 27 0.63108 0.32094 0.11105 0.1861 1.8577 -4.1457 -10.082 1.5185 7.7077 370.96 182.69 28 0.97766 0.98722 0.23521 0.053929 1.2998 -3.9616 -10.998 1.0002 6.8603 133.64 281.52 29 0.094175 0.76688 0.12078 0.1676 1.6638 -1.4805 -9.8115 1.6107 9.075 66.879 77.741 30 0.57883 0.21118 0.17048 0.10311 1.5749 -1.3229 -10.564 1.0831 2.1409 135.46 95.29 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-3 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 31 0.94664 0.2609 0.10912 0.17843 2.4064 -3.3455 -10.769 1.653 7.7886 334.92 156.8 32 0.59584 0.3372 0.11284 0.19882 1.4641 -3.8551 -10.131 1.5419 6.679 132.07 207.88 33 0.32113 0.037874 0.2104 0.16284 0.91225 -1.2881 -10.259 1.7135 7.2404 286.22 108.77 34 0.29157 0.36888 0.18025 0.18707 1.0402 -4.319 -9.9468 0.99292 5.1509 110.2 394.13 35 0.74654 0.033906 0.15763 0.13045 1.8976 -2.3712 -10.312 1.1913 4.8234 163.19 90.119 36 0.27276 0.49577 0.13898 0.19081 1.1846 -3.1034 -10.459 1.4026 7.3466 386.78 224.64 37 0.37341 0.7327 0.064858 0.1695 1.2109 -1.7128 -10.317 1.4201 5.5295 301.55 313.64 38 0.81269 0.71257 0.17073 0.15785 2.2255 -3.9375 -10.273 1.3814 5.664 285.61 164.78 39 0.20651 0.81858 0.17469 0.1795 0.72671 -2.9076 -10.422 1.0858 4.3503 288.61 340.14 40 0.41729 0.39756 0.27779 0.11298 1.3697 -3.5408 -10.244 1.3096 5.9389 399.46 269.69 41 0.5347 0.10605 0.19533 0.17748 1.3558 -1.2155 -10.058 1.4409 7.5078 267.17 243.12 42 0.68784 0.35898 0.17567 0.15113 1.3862 -3.119 -10.399 1.5773 8.3875 61.025 304.79 43 0.20429 0.98413 0.18889 0.19525 1.0585 -3.9954 -9.6862 1.6986 4.2141 361.36 179.52 44 0.17996 0.079534 0.21288 0.19748 0.83332 -2.9663 -10.08 1.2322 6.6549 160.54 369.77 45 0.23268 0.70271 0.13104 0.095923 0.61091 -3.7591 -9.5589 1.2574 5.0532 111.45 135.23 46 0.94002 0.68555 0.17212 0.14843 2.499 -4.2914 -9.9183 5.4986 12.997 201.68 205.42 47 0.9219 0.62997 0.048637 0.21442 1.2257 -3.4446 -10.122 1.5445 7.2167 117.91 311.11 48 0.11753 0.38704 0.13991 0.20593 1.4879 -2.9231 -10.638 1.6764 7.8139 338.16 50.193 49 0.827 0.80175 0.25328 0.17901 1.4701 -3.0873 -9.9755 1.1679 5.2619 300.29 137.8 50 0.26421 0.52885 0.25032 0.19922 1.6234 -2.0279 -10.068 5.9955 12.169 311.01 319.75 51 0.064713 0.27162 0.15502 0.14136 1.1368 -1.8908 -10.284 1.726 7.4901 49.767 245.94 52 0.30783 0.76468 0.14528 0.22367 1.0829 -2.6102 -10.349 1.3565 6.4651 204.45 378.12 53 0.38381 0.55173 0.15182 0.14712 0.23855 -2.858 -10.671 1.7973 5.1993 36.678 97.266 54 0.72186 0.96916 0.18828 0.17131 1.6293 -1.9453 -9.8153 1.8224 9.4862 44.982 145.4 55 0.40607 0.83325 0.25785 0.096324 1.2842 -1.5205 -10.66 1.2942 6.2467 341.24 166.75 56 0.90988 0.84697 0.21523 0.2761 1.5133 -3.288 -10.051 1.1281 4.5134 90.968 395.59 57 0.19368 0.66653 0.28314 0.20833 1.025 -3.3438 -9.9961 1.6278 7.5936 320.89 283.45 58 0.75213 0.15725 0.20111 0.23127 1.4182 -4.4429 -10.254 1.3372 7.9413 202.97 321.09 59 0.51425 0.75492 0.1873 0.072509 1.8376 -3.1668 -10.11 1.5346 7.5754 379.86 105.09 60 0.33748 0.30986 0.1379 0.20891 2.3767 -2.6185 -10.321 3.5 7.8272 145.14 262.78 61 0.33121 0.47933 0.19631 0.18439 0.76825 -3.4808 -9.979 4.244 8.518 105.62 199.2 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-4 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 62 0.17246 0.77804 0.14847 0.19701 0.45371 -3.5141 -9.9163 1.6616 6.9774 23.745 273.78 63 0.11079 0.34953 0.17999 0.18161 1.459 -3.6508 -10.614 1.1611 4.379 194.27 37.474 64 0.77508 0.018099 0.22246 0.22977 1.1456 -3.6972 -9.5041 1.9761 8.666 298.55 126.6 65 0.9675 0.14511 0.15072 0.20751 1.2068 -2.2546 -9.9972 1.1835 6.1704 269.3 144.68 66 0.65465 0.78618 0.17502 0.18945 0.94653 -3.3942 -10.481 1.3794 5.1835 254.59 374.35 67 0.31623 0.058215 0.19715 0.19132 0.9235 -1.644 -10.129 1.1442 4.0732 174.12 362.92 68 0.053659 0.46803 0.2408 0.15517 0.73387 -2.0934 -10.4 1.7598 8.0943 377.41 397.82 69 0.49169 0.87844 0.22613 0.21365 1.5542 -3.0917 -10.733 1.4624 6.9132 31.094 257.93 70 0.48746 0.80687 0.18213 0.27987 0.68653 -2.2711 -10.492 1.689 7.9085 279.5 219.07 71 0.25288 0.062208 0.23415 0.26998 1.6942 -2.6728 -10.417 1.4776 7.0384 229.26 149.13 72 0.50847 0.60382 0.15427 0.17439 1.544 -2.3075 -10.155 0.68438 3.1663 72.667 141.64 73 0.29974 0.64922 0.24811 0.11975 0.41584 -2.4904 -10.536 1.3651 5.7509 108.04 369.3 74 0.001166 0.19266 0.21429 0.20577 1.8758 -3.0257 -10.341 1.2398 6.1983 377 279.11 75 0.042079 0.79283 0.21926 0.20281 1.4286 -1.3395 -10.616 1.3141 4.2133 64.565 29.08 76 0.45846 0.64422 0.18071 0.12158 1.4986 -3.6824 -10.693 1.7602 4.9213 43.315 271.59 77 0.95161 0.41143 0.20249 0.19316 1.5263 -3.8388 -11.053 1.5576 7.8909 186.11 348.05 78 0.26781 0.91957 0.19013 0.25676 1.6361 -1.5587 -10.004 2.3748 8.0176 262.22 335.59 79 0.41006 0.75838 0.11607 0.18122 0.90185 -2.9452 -10.574 1.4521 7.3697 345.07 47.677 80 0.51545 0.57455 0.22788 0.19986 1.0973 -2.6487 -9.7701 0.99093 6.6515 150.32 263.91 81 0.95733 0.066521 0.10282 0.22548 1.5359 -2.526 -10.375 1.7889 6.6458 81.188 250.25 82 0.88537 0.41883 0.22329 0.13661 0.77396 -2.1389 -11.108 1.3361 4.2183 290.92 231.16 83 0.36615 0.5453 0.13476 0.24087 1.1623 -3.7423 -10.506 1.301 5.2676 275.37 189.66 84 0.16779 0.45269 0.15697 0.11679 0.7852 -3.9283 -9.9037 1.6366 7.4887 227.39 112.42 85 0.16085 0.096493 0.17871 0.22874 1.777 -3.6095 -11.122 1.7966 7.708 323.55 64.592 86 0.72935 0.34271 0.12544 0.22486 1.2609 -3.7092 -9.4071 1.482 7.6459 211.9 342.89 87 0.83287 0.32868 0.13686 0.20156 0.80618 -2.5733 -10.297 1.4215 7.0502 168.87 303.07 88 0.76408 0.6793 0.17136 0.29058 1.0047 -3.0518 -9.4712 1.6056 7.2449 76.778 118.54 89 0.095763 0.40949 0.20964 0.16791 1.5617 -2.4667 -9.3754 1.6457 4.9158 41.372 196.41 90 0.48254 0.42029 0.24328 0.23031 1.6577 -3.8094 -10.49 3.1973 8.1647 250.8 105.95 91 0.19603 0.52282 0.17748 0.13717 1.2429 -1.5273 -10.554 1.2838 7.2846 21.507 287.4 92 0.18135 0.68067 0.21231 0.10727 1.1721 -1.0366 -10.499 1.7196 6.3647 384.59 265.16 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-5 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 93 0.24519 0.085228 0.22374 0.16178 1.2181 -2.7725 -10.142 1.2655 4.349 147.09 120 94 0.00815 0.88372 0.16053 0.21214 1.1511 -2.7587 -10.651 1.7821 11.569 157.39 295.32 95 0.88017 0.97634 0.13176 0.15667 0.75645 -4.8566 -10.544 1.4468 6.9344 58.853 346.58 96 0.65912 0.22764 0.070533 0.15584 1.7601 -1.59 -9.9109 1.4401 5.3184 314.2 43.223 97 0.61399 0.31798 0.23951 0.12847 0.85851 -3.1242 -10.582 1.5445 8.596 343.62 288.63 98 0.038079 0.28563 0.089285 0.21639 1.1241 -3.7934 -10.917 1.2656 5.1581 317.64 66.138 99 0.55453 0.63089 0.19061 0.22716 1.0105 -2.2082 -10.679 1.6838 9.6272 195.33 70.128 100 0.86079 0.48698 0.12253 0.20049 0.56076 -2.2218 -9.5403 1.4352 5.3442 190.67 259.48 101 0.78665 0.82048 0.052355 0.14924 0.19142 -2.4254 -10.035 1.1362 5.5581 207.12 372 102 0.01354 0.92652 0.20619 0.1519 1.2618 -2.7006 -10.672 2.7514 7.029 256.13 141.44 103 0.58308 0.70661 0.16817 0.1885 1.8112 -3.0639 -9.7574 1.4899 4.6051 220.76 75.981 104 0.13048 0.91356 0.1939 0.20205 1.7447 -1.7877 -9.4766 1.0647 5.3233 247.02 387.98 105 0.28326 0.59488 0.092197 0.16021 0.62008 -2.2965 -9.9623 1.1416 5.1875 211.79 240.67 106 0.74173 0.006837 0.18534 0.13162 1.438 -1.0161 -10.409 1.3379 7.8773 304.39 26.481 107 0.81661 0.94903 0.16504 0.15313 1.0701 -3.3763 -10.594 0.51139 3.3166 263.39 267.4 108 0.49681 0.84374 0.27156 0.23532 1.6115 -2.0365 -10.29 1.359 6.766 129.76 124.99 109 0.70677 0.50237 0.27545 0.23256 0.66038 -2.7875 -10.938 1.6052 7.9792 385.61 253.24 110 0.71628 0.20405 0.15244 0.2108 0.67724 -3.8943 -10.787 1.6233 5.338 140.3 323.6 111 0.020519 0.11671 0.13676 0.21789 1.8909 -1.3647 -10.447 1.466 7.9455 94.978 214.52 112 0.42269 0.86654 0.23582 0.18235 1.3075 -1.7508 -10.413 0.99845 2.3406 325.92 227.97 113 0.9942 0.25223 0.21716 0.17794 1.1071 -3.9809 -9.8537 1.4078 5.1478 96.249 366.8 114 0.89097 0.74818 0.25081 0.22697 0.69674 -2.0799 -10.604 1.3234 6.3414 104.87 59.842 115 0.62132 0.46444 0.18441 0.15 1.6799 -3.4277 -9.4566 1.1019 2.294 26.732 109.8 116 0.86743 0.63615 0.15577 0.12705 0.3135 -1.6733 -10.301 1.4408 4.6148 38.838 74.671 117 0.25736 0.88827 0.16637 0.15376 0.79901 -1.9871 -10.377 1.3022 4.9784 364.36 51.185 118 0.79535 0.53043 0.16581 0.28089 1.4781 -3.3028 -10.504 4.3222 11.776 356.64 210 119 0.82023 0.89271 0.17265 0.13346 1.7514 -2.6625 -10.885 1.7887 8.295 245.89 386.18 120 0.78008 0.029057 0.24583 0.22147 1.1758 -1.3955 -9.6455 1.0774 4.4117 63.359 34.305 121 0.99644 0.001809 0.25403 0.24598 1.7237 -3.2987 -10.619 1.7513 8.0951 348.89 254.81 122 0.43434 0.56853 0.21893 0.13887 0.70301 -1.8625 -10.015 3.8152 12.36 362.37 225.81 123 0.66334 0.9426 0.12918 0.15897 1.0999 -2.541 -10.646 1.0579 6.1532 284.03 20.15 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-6 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 124 0.34894 0.61624 0.1638 0.20696 1.4508 -1.6157 -9.7203 1.1641 6.4144 225.27 330.18 125 0.6482 0.55825 0.19996 0.14063 1.4038 -2.8694 -10.306 1.0934 6.2914 172.53 87.277 126 0.52262 0.47435 0.15944 0.15274 1.6703 -2.6884 -9.8678 1.3137 7.6635 52.594 353.42 127 0.12093 0.99857 0.14089 0.17042 1.521 -3.0728 -9.699 1.3607 5.8605 397.46 102.3 128 0.50376 0.40211 0.12462 0.24028 1.3506 -3.7681 -10.233 1.8162 8.3619 240.41 30.549 129 0.4494 0.58139 0.08441 0.15786 1.3227 -3.7514 -9.7281 1.4336 7.4172 219.4 277.99 130 0.87816 0.65641 0.20889 0.17611 1.834 -1.6861 -9.3586 1.7359 6.0229 48.342 160.61 131 0.8586 0.42898 0.11757 0.24908 1.2823 -3.265 -10.173 1.2161 7.4377 68.552 180.1 132 0.42846 0.043645 0.14276 0.19387 1.5002 -1.2474 -9.9678 1.6985 10.784 116.86 80.647 133 0.68102 0.87416 0.1497 0.14457 1.2919 -3.8169 -11.011 1.7445 7.0723 353.29 359.63 134 0.79019 0.44076 0.16073 0.16496 1.2304 -3.1606 -9.5735 1.0969 4.0565 270.84 248.91 135 0.24348 0.44885 0.11533 0.25325 0.37138 -1.7344 -10.023 1.5748 7.043 138.51 344.03 136 0.54706 0.014079 0.26015 0.17058 1.3755 -1.8165 -10.17 1.1307 5.3682 235.84 256.87 137 0.23602 0.39414 0.21771 0.26047 0.95554 -2.5023 -10.689 1.1687 3.9222 184.39 334.35 138 0.59063 0.43338 0.2567 0.19021 1.0313 -3.3801 -10.383 1.4407 7.3211 209.21 375.4 139 0.96152 0.33488 0.11912 0.23777 0.63887 -2.1551 -10.643 1.4238 7.3109 149.15 328.56 140 0.057431 0.90967 0.18381 0.14781 1.486 -2.39 -9.783 1.6775 7.3174 374.98 356.74 141 0.67141 0.24933 0.20516 0.24424 1.0503 -3.2255 -10.041 1.0837 4.6347 100.06 177.11 142 0.28613 0.99468 0.20035 0.12554 1.2671 -3.1936 -11.151 1.2299 4.7301 92.315 68.913 143 0.30444 0.35477 0.13232 0.25113 1.7961 -2.0657 -9.9496 1.0069 5.1081 265.61 310.14 144 0.18719 0.12198 0.075385 0.21826 1.6441 -1.4681 -9.9415 1.7274 5.0211 77.379 93.901 145 0.58918 0.45993 0.099761 0.2382 0.49254 -2.3316 -10.432 1.3627 6.2112 192.59 163.21 146 0.34133 0.04982 0.22967 0.10123 1.4409 -3.3182 -10.684 1.5502 5.4328 136.57 382.91 147 0.047805 0.29341 0.093901 0.1227 1.5628 -3.5622 -10.533 1.2252 6.1875 252.7 174.65 148 0.84534 0.58786 0.18263 0.14408 0.60164 -1.9215 -10.654 1.1387 4.179 155.88 132.05 149 0.87341 0.66188 0.12757 0.14625 1.7067 -4.6177 -10.15 1.0285 3.8389 125.08 314.85 150 0.73249 0.93472 0.16928 0.18818 1.597 -1.1944 -10.052 1.7162 6.8352 34.243 351.8 151 0.75869 0.56129 0.14396 0.26452 1.4149 -3.7228 -10.329 1.7684 7.2748 336.65 379.84 152 0.60477 0.10206 0.19316 0.13411 1.5702 -2.3524 -10.548 1.5811 7.1311 216.59 308.76 153 0.35691 0.37418 0.23304 0.20966 1.3384 -1.419 -11.288 1.9484 10.538 324.44 80.964 154 0.072725 0.27833 0.22884 0.14222 1.7334 -3.5069 -10.517 1.4743 4.4277 55.745 388.77 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-7 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 155 0.39335 0.71654 0.14475 0.16243 1.0566 -2.4475 -10.388 1.1995 4.3703 318.35 188.76 156 0.15917 0.96062 0.2046 0.19583 0.59304 -3.4141 -10.666 1.763 8.3527 170.26 173.83 157 0.39965 0.23549 0.17357 0.13773 1.7958 -3.9008 -10.217 1.3955 6.2267 114.07 115.69 158 0.56161 0.17895 0.22476 0.18496 1.529 -2.8009 -10.075 0.25242 2.953 234.54 290.84 159 0.47147 0.858 0.13501 0.13566 0.64763 -2.4053 -10.699 2.0714 6.9061 259.03 191.78 160 0.13672 0.85446 0.19772 0.22029 1.5876 -2.3436 -10.088 1.4322 5.9479 166.84 31.595 161 0.70147 0.62008 0.22654 0.14342 1.3647 -3.6558 -9.3177 1.5789 7.6938 239.67 324.09 162 0.066647 0.24255 0.19121 0.12682 0.85199 -3.4406 -10.359 1.3309 4.5934 280.82 213.09 163 0.89606 0.070428 0.096858 0.17308 1.0672 -2.1244 -10.328 2.7149 8.9685 152.5 229.8 164 0.02568 0.3813 0.10695 0.1826 1.3181 -3.4742 -10.485 1.0952 6.1953 182.25 298.74 165 0.35061 0.26555 0.21632 0.18526 1.1954 -3.3565 -10.435 1.6407 11.12 199.68 63.421 166 0.92835 0.49267 0.12642 0.21678 0.65329 -3.877 -10.588 1.4321 6.2817 143.21 39.647 167 0.71389 0.92211 0.24224 0.17395 1.9965 -3.5493 -10.097 1.4841 5.9563 176.3 194.43 168 0.62881 0.60875 0.19841 0.1838 1.878 -1.0817 -9.8839 1.4514 6.1409 307.81 97.929 169 0.69732 0.28369 0.18911 0.1926 1.2536 -3.0156 -10.187 1.1429 5.641 237.54 91.586 170 0.084344 0.89774 0.1668 0.16429 2.5922 -3.8607 -9.6075 1.1017 6.7401 123.68 216.56 171 0.85202 0.1316 0.19256 0.16686 1.1878 -3.0046 -10.56 1.3442 7.3912 389.06 22.542 172 0.38838 0.18377 0.15513 0.21493 1.3441 -3.1384 -10.015 1.0801 5.1351 118.81 184.09 173 0.085109 0.21815 0.13377 0.17292 1.868 -3.6307 -10.338 1.6482 8.6312 74.692 168.9 174 0.97385 0.16997 0.18179 0.16388 0.96591 -3.216 -10.581 5.5253 10.554 395.28 338.42 175 0.98033 0.5781 0.15892 0.12967 1.7293 -3.3332 -10.63 4.2776 12.983 31.891 316.99 176 0.69471 0.20916 0.12876 0.26707 1.3352 -3.6736 -10.162 1.1452 3.1774 180.52 219.72 177 0.2195 0.95555 0.20163 0.045592 0.74502 -3.4606 -10.226 1.6675 7.3099 348.24 152.59 178 0.44044 0.29674 0.14158 0.24225 1.507 -3.9153 -10.521 1.4003 4.6243 390.82 198.56 179 0.53637 0.18607 0.082572 0.10823 0.71592 -1.1148 -10.597 2.0903 8.5282 224.89 365.16 180 0.21493 0.024592 0.15055 0.091297 0.97907 -4.5409 -10.033 1.2357 5.5589 372.43 45.443 181 0.83581 0.12616 0.20355 0.19617 0.98965 -3.2402 -10.251 1.4982 6.1282 57.534 136.02 182 0.14532 0.81391 0.16419 0.13944 1.8493 -3.5703 -9.5983 1.3632 6.1587 25.051 326.63 183 0.73925 0.8359 0.20368 0.14546 1.0133 -1.8463 -10.84 0.80881 1.8179 305.11 123.38 184 0.91963 0.7744 0.23864 0.25804 2.2662 -3.5828 -9.3523 1.4038 5.3787 314.76 157.91 185 0.52856 0.59701 0.18463 0.086432 0.84059 -3.2062 -9.4032 1.6226 6.5072 330.73 54.46 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-8 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 186 0.32825 0.17437 0.23089 0.12394 1.691 -3.4955 -10.57 1.1034 5.5235 351.96 296.52 187 0.80375 0.67066 0.26343 0.1607 1.7672 -2.5861 -9.6591 3.1931 9.5432 161.8 360.73 188 0.76892 0.7972 0.20806 0.23394 0.86958 -3.6122 -10.103 1.145 4.7396 293.68 201.86 189 0.45274 0.052696 0.28832 0.22293 1.9214 -1.1328 -10.347 5.3608 8.4137 359.62 354.89 190 0.12775 0.25773 0.16217 0.11778 1.3804 -2.4795 -9.4334 1.7721 8.3851 28.238 150.99 191 0.030259 0.51272 0.19591 0.19479 0.15589 -3.5969 -10.21 1.2344 7.0844 381.67 275.41 192 0.43598 0.48281 0.14608 0.20493 1.2364 -3.5284 -10.442 1.3869 6.0249 222.79 392.35 193 0.80683 0.31282 0.29252 0.24753 0.8914 -3.7818 -10.525 1.4914 4.0691 197.7 122.39 194 0.98634 0.65179 0.10579 0.23597 1.0463 -4.9046 -10.115 0.029211 6.0052 274.14 209.18 195 0.37937 0.93822 0.19449 0.13212 1.0804 -2.1797 -10.465 1.2632 4.7519 242.74 235.74 196 0.46288 0.50794 0.16731 0.29215 1.593 -3.1837 -9.9573 1.2085 5.1291 178.61 203.67 197 0.57279 0.72439 0.26898 0.11042 0.1268 -2.9724 -10.203 1.4679 6.7437 309.71 84.214 198 0.60957 0.43761 0.17809 0.25562 1.3057 -2.9982 -10.196 1.4713 8.3448 83.824 132.25 199 0.90293 0.36087 0.20795 0.11238 1.3925 -1.9654 -10.234 1.1741 5.5667 277.61 332.46 200 0.10451 0.23312 0.22015 0.068105 0.87763 -2.8445 -9.9863 0.13075 1.9303 164.45 57.659 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-9 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 1 6.1493 3.7076 -0.25613 1875.6 0.90315 1.249 0.14801 0.37912 0.95332 0.49935 0.55136 2 0.13979 2.9947 -0.90495 2066.2 1.1938 0.77885 0.092137 0.47786 0.91792 0.8188 0.97184 3 7.0802 5.5188 -0.04399 1936.2 0.90379 0.77851 0.60439 0.68826 0.66009 0.53068 0.82956 4 6.9144 5.3198 0.89094 1914 3.1598 1.4824 0.41319 0.8772 0.87114 0.76593 0.015416 5 5.4386 3.2889 -1.1703 1846.5 0.90303 1.5138 0.42084 0.42053 0.66879 0.14968 0.65052 6 5.707 3.7543 0.35869 1871.3 0.90329 1.1456 0.016647 0.81447 0.35119 0.19017 0.45259 7 15.582 5.9308 -0.22168 1957.1 3.4966 0.83018 0.54561 0.74242 0.22112 0.6963 0.84463 8 8.0173 5.9057 -1.3916 1895.9 0.90319 1.8458 0.48397 0.53618 0.81963 0.2233 0.06631 9 5.9674 4.076 0.12144 1972.7 0.90359 0.77867 0.20968 0.66388 0.56603 0.72163 0.16671 10 6.1912 5.9646 0.20946 1848.1 3.3813 0.77817 0.35921 0.91146 0.086184 0.26383 0.61428 11 8.0239 5.8593 0.57785 1955.5 3.0428 1.0566 0.25235 0.28583 0.14377 0.33995 0.37274 12 7.2804 4.434 0.978 1908.5 0.96748 2.6259 0.96923 0.38967 0.53011 0.37712 0.87938 13 7.9246 6.2089 -0.44711 1824 1.3524 1.436 0.91852 0.74563 0.60164 0.51425 0.28382 14 6.9083 4.3284 -0.01196 1860.2 0.90381 2.8391 0.061248 0.59919 0.035534 0.42406 0.12351 15 7.6659 4.8564 -0.46491 1901.3 1.0338 1.2741 0.18335 0.93868 0.44241 0.83114 0.66251 16 6.9608 5.7375 0.15593 1789.4 1.5556 2.8528 0.24504 0.23616 0.41568 0.56078 0.24768 17 7.723 6.1141 0.071892 1904.9 0.90311 2.1018 0.56412 0.71879 0.45866 0.6612 0.88127 18 7.4356 5.583 0.089054 1899.8 2.2769 1.4215 0.46985 0.17038 0.36892 0.4337 0.41587 19 15.261 6.4804 -0.2701 2008.9 3.3885 2.2946 0.15415 0.29201 0.926 0.13578 0.10665 20 6.398 5.6174 0.37412 1897.5 1.6537 0.90638 0.93395 0.38039 0.88069 0.83584 0.78477 21 6.5091 5.3612 0.14902 1967 2.8222 1.5622 0.70752 0.19571 0.96397 0.40507 0.072601 22 6.361 4.3835 0.26446 1941.6 2.4794 1.1297 0.89898 0.51774 0.51472 0.44474 0.076803 23 5.4631 3.0854 0.10788 1871.8 2.7048 0.77872 0.11813 0.97456 0.31021 0.6663 0.22816 24 5.6171 3.0148 -1.2654 1913.5 2.9966 0.8072 0.59446 0.50489 0.98748 0.23154 0.36614 25 7.5432 5.9876 -0.20048 1786.8 1.5056 1.554 0.95635 0.59051 0.050116 0.64233 0.45837 26 19.454 5.9545 0.27664 1876.9 0.90357 2.6816 0.74104 0.20259 0.33288 0.00056 0.94328 27 5.5521 4.6393 -0.30598 1905.6 3.2025 1.1549 0.48661 0.5346 0.40274 0.22763 0.38021 28 5.6577 4.1899 -0.34112 1986.6 1.743 2.5966 0.32813 0.3461 0.52155 0.30517 0.35838 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-10 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 29 6.9259 4.8134 -0.1107 1949.3 0.90353 1.2222 0.72812 0.35529 0.48028 0.18916 0.43491 30 6.2501 3.6112 0.61346 1917 0.90384 2.0319 0.57539 0.27621 0.90553 0.61556 0.49737 31 7.9127 8.0006 0.000996 1997.8 3.5195 2.0158 0.67078 0.43256 0.86789 0.37068 0.3227 32 6.8819 5.103 -0.13694 1826.2 2.9475 0.82037 0.63578 0.087969 0.059871 0.013958 0.61861 33 7.5956 4.9153 0.43555 1928.6 3.0686 1.0455 0.32401 0.28237 0.62066 0.27631 0.64255 34 5.8952 3.1641 -0.2913 1938 0.90391 2.405 0.57426 0.17807 0.63746 0.13035 0.049985 35 6.4071 3.8918 -0.05131 1857.7 0.90374 1.7737 0.38832 0.5125 0.7477 0.040306 0.80321 36 6.8402 4.7547 0.76045 1884.8 1.9106 0.77881 0.021301 0.00988 0.32113 0.24313 0.62202 37 7.5056 4.5429 -0.33819 1879.9 0.9031 1.6376 0.85906 0.67081 0.77494 0.5175 0.87397 38 7.0917 6.0084 -0.3587 1821.8 2.5739 1.3567 0.49032 0.78578 0.8421 0.92213 0.69837 39 7.0048 3.2365 -0.40327 1946.6 3.2872 1.7059 0.34929 0.10812 0.86475 0.26755 0.44695 40 6.9305 5.0561 -1.0631 1928.9 3.4907 0.77805 0.23383 0.96955 0.55518 0.21934 0.14791 41 6.6206 4.6125 -0.31852 1977.6 0.90347 0.78696 0.78578 0.67741 0.85998 0.44835 0.56415 42 14.413 8.5213 -0.81469 1867.6 0.90364 1.887 0.79542 0.48809 0.30997 0.68955 0.27574 43 7.0801 4.4074 0.23203 1829.1 2.3007 1.3741 0.054658 0.409 0.65079 0.16031 0.03927 44 6.4178 4.5582 0.42998 1896.6 2.8908 1.5358 0.44201 0.36493 0.58549 0.10303 0.34881 45 6.5805 5.1817 0.025447 1964 1.6772 2.5271 0.90287 0.84512 0.23369 0.88767 0.7561 46 6.7732 4.3508 0.17992 1906.4 0.9037 1.4949 0.76341 0.65504 0.38765 0.92522 0.81075 47 7.8863 5.3757 -0.6572 1839.2 2.7542 1.3217 0.55681 0.080545 0.68236 0.78279 0.68201 48 5.5915 3.1849 0.38826 1849.6 0.90382 1.4538 0.47267 0.5233 0.42106 0.49153 0.4295 49 7.2685 4.1403 0.33525 1887 1.5231 1.4289 0.30719 0.9826 0.97391 0.34844 0.30095 50 8.1591 7.477 0.46714 1907.9 1.9352 1.4188 0.75527 0.79521 0.79124 0.59169 0.94693 51 6.7672 4.4528 0.18511 1919.4 2.3538 1.6967 0.11262 0.78394 0.065009 0.96761 0.93778 52 6.2051 3.8 -0.0048 1843.4 0.90378 2.1284 0.21311 0.45059 0.101 0.87173 0.85482 53 0.001592 2.0902 -0.53103 2040 1.7023 1.7024 0.63397 0.75733 0.63411 0.59665 0.73295 54 7.7203 3.6933 0.48981 1940 2.5819 0.77875 0.74928 0.001434 0.017975 0.15992 0.5667 55 6.4049 3.0945 -0.12414 2075.6 0.90336 1.6481 0.59924 0.8652 0.39361 0.17097 0.78623 56 6.2952 3.7152 -0.19316 1881.2 2.2225 1.0983 0.46359 0.90716 0.64016 0.016186 0.5749 57 7.154 3.5316 -0.02042 1862.5 0.90385 2.182 0.98781 0.7921 0.91338 0.19927 0.20202 58 5.8708 2.9401 -0.26747 2097.2 0.90303 1.6425 0.10519 0.22164 0.62929 0.081447 0.65732 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-11 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 59 6.8836 3.7417 -0.13756 1890.7 3.4252 1.9758 0.16734 0.57493 0.6155 0.97189 0.060699 60 7.927 6.0964 -1.3759 1794.2 2.1267 1.3454 0.75226 0.55725 0.82696 0.85085 0.68955 61 7.6493 4.5099 -0.25796 1816.9 1.789 0.77828 0.20405 0.61318 0.76903 0.7736 0.5395 62 8.144 5.6387 -0.44055 1865.6 0.90313 1.6613 0.26243 0.87413 0.71708 0.71988 0.053525 63 5.7201 3.568 0.22399 1974.2 1.7265 0.86279 0.94684 0.43978 0.19613 0.63319 0.52571 64 7.8152 7.7093 -0.98719 2025.1 0.90356 2.794 0.088359 0.48033 0.84602 0.86047 0.96369 65 5.4064 3.8242 0.40448 1662.6 1.995 0.88188 0.19983 0.046866 0.94455 0.35625 0.19656 66 6.8026 1.7728 -0.45796 1930.3 1.967 0.77896 0.69036 0.15279 0.70221 0.95827 0.098062 67 6.1203 4.121 0.02024 1931.6 0.90386 0.77816 0.72359 0.12183 0.58056 0.039986 0.54263 68 7.5772 6.7573 -0.10442 1940.9 2.2592 2.2193 0.073801 0.96441 0.44882 0.88064 0.59544 69 6.2977 3.065 -0.23475 1963.3 2.7847 1.2303 0.97696 0.20797 0.084584 0.57374 0.70334 70 7.6321 5.7935 -0.03985 1780.6 3.5667 0.79181 0.7142 0.26741 0.78112 0.79843 0.88713 71 7.1083 4.7049 -0.35404 1952.3 0.91759 0.98496 0.99908 0.803 0.59694 0.31095 0.11612 72 5.6574 3.1777 0.04461 1852.1 0.90392 1.7219 0.45309 0.23211 0.34683 0.29814 0.033845 73 7.5767 5.1335 0.09073 1990.3 1.1033 1.4748 0.61349 0.70253 0.6485 0.95109 0.83954 74 6.7295 5.041 0.036364 1869.4 1.3657 1.2939 0.40039 0.22715 0.12556 0.84679 0.92907 75 5.6064 3.6735 0.32454 1947.8 2.1186 1.2692 0.13788 0.64172 0.39798 0.84111 0.76703 76 6.5068 4.3706 0.42735 1850.1 3.5552 1.1377 0.93568 0.052459 0.43316 0.27091 0.95719 77 8.0066 6.1562 0.39433 1883.3 2.1891 2.4279 0.036244 0.31983 0.85241 0.099715 0.98777 78 6.9771 4.9488 0.446 1977 0.90318 0.77863 0.52811 0.32228 0.69329 0.5458 0.17655 79 6.5367 3.7835 -0.84437 2036.5 3.0898 2.3931 0.23949 0.58398 0.51926 0.15459 0.62762 80 6.5752 3.3485 -0.29877 1968.9 2.9533 1.5442 0.79325 0.8985 0.93623 0.053707 0.48373 81 7.0924 3.2418 -0.70629 1962.3 0.9032 1.288 0.49932 0.12507 0.89771 0.82865 0.54536 82 6.8652 3.6377 -0.02764 1969.6 1.2058 1.7129 0.33092 0.65045 0.69902 0.23748 0.72851 83 7.3348 5.4404 -0.20594 1760 3.6174 1.5253 0.92293 0.72545 0.89401 0.91693 0.47477 84 6.8026 5.7136 -0.07956 2004.7 0.90395 1.1809 0.36004 0.035625 0.67331 0.77605 0.8152 85 7.085 3.85 -0.73072 1903 2.5396 2.4615 0.10302 0.13938 0.2868 0.79406 0.9918 86 6.8698 4.1013 -0.59536 1922.1 3.4561 1.4602 0.4156 0.099152 0.46067 0.50898 0.35323 87 7.4268 5.2303 0.4476 1909.9 2.9123 2.566 0.88833 0.71028 0.55161 0.029548 0.60303 88 6.8131 4.6657 0.92386 1840.5 1.3934 1.7451 0.33803 0.99092 0.099285 0.11672 0.40881 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-12 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 89 8.1135 5.1499 -0.37491 1900.3 0.90326 1.2421 0.31854 0.46209 0.3012 0.5016 0.12874 90 7.596 6.2424 0.35281 1916.2 0.90397 0.77889 0.68696 0.76919 0.80317 0.94606 0.006143 91 5.503 3.3187 0.12577 1959.2 0.90339 1.0995 0.12672 0.92108 0.75997 0.99265 0.79816 92 18.034 6.2536 0.035734 1882.1 1.6093 0.77841 0.89491 0.92686 0.50891 0.30263 0.52301 93 5.9194 3.0336 0.062279 1942.7 0.90349 1.7296 0.029419 0.54533 0.97505 0.76008 0.082954 94 7.8762 5.3551 -0.08548 1993.1 0.90389 1.7347 0.004466 0.7771 0.81418 0.60279 0.77636 95 6.7676 4.4996 0.33088 1934.2 0.90367 0.779 0.27625 0.75346 0.94982 0.73642 0.92474 96 6.2249 3.3144 -0.46538 1815.1 3.5953 2.3636 0.50903 0.54324 0.52673 0.1679 0.64838 97 6.0388 2.7715 0.11734 1845.5 2.6544 1.0609 0.86021 0.61537 0.43719 0.29445 0.4137 98 5.4833 2.9698 0.84905 1994.9 1.2393 1.5103 0.53499 0.73858 0.54758 0.28177 0.71001 99 6.0469 2.608 -0.07007 1925.1 0.90337 1.4681 0.31493 0.44407 0.026816 0.41548 0.26677 100 7.0153 5.4693 0.7169 2131.4 1.3278 0.77801 0.37156 0.39791 0.34029 0.046676 0.71905 101 7.562 5.2438 0.53172 1863.9 1.8433 1.2537 0.52369 0.89111 0.72414 0.94363 0.97783 102 6.3275 4.8416 0.056803 1958.2 2.6805 1.3798 0.92714 0.1456 0.15558 0.32354 0.57921 103 6.3913 5.1183 0.9123 1809.1 3.6533 1.0224 0.61812 0.30333 0.26082 0.39232 0.38884 104 6.3176 4.0453 -0.16064 1765.8 0.9403 2.5396 0.66785 0.29726 0.31575 0.71377 0.40333 105 1.8792 3.8256 -0.43173 2012.3 2.3309 1.5695 0.88151 0.50933 0.15264 0.36659 0.76274 106 6.1733 4.26 -0.22998 2019.2 2.8064 1.0266 0.22383 0.85892 0.002543 0.12428 0.23763 107 7.4244 4.316 0.41343 1981.6 0.98874 1.5407 0.30208 0.62662 0.74214 0.43735 0.50232 108 6.7656 4.1715 0.14963 1917.9 3.6802 1.5234 0.8293 0.57726 0.96774 0.078148 0.29635 109 7.1081 3.9256 0.104 1812 2.9781 1.0732 0.22898 0.49888 0.36227 0.80137 0.026276 110 5.716 3.2754 0.30823 1873 3.3533 0.7781 0.5898 0.88117 0.18919 0.96142 0.73885 111 5.5159 1.9335 0.047852 1991.6 3.2485 1.0785 0.55213 0.70952 0.48706 0.97908 0.25633 112 6.1179 4.7172 0.070586 1904.1 1.4289 1.6676 0.033208 0.42755 0.76087 0.81213 0.74691 113 7.4123 5.639 0.29412 1923.5 1.018 1.7611 0.12009 0.49013 0.49325 0.067976 0.15316 114 16.09 6.1433 0.40963 2000 0.90369 0.77822 0.069784 0.93143 0.33687 0.70245 0.63608 115 5.7307 3.6202 0.82416 1923.8 0.90344 1.4409 0.013986 0.63208 0.57667 0.39511 0.51207 116 5.5766 3.8772 -0.05986 1892.8 1.4837 0.85576 0.87464 0.021304 0.83896 0.45149 0.21883 117 5.4557 3.4754 -0.055 1944.8 1.0634 0.77891 0.16343 0.15549 0.32769 0.80689 0.95205 118 10.416 6.8428 0.52583 1935.9 0.90322 2.7216 0.8338 0.60597 0.1746 0.60799 0.53258 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-13 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 119 7.7888 6.0854 0.59735 1803.9 0.90352 1.6841 0.25947 0.3505 0.13133 0.69187 0.46983 120 14.987 5.5024 -0.28378 1889.1 0.90351 2.1477 0.17971 0.01696 0.12417 0.65725 0.21304 121 6.5408 3.9942 0.25196 1933.7 0.90341 1.5891 0.3682 0.32693 0.14919 0.82472 0.49172 122 10.671 5.3934 0.80396 2022.8 0.90395 2.5036 0.26875 0.30965 0.53749 0.75493 0.63438 123 5.8361 4.5879 0.017479 2045.4 3.0164 2.7454 0.60795 0.21768 0.77931 0.20398 0.16495 124 7.1499 5.6726 0.34544 2019.8 2.4344 1.9289 0.18763 0.16686 0.20988 0.5691 0.58279 125 7.6797 8.1239 0.096832 1842.8 2.5249 1.5968 0.98125 0.76469 0.2517 0.3173 0.85904 126 5.932 3.5889 0.28785 1832.8 2.4076 1.5787 0.39829 0.95212 0.034587 0.52336 0.1135 127 6.7048 5.0797 0.17443 1981 1.2767 1.6157 0.056255 0.90495 0.98011 0.48855 0.91575 128 7.5849 5.2913 -0.12699 1835.2 1.5866 1.3035 0.87817 0.94688 0.25589 0.33424 0.20698 129 7.212 3.9432 0.1424 1798.4 1.7706 1.7714 0.47718 0.47024 0.19356 0.55568 0.55688 130 7.831 5.1913 -0.31069 1720.1 3.1815 2.2739 0.95338 0.39089 0.73424 0.72894 0.50726 131 8.0972 7.2211 0.64357 1965.9 0.90343 1.116 0.69971 0.58612 0.92169 0.67742 0.27223 132 7.6639 5.7891 -0.2927 1985.9 0.90305 1.5025 0.1319 0.56659 0.26685 0.90542 0.13879 133 8.0294 5.5701 0.36393 1938.8 1.3017 1.6536 0.90639 0.66534 0.7532 0.2594 0.31207 134 6.2922 3.5566 -0.18177 1961 3.4344 1.1616 0.24114 0.94237 0.65911 0.34417 0.28603 135 6.7919 4.9812 -0.11658 1859.2 0.90309 1.0038 0.042086 0.3139 0.012702 0.70527 0.89991 136 6.9603 4.733 0.67106 2061.5 0.90365 0.93824 0.43459 0.98723 0.17691 0.36239 0.39637 137 5.9763 4.7807 -0.0749 1892.1 1.4591 1.6802 0.8406 0.24623 0.24321 0.74055 0.34012 138 5.8133 4.1604 0.20124 1927.6 0.90399 2.8913 0.4496 0.73276 0.79884 0.86859 0.29014 139 7.209 3.3904 0.34952 1756 1.1114 2.2309 0.85058 0.013066 0.70983 0.98059 0.4625 140 10.967 6.066 -0.23887 2084.8 2.1687 1.4077 0.19363 0.91877 0.57169 0.062484 0.59253 141 6.5514 5.0181 0.28548 1915.2 2.1627 1.96 0.81428 0.213 0.23506 0.62553 0.8923 142 6.4987 3.5084 -0.21553 2033.8 1.5521 2.7681 0.28203 0.030125 0.99984 0.93706 0.43827 143 5.6205 2.9164 -1.4733 2007.2 0.90372 1.0108 0.78117 0.1124 0.90435 0.68037 0.00137 144 15.631 5.7692 0.13213 1920.1 0.90361 1.478 0.45778 0.62244 0.20289 0.1124 0.67711 145 6.5031 5.0007 -0.37782 1782.1 3.6308 1.3834 0.54002 0.83238 0.54177 0.059496 0.055209 146 7.3723 4.2696 -0.17206 1856.2 1.4484 1.7392 0.58368 0.82026 0.49892 0.93132 0.8671 147 5.9872 3.4647 0.46085 1874.5 2.7317 1.1979 0.28947 0.064219 0.008741 0.086082 0.042408 148 7.4014 5.6886 -0.32636 2010.9 2.048 1.5757 0.83873 0.18767 0.45303 0.24793 0.17381 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-14 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 149 5.9334 3.358 0.16814 1861 3.7102 1.4905 0.71606 0.45623 0.60712 0.106 0.8472 150 7.5823 4.8848 -0.36515 1955.4 0.90362 1.5925 0.772 0.25397 0.046208 0.35463 0.7418 151 7.765 6.2909 0.24095 1887.6 0.9033 1.0412 0.99159 0.37394 0.16138 0.8983 0.33576 152 6.8184 4.6906 -0.16259 1876 0.92863 1.8934 0.078416 0.26234 0.47477 0.41185 0.8627 153 10.24 6.0373 0.080839 1950.4 0.90306 0.95402 0.37664 0.16391 0.072875 0.20549 0.98379 154 0.55423 3.1138 -0.1468 1801.7 0.90376 1.3353 0.67507 0.85191 0.56233 0.91132 0.77248 155 5.3984 2.9881 -0.18609 1852.6 2.0553 1.7596 0.64711 0.24118 0.78982 0.14203 0.022912 156 7.4192 4.4159 0.23382 1946.4 0.90324 1.3632 0.29059 0.11742 0.16658 0.5841 0.33087 157 1.2752 3.9764 -0.34614 1932 3.2184 0.77879 0.21752 0.56409 0.37232 0.071179 0.086622 158 5.5865 3.9088 0.38434 1818.8 1.876 0.92785 0.40653 0.028803 0.093443 0.45984 0.90492 159 16.91 5.8988 -1.1077 1823.5 2.4529 1.8267 0.09683 0.8887 0.99051 0.28945 0.44384 160 5.3907 2.9297 0.29815 1921.2 3.3049 1.6886 0.77907 0.84141 0.82286 0.40239 0.14267 161 7.9461 5.8762 -0.39788 1805.6 1.0831 0.77834 0.94128 0.067398 0.59004 0.87679 0.1026 162 7.0477 3.1286 -0.47182 1748.7 1.8898 1.085 0.73848 0.27179 0.11254 0.033604 0.25055 163 6.6373 4.2243 -0.42075 1943.2 2.0836 0.77865 0.5124 0.090902 0.29907 0.78995 0.93382 164 5.7946 4.965 -0.27865 1979 2.3667 0.77856 0.65853 0.044761 0.71303 0.009268 0.13014 165 6.0033 3.2186 -0.21132 1975.6 3.1379 0.94558 0.42716 0.99581 0.93247 0.63505 0.79472 166 6.7439 5.457 -0.38635 1954 0.90328 1.5573 0.80914 0.14267 0.18078 0.46381 0.36175 167 7.0064 3.4989 -0.03073 1830.6 1.1302 1.6278 0.97148 0.19133 0.83382 0.54465 0.22192 168 6.3715 2.5263 -0.48095 1831.6 0.903 1.2828 0.86946 0.419 0.13968 0.55282 0.99942 169 6.2635 3.4 0.21954 1999.3 0.99714 0.8477 0.34431 0.073091 0.68898 0.89467 0.4245 170 14.659 8.659 0.45565 1814.2 2.6418 1.1898 0.68117 0.33547 0.40532 0.90013 0.91304 171 6.5549 4.4726 0.16509 1893.7 2.401 1.1109 0.70351 0.69854 0.72757 0.98757 0.75225 172 6.1013 5.7161 -0.15267 1983.3 1.2186 1.4499 0.81611 0.25826 0.61445 0.46792 0.90571 173 7.5434 5.527 0.20554 2050.5 2.6047 2.3379 0.76866 0.058454 0.21765 0.58804 0.3155 174 8.2794 4.0664 0.96462 1911.2 2.7415 0.89771 0.082041 0.40006 0.060625 0.38108 0.96639 175 7.9979 4.2885 0.31596 1894.7 0.90325 1.6091 0.91047 0.82838 0.88732 0.99868 0.18895 176 6.8041 6.0221 -1.2186 1776.4 3.2702 0.7785 0.66477 0.46953 0.042516 0.62485 0.48731 177 6.6767 4.7963 -0.09508 1855.9 2.0157 0.88506 0.96164 0.33283 0.29031 0.47929 0.60973 178 6.4386 2.255 -0.45186 1988.5 2.8606 0.77832 0.006732 0.52745 0.28427 0.74792 0.23012 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-15 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 179 7.141 5.5461 0.006338 1837.4 0.90374 0.77859 0.15811 0.55268 0.023901 0.18067 0.47559 180 7.8443 6.2661 0.37781 1899.1 2.8672 1.3971 0.62791 0.36613 0.37716 0.25127 0.19465 181 7.0736 4.9344 0.27154 1926.4 1.6385 0.77808 0.84643 0.60261 0.079115 0.17635 0.72495 182 6.7374 1.996 -0.39143 1880.1 1.822 2.081 0.53641 0.4478 0.35914 0.38798 0.014873 183 5.5053 3.436 0.47384 2052.7 2.5136 1.3331 0.43998 0.95684 0.41408 0.21347 0.83035 184 16.604 6.1784 0.70686 2016.2 0.90358 1.3131 0.82124 0.41314 0.95968 0.61257 0.39318 185 7.3825 6.1914 -0.94859 2028.7 0.90389 1.2114 0.14096 0.86368 0.87878 0.73015 0.824 186 6.3639 3.4209 0.3194 1970.8 1.8143 1.6253 0.17332 0.83925 0.42664 0.75893 0.18395 187 7.7803 5.8127 -0.42838 1853.7 1.1646 2.6512 0.29535 0.6393 0.2468 0.32991 0.2443 188 7.3968 5.3167 -0.40788 1889.8 1.2623 1.2132 0.62056 0.077406 0.27678 0.12604 0.51919 189 8.0923 5.8459 -0.0098 1878.8 0.90314 1.1667 0.27374 0.81653 0.73931 0.52789 0.26466 190 7.4329 5.2743 0.42213 1912.5 0.90346 0.77845 0.80183 0.10476 0.10591 0.85939 0.80646 191 6.1279 4.0069 -0.09548 1868.6 1.4057 1.3999 0.50392 0.80569 0.22811 0.023383 0.32794 192 6.3392 4.6196 -0.41476 2003.6 3.3367 1.791 0.64456 0.1335 0.21443 0.53591 0.66755 193 6.1161 4.8803 -1.3166 1866 0.90332 0.7784 0.73013 0.97535 0.38237 0.67251 0.69203 194 0.30637 2.8997 0.24466 1735.4 1.9855 1.6741 0.38362 0.34451 0.67767 0.42816 0.70837 195 5.4753 2.3675 -0.24962 1768.8 0.90341 1.6045 0.51658 0.77213 0.27475 0.48303 0.58716 196 7.3568 5.2147 -0.176 1795.8 1.3102 0.9639 0.35128 0.64598 0.11775 0.64953 0.3061 197 6.8571 4.5789 -0.33088 1836.8 0.90334 1.7525 0.56869 0.694 0.50191 0.4735 0.6721 198 7.1083 4.0231 0.77472 1951.9 1.152 0.99489 0.39476 0.72323 0.46947 0.57942 0.092109 199 6.6074 5.4246 0.25766 1885.4 2.2515 1.178 0.65197 0.18141 0.47965 0.65273 0.37658 200 6.1683 4.2044 0.19183 1910.7 3.1226 0.77824 0.046482 0.68272 0.80814 0.091389 0.15855 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-16 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 1 0.92233 0.25505 0.74124 15.158 1.313 191.85 170.3 90.304 87.115 4.2804 2 0.95718 0.43026 0.82308 5.231 1.996 438.05 321.83 296.2 128.74 4.5635 3 0.39566 0.78442 0.12747 7.789 1.8919 315.77 508.4 96.723 102.66 4.6501 4 0.83861 0.26775 0.71883 8.064 1.8993 823.19 978.39 33.548 93.633 4.8718 5 0.52003 0.57509 0.094709 6.281 2.5643 875.12 769.2 55.826 102.81 3.7980 6 0.40076 0.96621 0.9459 9.449 2.1515 789.01 900.47 58.053 74.556 5.1715 7 0.094518 0.093636 0.46901 4.946 2.6278 786.48 844.16 100.7 111.5 4.5060 8 0.32186 0.17194 0.84957 5.365 1.8634 865.84 827.29 63.628 76.41 5.8273 9 0.30145 0.85606 0.16371 15.893 2.2814 364.19 527.36 120.34 112.2 5.5088 10 0.57727 0.11274 0.96106 7.689 1.4344 797.1 251.58 98.732 110.55 4.1104 11 0.74875 0.15598 0.086856 1.125 2.1713 322.86 935.95 108.93 141.46 3.9581 12 0.6884 0.20431 0.40849 9.047 1.3276 366.98 176.25 115.46 97.821 4.6365 13 0.11426 0.97927 0.80415 0.968 3.3988 237.1 459.82 125.54 115.14 5.0327 14 0.077847 0.038325 0.39857 4.660 1.8369 892.57 306.82 99.777 89.356 4.7745 15 0.47977 0.67091 0.53651 2.573 2.1315 342.82 722.33 47.92 94.597 4.9787 16 0.56804 0.91726 0.52864 5.602 2.5869 947.77 592.07 124.29 126.95 5.8763 17 0.97516 0.75352 0.96649 4.996 1.738 277.76 398.99 108.06 98.209 5.0810 18 0.22547 0.098027 0.27507 1.676 2.8558 181.8 804.65 109.59 83.384 3.7712 19 0.11894 0.90477 0.51826 1.077 1.7207 169.97 229.43 106.12 94.169 3.9250 20 0.44268 0.65648 0.4869 3.141 2.2336 382.72 520.65 109.97 87.421 3.6536 21 0.86671 0.87858 0.86223 3.002 1.8704 915.02 368.66 96.453 125.67 4.1820 22 0.37889 0.51061 0.8531 4.304 1.4624 483.89 143.12 169.19 103.75 5.6731 23 0.18952 0.45367 0.61803 4.741 0.83082 357.62 604.77 109.04 115.5 5.3456 24 0.77685 0.032638 0.93762 3.898 1.5078 839.57 137.68 95.04 101.48 5.6393 25 0.48162 0.79486 0.64681 3.671 1.8783 901.9 765.48 96.029 101.76 4.9227 26 0.67481 0.28202 0.28096 2.710 2.2218 749.18 638.22 124.09 116.2 4.1439 27 0.016023 0.91494 0.79437 15.809 0.67777 386.2 670.05 268.23 156.79 3.9292 28 0.48515 0.29132 0.2558 5.676 1.7298 728.67 595.11 48.879 87.909 4.7882 29 0.31677 0.86088 0.87083 1.401 3.1006 710.85 801.34 223.13 124.07 5.5724 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-17 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 30 0.47158 0.95708 0.22766 9.231 1.3287 578.95 287.2 103.57 106.62 4.5271 31 0.87638 0.25117 0.35533 13.125 2.1624 600.92 550.08 95.733 92.572 4.4803 32 0.84049 0.75826 0.066926 4.410 1.385 205.98 336.68 44.124 82.144 4.3017 33 0.79945 0.36122 0.71376 4.877 2.6009 269.1 816.16 26.919 75.323 4.2503 34 0.087804 0.8988 0.88781 2.241 2.7057 525.12 994.94 89.955 77.693 3.8711 35 0.73521 0.77603 0.2629 1.957 2.0292 927.46 543.12 121.2 91.276 4.8427 36 0.28329 0.060343 0.24624 17.711 3.0503 172.61 355.55 70.693 76.655 4.9358 37 0.82935 0.82288 0.070104 2.402 1.9786 920.22 181.29 52.094 74.015 4.6561 38 0.042963 0.33111 0.15903 1.183 1.4821 829.07 374.93 117.73 93.13 4.5549 39 0.85708 0.73262 0.89719 3.329 1.9402 293.68 894.64 98.184 107.62 4.0871 40 0.60087 0.72999 0.42689 10.239 2.6368 906.51 560.1 129.16 105.03 3.2589 41 0.49271 0.10448 0.77958 2.445 2.3116 231.07 691.6 99.503 85.243 3.8497 42 0.64192 0.96389 0.50726 2.844 2.2754 944.28 158.05 100.71 95.463 5.5640 43 0.2041 0.71481 0.94157 7.315 2.1155 968.83 620.16 127.49 100.21 4.9771 44 0.18387 0.27955 0.6511 3.041 2.3907 152.04 292.65 104.9 84.399 5.5546 45 0.98648 0.43556 0.40458 0.417 2.7365 900.41 774.39 93.399 121.6 5.6584 46 0.23594 0.70606 0.097513 4.133 2.3716 724.12 192.57 123.5 105.44 4.6247 47 0.9144 0.46205 0.26876 1.828 2.0254 257.4 617.25 101.5 108.69 5.0652 48 0.63216 0.56861 0.30615 4.532 1.1684 696.14 654.18 108.09 121.87 5.4658 49 0.51583 0.8261 0.74634 1.277 2.1974 850.09 213.01 68.76 99.02 4.5905 50 0.8528 0.83683 0.2883 6.354 2.0765 249.14 868.01 120.19 90.383 4.4906 51 0.53245 0.42635 0.90682 18.841 2.7894 636.37 916.94 31.245 96.036 4.3295 52 0.3125 0.12124 0.18823 3.581 1.7479 228.58 660.12 119.08 108.23 5.5882 53 0.79448 0.99326 0.38079 0.862 2.1889 308.05 927.64 127.89 111.08 5.7803 54 0.2736 0.41402 0.75965 0.664 0.46339 756.15 726.75 121.96 80.495 4.9715 55 0.82136 0.94926 0.57277 3.463 0.97016 506.62 873.56 111.78 96.438 5.6818 56 0.24226 0.47853 0.65891 9.264 2.3606 799.26 884.41 123.18 87.709 4.9327 57 0.30565 0.31586 0.63843 13.715 1.6016 999.94 681.02 118.62 89.156 4.4186 58 0.87226 0.30481 0.23333 4.827 0.25367 431.79 571.3 92.604 97.251 4.3427 59 0.34771 0.81349 0.55574 2.905 2.5133 652.12 480.85 52.708 92.983 5.9321 60 0.53539 0.18244 0.43489 0.078 0.93803 966.49 813.06 108.88 96.181 4.9131 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-18 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 61 0.69358 0.072783 0.20895 6.208 2.2049 327.18 326.07 113.29 109.16 4.9928 62 0.37424 0.005167 0.43543 3.770 2.1004 773.99 539.24 61.532 88.724 5.1110 63 0.80636 0.65482 0.62131 4.271 1.5823 802.08 319.46 93.79 70.915 5.6913 64 0.95066 0.54284 0.91978 12.312 2.4195 348.42 276.85 82.819 97.502 5.6667 65 0.94153 0.97469 0.057611 14.551 1.4013 765.3 746.99 64.415 83.784 5.6949 66 0.38226 0.048251 0.4617 13.256 3.199 105.66 821.22 96.256 89.718 5.4470 67 0.62941 0.61653 0.38797 8.296 1.7649 512.22 908.36 126.18 127.89 5.4320 68 0.56358 0.98803 0.62566 4.697 1.6497 597.5 255.95 113.55 99.808 5.3808 69 0.753 0.13847 0.19972 2.381 1.0524 411.65 757.85 47.151 102.43 4.5852 70 0.41038 0.61048 0.47687 3.750 4.5701 628.82 652.53 107.02 114.16 3.9909 71 0.50596 0.76298 0.75346 4.791 2.553 777.39 630.04 128.15 117.51 5.3169 72 0.35308 0.58728 0.83407 11.250 1.49 501.84 854.87 100.54 101.63 4.7010 73 0.72002 0.84202 0.17657 10.774 1.6344 806.66 134.47 101.57 109.6 4.7159 74 0.14626 0.68295 0.07776 4.085 1.619 813.08 740.3 105.18 104.64 4.2315 75 0.066744 0.38841 0.026305 12.916 1.7716 145.68 396.12 111.4 124.17 5.4556 76 0.40925 0.42092 0.041884 1.901 2.9928 912.04 342.71 126.98 113.06 4.6658 77 0.75816 0.63356 0.19002 0.972 2.0748 683.34 714.72 16.105 69.555 4.9426 78 0.17325 0.53555 0.79986 11.716 0.036259 271.18 756.88 127.94 103.52 4.6721 79 0.17749 0.08885 0.50064 0.735 1.2689 759.01 860.64 110.31 118.45 4.5498 80 0.65533 0.31436 0.13959 0.533 2.8701 372.36 364.79 16.123 81.2 4.3902 81 0.13682 0.5298 0.543 1.222 0.793 355.91 752.04 107.09 108.04 5.8997 82 0.34247 0.32268 0.29273 14.707 2.135 420.4 302.23 169.79 117.2 5.3603 83 0.8816 0.1638 0.004696 3.298 2.5754 477.61 687 115.38 138.11 4.8906 84 0.021631 0.93282 0.034844 0.496 1.6476 576.68 738.93 120.33 95.649 4.5763 85 0.36704 0.28987 0.33286 2.052 1.8058 215.64 664.61 111.45 100.39 5.5779 86 0.49834 0.98297 0.2155 2.143 2.2666 962.97 313.04 110.97 110.15 5.4691 87 0.26303 0.59693 0.14617 2.230 3.1643 137.62 695.13 299.14 109.9 5.3922 88 0.77494 0.5598 0.64268 13.897 3.326 343.39 381.16 117.26 73.277 5.6234 89 0.29397 0.38192 0.4223 3.828 3.2587 982.55 430.74 112.79 103.68 5.3744 90 0.89941 0.35616 0.44701 0.593 1.22 568.32 573.95 116.53 130.47 5.6770 91 0.76656 0.80189 0.45487 4.908 1.962 118.83 126.83 110.22 131.81 5.6881 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-19 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 92 0.63929 0.74595 0.53056 2.347 1.3698 333.02 989.47 120.59 99.181 4.2700 93 0.86447 0.92068 0.66988 2.098 2.24 559.88 344.58 128.29 119.99 5.6460 94 0.9357 0.50364 0.31131 1.976 3.4595 424.79 512.48 81.96 98.194 4.9060 95 0.35996 0.37754 0.98715 12.749 1.7585 199.83 416.67 214.97 120.86 3.7339 96 0.99924 0.64932 0.6606 0.800 0.41495 134.12 114.86 237.13 110.95 3.5904 97 0.28863 0.35212 0.36658 2.730 1.6868 102.1 795.33 102.76 81.501 5.1375 98 0.99314 0.34661 0.10037 0.647 3.0595 318.89 309.2 99.114 93.699 4.4413 99 0.42653 0.23963 0.037187 7.917 1.417 873.02 402.88 90.315 85.688 5.8433 100 0.33084 0.79766 0.17138 7.995 1.2469 583.6 247.25 108.06 107.42 5.6115 101 0.42259 0.22354 0.7233 3.626 1.7033 713.27 211.67 53.206 85.996 4.8792 102 0.84776 0.62524 0.73714 4.336 2.6104 284.91 941.27 93.82 97.341 4.7655 103 0.057725 0.36634 0.76158 12.561 1.2976 633.5 464.4 69.486 105.78 4.8590 104 0.96879 0.47187 0.13328 1.373 0.89703 691.48 731.85 46.285 77.453 4.4407 105 0.7066 0.37193 0.57744 4.452 1.4986 679.35 502.4 103.07 90.736 3.9455 106 0.2104 0.71681 0.99385 9.661 1.93 718.95 370.31 92.207 106.78 5.9834 107 0.032139 0.30865 0.35219 0.770 2.4818 958.73 102 92.673 95.276 5.5449 108 0.78493 0.55127 0.23633 3.241 1.91 465.56 857.75 96.317 123.31 5.4404 109 0.54848 0.08343 0.68564 2.518 2.4269 618.97 536.05 99.752 113.53 4.9968 110 0.96153 0.89494 0.54785 6.785 0.337 854.01 921.47 100.86 107.96 5.7257 111 0.62488 0.044425 0.91427 3.854 1.6652 981.82 472.75 91.209 95.83 4.7466 112 0.69681 0.85203 0.92816 6.698 1.5314 165.82 830.4 124.37 114.99 4.8282 113 0.52809 0.86964 0.70423 1.461 2.0875 647.98 162.04 127.06 120.16 4.5992 114 0.61818 0.58153 0.80775 2.611 1.6168 519.13 930.53 108.83 84.747 5.6487 115 0.46203 0.41723 0.31862 3.167 1.123 937.13 195.45 99.599 96.639 3.8759 116 0.20919 0.33963 0.49977 10.959 1.8505 292.87 785.6 106.33 79.1 4.9638 117 0.39316 0.84877 0.86639 1.510 2.3377 221.66 466.18 96.406 94.934 4.7551 118 0.51324 0.69222 0.84208 10.391 2.0452 845.4 791.83 80.688 72.275 4.9250 119 0.50401 0.18607 0.37533 9.622 2.6881 730.58 236.97 58.767 79.498 5.8599 120 0.97274 0.72227 0.32996 8.551 2.0178 702.2 441.76 23.371 85.839 3.6388 121 0.90393 0.76623 0.69825 1.537 2.2099 124.07 120.97 129.61 115.89 5.9687 122 0.16682 0.90667 0.3208 2.812 1.1146 887.34 601.3 101.88 89.549 4.9881 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-20 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 123 0.88685 0.78667 0.33837 3.377 1.8277 594.89 487.94 99.719 100.93 4.6396 124 0.93377 0.88469 0.049508 14.072 0.54525 389.24 983.39 96.849 102.08 5.2270 125 0.8012 0.49335 0.59546 3.433 2.979 480.65 433.28 97.548 81.699 4.8332 126 0.27749 0.078469 0.90494 8.195 1.963 547.81 265.01 111.24 112.29 3.7221 127 0.15151 0.11629 0.56557 5.101 2.4552 178.03 424.58 108.54 135.4 4.8871 128 0.23227 0.66062 0.60165 4.047 2.6825 264.86 331.56 127.96 108.46 5.4989 129 0.55875 0.88816 0.47306 16.849 2.1129 528.17 486.76 23.377 98.536 5.5355 130 0.2558 0.46514 0.20482 4.371 1.9442 862.28 297.69 119.44 112.74 5.5138 131 0.98325 0.44402 0.78375 1.879 2.0021 196.29 493.03 104.65 109.29 4.8069 132 0.70346 0.6861 0.51445 2.790 2.6619 933.76 608.58 106.59 86.628 5.2099 133 0.43036 0.74351 0.67275 2.993 2.3754 113.09 563.74 108.84 92.665 4.8474 134 0.59479 0.24391 0.18118 2.673 2.8191 611.49 703.65 17.447 92.329 3.4887 135 0.029181 0.54944 0.44236 7.478 3.5157 554.31 284.02 19.775 100.62 5.6529 136 0.29642 0.40806 0.16692 4.512 2.9033 660.81 166.35 91.784 87.352 3.8309 137 0.71369 0.59312 0.59332 3.694 3.0078 515.99 578.66 50.496 86.272 3.4490 138 0.91854 0.19074 0.63055 3.529 3.307 140.74 648.08 123.04 96.886 4.9556 139 0.45967 0.51566 0.95385 7.008 1.676 664.82 585.21 85.754 94.293 4.8637 140 0.25344 0.93944 0.52473 10.442 1.5508 336.3 476.3 112.83 116.62 4.9499 141 0.099923 0.80992 0.89486 3.231 1.1519 995.02 449.12 93.917 93.336 4.8208 142 0.24977 0.13496 0.98272 10.658 2.4377 394.86 674.88 118.52 132.7 5.7715 143 0.036624 0.20762 0.24422 4.612 3.5447 304.25 234.78 116.07 124.91 4.1553 144 0.051719 0.26209 0.006894 8.680 1.5218 879.45 947.05 119.99 113.85 5.3273 145 0.57483 0.63694 0.58037 9.901 2.1419 442.83 152.68 12.842 88.442 5.5179 146 0.41881 0.15465 0.36144 2.311 1.8391 410.47 719.9 101.76 93.923 5.9539 147 0.22244 0.14066 0.14225 7.603 2.0595 827.17 889.36 116.49 104.14 5.2782 148 0.68188 0.19518 0.10796 3.925 2.6459 300.53 634.47 118.02 91.116 3.9851 149 0.72764 0.10513 0.88462 1.599 2.5012 891.05 390.81 66.221 78.156 5.4854 150 0.43902 0.44513 0.11251 5.203 1.2316 241.1 546.37 105.69 110.49 4.8009 151 0.83171 0.60065 0.25367 4.160 2.3044 186.78 223.17 26.465 91.677 5.7046 152 0.21903 0.05082 0.99545 1.323 1.7878 624.78 842.01 104.69 98.913 5.4203 153 0.73195 0.12708 0.83865 1.791 2.8058 783.67 956.27 104.7 102.2 4.4565 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-21 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 154 0.6762 0.029674 0.77487 6.511 1.1833 988.97 531.89 112.04 104.21 5.4115 155 0.15591 0.40127 0.2951 3.088 0.99647 454.6 912.9 118.23 84.029 5.5970 156 0.65336 0.16679 0.45652 16.213 1.0783 488.62 243.89 100.77 82.78 4.4704 157 0.78953 0.64082 0.81817 2.941 2.4897 815.64 679.99 100.08 103.24 4.6806 158 0.92559 0.17548 0.58945 16.672 2.3218 456.58 186.9 47.529 97.876 4.0638 159 0.6146 0.60552 0.56322 1.685 0.70349 212.34 996.89 40.481 84.26 5.8121 160 0.16497 0.000294 0.68255 12.220 1.5591 461.05 178.25 177.41 94.482 5.4813 161 0.59504 0.87101 0.019925 10.114 2.5235 563.58 882.73 122.08 111.91 4.5191 162 0.19052 0.39438 0.72575 5.808 1.697 738.55 847.2 99.741 101.24 4.3831 163 0.74153 0.34185 0.87858 15.300 2.0564 495.2 499.64 61.494 106.25 3.7808 164 0.083627 0.52435 0.34361 1.094 1.4214 534.17 808.26 127.98 88.797 3.9056 165 0.45195 0.81843 0.81288 0.701 2.3472 471.15 977.34 105.15 90.127 4.7870 166 0.81384 0.22875 0.97654 0.445 2.251 613.59 205.96 112.9 106.05 5.5267 167 0.2695 0.73651 0.30146 11.463 2.9584 858.45 589.16 96.349 99.705 4.6130 168 0.66599 0.29998 0.92251 2.185 1.2731 115.43 148.63 102.27 85.113 4.0060 169 0.1286 0.21367 0.73255 3.996 1.448 952.98 968.45 43.687 82.369 4.6983 170 0.90937 0.2454 0.34744 1.752 1.09 689.46 442.49 93.817 100.01 5.2650 171 0.001231 0.77299 0.11959 8.781 3.8606 554.82 261.49 127.63 106.41 3.1175 172 0.4656 0.83016 0.93346 13.446 3.1732 244.5 699 105.07 61.47 4.7295 173 0.19628 0.022893 0.76523 11.081 3.6345 500.05 780.29 105.03 90.458 5.6042 174 0.54137 0.23146 0.60978 0.367 1.8184 416.75 968.89 95.594 122.48 5.6344 175 0.36311 0.99983 0.053292 4.567 3.1094 707.24 953.45 119.63 95.041 5.1588 176 0.60953 0.70036 0.27276 2.534 2.7539 155.74 945.94 99.692 100.87 4.5358 177 0.064173 0.21845 0.15009 12.027 1.9175 654.72 623.42 104.98 118.15 4.3634 178 0.76396 0.92607 0.21335 6.586 2.4006 433.07 555.74 126.82 102.99 5.9885 179 0.10918 0.39894 0.41905 1.639 1.3675 740.08 105.31 109.7 104.85 5.2525 180 0.89186 0.018397 0.12176 4.221 1.9905 403.18 777.53 122.92 98.747 4.9020 181 0.13459 0.45851 0.67736 6.880 0.97985 131.08 877.56 31.075 78.69 5.5495 182 0.94536 0.066174 0.22481 1.313 2.8343 450.78 266.84 107.18 80.179 4.4101 183 0.074184 0.27323 0.063419 9.988 2.8894 259.14 358.23 105.52 80.941 4.6913 184 0.33522 0.56336 0.69415 6.146 1.5716 538.12 202.45 64.375 91.579 5.9230 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-22 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 185 0.38501 0.57366 0.4949 3.517 0.89307 767.45 408.75 102.49 118.82 4.6171 186 0.64828 0.67742 0.78821 7.207 0.75759 543.77 423.04 120.39 114.51 4.2114 187 0.55432 0.3274 0.82971 2.035 1.3431 672.33 834.53 124.19 104.48 4.7366 188 0.58086 0.49706 0.48494 19.322 1.0364 641.42 130.4 275.32 113.4 5.3329 189 0.010006 0.95063 0.41403 0.843 1.591 929.22 413.17 90.251 83.199 3.3167 190 0.81791 0.48478 0.97384 4.037 2.9223 974.17 384.56 109.61 105.37 5.5808 191 0.10396 0.14898 0.95984 11.665 2.4702 743.93 640.94 117.27 96.809 5.0963 192 0.008292 0.48702 0.022384 0.289 2.7737 284.09 219.8 108.01 88.152 5.6072 193 0.66128 0.010403 0.85706 0.887 2.5306 587.59 453 109.69 107.23 5.2849 194 0.44669 0.056335 0.013682 8.833 1.7959 668.91 963.31 34.465 91.033 5.2949 195 0.58695 0.50667 0.080381 0.924 0.60612 162.67 903.2 37.662 92.086 5.6213 196 0.14264 0.66797 0.39326 5.436 2.2902 604.69 272.75 100.65 91.916 5.2178 197 0.71574 0.5321 0.55188 1.006 0.84056 837.67 112.33 45.028 89.853 5.0028 198 0.048634 0.62298 0.37462 5.964 2.7289 218.81 349.72 103.43 99.369 5.1921 199 0.12266 0.69669 0.61218 7.132 1.2041 398.88 514.47 118.09 119.54 5.4031 200 0.32612 0.9429 0.70614 5.875 2.4135 375.84 709.58 112.16 86.921 4.3237 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-23 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 1 6309.1 4730.4 6.5351 4824.9 617.72 3.8786 -4.572 2 5007.6 5342.1 5.4447 3283.2 560.12 3.4041 -5.7843 3 5589.4 8261.8 4.8395 5971.4 534.18 3.6749 -8.8173 4 7302.6 6245.2 6.6296 6323.1 827.68 3.9087 -8.0077 5 5992.9 6287 4.8973 3155 674.44 2.2705 -5.7211 6 5262.8 4788 6.7566 4040.3 690.22 2.8873 -6.7879 7 2893 8144.2 5.2392 4133.2 606.63 3.5717 -7.6456 8 3603.4 6889.1 4.5868 4957.6 306 2.5735 -8.5382 9 5643.8 7741.2 5.6826 4672.8 867.06 2.6883 -8.3826 10 3583.3 5909.9 5.7904 5535.5 750.13 3.5812 -7.8268 11 8540.9 5513.8 4.8169 3188.8 740.75 2.7641 -5.4308 12 5508.4 2825.5 6.6948 5720.5 770.37 3.4680 -7.4885 13 8724.2 7377.1 6.8118 3442.1 266.83 2.1051 -7.9463 14 5089.3 7061.1 6.3204 6041.6 657.5 2.3401 -5.3155 15 5808.5 5920.6 5.3310 3614.8 668.57 3.6235 -6.3063 16 4777.5 5522.6 5.8099 6539.7 965.15 3.5680 -6.038 17 4977.8 3305.5 5.5915 4220.7 389.36 2.6242 -8.9285 18 6542.9 2272 6.3937 3590.5 314.42 3.3368 -5.1203 19 4993 5558.6 6.3339 4950.8 931.04 2.7255 -5.015 20 6706.8 5120.3 5.7864 6480.9 748.94 2.5836 -8.6327 21 5726.8 5387.4 5.2634 6331.2 876.74 3.6523 -7.7092 22 6860.1 3553.6 5.0370 5142 910.33 2.8175 -6.4254 23 7545.6 2579 5.3519 6001 773.03 3.6354 -3.895 24 7054.6 3372.9 5.8597 5089.8 882.09 2.7515 -6.355 25 3854.7 6983.9 6.5554 3213.3 211.23 3.5346 -6.8006 26 6472.6 3036.3 5.8147 3001 396.27 3.2209 -7.9992 27 4620.5 5009.2 6.4296 5355.6 757.18 3.2262 -5.2569 28 5306.4 7479 5.1151 4520.6 677.06 3.6131 -8.3503 29 5660.7 7023 6.2314 6300.8 393.27 2.7444 -8.4815 30 4297.1 5867.5 6.0915 5966.3 887.33 3.5988 -8.7293 31 5051.6 4283 6.8673 4550.5 474.94 3.5616 -8.1127 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-24 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 32 6115.2 4876.6 4.1311 4318.2 714.81 2.6805 -5.0346 33 8317 5640.6 5.8788 5113.8 602.9 3.0525 -5.9699 34 2275.6 5746.9 5.3663 6611.1 803.33 2.5272 -8.3377 35 4908.8 4073.5 6.4875 4277.7 779.54 2.5392 -8.296 36 6693 5035 6.9595 4693.2 411.36 3.6880 -5.8621 37 4723.8 7013.3 4.8852 6499.2 705.79 2.1769 -7.9177 38 6277.4 5160.7 6.9065 6124.2 709.48 3.3973 -4.4364 39 5181.5 4893.3 5.5222 5800.6 720.07 2.8232 -7.2399 40 7778.2 4527.7 5.9593 3033 343.37 3.2912 -6.1793 41 5349.7 7316.6 4.9502 5821.6 777.99 2.9877 -8.9181 42 6431.5 6816.2 4.8666 4617.6 549.49 3.1674 -6.3317 43 2724.4 3759.5 4.9395 1221 796.79 2.9675 -7.5121 44 6243.5 5785.8 5.8712 6359.9 590.83 2.8696 -7.3863 45 5925.8 4714.3 6.1445 4464.6 243.19 2.7023 -8.425 46 1965 6376.5 6.6558 6440.8 894.15 2.9331 -7.8574 47 5037.4 6725.3 4.7309 2887.8 903.14 3.6463 -8.4126 48 7443 4304 5.7277 4745.8 538.95 2.8814 -6.7385 49 4462 5212.8 5.9290 6080.2 422.12 3.5294 -8.0285 50 4035.1 5657.4 5.7352 6162.7 509.71 2.8766 -6.7708 51 5554.9 6420.5 5.2172 5620.3 453.26 2.3533 -8.2752 52 8071.4 4949.3 6.4202 3665.8 228.18 2.8028 -8.5786 53 7348.9 5477.7 6.9912 4604.2 653.48 3.0161 -5.961 54 5461.1 5625.9 5.7499 4374.7 331.77 3.4751 -7.1264 55 7018.4 7145.9 4.9984 3269 110.95 3.6719 -5.6324 56 3837.1 4805 5.6154 5041.6 936.66 2.6705 -5.6515 57 6594.9 6131.6 6.7445 3732.9 524.79 2.6578 -8.6058 58 5954.2 3231.6 6.4616 5512.2 987.52 3.4315 -6.5611 59 5596.7 5326.9 4.7420 4582.7 763.5 3.6969 -4.6876 60 5418.1 4607.3 6.4741 6579.8 807.2 3.6680 -7.1741 61 5133.5 4100.7 6.5664 4294.6 520.07 2.4733 -6.8259 62 5157.4 4938.7 5.8312 6408.7 256.39 3.8385 -6.0998 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-25 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 63 4670.8 4844 6.5497 6558.7 292.95 3.3557 -5.5944 64 4867.2 5144 4.9779 6514.3 993.65 3.5556 -5.5647 65 3446.8 7923 6.3795 4354.9 382.29 2.8582 -4.9253 66 5491.3 8625.9 4.8559 5495 906.26 3.4896 -4.7857 67 6156.1 4018.3 5.9815 6404.6 790.76 3.2972 -6.6733 68 6385.1 4135.9 6.6414 3833.9 641.08 3.9440 -4.0582 69 7549.7 4323.1 5.9031 6780.7 857.31 3.4630 -7.6129 70 5771 3145.7 4.9035 5579.7 471.12 2.7098 -7.2777 71 7105.6 6195.3 5.2926 3406.9 834.26 2.2552 -4.6302 72 6982 4346.1 5.4560 5564.9 408.06 3.1792 -5.6844 73 4534.3 6800.1 4.6366 1895.6 489.25 3.1359 -5.2873 74 1379.9 6227.9 6.0219 141.19 756.85 3.0487 -7.0552 75 2698.3 5880.5 5.6957 3098.8 367.47 2.8960 -8.7995 76 5210.5 6572.4 6.7109 3475.8 134.04 2.1340 -5.8189 77 4280 1694.7 4.2831 4996.3 360.62 2.5599 -7.2497 78 3914.1 5389.7 5.6608 5933.4 853.07 3.5461 -6.2719 79 9002.5 4631.3 6.3418 4915 403.1 3.5942 -8.0875 80 6572.1 5364.9 5.1451 4057.6 477.94 3.7520 -8.6709 81 6921.6 2799.2 5.7018 4897.6 445.81 3.4561 -6.4535 82 4152.2 7436.8 4.9250 4190 683.38 2.2281 -6.5244 83 7164.9 4389.7 5.6492 3320.4 693.33 2.8429 -6.4857 84 2388.7 6013.4 5.7170 5696.7 163.8 2.6344 -4.3981 85 6874.5 3492.4 5.5117 5013.6 983.28 3.9624 -4.5272 86 3782.3 6217 5.9032 6214.5 461.19 2.6480 -7.4294 87 3630.1 7190.7 4.5803 6282 952.5 3.4821 -8.0503 88 4365.5 5547 6.8266 3923.8 925.98 3.6803 -4.5105 89 3683.3 4475 5.0791 5231.6 430.68 3.6910 -6.8462 90 6008.9 5068.9 6.4046 4138.7 249.24 3.3073 -7.9359 91 3750 9774.6 6.0279 3655.1 918.62 3.0975 -7.889 92 6233.9 6352.9 6.9300 5828.7 568.55 2.3213 -6.2493 93 3459.8 4572.1 6.3086 4889 825.23 2.6000 -7.4708 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-26 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 94 7865.3 5818.5 5.6892 3166 202.33 2.5084 -3.7317 95 4228.9 6409.7 6.2134 5202.8 836.23 3.4954 -5.393 96 5531.3 5697.5 6.1669 3971.1 872.68 3.6501 -5.5001 97 3939.6 8295.4 4.6709 3557.2 767.05 2.7793 -6.6074 98 5965.7 5955.8 5.3185 4487.9 651.73 2.5491 -8.3675 99 3738.6 3419.1 5.6059 5870.2 947.46 2.7711 -7.0308 100 4802.2 6453.6 6.5686 6737.4 615.38 2.8674 -7.7203 101 3334.5 6512.4 4.4403 3795.9 849.13 2.8082 -6.1279 102 8595.9 3630.2 5.4799 4640.8 784.32 2.7580 -8.0694 103 7182.9 6042.8 5.8660 3052.4 971.84 2.7981 -8.8338 104 4958.2 6673.9 6.5135 6648.8 496.73 3.2720 -7.0745 105 3082.9 6544.4 6.5400 6601.3 532.24 3.1580 -6.6485 106 3965.4 3727.4 4.3639 5069.1 582.39 2.9045 -5.4409 107 9913.3 5460.2 6.6081 5103.4 697.14 3.5093 -7.6354 108 4795.8 4668.7 5.5864 6681.4 153.12 2.9743 -7.6714 109 6304.8 4165.6 5.9615 3428.4 456.57 2.4158 -6.9696 110 4754.5 7780.4 4.7672 4500.4 374.42 3.2487 -4.9795 111 7603.7 8058.4 5.9161 3516 319.59 3.8641 -8.708 112 4583.3 6781.7 4.5036 6016.5 923.56 3.6818 -7.1837 113 4824.3 6329.4 6.3703 6695.2 648.33 3.1176 -7.1191 114 5680.8 6059.6 6.6830 3694.1 730.7 2.9181 -8.9704 115 5790.5 5772.9 6.4466 3566.9 858.66 2.4464 -7.5521 116 6135.5 5134.4 5.8476 6374.1 816.55 3.4484 -7.0902 117 6639.2 4002.7 4.6930 5443.8 611.58 2.3651 -7.7541 118 7935.2 6464.4 6.6406 4340.5 999.65 2.6193 -6.1412 119 6028.1 2417.6 5.9375 5657.6 624.34 3.5238 -8.158 120 5565.1 5717 6.2693 5849.5 119.59 2.4063 -8.9883 121 5245.4 5254.6 5.8866 5220.3 514.58 2.8493 -7.2082 122 4859.2 8446.5 4.5456 3622.5 722.78 2.9518 -6.9556 123 4938.5 4907.2 5.9711 5776.5 594.79 3.6188 -8.4713 124 4263.1 6587 5.6385 3357.1 742.58 3.5120 -5.9011 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-27 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 125 6522 4395.8 5.5446 5683.3 289.63 3.5772 -6.5865 126 6063.9 4229.3 6.8772 4852.6 347.87 2.7207 -7.7741 127 6655.9 5738.2 6.2526 2360.3 220.63 2.9231 -8.1362 128 5176.9 5850.1 6.5980 3398.7 279.91 3.5034 -6.0613 129 7281.7 6652.4 6.2753 3858.1 504.53 3.4137 -6.0073 130 5363.8 3970 5.9472 3952 545.05 2.9417 -8.2235 131 6036.8 5837.6 5.9920 5341.6 570.11 3.3768 -8.1668 132 5744.8 3624.1 5.4277 4555 812.12 2.9728 -7.3502 133 4693.1 4979.4 6.6769 3229.1 208.85 2.7330 -7.0104 134 5832.9 3820.4 6.6750 3531.8 957.43 2.8329 -6.6947 135 6088.4 6504 6.6494 4237.7 700.06 2.9378 -4.3359 136 4699.9 6627.1 6.7938 6200.4 822.84 2.1494 -5.7531 137 6505.9 4594.3 5.9507 3809.9 498.66 2.9847 -7.5684 138 4337.4 4680.7 6.3561 6640.2 192.87 2.4825 -5.3565 139 3542.1 4758.5 5.8380 3697.6 663.39 3.4455 -7.4479 140 5904.2 5223.5 5.6201 3766.7 254.42 3.3204 -6.7548 141 6444.3 5584.3 5.6273 4406.8 939.57 3.5486 -6.9388 142 4544.6 7527.3 5.7533 3312.6 733.53 2.6092 -6.1196 143 4605.5 7679.4 6.5916 6234.3 916.07 2.9248 -6.7004 144 5897.9 5606.4 5.8254 4030.4 620.29 3.6389 -7.371 145 3214.5 7092.3 5.1766 5281.3 944.22 3.4867 -6.5065 146 7462.2 7369.8 5.3910 4257.1 435.09 3.3861 -6.4789 147 5103.6 6925.5 4.3864 3061.2 840.62 3.0916 -7.2809 148 6768.2 5482.9 6.5755 6759.3 814.05 3.0240 -7.8089 149 4003.2 7607.4 5.0107 5456.8 440.8 3.6597 -5.0888 150 8022.6 6688.6 6.1236 5386.6 280.49 3.1915 -5.1417 151 7385 5990.2 6.5229 4207.8 528.33 2.8321 -8.2405 152 5476.4 6935.5 6.6920 5163.7 232.73 3.7372 -7.6861 153 7657.2 3914.4 5.5505 4656 482.77 3.6637 -4.374 154 6613.2 4824.2 5.4669 3989.2 188.78 2.0249 -8.8522 155 4174.4 5260.6 6.0568 4797.1 637.17 3.6560 -6.1817 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-28 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 156 4384.3 4742 5.5270 541.24 681.73 3.5181 -7.5344 157 6401.8 3705 6.4784 4716.4 737.32 3.3493 -8.6836 158 4075.5 4987.3 6.8507 6061.8 447.66 3.5606 -6.3775 159 4126.3 9063.8 6.6274 5601.3 954.54 3.5888 -7.4084 160 3047.5 4545.2 5.9215 2606.8 553.13 2.9480 -8.8816 161 5317.5 5310.4 5.2054 4788.7 800.32 3.6927 -8.2007 162 4044.6 4444.7 6.4576 4100.6 981.31 3.3876 -4.2662 163 5855.3 3867.3 6.9439 3898.7 899.82 3.3137 -7.3117 164 6833.2 4440.7 4.7797 4979.9 644.04 2.9990 -6.9054 165 5281.1 7158.9 5.4064 3128.2 628.51 2.4957 -7.598 166 2947.2 1920 5.2725 4441.5 879.62 3.2435 -5.2248 167 6202.2 3271 5.9978 5412 579.7 3.1305 -4.7488 168 4188.8 3107.8 5.7779 6704.9 353.62 3.7884 -4.8991 169 5070.1 6842.6 5.7652 5478.8 297.66 2.9944 -6.2265 170 4399.1 5674.1 5.5660 5742.2 891.97 2.4558 -6.8629 171 5627.1 6268.8 6.6095 3374.3 426.2 3.2084 -6.4087 172 6748.7 7287.1 6.6205 4159.3 703.3 2.9821 -6.3856 173 6787.9 7970.3 6.1174 5260.7 268.5 3.5398 -5.1919 174 6186.4 7869.5 6.6647 3748.4 340.47 3.4275 -6.0434 175 5228.2 5434.1 5.6690 1418.7 180.84 3.6291 -7.3288 176 7144.7 5181.5 4.9585 6180 327.57 3.0748 -8.9459 177 3394.1 7560.4 5.9763 5305.7 843.16 2.9581 -5.8791 178 7724.3 6023.7 6.5819 3251.3 313.53 3.6042 -7.157 179 4440.5 6145.1 4.7188 6453.4 977.55 2.6958 -8.7779 180 6999.5 5277.7 6.1857 5320.7 418.41 3.5930 -6.5596 181 5711 6168.9 5.9346 4842.2 511.78 3.4179 -8.5473 182 5402.8 4243.5 5.5720 5188.1 167.1 3.3708 -5.4973 183 5866.1 2595.4 5.4095 700.81 861.91 3.6422 -8.1846 184 7249 2974.5 5.4930 3851.2 141.38 3.4392 -6.2812 185 4647.9 4503.3 6.5013 4093.8 365.62 2.9097 -8.5817 186 3142.8 6104.4 6.2958 5925.6 562.62 3.2596 -8.6539 Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-29 October 2004 Table B-1. Resampled Stochastic Parameter Values (Continued) real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 187 6954.6 6746.3 6.5090 4764.7 788.4 2.2855 -7.8687 188 8147.1 8715.9 5.9861 5888.5 667.15 3.3601 -6.6348 189 5368.6 3526.3 6.9769 4424.9 967.31 3.3299 -6.9914 190 6359 3945.3 4.8049 6246.1 555.85 2.0420 -7.787 191 6330 4117 4.9715 5631.4 587.59 3.6088 -8.7485 192 4483.9 6078.1 6.6680 3896.4 378.1 3.2772 -4.8491 193 3289.1 5088.1 4.0572 4001.4 600.52 3.9912 -6.895 194 2548.5 3789.7 6.2105 3110.5 102.37 2.8567 -7.9751 195 8255.2 5962.6 5.6564 5763.1 631.46 2.7879 -4.7318 196 6161.5 7222.2 6.9137 6135 576.05 3.1997 -8.4518 197 4506.1 5051 5.7987 3483.6 486.68 3.6209 -8.5185 198 5427.5 4202.9 6.4161 1670.4 463.56 2.9615 -8.3199 199 4889 5419 5.8950 6096.5 147.01 2.9019 -8.8695 200 5703.4 6314.5 4.2159 5402.6 724.4 2.3891 -6.2063 Output DTN: SN0407T0502103.013. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-30 October 2004 Table B-2. Comparison of Simulated Median Transport Times for the Re-Sampled Parameters and the Base Case at Three Levels of Cumulative Probability 5th Percentile Transport Time (years) Median Transport Time (years) 95th Percentile Transport Time (years) Carbon, Technetium, Iodine (Re- Sampling) 70 620 15570 Carbon, Technetium, Iodine (Base-Case) 90 640 13100 % Difference 22.2 3.1 18.9 Americium, Thorium, Protactinium (Re- Sampling) >100000 >100000 >100000 Americium, Thorium, Protactinium (Base Case) >100000 >100000 >100000 % Difference 0.0 0.0 0.0 Cesium (Re-Sampling) >100000 >100000 >100000 Cesium (Base Case) >100000 >100000 >100000 % Difference 0.0 0.0 0.0 Plutonium (Re-Sampling) 16000 >100000 >100000 Plutonium (Base Case) 25000 >100000 >100000 % Difference 36.0 0.0 0.0 Neptunium (Re-Sampling) 2090 16450 >100000 Neptunium (Base Case) 2300 18200 >100000 % Difference 9.1 9.6 0.0 Plutonium and Americium – Irreversible Colloids (Re-Sampling) 820 22130 >100000 Plutonium and Americium – Irreversible Colloids (Base Case) 900 18500 >100000 % Difference 8.9 20. 0.0 Radium (Re-Sampling) >100000 >100000 >100000 Radium (Base Case) >100000 >100000 >100000 % Difference 0.0 0.0 0.0 Strontium (Re-Sampling) 42100 >100000 >100000 Strontium (Base Case) 86700 >100000 >100000 % Difference 51.4 0.0 0.0 Uranium (Re-Sampling) 1850 23360 >100000 Uranium (Base Case) 2400 24300 >100000 % Difference 22.9 3.9 0.0 Plutonium and Americium – Irreversible Colloids – Fast Fraction (Re-Sampling) 50 330 3570 Plutonium and Americium – Irreversible Colloids – Fast Fraction (Base Case) 70 310 2340 % Difference 29. 6.5 53. Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-31 October 2004 10 100 1000 10000 100000 Median Transport Time (years) 0 0.2 0.4 0.6 0.8 1 Cumulative Probability Figure B-1. CDF of Median Simulated Transport Time of Nonsorbing Species (Carbon, Technetium, and Iodine) for the Base Case (Solid Blue Line) and the Re-Sampled Parameters (Dashed Red Line) Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 REV 02 B-32 October 2004 INTENTIONALLY LEFT BLANK