SZ Flow and Transport Model Abstraction Rev 00, ICN 00 MDL-NBS-HS-000021 July 2003 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) calculations. This task also includes assessment of uncertainty in parameters related 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 simulations of radionuclide releases to the biosphere. These radionuclide breakthrough curves contain information on the radionuclide transport times through the SZ. • The SZ One-Dimensional (1-D) Transport Model, which is incorporated in the TSPA 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 for the SZ 1-D Transport Model. The scope of this model report includes of the technical basis for Features Events and Processes (FEPS) and contributes to the characterization of the SZ as a natural barrier, which provides evidence related to the capability of the SZ to delay movement of radionuclides through the SZ to the accessible environment. The scope of this report also contributes to the technical basis for the SZ transport system description used in the License Application (LA), and provides evidence for the acceptance criteria as specified in the Yucca Mountain Review Plan (YMRP) (NRC 2003 [163274]). The scope of the 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 is subject to the limitations imposed by the assumptions listed in Section 5 of this model report. Limitations in knowledge of specific parameter values are addressed in the analysis of parameter uncertainties in this report. The radionuclide breakthrough curves generated for the SZ Transport Abstraction model are limited to 100,000 years, for present climatic conditions. This limits the time period that can be simulated with the TSPA model 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 model would be significantly less than 100,000 years. If the glacial-transition climate state is applied for most of simulation period in the TSPA model, the SZ breakthrough curves would be scaled by a factor of approximately 4, limiting the TSPA model simulation time to about 25,000 years. Information on the correlation between distribution coefficients (Kds) used in the sampling of uncertain parameters for the SZ Transport Abstraction Model and the SZ 1-D Transport Model is given in Table 4-3 and Table 6-8. The technical bases for correlations between distribution coefficients (or the lack thereof) are documented in BSC 2003 [162419], Section I.10. MDL-NBS-HS-000021, REV 00 11 July, 2003 Evaluation of uncertainty in horizontal anisotropy of permeability is summarized in Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is given in BSC 2003 [162415],Section 6.2.6. Implementation of uncertainty in horizontal anisotropy in the SZ Transport Abstraction Model and 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. The technical bases for uncertainty in distribution coefficients are documented in BSC 2003 [162419], Section I. Information on the geological uncertainty in the location of the contact between tuff and alluvium and the consequent uncertainty in the flow path lengths in the alluvium is presented in Section 6.5.2.2. This evaluation of uncertainty includes currently available information from the Nye County drilling program. The 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 model report is governed by the Office of Civilian Radioactive Waste Management (OCRWM) Technical Work Plan For: Saturated Zone Flow and Transport Modeling and Testing, TWP-NBS-MD-000002 (BSC 2003 [163965]), Work Package ASZM04. The work documented in this model report was conducted in accordance with the quality assurance procedure AP-SIII.10Q, Models [164074]. In this report, a unique six-digit numerical identifier (the Document Input Reference System [DIRS] number) is placed in the text following the reference callout (e.g., BSC 2001 [155950]). The purpose of the DIRS numbers is to assist the reader in locating a specific reference in the DIRS database. MDL-NBS-HS-000021, REV 00 12 July, 2003 2. QUALITY ASSURANCE Development of this model report and the supporting modeling activities is subject to the Yucca Mountain Project (YMP) quality assurance (QA) program (BSC 2003 [163965], Section 8, Work Package ASZM04). Approved QA procedures identified in the technical work plan (BSC 2003 [163965], 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 2003 [163965], Section 8). This model report provides values for hydrologic properties of a natural barrier that is important to the demonstration of compliance with the post-closure performance objectives prescribed in 10 CFR 63.113. Therefore, it is classified as a “Quality Level – 1” with regard to importance to waste isolation, as defined in AP-2.22Q Rev 0, ICN 1, Classification Criteria and Maintenance of the Monitored Geologic Repository Q-List [163021]. The report contributes to the analysis and modeling data used to support performance assessment; the conclusions do not directly impact engineered features important to safety, as defined in AP-2.22Q. MDL-NBS-HS-000021, REV 00 13 July, 2003 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 indicated in the Software Configuration Management (SCM) database. All software was obtained from SCM and is appropriate for the application. Qualified codes were used only within the range of validation as required by AP-SI.1Q, Rev. 5, ICN 0, Software Management [163085]. 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 V 2.20 (LANL 2003 [161725]) 10086- 2.20-00 This code is a finite-element heatand 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 V 7.50.100 (BSC 2003 [161572]) 10344- 7.50.100- 00 This code is the modeling software used in the TSPA. Probabilistic simulations are represented graphically in GoldSim. Dell OptiPlex GX260 - Windows 2000 Professional 5.0.2195 Sandia National Laboratories 01/07/2003 SZ_Pre V 2.0 (SNL 2003 [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 for use in TSPA analyses. Sun UltraSPARC - SunOS 5.7 Sandia National Laboratories 04/28/2003 SZ_Post V 3.0 (SNL 2003 [163571]) 10915- 3.0-00 This software is used to translate the output files from the SZ site-scale model 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 (LANL 2001 [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 V.2.2 (SNL 2003 [163344]) 10207- 2.2-00 This software is used to calculate saturated-zone response curves based on unsaturated-zone radionuclide source terms, generic saturated-zone responses, and climate scenarios for the YMP. Dell OptiPlex GX260 - Windows 2000 Professional 5.0.2195 Sandia National Laboratories 01/13/2003 Note: The SZ_Convolute v. 2.2 software code (STN: 10207-2.2-00, SNL 2003 [163344]) was used in the modeling and analyses in this report. SZ_Convolute v. 3.0 (STN: 10207-3.0-00, SNL 2003 [164180]) (or later version) will be used for implementation of the SZ Transport Abstraction Model in TSPA-LA. MDL-NBS-HS-000021, REV 00 14 July, 2003 3.2 EXEMPT SOFTWARE The commercially available software cited below is appropriate for use in this application. The results were spot-checked by hand to ensure the results were correct. The computer used was a Dell OptiPlex GX1 with Pentium II processor, running Microsoft Windows 2000 5.0.2195. The range of validation for Excel, Surfer, and Grapher is the set of real numbers. 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: SN0306T0502103.006. • Surfer 8.0: Used for plotting and visualization. • Grapher 4.0: Used for plotting graphs. • Igor 4.07: Used for plotting graphs. MDL-NBS-HS-000021, REV 00 15 July, 2003 4. INPUTS 4.1 DATA, PARAMETERS, AND OTHER MODEL INPUTS 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. 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). 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 discussed in Section 6.5.1 and 6.5.2. Parameter uncertainties are addressed by providing ranges, probability distributions and bounding assumptions as appropriate for each parameter. Table 4-1. Input Data 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 2002 [159530]) OFR 94-469 (Buesch et al. 1996 [100106]); Flint 1998 [100033]; OFR 94-460 (Moyer and Geslin 1995 [101269]); (HFM Units 12 and 11) TDR-NBS-GS-000020, BSC 2001 [163479] (HFM Units 12 and 11) SN0004T0501399.003 [155045] (HFM Units 15-13, 10-8) MO0109HYMXPROP.001 [155989] (HFM Units 12 and 11) MO0010CPORGLOG.002 [155229] (HFM Units 12 and 11 ) Effective Porosity Alluvium Bedinger, et al. 1989 [129676] (HFM Units 19 and 7) EDCON 2000 [154704] (HFM Units 19 and 7) Burbey and Wheatcraft [129679] 1986 (HFM Units 19 and 7) DOE 1997 [103021], Table 8-2, p. 8- 6, Table 8-1 p. 8-5 (HFM Units 19 and 7) MO0105HCONEPOR.000 [155044] (HFM Units 19 and 7) MO0105GPLOG19D.000 [163480] (HFM Units 19 and 7) Burbey and Wheatcraft is considered Technical Information, no DTN. (HFM Units 19 and 7) DOE 1997 is considered Technical Information, no DTN. (HFM Units 19 and 7) MDL-NBS-HS-000021, REV 00 16 July, 2003 Data Name Originating Report DTN Effective Porosity in the Other Units Bedinger, et al. 1989 [129676] (HFM Units, 18, 17, 16, 6-2, 1) MO0105HCONEPOR.000 [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 2002 [159530]) OFR 94-469 (Buesch et al. 1996 [100106]); Flint 1998 [100033]; OFR 94-460 (Moyer and Geslin 1995 [101269]), (HFM Units 12 ,11 and 9) TDR-NBS-GS-000020, BSC 2001 [163479] (HFM Units 17, 12, 11, 6-2) SN0004T0501399.002 [155046] (HFM Units 15-13, 10, 8) SN0004T0501399.003 [155045] (HFM Units 15-13, 10-8) MO0109HYMXPROP.001 [155989] (HFM Units 12 11, and 9) MO0010CPORGLOG.002 [155229] (HFM Units 17, 12 and 11, 6-2) Effective Diffusion Coefficient BSC 2001 [163566] (HFM Units 8- 15) MO0109HYMXPROP.001 [155989] (HFM Units 8-15) Bulk Density - Alluvium EDCON 2000 [154704] (HFM Units 19 and 7) MO0105GPLOG19D.000 [163480] (HFM Units 19 and 7) Flowing Interval Porosity in the Volcanic Units BSC 2003 [161773], p. 41 and 64 (HFM Units 8-15) CRWMS M&O 1997 [100328], p. 28 (HFM Units 8-15) DOE 1997 [103021], p. 5-14 (HFM Units 8-15) Wilson et al. 1994 [100191], Volume 1, Chapter 7, Table 7-19, p. 7-30 (HFM Units 8-15) Product Output, information not in DTN (HFM Units 8-15) Technical Information no DTN (HFM Units 8-15) Technical Information no DTN (HFM Units 8-15) Technical Information no DTN (HFM Units 8-15) Lithostratigraphy in Wells EWDP- 10SA and EWDP-22SA N/A GS030108314211.001 [163483] Coordinates of Well Locations USGS 2001 [157611] GS010908312332.002 [163555] Uncertainty in Groundwater Specific Discharge CRWMS M&O 1998 [100353] MO0003SZFWTEEP.000 [148744] Uncertainty in Groundwater Specific Discharge at the Alluvial Tracer Complex BSC 2003 [162415] LA0303PR831231.002 [163561] UZ Site-Scale Model Flow Field – Present Climate CRWMS M&O 2000 [122797] LB990801233129.004 [117129] UZ Site-Scale Model Flow Field – Glacial-Transition Climate CRWMS M&O 2000 [122797] LB990801233129.009 [118717] UZ Site-Scale Model Flow Field – Monsoonal Climate CRWMS M&O 2000 [122797] LB990801233129.015 [118730] Note: The column containing the originating report is provided for reference only. The direct source of the data used in this AMR is listed in the DTN column. The HFM Unit numbers given refer to the unit definitions in Table 6-9. MDL-NBS-HS-000021, REV 00 17 July, 2003 Other model input information is listed in Table 4-2. Table 4-2. Other Model/Analysis Inputs 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 [164362] Matrix Diffusion Type Curves The analytical solution type curves for matrix diffusion in fractured media. These type curves are used in the particle tracking algorithm of the FEHM software to simulate radionuclide transport in fractured porous media. LA0302RP831228.001 [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-EBS0-00401-000-00C, BSC 2003 [162289] 800-IED-EBS0-00402-000-00B, BSC 2003 [161727] Boundary of Accessible Environment Latitude of the accessible environment, as defined by regulation 10 CFR 63.302 [156605], regulatory input, technical information, no DTN 4.1.2 Parameters and Parameter Uncertainty The parameters and parameter uncertainty from external sources used directly in the modeling documented in this report are shown in Table 4-3. 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. MDL-NBS-HS-000021, REV 00 18 July, 2003 Table 4-3. Input Parameters Parameter Name Parameter Source DTN Value(s) Units Distribution KDNPVO (neptunium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] CDF: Probability Value 0.0 0.0 0.05 1.0 0.90 1.6 1.0 6.0 ml/g Distribution KDNPAL (neptunium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] CDF: Probability Value 0.0 1.8 0.05 4.0 0.95 8.7 1.0 13.0 ml/g Distribution KDSRVO (strontium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] Uniform: Minimum 20. Maximum 400. ml/g Distribution KDSRAL (strontium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] Uniform: Minimum 20. Maximum 400. ml/g Distribution KDUVO (uranium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] CDF: Probability Value 0.0 0.0 0.05 5.4 0.95 6.9 1.0 20.0 ml/g Distribution KDUAL (uranium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] 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 2003 [162419] LA0302AM831341.001 [163556] Uniform: Minimum 100. Maximum 1000. ml/g Distribution KDRAAL (radium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] Uniform: Minimum 100. Maximum 1000. ml/g Distribution MDL-NBS-HS-000021, REV 00 19 July, 2003 Parameter Name Parameter Source DTN Value(s) Units Distribution KD_Pu_Vo (plutonium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] CDF: Probability Value 0.0 10. 0.25 75. 0.95 100. 1.0 300. ml/g Distribution KD_Pu_Al (plutonium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] Beta: Mean 100. Standard Deviation 15. Minimum 50. Maximum 300. ml/g Distribution KD_Am_Vo (americium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. ml/g Distribution KD_Am_Al (americium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. ml/g Distribution KD_Cs_Vo (cesium sorption coefficient in volcanic units) BSC 2003 [162419] LA0302AM831341.001 [163556] CDF: Probability Value 0.0 100. 0.05 3700. 1.0 7500. ml/g Distribution KD_Cs_Al (cesium sorption coefficient in alluvium) BSC 2003 [162419] LA0302AM831341.001 [163556] Truncated Normal: Mean 728. Standard Deviation 464. Minimum 100. Maximum 1000. ml/g Distribution FISVO (flowing interval spacing in the volcanic units) BSC 2001 [156965] SN9907T0571599.001 [122261] CDF: (Log-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 MDL-NBS-HS-000021, REV 00 20 July, 2003 Parameter Name Parameter Source DTN Value(s) Units Distribution CORAL (colloid retardation factor in the alluvium) BSC 2003 [163932] LA0303HV831352.004 [163559] CDF: (Log-transformed) Probability Value 0.0 0.903 0.331 0.904 0.50 1.531 1.0 3.715 NA Distribution CORVO (colloid retardation factor in the volcanic units) BSC 2003 [163932] LA0303HV831352.002 [163558] CDF: (Log-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 NA Distribution HAVO (ratio of horizontal anisotropy in permeability) BSC 2003 [162415] SN0302T0502203.001 [163563] CDF: Probability Value 0.0 0.05 0.10 1.0 0.60 5. 1.0 20. NA Distribution LDISP (longitudinal dispersivity) CRWMS M&O 1998 [100353] MO0003SZFWTEEP.000 * [148744] Truncated Normal: (Logtransformed) Mean 2.0 Standard Deviation 0.75 m Distribution Kd_Pu_Col (plutonium sorption coefficient onto colloids) BSC 2003 [161620] SN0306T0504103.006 [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 2003 [161620] SN0306T0504103.006 [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 MDL-NBS-HS-000021, REV 00 21 July, 2003 Parameter Name Parameter Source DTN Value(s) Units Distribution Kd_Cs_Col (cesium sorption coefficient onto colloids) BSC 2003 [161620] SN0306T0504103.006 [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 2003 [161620] SN0306T0504103.005 [164132] CDF: (Log-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 -3.6 g/ml Distribution Correlation coefficient for U Kd in volcanic units and alluvium BSC 2003 [162419] LA0302AM831341.001 [163556] 0.75 ml/g Single Value Correlation coefficient for Np Kd in volcanic units and alluvium BSC 2003 [162419] LA0302AM831341.001 [163556] 0.75 ml/g Single Value Correlation coefficient for Pu Kd in volcanic units and alluvium BSC 2003 [162419] LA0302AM831341.001 [163556] 0.50 ml/g Single Value Correlation coefficient for U Kd and Np Kd BSC 2003 [162419] LA0302AM831341.001 [163556] 0.50 ml/g Single Value NOTE: * MO0003SZFWTEEP.000 [148744] contains qualified data from an Expert Elicitation that was determined to comply with Expert Elicitation Procedure AP-AC.1Q [138711], which is consistent with the Branch Technical Position on Expert Elicitation NUREG-1563 (Kotra et al. 1996 [100909]). MDL-NBS-HS-000021, REV 00 22 July, 2003 4.2 CRITERIA The general requirements to be satisfied by the TSPA are stated in 10 CFR 63.114 (10 CFR 63 [156605]). Technical requirements to be satisfied by the TSPA are identified in the Yucca Mountain Project Requirements Document (Canori and Leitner 2003 [161770], Table B-9). The acceptance criteria that will be used by the Nuclear Regulatory Commission (NRC) to determine whether the technical requirements have been met are identified in the Yucca Mountain Review Plan NUREG-1804, Draft Final Revision 2 (YMRP; NRC 2003 [163274]). The pertinent requirements and criteria for this report are summarized in Table 4-2. Table 4-4. Project Requirements for This Model Report Requirement Numbera Requirement Titlea 10 CFR 63 Link [156605] YMRP Acceptance Criteriab PRD-002/T-014 Performance Objectives for the Geologic Repository After Permanent Closure 10 CFR 63.113 2.2.1.1.3, criteria 1 to 3 PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 2.2.1.3.8.3, criteria 1 to 4; 2.2.1.3.9.3, criteria 1 to 5 PRD -002/T-016 Requirements for Multiple Barriers 10 CFR 63.115 2.2.1.1.3, criteria 1 to 3 NOTE: a from Canori and Leitner 2003 [161770]. b from NRC 2003 [163274] The acceptance criteria identified in Sections 2.2.1.1.3, 2.2.1.3.8.3, and 2.2.1.3.9.3 of the YMRP (NRC 2003 [163274]) are given below, followed by a short description of their applicability to this model report. Criteria item numbers not shown are considered to not apply to this model. Section 2.2.1.1.3 Acceptance Criteria [for 2.2.1.1 System Description and Demonstration of Multiple Barriers], which are based on meeting the requirements at 10 CFR 63.113(a) and 63.115(a)–(c): • Acceptance Criterion 1, Identification of Barriers is Adequate Barriers relied on to achieve compliance with 10 CFR 63.113(b), as demonstrated in the total system performance assessment, are adequately identified, and are clearly linked to their capability. The barriers identified include at least one from the engineered system and one from the natural system. This model report describes the SZ radionuclide transport simulation results for use in the TSPA calculation. This includes the 1-D model description, which is incorporated in the TSPA calculations to simulate transport, decay, and ingrowth of radionuclide decay chains in the SZ. Also discussed in Section 6.5.2 is the analysis of uncertainty in input parameters for the SZ Transport Abstraction Model and for the SZ 1-D Transport Model. MDL-NBS-HS-000021, REV 00 23 July, 2003 • Acceptance Criterion 2, Description of Barrier Capability to Isolate Waste is Acceptable The capability of the identified barriers to prevent or substantially reduce the rate of movement of water or radionuclides from the Yucca Mountain Repository is adequately identified and described: 1. The information on the time period over which the SZ barrier performs its intended function, including any changes during the compliance period, is provided in Section 6.7. 2. The uncertainty associated with barrier capabilities is adequately described in Section 6.7. • Acceptance Criterion 3, Technical Basis for Barrier Capability is Adequately Presented The technical bases are consistent with the technical basis for the performance assessment, although not explicitly addressed in this report it is addressed in the TSPA. The technical basis for assertions of barrier capability is commensurate with the importance of each barrier’s capability and the associated uncertainties. Section 2.2.1.3.8.3 Acceptance Criteria (for 2.2.1.3.8 Flow Paths in the Saturated Zone), which are based on meeting the requirements of 10 CFR 63.114(a)–(c) and (e)–(g), relating to flow paths in the saturated zone model abstraction: • Acceptance Criterion 1, System Description and Model Integration are Adequate: 2. The description of the aspects of hydrology, geology, geochemistry, design features, physical phenomena, and couplings that may affect flow paths in the saturated zone is adequate. Conditions and assumptions in the abstraction of flow paths in the saturated zone are readily identified and consistent with the body of data presented in the description (see Section 6.3). 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 DOE 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 NRC 2003 [163274]). The descriptions and technical bases provide transparent and traceable support for the abstraction of flow paths in the saturated zone (see Section 6.3). 5. Sufficient data and technical bases to assess the degree to which features, events, and processes have been included in this abstraction are provided (see Section 6.2). 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 (see the introductory text in Section 6.5). 10. Guidance in NUREG-1297 (Altman et al. 1988 [103597]) and NUREG-1298 (Altman et al. 1988 [103750]) or other acceptable approaches for peer review and data qualification is followed (see Section 6.5.2.1). MDL-NBS-HS-000021, REV 00 24 July, 2003 • Acceptance Criterion 2, Data are Sufficient for Model Justification: 1. Geological, hydrological, and geochemical values used in the safety case 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, as described in Section 6.5.2. 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 (see Section 6.5.2). • 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 (see Section 6.5.2). 2. Uncertainty is appropriately incorporated in model abstractions of hydrologic effects of climate change, based on a reasonably complete search of paleoclimate data (see the introduction to Section 6.5). 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 (see Section 6.5.2). 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 [100909]) (see Section 6.5.2.1). • 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 (see Section 6.2). 2. Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed (see Section 6.4). 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, as described in Section 6.4. • Acceptance Criterion 5, Model Abstraction Output Is Supported by Objective Comparisons: MDL-NBS-HS-000021, REV 00 25 July, 2003 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) (see Section 7). 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 (see Sections 6.6 and 7). 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 (Section 7). Section 2.2.1.3.9.3 Acceptance Criteria [for 2.2.1.3.9 Radionuclide Transport in the Saturated Zone], which are based on meeting the requirements of 10 CFR 63.114(a)–(c) and (e)–(g), relating to the radionuclide transport in the saturated zone model abstraction: • Acceptance Criterion 1, System Description and Model Integration are Adequate: 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, as described in Section 6.3. 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 DOE abstractions (see Section 6.5). 4. Boundary and initial conditions used in the abstraction of radionuclide transport in the saturated zone are propagated throughout its abstraction approaches (see Section 6.3). 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, as described in Section 6.2. 6. Guidance in NUREG-1297 (Altman et al. 1988 [103597]) and NUREG-1298 (Altman et al. 1988 [103750]) or other acceptable approaches for peer review and data qualification is followed (see Section 6.5.2.9). • Acceptance Criterion 2, Data are Sufficient for Model Justification: 1. Geological, hydrological, and geochemical values used in the safety case 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 (see Section 6.5.2). • Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the Model Abstraction: MDL-NBS-HS-000021, REV 00 26 July, 2003 1. Models use parameter values, assumed ranges, probability distributions, and/or bounding assumptions that are technically defensible, and reasonably account for uncertainties and variabilities (see Section 6.5.2). 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 [163274]) (see Section 6.5.2). 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 (see Sections 6.3 and 6.5.2). 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 [100909]) (see Section 6.5.2.9). • 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 (see Section 6.2). 2. Conceptual model uncertainties are adequately defined and documented, and effects on conclusions regarding performance are properly assessed (see Section 6.4). 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 (see Section 6.4). • Acceptance Criterion 5, Model Abstraction Output is Supported by Objective Comparisons: 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 (see Section 7). 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 (see Sections 6.5 and 7). 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 (see Section 7). MDL-NBS-HS-000021, REV 00 27 July, 2003 4.3 CODES AND STANDARDS No specific formally established codes or standards have been identified as applying to this modeling activity. This activity does not directly support License Application (LA) design. MDL-NBS-HS-000021, REV 00 28 July, 2003 5. ASSUMPTIONS There are several types of assumptions related to model development. The assumptions listed in this section of the AMR are restricted to those that meet the definition given in the quality assurance procedure AP-SIII.10Q, Models [164074], Section 3.2. 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.” There are additional technical modeling bases (assumptions) related to the modeling framework that are documented in Section 6 of this AMR (primarily in Section 6.3). Underlying assumptions are embodied in the transport parameters used in the SZ Transport Abstraction Model and in the SZ 1-D Transport Model for decay chains. Complete descriptions of these underlying assumptions and associated justification are presented in the revision to the Site-Scale Saturated Zone Transport model report (BSC 2003 [162419], Section 5), the Saturated Zone In-Situ Testing scientific analysis report (BSC 2003 [162415], Section 5), and in the Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [163932], Section 5). 1. It is assumed that the equilibrium, linear sorption model applies to sorption of radionuclides in the matrix of the volcanic units and in the alluvium of the valley-fill units. This assumption is carried forward from the Site-Scale Saturated Zone Transport model report (BSC 2003 [162419], Section 6.3). The Kd model of equilibrium, linear sorption is an applicable approximation of sorptive behavior in both laboratory experiments and at the field scale. In addition, the ranges in uncertainty distributions for sorption coefficients of radionuclides encompass the transport results that would be obtained using other non-linear models of sorption behavior. The contrasts in slope of the isotherm for moderately nonlinear sorptive behavior fall within the range of linear isotherms considered in the uncertainty distributions for sorption coefficients used in the modeling. This assumption is used in Sections 6.3.1, 6.5.1, and 6.5.2.8. This assumption needs no further confirmation, given that a wide range of non-linear sorptive behavior is encompassed by the uncertainty distributions in sorption coefficients used in the SZ Transport Abstraction Model and in the SZ 1-D Transport Model. 2. 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 Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [163932], 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. 3. 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 Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [163932], Section 6.3). The MDL-NBS-HS-000021, REV 00 29 July, 2003 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 may occur. The alternative to this assumption, 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. 4. The assumption is made that the average concentration of radionuclides in the groundwater supply of the hypothetical community is an appropriate estimate of radionuclide concentration for the calculation of radiological dose. Realistically, the concentrations of radionuclides encountered by wells in the hypothetical community 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. This assumption is used in Section 6.3.3. This assumption needs no further confirmation, given that there is a regulatory basis for this approach to calculating average concentrations of radionuclides and radiological dose at 10 CFR 63.332 (10 CFR 63 [156605]). 5. 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 Saturated Zone In-Situ Testing scientific analysis report (BSC 2003 [162415], Section 6.2.6). The inferred flowpath 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 2003 [162415]), 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. 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. 6. 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 reality, 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 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 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, MDL-NBS-HS-000021, REV 00 30 July, 2003 given that this simplified approach tends to underestimate the transport times for radionuclides in the SZ and is thus pessimistic with regard to repository performance. 7. 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 basically the same under glacial-transition climatic conditions in simulations using the SZ regional-scale flow model (D’Agnese et al. 1999 [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 shown to underestimate radionuclide transport times in sensitivity studies documented in BSC 2003 [162419], Attachment V. 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. MDL-NBS-HS-000021, REV 00 31 July, 2003 6. MODELS 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 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 model. The general approach to modeling radionuclide migration and the assessment of uncertainty in the SZ is also described by Arnold et al. 2003 [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 model. In the TSPA 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 (10 CFR 63.302 (10 CFR 63 [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 [164314], in which the method is called the transfer function model. The most important assumptions of the convolution method are linear system behavior and steady-state flow conditions in the saturated zone. The SZ 1-D Transport Model is used in the TSPA 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 from these radioactive decay chains are significant contributors to the total radiological dose, regulations concerning groundwater protection contained at 10 CFR 63.331 (10 CFR 63 [156605]) require explicit analysis of their concentrations in the water supply of the critical group. Consequently, only the results for daughter-radionuclides from the SZ 1-D Transport Model are input to the TSPA simulations. Although transport of the parent radionuclides is also included in the SZ 1-D Transport Model, the results for parentradionuclides input to the TSPA simulations are those derived from the SZ Transport Abstraction Model. The SZ 1-D Transport Model for TSPA differs from the SZ Transport Abstraction Model in that it is implemented directly with the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) in the TSPA model. MDL-NBS-HS-000021, REV 00 32 July, 2003 6.2 FEATURES, EVENTS, AND PROCESSES FOR THIS MODEL REPORT The development of a comprehensive list of FEPs potentially relevant to post-closure performance of the potential Yucca Mountain repository is an ongoing, iterative process based on site-specific information, design, and regulations. The approach for developing an initial list of FEPs in support of the TSPA-SR (CRWMS M&O 2000 [153246]) was documented by Freeze et al. 2001 [154365]. The initial FEPs list contained 328 FEPs, of which 176 were included in TSPA-SR models (CRWMS M&O 2000 [153246], Tables B-9 through B-17). To support the TSPA-LA, the FEPs list was re-evaluated in accordance with The Enhanced Plan for Features, Events, and Processes (FEPs) at Yucca Mountain (BSC 2002 [158966], Section 3.2). The included FEPs abstractions incorporated in the TSPA-LA model, which are implemented through specific process models or input parameters, are specifically addressed in saturated zone model reports (Table 6-1). The rationale for excluding a FEP from the TSPA-LA model will be given in the upcoming revision (REV02) of Features, Events, and Processes in SZ Flow and Transport (CRWMS M&O 2001 [153931]). The assignments of included FEPs to SZ reports for documentation are found in the Technical Work Plan For: Saturated Zone Flow and Transport Modeling and Testing, TWP-NBS-MD-000002 (BSC 2003 [163965], Section 2.5). Table 6-1. Included FEPs for the Saturated Zone TSPA-LA FEP Number FEP Name Responsible SZ Report 1.2.02.01.0A Fractures this report 1.2.02.02.0A Faults this report 1.4.07.02.0A Wells this report 2.2.03.01.0A Stratigraphy Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 2.2.03.02.0A Rock Properties of Host Rock and Other Units this report 2.2.07.12.0A Saturated Groundwater Flow in the Geosphere Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 2.2.07.13.0A Water-Conducting Features in the SZ this report 2.2.07.15.0A Advection and Dispersion in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.07.16.0A Dilution of Radionuclides in Groundwater this report 2.2.07.17.0A Diffusion in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.08.01.0A Chemical Characteristics of Groundwater in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.08.06.0A Complexation in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.08.08.0A Matrix Diffusion in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.08.09.0A Sorption in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 2.2.08.10.0A Colloid Transport in the SZ this report MDL-NBS-HS-000021, REV 00 33 July, 2003 FEP Number FEP Name Responsible SZ Report 2.2.08.11.0A Groundwater Discharge to Surface Within the Reference Biosphere this report 2.2.10.03.0A Natural Geothermal Effects on Flow in the SZ Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 2.2.12.00.0B Undetected Features in the SZ this report 3.1.01.01.0A Radioactive Decay and Ingrowth this report Table 6-2 lists the FEPs included in the TSPA-LA for which this model report provides the technical basis and provides a summary of their disposition in TSPA-LA. Table 6-3 lists the FEPs that are partially addressed by the results of this model report. These results are used elsewhere (as shown in Table 6-1) to determine the include/exclude status of the FEP and/or its implementation in TSPA-LA. Details of the implementation of these FEPs are summarized in Sections 5, 6.3, 6.5, and 6.7. MDL-NBS-HS-000021, REV 00 34 July, 2003 Table 6-2. Saturated Zone Included FEPs for Which This Model Report Provides the Technical Basis FEP Number and Name FEP Description Section in Report Where FEP Discussed Disposition in TSPA-LA 1.2.02.01.0A Fractures Groundwater flow in the Yucca Mountain region and transport of any released radionuclides may take place along fractures. The rate of flow and the extent of transport in fractures are influenced by characteristics such as orientation, aperture, asperity, fracture length, connectivity, and the nature of any linings or infills. 6.5.2.1, 6.5.2.4, 6.5.2.5, 6.5.2.9, 6.5.2.10, 6.5.2.12 6.5.2.15 The SZ Transport Abstraction Model includes fractures and uncertainty in the hydraulic and transport properties of the fracture system in volcanic units along the flow path from beneath the repository. The characteristics of the fracture properties such as fracture orientation, connectivity, aperture size, degree of infilling, and tortuosity are modeled in the SZ Transport Abstraction Model and the SZ 1-D Transport Model through the following probabilistically modeled parameters: flowing interval porosity (FPVO), flowing interval spacing (FISVO), groundwater specific discharge (GWSPD), longitudinal dispersivity (LDISP), horizontal anisotropy (HAVO), and colloid retardation (CORVO). 1.2.02.02.0A Faults Numerous faults of various sizes have been noted in the Yucca Mountain Region and in the repository area specifically. Faults may represent an alteration of the rock permeability and continuity of the rock mass, alteration or short-circuiting of the flow paths and flow distributions close to the repository, and represent unexpected pathways through the repository. 6.5.2.1 6.5.2.10 Geologic features and hydrostratigraphic units are explicitly included in the SZ Transport Abstraction Model in a configuration that accounts for the effects of existing faults, based on the hydrogeologic framework model. Model configuration of these discrete features is developed in the SZ Site-Scale Flow Model (BSC 2003 [162649], Section 6.3.2 ). The offsets of hydrostratigraphic units across major faults are incorporated into the model, and some key faults (e.g., Solitario Canyon fault, Highway 95 fault, and Fortymile Wash structure) are explicitly included as high- or low-permeability features. Model parameters, including horizontal anisotropy (HAVO) and groundwater specific discharge (GWSPD), implicitly include the potential impacts of faults on groundwater flow and are modeled probabilistically to account for the uncertainty in hydraulic properties associated with faults and fractures in the volcanic units. MDL-NBS-HS-000021, REV 00 35 July, 2003 FEP Number and Name FEP Description Section in Report Where FEP Discussed Disposition in TSPA-LA 1.4.07.02.0A Wells One or more wells drilled for human use (e.g., drinking water, bathing) or agricultural use (e.g., irrigation, animal watering) may intersect the contaminant plume. 5. 6.3.3 The effects of wells on the dose to members of the critical group are included through the volume of contaminated groundwater used by that group. The groundwater system in the vicinity of the hypothetical community’s well system is modeled assuming that all the contaminants discharged at the 18-km boundary are intercepted by the community’s wells. The total volume extracted from all wells to be used by the farming community is 3,000 acre-feet per year (per guidance given in 10 CFR Part 63 Subpart 63.332, (3) [156605]). 2.2.03.02.0A Rock Properties of Host Rock and Other Units Physical properties such as porosity and permeability of the relevant rock units, soils, and alluvium are necessary for the performance assessment. Possible heterogeneities in these properties should be considered. Questions concerning events and processes that may cause these physical properties to change over time are considered in other FEPs. 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 Geologic features and heterogeneous hydrostratigraphic units are explicitly included in the SZ Transport Abstraction Model as cells with specific hydrologic parameter values in a configuration based on the hydrogeologic framework used in the SZ Site-Scale Flow Model (BSC 2003 [162649], Section 6.3.2). Spatial variability in rock properties is encompassed within uncertainty distributions for key parameters, such as groundwater specific discharge (GWSPD), horizontal anisotropy (HAVO), flowing interval spacing (FISVO), and sorption coefficients. Uncertainty in the location of the contact between alluvium and volcanic units at the southern end of the site-scale model is modeled probabilistically using the parameters related to the northern and western boundaries of the alluvial uncertainty zone, respectively (FPLAN and FPLAW). 2.2.07.13.0A Water- Conducting Features in the SZ Geologic features in the saturated zone may affect groundwater flow by providing preferred pathways for flow. 6.5.2.1, 6.5.2.4, 6.5.2.5, 6.5.2.9, 6.5.2.10 Groundwater flow in fractures of the volcanic units is an explicit feature of the SZ Transport Abstraction Model and the SZ 1-D Transport Model. These models simulate saturated flow and advective transport through flowing intervals, a subset of water-conducting features within the fracture system. The uncertainty in the system is represented in the model using probabilistic simulations of flowing interval porosity (FPVO), flowing interval spacing (FISVO), groundwater specific discharge (GWSPD), longitudinal dispersivity (LDISP), and horizontal anisotropy (HAVO). The ranges of uncertainty in these parameters encompass the possibility of channelized flow along preferred pathways. MDL-NBS-HS-000021, REV 00 36 July, 2003 FEP Number and Name FEP Description Section in Report Where FEP Discussed Disposition in TSPA-LA 2.2.07.16.0A Dilution of Radionuclides in Groundwater Dilution due to mixing of contaminated and uncontaminated water may affect radionuclide concentrations in groundwater during transport in the saturated zone and during pumping at a withdrawal well. 5., 6.5.2.9, 6.7.2 The process of transverse hydrodynamic dispersion is explicitly incorporated in the SZ Transport Abstraction Model, leading to dilution of simulated contaminant concentrations. Dilution as a result of pumping is implicitly included in the TSPA exposure model. The SZ Transport Abstraction Model is used to estimate the flux of contaminants into the volume of water consumed in the regulatory-mandated exposure scenario. The volume of water (per guidance given in 10 CFR Part 63 Subpart 63.332, (3) [156605]) pumped from the hypothetical farming community is 3000 acre-feet (about 3.7 x 109 liters) which is larger than the simulated volumetric flow of contaminated groundwater crossing the 18 km boundary. Therefore, the degree of dilution is the ratio of the flux of contaminated groundwater to volume of water pumped by the hypothetical farming community. 2.2.08.10.0A Colloidal Transport in the SZ Radionuclides may be transported in groundwater in the SZ as colloidal species. Types of colloids include true colloids, pseudo colloids, and microbial colloids. 6.3.1, 6.5.1, 6.5.2.11, 6.5.2.12 The colloid-facilitated transport of radionuclides is explicitly included in the SZ Transport Abstraction Model and the SZ 1- D Transport Model. Colloids are subject to advection in the fractures of tuff units and are excluded from diffusion into the rock matrix. Radionuclide transport in association with colloids is simulated to occur by two modes: 1) as reversibly sorbed onto colloids, and 2) as irreversibly attached to colloids. Reversible sorption of radionuclides may occur onto any colloidal material present in the groundwater, and measurements of natural colloids in groundwater of the SZ include mineral and microbial colloids. Colloids with irreversibly attached radionuclides originate from the degradation of the glass waste form in the repository. The parameters related to reversible sorption onto colloids are Kd_Am_Col, Kd_Pu_Col, Kd_Cs_Col, and Conc_Col. The parameters related to the retardation of colloids with irreversibly attached radionuclides are CORVO and CORAL. 2.2.08.11.0A Groundwater Discharge to Surface Within the Reference Biosphere Radionuclides transported in groundwater as solutes or solid materials (colloids) from the far field to the biosphere will discharge at specific "entry" points that are at or near the receptor location. Surface discharge points may be to holding ponds, to unsaturated soils, or through wells used for irrigation, livestock, or drinking water supply. 5, 6.3.3 The groundwater system in the vicinity of the hypothetical community’s well system is modeled such that all the contaminants discharged at the 18-km boundary are intercepted by the community’s wells. Direct discharge of groundwater to the surface via springs, unsaturated soils, etc. is not included, given the simplifying assumption of complete capture of the contaminant plume in the wells. MDL-NBS-HS-000021, REV 00 37 July, 2003 FEP Number and Name FEP Description Section in Report Where FEP Discussed Disposition in TSPA-LA 2.2.12.00.0B Undetected Features in the SZ This FEP is related to undetected features in the SZ portion of the geosphere that can affect long-term performance of the disposal system. Undetected but important features may be present and may have significant impacts. These features include unknown active fracture zones, inhomogeneities, faults and features connecting different zones of rock, and different geometries for fracture zones. 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 Undetected features in the SZ, such as fracture zones, inhomogeneities, and faults and their potential impacts on groundwater flow are implicitly incorporated in the SZ Transport Abstraction Model and the SZ 1-D Transport Model. Such features could impact groundwater flow with regard to the specific discharge in the SZ system, the direction of groundwater flow from horizontal anisotropy, and/or the degree of groundwater flow focusing in flowing intervals. The impacts of such potential features are encompassed within uncertainty distributions for key parameters, such as groundwater specific discharge (GWSPD), horizontal anisotropy (HAVO), flowing interval spacing (FISVO). 3.1.01.01.0A Radioactive Decay and Ingrowth Radioactivity is the spontaneous disintegration of an unstable atomic nucleus that results in the emission of subatomic particles. Radioactive isotopes are known as radionuclides. Radioactive decay of the fuel in the repository changes the radionuclide content in the fuel with time and generates heat. Radionuclide quantities in the system at any time are the result of the radioactive decay and the growth of daughter products as a consequence of that decay (i.e., ingrowth). Over a 10,000-year performance period, these processes will produce daughter products that need to be considered in order to adequately evaluate the release and transport of radionuclides to the accessible environment. 6.3.1, 6.5, 6.5.1 Radioactive decay during transport in the SZ is explicitly included in the convolution integral method used to couple the SZ Transport Abstraction Model with the TSPA model and in the SZ 1-D Transport Model. Ingrowth is accounted for in two different ways in the TSPA models. First, the initial inventory in the waste is adjusted to account for the radionuclide parents that obviously impact the simulated dose, resulting in a “boosting” of the initial inventory of some daughter products in the SZ Transport Abstraction Model. Second, a separate set of SZ transport simulations is run to calculate explicitly the decay and ingrowth for the four main radionuclide chains, using the SZ 1-D Transport Model. MDL-NBS-HS-000021, REV 00 38 July, 2003 Table 6-3. Saturated Zone Included FEPs Supported by the Results in This Model Report FEP Number and Name FEP Description Section in Report Where FEP is Discussed 2.2.03.01.0A Stratigraphy Stratigraphic information is necessary information for the performance assessment. This information should include identification of the relevant rock units, soils and alluvium, and their thickness, lateral extents, and relationships to each other. Major discontinuities should be identified. 6.5.2.1 6.5.2.2 2.2.07.15.0A Advection and Dispersion in the SZ Advection and dispersion processes affect contaminant transport in the SZ. 6.5.2.1 6.5.2.9 6.5.2.10 2.2.07.17.0A Diffusion in the SZ Molecular diffusion processes may affect radionuclide transport in the SZ. 6.5.2.1 6.5.2.4 6.5.2.5 6.5.2.6 2.2.08.01.0A Chemical Characteristics of Groundwater in the SZ Chemistry and other characteristics of groundwater in the saturated zone may affect groundwater flow and radionuclide transport of dissolved and colloidal species. Groundwater chemistry and other characteristics, including temperature, pH, Eh, ionic strength, and major ionic concentrations, may vary spatially throughout the system as a result of different rock mineralogy. This FEP is included through distributions of Kd values. 6.5.2.8 6.5.2.11 6.5.2.12 2.2.08.06.0A Complexation in the SZ Complexing agents such as humic and fulvic acids present in natural groundwaters could affect radionuclide transport in the SZ. This FEP is included through distributions of Kd values. 6.5.2.8 6.5.2.11 6.5.2.12 2.2.08.08.0A Matrix Diffusion in the SZ Matrix diffusion is the process by which radionuclides and other species transported in the SZ by advective flow in fractures or other pathways move into the matrix of the porous rock by diffusion. Matrix diffusion can be a very efficient retarding mechanism, especially for strongly sorbed radionuclides, due to the increase in rock surface accessible to sorption. 6.5.2.4 6.5.2.5 6.5.2.6 2.2.08.09.0A Sorption in the SZ Sorption of dissolved and colloidal radionuclides in the SZ can occur on the surfaces of both fractures and matrix in rock or soil along the transport path. Sorption may be reversible or irreversible, and it may occur as a linear or nonlinear process. Sorption kinetics and the availability of sites for sorption should be considered. Sorption is a function of the radioelement type, mineral type, and groundwater composition. 6.5.2.8 6.5.2.11 6.5.2.12 MDL-NBS-HS-000021, REV 00 39 July, 2003 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 and the SZ Site-Scale Transport Model (BSC 2003 [162649], Section 6.3; BSC 2003 [162419], Sections 5 and 6.3). The SZ Site-Scale Flow Model and alternative conceptualizations of groundwater flow are also described by Zyvoloski et al. 2003 [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 one-dimensional 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 simulations. 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 flow system (BSC 2003 [162649], 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 [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 2003 [162649], 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 may impart horizontal anisotropy in the permeability between the major faults in this area of the SZ system. Groundwater flow enters the SZ site-scale flow system primarily as underflow at the lateral boundaries of the model domain (BSC 2003 [162649], 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 2003 [162649], 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 MDL-NBS-HS-000021, REV 00 40 July, 2003 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 time 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 2003 [162419], Section 6.3). In addition, radionuclides are subject to radioactive decay and ingrowth during migration in the SZ in the TSPA analyses. These processes are illustrated in Figure 6-1 and Figure 6-2. Figure 6-1. Illustration of the Conceptual Model of Radionuclide Transport Processes in the Saturated Zone MDL-NBS-HS-000021, REV 00 41 July, 2003 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 2003 [162419], 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. 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 2003 [162419], Section 6.5.2.4). 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 tends to support 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 may 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. MDL-NBS-HS-000021, REV 00 42 July, 2003 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. In fractured media, sorption is conceptualized to occur in the rock matrix; no sorption is conceptualized to occur on the fracture surfaces or coatings. 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 2003 [163932], 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 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. 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 kinetic 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 those radionuclides that have parent radionuclides. In this simplified approach, the mass of the daughter radionuclide is boosted by the maximum mass of the parent radionuclide that would decay over the remaining TSPA simulation time. The boosting of the daughter radionuclide mass occurs for the input to the SZ Transport Abstraction Model (i.e., at the UZ – SZ interface). The daughter radionuclides that are boosted in this manner are Pu-239 (from Am- 243), Np-237 (from Am-241), U-236 (from Pu-240), U-238 (from Pu-242), and U-234 (from U- 238 and Pu-238). MDL-NBS-HS-000021, REV 00 43 July, 2003 Figure 6-2. Illustration of the Conceptual Model of Colloid-Facilitated Radionuclide Transport in Fractured Tuff in the Saturated Zone MDL-NBS-HS-000021, REV 00 44 July, 2003 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. It is also assumed that the groundwater flow conditions in the SZ system are in steady state. This approach is carried forward from the Site-Scale Saturated Zone Flow Model report (BSC 2003 [162649], Section 5). The Site-Scale Saturated Zone 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 [100465], p. 29-32). The convolution integral method has been extended to incorporate multiple steady-state flow conditions for alternative climate states in the TSPA 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. Although this dual-porosity conceptual model of radionuclide transport represents a significant simplification of the complex fracture network 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 simulations tends to capture 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 Site-Scale Saturated Zone Transport model report (BSC 2003 [162419], 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 farming community 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, the model does implicitly account for the drawdown of water levels associated with pumping at the southern MDL-NBS-HS-000021, REV 00 45 July, 2003 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 threedimensional SZ Transport Abstraction Model is simplified to one-dimensional 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 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. 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 daughter product in three of the radionuclide decay chains simulated in the one-dimensional 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 daughter radionuclides have relatively short half lives (less than 25 years). This approach overestimates the concentration of daughter products because it implies an instantaneous increase in the mass of the final daughter product to be in equilibrium with the mass of parent radionuclide present. The groundwater flux within each one-dimensional “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 flowpath is derived from the corresponding region of the three-dimensional SZ Transport Abstraction Model. MDL-NBS-HS-000021, REV 00 46 July, 2003 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 [153246], Section 4.4). The conceptual model of radionuclide releases from the SZ to the biosphere includes pumping of groundwater from wells by the hypothetical farming community. The location of this hypothetical farming community is specified in the regulations for the Yucca Mountain site (10 CFR 63.302 (10 CFR 63 [156605])). In addition, the quantity of groundwater used by the hypothetical farming community is specified by the regulations to be 3,000 acre-ft/year (10 CFR 63.332 (10 CFR 63 [156605])). The conceptualization of the pumping system is that the entire plume of radionuclides in the SZ would be captured by the pumping wells of the hypothetical farming community and that these contaminants would be homogeneously distributed in the specified volume of groundwater. Although variations in radionuclide concentration would probably exist among the pumping wells, the radiological dose among the population of this community would tend to be homogenized by exchange of radionuclides through various pathways within the biosphere. 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 package and highly focused transport of radionuclides in the UZ flow system, as may occur early in the post-closure 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 tends to maximize 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. 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). MDL-NBS-HS-000021, REV 00 47 July, 2003 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 2003 [162419], Section 6.5.2). 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) (10 CFR 63.302 (10 CFR 63 [156605])) in the SZ is captured by pumping wells of the hypothetical farming community. This approach implies that the total volumetric groundwater usage by the hypothetical community 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 alternative conceptual models (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 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. Alternative Conceptual Models Considered Alternative Conceptual Model 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). MDL-NBS-HS-000021, REV 00 48 July, 2003 Alternative Conceptual Model Key Assumptions Screening Assessment and Basis 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. 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 non-sorbing 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. MDL-NBS-HS-000021, REV 00 49 July, 2003 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 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 2003 [162415], Section 6.2.6). The uncertainty distribution for HAVO indicates that there is a 10% 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% 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 1, is included in this continuous uncertainty distribution for the parameter HAVO. MDL-NBS-HS-000021, REV 00 50 July, 2003 6.5 MODEL FORMULATION FOR BASE-CASE MODELS SZ Transport Abstraction Model The SZ Site-Scale Flow Model (BSC 2003 [162649]) and the SZ Site-Scale Transport Model (BSC 2003 [162419]) 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 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 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 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 BSC 2003 [162649], 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. MDL-NBS-HS-000021, REV 00 51 July, 2003 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 for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 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 MDL-NBS-HS-000021, REV 00 52 July, 2003 Radionuclide transport is simulated in the SZ Transport Abstraction Model using a particle tracking method. This method, as implemented by the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [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, 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. In the TSPA analyses the convolution integral method used in the SZ Transport Abstraction Model 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 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; and, 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 v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]) in the TSPA 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 saturated zone are incorporated into the convolution integral analysis in the TSPA by assuming instantaneous change from one steady-state flow condition to another steady-state condition in the saturated zone. Changes in climate state are assumed to affect the magnitude of groundwater flux through the saturated zone system but have a negligible impact on flowpaths. 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 saturated zone specific discharge. Three climate states are defined for the period from repository closure to 10,000 years in the future in the TSPA-SR calculations (CRWMS M&O 2000 [153246], p. 3-25). For the base-case TSPA analyses, present-day climatic conditions are modeled to occur from the present to 600 MDL-NBS-HS-000021, REV 00 53 July, 2003 years in the future, monsoonal conditions are imposed from 600 years to 2000 years in the future, and glacial-transition climatic conditions occur from 2000 years to 10,000 years. 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. Note that the glacialtransition climate state is approximately equivalent to the long-term average climate state, as referenced in CRWMS M&O 1998 [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 SZ regional-scale flow model (D’Agnese et al., 1999 [120425]; CRWMS M&O 1998 [100365]) and on the infiltration for the UZ site-scale flow model (BSC 2003 [164431], Section 6.1.4). Simulations using the SZ regional-scale flow model were conducted for the past-climate state that likely existed about 21,000 years ago (D’Agnese et al., 1999 [120425]). This climatic state approximately corresponds to the glacial-transition state, as defined for TSPA-SR calculations. A comparison of the groundwater flux in the SZ near Yucca Mountain under past-climate conditions (i.e., 21,000 years ago) using the SZ regionalscale 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 SZ regional-scale flow model. Information on the increased infiltration through the UZ sitescale flow model is used as the basis for estimating flux increases in the SZ for monsoonal conditions (DTN: LB990801233129.015 [118730]). Values of total infiltration in the area of the UZ site-scale flow model (second column of Table 6-5) are taken from the total of specified mass flow in the “GENER” card of the TOUGH2 input files “pa_chm1.dat”, “pa_glam1.dat”, and “pa_monm1.dat”. Similarly, the total infiltration through the UZ site-scale flow model for present and glacial-transition climatic conditions is calculated (DTN: LB990801233129.004 [117129] and DTN: LB990801233129.009 [118717]). Note in Table 6-5 that the ratio of glacial-transition infiltration in the UZ model to the present-day infiltration is the same value as the estimate of increased SZ groundwater flux from the SZ regional-scale 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 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. MDL-NBS-HS-000021, REV 00 54 July, 2003 Table 6-5. Groundwater Flow Scaling Factors for Climate Change Climate State Infiltration, UZ Model (Mean Case) (kg/s) Ratio to Present Climate, UZ Model SZ Groundwater Flux Ratio from SZ Regional- Scale Model SZ Groundwater Flux Ratio for TSPA Simulations Present-Day 5.64 a 1.0 1.0 1.0 Glacial- Transition 22.0 b 3.9 3.9 d 3.9 Monsoonal 15.2 c 2.7 N/A 2.7 a DTN: LB990801233129.004 [117129] b DTN: LB990801233129.009 [118717] c DTN: LB990801233129.015 [118730] d CRWMS M&O 1998 [100365], Table 8-16, p. T8-20. SZ 1-D Transport Model The SZ 1-D Transport Model is implemented with the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) in the TSPA simulator as a series of “pipes.” The same radionuclide transport processes that are simulated in the three-dimensional 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 three-dimensional 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 one-dimensional model. Average specific discharge along different segments of the flowpath 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 one-dimensional 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 2003 [162649], Section 6.5) and the SZ Site-Scale Transport Model (BSC 2003 [162419], Section 6.5.2) are presented in the corresponding reports MDL-NBS-HS-000021, REV 00 55 July, 2003 for these models. The SZ Site-Scale Flow Model forms the direct basis for the SZ Site-Scale Transport Model and the SZ Site-Scale Transport Model forms the direct basis for the SZ Transport Abstraction Model. Therefore, the mathematical bases for those models, as implemented by the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [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 BSC 2003 [162419], Section 6.5.2 for description of the particle tracking method). This method exhibits very limited numerical dispersion relative to standard finitedifference 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 analyses. The convolution integral method takes the radionuclide mass breakthrough curve for a continuous, unitary mass source from the SZ and the time-varying radionuclide mass from the UZ as inputs. The output is the timevarying 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 ) ( ) ( ) ( & (Equation 6-1) where Msz(t) is the radionuclide mass flux downstream in the SZ [M], t is time [T], ) (t muz & is the time dependent radionuclide mass flux entering the SZ from the UZ [M], t' is a time lag [T], and ) (t M ' is the derivative of the downstream radionuclide mass flux-time response curve [M] to a step input of mass mp [M]. This expression is taken from the convolution integral for concentration (CRWMS M&O 1998 [100365], p. 8-39) and rewritten in terms of radionuclide mass. Correction of Retardation The retardation factor for linear sorption of radionuclides during transport in porous media is defined as (Freeze and Cherry 1979 [101173], p. 404): d b f K R f . + = 1 (Equation 6-2) where Rf is the retardation factor in the porous media [-], .b is the bulk density [M/L3], f is the porosity of the porous media [-], and Kd is the distribution coefficient [L3/M]. The FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]) to be used in the SZ Transport Abstraction Model automatically calculates Rf based on input values of .b , f, and Kd. MDL-NBS-HS-000021, REV 00 56 July, 2003 Effective porosity ( fe ) [-] is a macroscopic parameter that helps account for discrete flow paths and channelized flow (see Section 6.5.2.3). 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 [100365], Equation 8-4, p. 8-55): T e d new d K K f f · = (Equation 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 = (Equation 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 CRWMS M&O 1997 [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 d adjusted d K K K + = (Equation 6-5) as derived from Equation 6-2 and CRWMS M&O 1998 [100365], Equation 8-8, p. 8-54 and 8- 56, and assigning the retardation factor for colloids with reversibly attached radionuclides a value of 1. Kd adjusted is the adjusted distribution coefficient [L3/M] to account for reversible sorption onto colloids. MDL-NBS-HS-000021, REV 00 57 July, 2003 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 one-dimensional advection-dispersion equation for a solute in the fractures (BSC 2003 [162419], Section 6.5.2) 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 , (Equation 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 coll . . - . . = . . 2 2 (Equation 6-7) where coll R 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 coll c f f K b q x C v x C D t C K R K R + - . . - . . = . . . .. . . .. . + + (Equation 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 colloidfacilitated 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 [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 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 + = (Equation 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]. MDL-NBS-HS-000021, REV 00 58 July, 2003 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 are subject to rapid transport without retardation, as described in BSC 2003 [163932], 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 medium, 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 ( - = (Equation 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 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 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+ = ' (Equation 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: MDL-NBS-HS-000021, REV 00 59 July, 2003 ) ( ) ( avg f m avg f f fraction f f f f - - = (Equation 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% of the total rock matrix is available for direct interaction with radionuclide advection and sorption in this example. 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 [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 . . 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 daughter radionuclides by calculating secular equilibrium between the final daughter 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. 228Ra is in secular MDL-NBS-HS-000021, REV 00 60 July, 2003 equilibrium with 232Th in the thorium series. 210Pb is in secular equilibrium with 226Ra in the uranium series. In the model setup, radionuclides 241Am, 243Am, 239Pu, 240Pu, and 242Pu are subject to transport as irreversibly attached to colloids; and 243aAm, 238Pu, 239aPu, 240aPu, 242aPu, 231Pa, 229Th, 230Th, and 232Th are subject to the equilibrium colloid-facilitated transport mode. The one-dimensional 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 [100449]). Figure 6-5. Transport Processes Simulated in One-Dimensional Pipe Pathways in the GoldSim v. 7.50.100 Software Code (STN: 10344-7.50.100-00), BSC 2003 [161572] Each pipe in the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) represents a one-dimensional mass transport model with uniform properties. 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 v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) also provides a graphical MDL-NBS-HS-000021, REV 00 61 July, 2003 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 are 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 v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]). The equation for calculating the retardation factor in the fracture with the coating on fracture surface is: ) ( 1 , , c s c c p m s m K A PT R f . f + + = (Equation 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 , , (Equation 6-14) It should be noted that representation of retardation in the fractures using the coating option in GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) 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 Model and the SZ Transport Abstraction Model. The values of the parameters T and c f 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 MDL-NBS-HS-000021, REV 00 62 July, 2003 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 (~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 three-dimensional 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 flowpath from the repository. A plot of the particle paths in the SZ Transport Abstraction Model indicates that the flowpath 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 flowpaths (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 one-dimensional radionuclide transport model, the length of the alluvium (out to 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). MDL-NBS-HS-000021, REV 00 63 July, 2003 535000 540000 545000 550000 555000 560000 UTM Easting (m) 4050000 4055000 4060000 4065000 4070000 4075000 4080000 4085000 4090000 UTM Northing (m) Source for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 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 MDL-NBS-HS-000021, REV 00 64 July, 2003 The SZ 1-D Transport Model represents a significant simplification of the three-dimensional groundwater flow system, relative to the SZ Transport Abstraction Model. To accurately capture the three-dimensional characteristics of the SZ flow and transport system in this one-dimensional 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. 1000 particles are released beneath the repository 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 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 v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) look-up table in the SZ 1-D Transport Model. Also 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 Average Specific Discharge (m/year) HAVO 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 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 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 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 5-13 km pipe segment MDL-NBS-HS-000021, REV 00 65 July, 2003 (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 13-18 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 v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) 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 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 we know and what we do not know 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 [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 MDL-NBS-HS-000021, REV 00 66 July, 2003 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 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 occurrences of this unit do not occur along the flow path from the repository. Consequently, it is not included in the models as a separate unit. Table 6-8. Model/Analyses Inputs Used in the SZ Transport Abstraction Model and 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 LA0302AM831341.001 [163556] CDF: Probability Value 0.0 0.0 0.05 1.0 0.90 1.6 1.0 6.0 ml/g Epistemic KDNPAL Neptunium sorption coefficient in alluvium LA0302AM831341.001 [163556] 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 LA0302AM831341.001 [163556] Uniform: Minimum 20. Maximum 400. ml/g Epistemic KDSRAL Strontium sorption coefficient in alluvium LA0302AM831341.001 [163556] Uniform: Minimum 20. Maximum 400. ml/g Epistemic KDUVO Uranium sorption coefficient in volcanic units LA0302AM831341.001 [163556] CDF: Probability Value 0.0 0.0 0.05 5.4 0.95 6.9 1.0 20.0 ml/g Epistemic MDL-NBS-HS-000021, REV 00 67 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty KDUAL Uranium sorption coefficient in alluvium LA0302AM831341.001 [163556] 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 LA0302AM831341.001 [163556] Uniform: Minimum 100. Maximum 1000. ml/g Epistemic KDRAAL Radium sorption coefficient in alluvium LA0302AM831341.001 [163556] Uniform: Minimum 100. Maximum 1000. ml/g Epistemic KD_Pu_Vo Plutonium sorption coefficient in volcanic units LA0302AM831341.001 [163556] CDF: Probability Value 0.0 10. 0.25 75. 0.95 100. 1.0 300. ml/g Epistemic KD_Pu_Al Plutonium sorption coefficient in alluvium LA0302AM831341.001 [163556] Beta: Mean 100. Standard Deviation 15. Minimum 50. Maximum 300. ml/g Epistemic KD_Am_Vo Americium sorption coefficient in volcanic units LA0302AM831341.001 [163556] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. ml/g Epistemic KD_Am_Al Americium sorption coefficient in alluvium LA0302AM831341.001 [163556] Truncated Normal: Mean 5500. Standard Deviation 1500. Minimum 1000. Maximum 10000. ml/g Epistemic KD_Cs_Vo Cesium sorption coefficient in volcanic units LA0302AM831341.001 [163556] CDF: Probability Value 0.0 100. 0.05 3700. 1.0 7500. ml/g Epistemic MDL-NBS-HS-000021, REV 00 68 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty KD_Cs_Al Cesium sorption coefficient in alluvium LA0302AM831341.001 [163556] Truncated Normal: Mean 728. Standard Deviation 464. Minimum 100. Maximum 1000. ml/g Epistemic FISVO Flowing interval spacing in volcanic units SN9907T0571599.001 [122261] CDF: (Log-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 CORAL Colloid retardation factor in alluvium LA0303HV831352.004 [163559] CDF: (Log-transformed) Probability Value 0.0 0.903 0.331 0.904 0.50 1.531 1.0 3.715 NA Epistemic CORVO Colloid retardation factor in volcanic units LA0303HV831352.002 [163558] CDF: (Log-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 NA Epistemic HAVO Ratio of horizontal anisotropy in permeability SN0302T0502203.001 [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. NA Epistemic MDL-NBS-HS-000021, REV 00 69 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty LDISP Longitudinal dispersivity MO0003SZFWTEEP.000 [148744] Truncated Normal: (Logtransformed) Mean 2.0 Standard Deviation 0.75 m Epistemic Kd_Pu_Col Plutonium sorption coefficient onto colloids SN0306T0504103.006 [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 Kd_Am_Col Americium sorption coefficient onto colloids SN0306T0504103.006 [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 [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 [164132] CDF: (Log-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 -3.6 g/ml Epistemic R_U_Kd Correlation coefficient for U Kd in volcanic units and alluvium LA0302AM831341.001 [163556] 0.75 ml/g N/A R_Np_Kd Correlation coefficient for Np Kd in volcanic units and alluvium LA0302AM831341.001 [163556] 0.75 ml/g N/A MDL-NBS-HS-000021, REV 00 70 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty R_Pu_Kd Correlation coefficient for Pu Kd in volcanic units and alluvium LA0302AM831341.001 [163556] 0.50 ml/g N/A R_U_Np Correlation coefficient for U Kd and Np Kd LA0302AM831341.001 [163556] 0.50 ml/g 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 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: (Log-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: (Log-transformed) Probability Value 0.0 -11.3 0.08 -10.7 0.50 -10.3 0.83 -9.9 1.0 -9.3 m^2/s Epistemic MDL-NBS-HS-000021, REV 00 71 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty GWSPD Groundwater specific discharge multiplier Internal to this report CDF: (Log-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 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 MDL-NBS-HS-000021, REV 00 72 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty 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 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 MDL-NBS-HS-000021, REV 00 73 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty 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 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 MDL-NBS-HS-000021, REV 00 74 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty 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 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 [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 MDL-NBS-HS-000021, REV 00 75 July, 2003 Input Name Input Description Input Source (DTN, if applicable) Value or Distribution Units Type of Uncertainty Bulk Density Expected bulk density values per volcanic unit Units 15-13, 10, 8; SN0004T0501399.002 [155046] and SN0004T0501399.003 [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: MO0105HCONEPOR.00 0 [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 MDL-NBS-HS-000021, REV 00 76 July, 2003 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 USGS 2001 [158608], Table 6-2 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 to the biosphere. This uncertainty was quantified as a distribution of specific discharge in the volcanic aquifer near Yucca Mountain by the SZ expert elicitation project (CRWMS M&O 1998 [100353], p. 3-43). 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 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 [100353], p. 3-43). 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) (BSC 2003 [162415], 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 MDL-NBS-HS-000021, REV 00 77 July, 2003 63.302 (10 CFR 63 [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, [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. The range of estimated specific discharge at the ATC spans about a factor of 7.8 (i.e., 1.2 m/year to 9.4 m/year). This indicates range of uncertainty in specific discharge that 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 [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% 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% 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% 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. 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. MDL-NBS-HS-000021, REV 00 78 July, 2003 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 DTN: SN0306T0502103.007 Figure 6-7. CDF of Uncertainty in Groundwater Specific Discharge Multiplier 6.5.2.2 Alluvium Uncertainty Zone Uncertainty in the geology below the water table exists along the inferred flowpath from the potential repository at distances of approximately 10 km to 20 km down gradient 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 vs. 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 MDL-NBS-HS-000021, REV 00 79 July, 2003 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 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 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). MDL-NBS-HS-000021, REV 00 80 July, 2003 540000 545000 550000 555000 560000 UTM Easting (m) 4050000 4055000 4060000 4065000 4070000 4075000 4080000 UTM Northing (m) NC-EWDP-2D NC-EWDP-19D NC-EWDP-22S NC-EWDP-10S UE-25 J-12 UE-25 JF#3 Source for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] Source for well locations: DTN: GS010908312332.002 [163555] DTN: GS030108314211.001 [163483] Note: 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 MDL-NBS-HS-000021, REV 00 81 July, 2003 6.5.2.3 Effective Porosity of Alluvium For the TSPA-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 [147972], Section 6.3). The basis for this parameter is from Bedinger et al. 1989 [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 [129676]) include a study of hydraulic characteristics of alluvium within the Southwest Basin and Range Province. This study is relevant to the local basin fill conditions and provides values for effective porosity as a stochastic parameter. Since TSPA-SR a site-specific value was determined for effective porosity from well EWDP-19D1 at the ATC based on a single-well pumping test (BSC 2003 [162415], Sections 6.4 and 6.5). 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. Effective porosity is important in determining the average linear ground water 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 discussion in Section 6.5.1, Equation 6-3. 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 one realization to the next. In comparison, constant parameters are constant spatially and also do not change from realization to realization. The parameter input sources used in this analysis are described in Error! Reference source not found. 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 used for TSPA-SR is shown in Figure 6-9. Figure 6-9 compares the distribution of Bedinger et al. 1989 [129676] (DTN: MO0105HCONEPOR.000 [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 from well EWDP-19D1 of 0.1 (BSC 2003 [162415], Section 6.4) is shown on Figure 6-9. This is considered a corroborative data point and falls within the uncertainty distribution for TSPA-SR. MDL-NBS-HS-000021, REV 00 82 July, 2003 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 DTN: MO0003SZFWTEEP.000 [148744] BSC 2003 [162415], Section 6.5 Burbey and Wheatcraft 1986 [129679], pp. 23-24 DOE 1997 [103021], Table 8-1, p. 8-5 and Table 8-2, p. 8-6 NOTE: The dashed black line is Neuman (MO0003SZFWTEEP.000 [148744]); the solid heavy blue line is MO0105HCONEPOR.000 [155044]; the solid pink line is Gelhar (MO0003SZFWTEEP.000 [148744]); the solid blue block is the effective porosity value calculated from EWDP-19D1 (BSC 2003 [162415], 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 [103021], Table 8-1, mean matrix porosity; the diamond outlined shapes are Burbey and Wheatcraft 1986 [129679] total porosity; the X is DOE 1997 [103021], Table 8-2, total porosity and the square outlined shape is DOE 1997 [103021], Table 8-1 mean bulk porosity. Figure 6-9. Effective Porosity Distributions and Values Compared The upper bound of the uncertainty distribution for effective porosity is re-evaluated because of new site-specific data obtained since 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 [129679], p. 23 and 24) within the Nevada Test Site (NTS) but several kilometers to the east, in Frenchman Flat; and total porosity shown in Tables 8-1 and 8-2 of the DOE 1997 [103021] report, pp. 8-5 and 8-6, see Table 6-10. The computed total porosity values from 19-D1 are shown in Table 6-11, which have an average value of 0.24. MDL-NBS-HS-000021, REV 00 83 July, 2003 Table 6-10. Total Porosity Summary( fT) Reference Total Porosity Comments DOE 1997 [103021], Table 8-1, p. 8-5 0.36 Mean bulk porosity DOE 1997 [103021], Table 8-2, p. 8-6 0.35 Total porosity Burbey and Wheatcraft 1986 [129679], pp. 23-24 0.34 Average of porosity values from Table 3 of that study average of above 0.35 N/A 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. 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. 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 DTN: SN0306T0502103.007 Figure 6-10. CDF of Uncertainty in Effective Porosity in the Alluvium MDL-NBS-HS-000021, REV 00 84 July, 2003 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. Figure 6-11. Example of Flowing Interval Spacing (BSC 2001 [156965]) 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 BSC 2001 [156965], Probability Distributions for Flowing Interval Spacing. There are no new data available to reevaluate the uncertainty distribution for this parameter, therefore a CDF based on the log-normal distribution (BSC 2001 [156965], 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 Typical Flowing Interval Spacing Flowing interval Borehole Fractures Typical Fracture Spacing MDL-NBS-HS-000021, REV 00 85 July, 2003 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. 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) DTN: SN0306T0502103.007 Figure 6-12. CDF of Uncertainty in Flowing Interval Spacing 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. 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 [147972], Section 6.7). The basis for this uncertainty distribution includes estimates of fracture porosity in intact MDL-NBS-HS-000021, REV 00 86 July, 2003 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 [147972], Section 6.7). The TSPA-SR probability distribution for the flowing interval porosity has been modified based on new sources of information about 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 AMR (BSC 2003 [161773], p. 41). The estimated average value of fracture porosity is 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 [100328], p. 2-4). 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 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 0.004 and 0.125, respectively (CRWMS M&O 1997 [100328], p. 28). The Nevada Environmental Restoration Project (DOE 1997 [103021]) evaluated the fracture spacing and apertures in seven cores from wells at Pahute Mesa. The volcanic rocks in these cores include the Timber Mountain tuff, Tuff Cones, Belted Range Aquifer and undistinguished welded tuff deposits. The estimated open fracture porosities based on the assumption of parallel plates, range from 6.1 × 10-6 to 4.7 × 10-4 in the welded tuffs and 2.6 × 10-6 to 4.7 × 10-4 in the tuff cores (DOE 1997 [103021], p. 5-14). Similarly, data compiled for TSPA-1993 (Wilson et al. 1994 [100191], Volume 1, Chapter 7, Table 7-19, p. 7-30) indicate average fracture porosities of 8.0×10-5 to 2.8×10-3, in core from USW G-1, USW GU-3, USW G-4 and UE25a#1e, when parallel plate fracture geometry is assumed. 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 4 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 [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) of -5.0, an upper bound of log10 (flowing interval porosity) -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 compared to the TSPA-SR uniform distribution (CRWMS M&O 2000 MDL-NBS-HS-000021, REV 00 87 July, 2003 [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. 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 DTN: SN0306T0502103.007 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 [162956]; Reimus et al. 2002 [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 MDL-NBS-HS-000021, REV 00 88 July, 2003 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; and, 3) the unique properties of a porous media’s lithology at a microscopic scale. The contribution of these uncertainties and variabilities in deriving a value of De is evaluated in the following subsections. 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 more affected by the structural properties of the porous medium, such as porosity, pore size distribution, and pore geometry, than by the mineralogy or geochemistry (Skagius and Neretnieks 1986 [156862], p. 389-398). Specific to Yucca Mountain, diffusion cell experiments documented by Coen 1987 [162960] on dilute sodium halite salt solutions diffusing through NTS tuff samples demonstrated De was directly proportional to the variability in matrix porosity and pore size distributions. Buchholtz ten Brink et al. 1991 [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. As an example, Bear 1972 [156269], Sections 4.8.2 and 4.8.3 relate effective matrix diffusion to porosity, formation factor (derived from geophysical logs), and the free water molecular diffusion coefficient as follows: F D Dm f 0 = (Equation 6-15) where Dm 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. MDL-NBS-HS-000021, REV 00 89 July, 2003 Domenico and Schwartz 1990 [100569], p. 368 document the relationship between porosity and effective diffusion with the following: 0 ) / ( D Dm t f = (Equation 6-16) where t (= Le/L) is the tortuosity [-], Le is the length of the channel for the fluid particle [L], 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 [100569], p. 368 define a range for Dm with the following empirical equation: Dm = 2 0 Df to 2 0 2 . .. . . .. . - f f D (Equation 6-17) Bound 1 Bound 2 This relationship captures the uncertainty and range of Dm in a heterogeneous system. It is only dependent 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 effective diffusion coefficient in the volcanic rock matrix (De) can be calculated. Mean porosity values were calculated using the relative humidity (RH) porosities found in DTN MO0109HYMXPROP.001 [155989] for the SZ hydrostratigraphic units defined in Characterization of Hydrogeologic Units Using Matrix Properties, Yucca Mountain, Nevada (Flint 1998 [100033]) as input. RH porosity is measured by drying the sample in an oven for 48 hours at 60oC and 65% relative humidity. (Note, Flint’s hydrostratigraphic units are subunits of the SZ 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 her units are heavily based on matrix rather than fracture properties, and it is the matrix properties that are important to diffusion in the SZ. Using RH porosity values in MO0109HYMXPROP.001 [155989], the minimum “average” porosity is 0.042, located in the Calico Hills-vitric unit (a subunit of the SZ’s Upper Volcanic Confining, Unit 14), the maximum “average” is 0.321, 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 in 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 (Equation 6-18) MDL-NBS-HS-000021, REV 00 90 July, 2003 Reimus et al. 2002 [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 are 99Tc (as TcO4 -), 14C (as HCO3 -) and 3HHO. Rock samples were taken from within the vicinity of Yucca Mountain, under Pahute Mesa and Area 25 of the Nevada Test Site. Based on these experiments Reimus et al. 2002 [163008] described three different approaches in deriving De. Two are dependent on linear regression relationships fitting the experimental results to diffusion cell measurements for: 1) both matrix porosity and permeability, and 2) only matrix porosity measurements. The third approach is simply compiling a cumulative distribution function based on their numerous diffusion cell results. Reimus et al. 2002 [163008], Section 4 found that differences in rock type account for 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 as 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 [163008], p. 2.25): ) (log 165 . 0 38 . 1 49 . 3 ) ( log 10 10 m m e k D + + - = f (Equation 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 base 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 [155989] within the Flint defined set of hydrostratigraphic units (listed as hydraulic conductivities in DTN: MO0109HYMXPROP.001 [155989], then converted to permeability). • Determine the maximum and minimum average porosity within the Flint defined set of hydrostratigraphic units (listed as RH porosities in DTN: MO0109HYMXPROP.001 [155989]). The highest mean log permeability is -13.25 in Calico Hill-vitric unit (a subunit of the SZ HFM Unit 14), the lowest mean log permeability is -19.39 in unit TLL (a subunit of SZ HFM Unit 15). The largest porosity, 0.321, is in Calico Hill-vitric unit; the smallest porosity, 0.042, is in unit TC (Tiva Canyon tuff). MDL-NBS-HS-000021, REV 00 91 July, 2003 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 (Equation 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 [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 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 multi-atom 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 [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- . MDL-NBS-HS-000021, REV 00 92 July, 2003 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 = (Equation 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 to 100oC (Li and Gregory 1974 [129827], p.704; Simpson and Carr 1958 [139449], p. 1201). Using the Stokes-Einstein relationship, the molecular diffusion coefficient for a given temperature, can be 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 [129827], p. 704): ) ( ) ( 0 0 1 0 0 1 1 0 T D T T T D . . = (Equation 6-22) Given the maximum potential range in temperature for the Yucca Mountain groundwater along the transport pathway of 20 to 50 oC (293.15 to 323.15 K and the viscosity of water at those temperatures (Viswanath and Natarajan 1989 [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 . . (Equation 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 MDL-NBS-HS-000021, REV 00 93 July, 2003 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. There are a large number of permeability and porosity measurements taken from the saturated zone 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 [145123]; Rundberg et al. 1987 [106481]) as indicated on the “Flint_Reim_TrRnd” spreadsheet in the EXCEL workbook “Eff_MtrxDif_11.xls” file (DTN: SN0306T0502103.006). 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 [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 [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 were 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 [145123] and Rundberg et al. 1987 MDL-NBS-HS-000021, REV 00 94 July, 2003 [106481] and 3HHO, TcO4, and 14C De reported by Reimus et al. 2002 [163008] and 2003 [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 [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 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 –5.3 to –7.3 cm2/s), with the 50 percentile set at –6.3. cm2/s. Converted to m2/s results in a log De range of –9.3 to –11.3 m2/s, with the 50 percentile set at –10.3. m2/s (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. MDL-NBS-HS-000021, REV 00 95 July, 2003 Note: The CDF to the left represents values of effective diffusion coefficient derived using Equation 6-19. Included in the plot are laboratory measurements of effective diffusion coefficient from Triay 1993 [145126] and Rundberg et al. 1987 [106481] to demonstrate the reasonableness of the derived values of effective diffusion coefficient. The CDF to the right represents laboratory and field-derived estimates. Triangles - 14C laboratory values; Squares - 3HHO laboratory values; Diamonds – TcO4 laboratory values; Circles – Br- and PFBA field values (Reimus et al., 2002 [163008] and Reimus et al., 2003 [162950]). DTN: SN0306T0502103.006 Figure 6-14. CDFs of Data Used in the Assessment of Uncertainty in Effective Diffusion Coefficient 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]) MDL-NBS-HS-000021, REV 00 96 July, 2003 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 -11.4 -11.2 -11.0 -10.8 -10.6 -10.4 -10.2 -10.0 -9.8 -9.6 -9.4 -9.2 Cumulative Probability Log Effective Diffusion Coefficient (m^2/s) DTN: SN0306T0502103.007 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 [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 [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 [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 [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 [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. MDL-NBS-HS-000021, REV 00 97 July, 2003 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 [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 well (EDCON 2000 [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 as well as the porosity and dry bulk density computed from Freeze and Cherry 1979 [101173], p. 337: grain w grain sat . . . . f - - = T (Equation 6-24) ( ) T f. . - = 1 grain b (Equation 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. [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 [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 bulkdensity. MDL-NBS-HS-000021, REV 00 98 July, 2003 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 [163480] MDL-NBS-HS-000021, REV 00 99 July, 2003 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 MDL-NBS-HS-000021, REV 00 100 July, 2003 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1500 1600 1700 1800 1900 2000 2100 2200 2300 Cumulative Probability Bulk Density of Alluvium (kg/m^3) DTN: SN0306T0502103.007 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. The Kd model also depends on chemical equilibrium between the aqueous phase and sorbed phase of a given species. MDL-NBS-HS-000021, REV 00 101 July, 2003 The Kd relationship is defined as follows (Domenico and Schwartz 1990 [100569], p. 441): C K S d = (Equation 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 by BSC 2003 [162419], Attachment I. The documentation provided by BSC 2003 [162419], Attachment I includes the technical bases 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 [101173], p. 394). Longitudinal dispersivity will be important only at the leading edge of the advancing plume, while 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 [100353], p. LG-12). Temporal changes in the groundwater flow field may 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 [100465], p. 29-32), 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 expert elicitation were used as the basis for determining the distribution for longitudinal and transverse dispersivity. 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 [100353], p. 3-21). These distributions for longitudinal dispersivity are consistent with his previous work (Gelhar 1986 [101131], pp. 135s-145s). CRWMS M&O 2000 [152259], p. 53 provided estimates of the transverse and longitudinal dispersion that may occur at the sub gridblock scale within the SZ MDL-NBS-HS-000021, REV 00 102 July, 2003 site-scale model. The estimation of dispersivity using sub-gridblock scale modeling is also described in McKenna et al. 2003 [163578]. The results from the sub-gridblock scale modeling (CRWMS M&O 2000 [152259], p. 55) are in general agreement with the estimates by the expert elicitation panel (CRWMS M&O 1998 [100353], p. 3-21). However, it should be noted that there is a significant difference in the spatial scale at which the analyses in CRWMS M&O 2000 [152259] (500 m) were conducted and the scales at which the expert elicitation (CRWMS M&O 1998 [100353]) estimates were made (5 km and 30 km). Nonetheless, both sources of information on dispersivity are mutually supportive. 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 CRWMS M&O 1998 [100353], p. 3-21 according to the following relationships: 200 L h a a = (Equation 6-27) 20000 L v a a = (Equation 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 log-normal 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. MDL-NBS-HS-000021, REV 00 103 July, 2003 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) DTN: SN0306T0502103.007 Figure 6-18. CDF of Uncertainty in Longitudinal Dispersivity 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 randomwalk 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 during transport. The effective longitudinal dispersivity simulated by the SZ Transport Abstraction Model may 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 [107306]: MDL-NBS-HS-000021, REV 00 104 July, 2003 2 2 . .. . . .. . = t t f L m L s a (Equation 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 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 dashed line) than the specified longitudinal dispersivity (for values of specified longitudinal dispersivity of less than 1000 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. 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 MDL-NBS-HS-000021, REV 00 105 July, 2003 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 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 saturated zone near the C-Wells complex is presented in the Saturated Zone In Situ Testing report (BSC 2003 [162415], 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 threedimensional (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 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 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 BSC 2003 [162415], 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). MDL-NBS-HS-000021, REV 00 106 July, 2003 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 v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [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 [150245] method is a ratio of 3.3 in a direction 15ş east of north. A projection that orients the principal direction north-south (0ş) 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, the YMP Parameters Team, 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 saturated zone near the C-wells complex. Figure 6-20b is the corresponding CDF. DTN: SN0302T0502203.001 [163563] Figure 6-20. Probability Density Function (a) and Corresponding Cumulative Distribution Function (b) for the Uncertainty in North-South/East-West Anisotropy Ratio MDL-NBS-HS-000021, REV 00 107 July, 2003 There are several noteworthy points based on three distinct regions of the anisotropy ratio distribution (DTN: SN0302T0502203.001 [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 [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 may 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 BSC 2003 [162415], 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% 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 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% probability decreasing to zero at a ratio of 0.05. An additional Papadopulos solution yielding an anisotropy ratio of 3.5 at 79° west of north (BSC 2003 [162415], Section 6.2.6) falls in this range. • Anisotropy ratio between 1 and 5. A uniformly distributed 50% 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 another. It should be noted that in a previous model of the saturated zone near Yucca Mountain (CRWMS M&O 2000 [147972], Section 6.12), anisotropy was binomially distributed with a 50% probability of isotropy (1:1) and a 50% 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 2003 [162415], 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 15o E, indicating that the anisotropy applied on the SZ Transport Abstraction Model grid is within approximately 15o 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 saturated zone to be modeled with the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]) in the SZ Transport Abstraction Model. Horizontal anisotropy in permeability is determined for a particular realization by the parameter HAVO. MDL-NBS-HS-000021, REV 00 108 July, 2003 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 and 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, non-equilibrium behavior results in unimpeded migration of some of the colloids. Consequently, a small fraction of these colloids are transported through the SZ with no retardation; whereas the larger fraction is delayed by a retardation factor. For the SZ transport simulations, a small (uncertain) fraction of the radionuclide mass irreversibly attached to colloids is transported without retardation and the remaining fraction of the radionuclide mass is retarded. A discussion of the fraction of colloids transported with no retardation is in BSC 2003 [163932], 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 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 ten 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 BSC 2003 [163932], 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 MDL-NBS-HS-000021, REV 00 109 July, 2003 associated probabilities. This CDF is based on the uncertainty distribution developed by BSC 2003 [163932], Table 7. A log cumulative probability distribution is used because the retardation factors span slightly more than 2 orders of magnitude. Retardation of colloids with irreversibly sorbed radionuclides in the volcanic units is specified for a particular realization by the parameter CORVO. 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 DTN: LA0303HV831352.002 [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. BSC 2003 [163932], 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 analogs for colloid transport. 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 by BSC 2003 [163932], Table 8. A log cumulative probability distribution is used because the retardation factors span slightly more than 3 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. MDL-NBS-HS-000021, REV 00 110 July, 2003 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 DTN: LA0303HV831352.004 [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 2003 [161620], Section 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 by BSC 2003 [161620], Table 10. Figure 6-23 to Figure 6-25 show the uncertainty distributions MDL-NBS-HS-000021, REV 00 111 July, 2003 input to the SZ Transport Abstraction Model for sorption coefficients onto colloids. The Ccol uncertainty distribution was also developed by BSC 2003 [161620], Table 5 (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 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 Attachment I 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) DTN: SN0306T0504103.006 [164131], Table 1 Figure 6-23. CDF of Uncertainty in Plutonium Sorption Coefficient onto Colloids MDL-NBS-HS-000021, REV 00 112 July, 2003 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) DTN: SN0306T0504103.006 [164131], Table1 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) DTN: SN0306T0504103.006 [164131], Table 1 Figure 6-25. CDF of Uncertainty in Cesium Sorption Coefficient onto Colloids MDL-NBS-HS-000021, REV 00 113 July, 2003 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) DTN: SN0306T0504103.005 [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: LA0302AM831341.001, [163556]). 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 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 saturated zone is appropriate for a single leaking waste package or for highly focused groundwater flow along a fault or single fracture in the unsaturated zone. 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 tends to overestimate 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 unsaturated zone as simulated by the UZ site-scale flow and transport model. Variations in the pattern of groundwater flow from the repository to MDL-NBS-HS-000021, REV 00 114 July, 2003 the water table exist among infiltration models, alternative conceptual models, and climate states for the UZ site-scale model (BSC 2003 [164431], 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. The four SZ radionuclide source regions are shown in Figure 6-27. Note that the CORPSCON software code (v. 5.11.08, STN: 10547-5.11.08-00, LANL 2001 [155082]) was used to convert the coordinates of the repository design (given in state plane coordinates in meters) to 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 CRWMS M&O 2000 [153246], Section 4.4) , in which a hypothetical borehole penetrates the repository and extends to the saturated zone. 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 unsaturated zone. 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, 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. MDL-NBS-HS-000021, REV 00 115 July, 2003 546000 547000 548000 549000 550000 551000 UTM Easting (m) 4075000 4076000 4077000 4078000 4079000 4080000 4081000 4082000 UTM Northing (m) 1 2 3 4 Sources for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 800-IED-EBS0-00402-000-00B, BSC 2003 [161727] 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 6.5.2.14 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. Note that the uncertainty distribution in effective porosity of alluvium is truncated at a maximum value of 0.30 (Figure 6-10). MDL-NBS-HS-000021, REV 00 116 July, 2003 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. 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 numbered 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 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 volcanic matrix is calculated as the weighted average of bulk density in hydrogeologic Units numbered 13 through 15, as given in Table 6-13, with double weighting given to Unit 13. 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, Error! Reference source not found. 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 BSC 2003 [162649], Section 6.6.2. All of the remaining units are expected to lie outside of any expected SZ model transport paths and thus the values of matrix porosity assigned to the MDL-NBS-HS-000021, REV 00 117 July, 2003 remaining units have no impact on the transport simulations. However, the model requires values for fm for all units whether they play a role in transport simulations or not. Therefore values as representative as possible were used. For the case of Units 15-13, the matrix porosity is based on the values from 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 (DTN: SN0004T0501399.003 [155045], MO0109HYMXPROP.001 [155989], MO0010CPORGLOG.002 [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 (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. 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 DTN: SN0306T0502103.008 6.5.2.19 Bulk Density of Volcanic Matrix Bulk density ( .b ) is defined by Freeze and Cherry (1979 [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 [110491], p. 42). 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 MDL-NBS-HS-000021, REV 00 118 July, 2003 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 BSC 2003 [162649], Section 6.6.2. All of the remaining units are expected to lie outside of any expected SZ model transport paths and 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 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 discussed in Section 6.5.2.7. MDL-NBS-HS-000021, REV 00 119 July, 2003 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 Formation and the Lone Formation of borehole UE-25p#1 (DTN: MO0010CPORGLOG.002 [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 [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 2002 [159530]) contains a graph (Figure 24b, on page 71) 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 [155046]) m b f . · - = 8924 . 2 5019 . 2 (Equation 6-30) Table 6-8 lists the values of fm for the 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 sitespecific 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 the SZ Units 11 and 12 (DTN: MO0109HYMXPROP.001 [155989] and MO0010CPORGLOG.002 [155229]). The bulk density values come from the 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 (11-13) and Unit 15. Lava Flows (Unit 16) and Granites (Unit 1) - Rearrangement of the terms from an equation by Hillel 1980 [101134], p. 12, Equation 2.14) yields the following general relationship between bulk density and porosity: ( ) grain T b . f . · - = 1 (Equation 6-31) MDL-NBS-HS-000021, REV 00 120 July, 2003 where .grain equals particle density [M/L3]. The same text reference considers it appropriate that .grain can be equal to 2.65g/cm3 (Hillel 1980 [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, Error! Reference source not found.. 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. 1989 [129676], Table 1, p. A18 report 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. Bedinger et al. 1989 [129676] 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 from Bedinger et al. 1989 [129676], Table 1 page A18 (DTN: MO0105HCONEPOR.000 [155044]) are used for all of the hydrogeologic units described in this paragraph. The upper and 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 MO0105HCONEPOR.000 [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 in Table 1 of Bedinger et al. 1989 [129676]. 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. MDL-NBS-HS-000021, REV 00 121 July, 2003 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 DTN: SN0306T0502103.007 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 simulations using the convolution integral method. The SZ 1-D Transport Model is intended for direct incorporation into the TSPA model. The SZ 1-D Transport Model is developed independently of the TSPA model, but contains the elements necessary for implementation within the TSPA model. 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 nine groupings of radionuclides indicated by the first column in Table 6-15. The modes of radioelement transport are as: 1) solute, 2) colloidfacilitated transport of radionuclides reversibly attached to colloids, and 3) colloid-facilitated transport of radionuclides irreversibly attached to colloids. As indicated in Table 6-15, the nonsorbing radioelements 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. MDL-NBS-HS-000021, REV 00 122 July, 2003 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 DTN: SN0306T0502103.008 The radioelement breakthrough curves from the SZ Transport Abstraction Model for the 200 Monte Carlo realizations of SZ flow and transport are generated in the following manner. 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 2003 [162649]) 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 v. 2.0 software code (STN: 10914-2.0-00, SNL 2003 [163281]) is a pre-processor that is used to prepare the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]) input files for each of the 200 realizations. The pre-processor 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 v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]) input files. A total of 7200 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 [163557]. The SZ_Post v. 3.0 software code (STN: 10915-3.0-00, SNL 2003 [163571]) is a post-processor that is used to extract the breakthrough curves from the FEHM v. 2.20 software code (STN: 10086- 2.20-00, LANL 2003 [161725]) output files and concatenate all 200 realizations into a single file for input to the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]) for use in the TSPA-LA. MDL-NBS-HS-000021, REV 00 123 July, 2003 For implementation of the SZ Transport Abstraction Model in the TSPA model, the specific radionuclides and the timing of climate change events must be specified in the control file for the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]). The radionuclides for each radioelement and their corresponding values of half-life are specified in order for the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [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 model simulation are also specified in the control file for the SZ_Convolute v. 3.0 software code (STN: 10207-3.0- 00, SNL 2003 [164180]). The multiplier of groundwater flow rate in the SZ (relative to present conditions) for each climate state is also specified for the TSPA 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 Model requires that the “standalone” version of the model developed in this report be correctly integrated into the TSPA Model. The SZ 1-D Transport Model was developed in anticipation of integration into the TSPA Model, but the following aspects of the integration must be checked for implementation in the TSPA 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 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 Model. The parameter values for the 200 realizations of the SZ Transport Abstraction Model are stored as a table in the TSPA 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 Attachment I of this AMR and in DTN: SN0306T0502103.007. The variable controlling changes in climate state in the TSPA Model must be correctly linked with the SZ 1-D Transport Model. MDL-NBS-HS-000021, REV 00 124 July, 2003 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 down gradient 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 Figure 6-28 to Figure 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 a continuous, steady source at the water table below the repository (source region 1), initiated at time equal to zero. Also 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 v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]). Although individual breakthrough curves may 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. MDL-NBS-HS-000021, REV 00 125 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-28. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Carbon, Technetium, and Iodine at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 126 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-29. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Americium, Thorium, and Protactinium on Reversible Colloids at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 127 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-30. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Cesium on Reversible Colloids at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 128 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-31. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Plutonium on Reversible Colloids at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 129 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-32. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Neptunium at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 130 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-33. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Plutonium and Americium on Irreversible Colloids at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 131 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-34. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Radium at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 132 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-35. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Strontium at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 133 July, 2003 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 DTN: SN0306T0502103.008 Figure 6-36. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) for Uranium at 18-km Distance Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide decay. Results shown for 200 realizations. MDL-NBS-HS-000021, REV 00 134 July, 2003 6.7 DESCRIPTION OF BARRIER CAPABILITY The SZ forms a barrier to the migration of radionuclides and 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 Eddebbarh et al. 2003 [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 multiple realizations of the SZ system with the SZ Transport Abstraction Model and shown in the breakthrough curves for various radionuclides in Figure 6-28 to Figure 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 Figure 6-28 to Figure 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 previous SZ transport modeling results (Arnold et al. 2003 [163857]). Those analyses 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 non-sorbing species, such as carbon, technetium, and iodine, the delay afforded by the SZ may 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 MDL-NBS-HS-000021, REV 00 135 July, 2003 of time in the transport simulations) for all radionuclides. 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. MDL-NBS-HS-000021, REV 00 136 July, 2003 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 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. Non-sorbing 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 non-sorbing 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% 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 MDL-NBS-HS-000021, REV 00 137 July, 2003 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 transport times in the SZ and relatively short half-lives, this process renders the SZ an extremely effective barrier. Sr-90 and Cs-137 transport times would exceed several thousand half-lives, i.e. greater than 100,000 years, based on the median transport time among all realizations (Table 6-16). For comparison, the reduction in radioactivity after 20 half-lives is more than six orders of magnitude. For some radionuclides there would be a modest reduction in radionuclide mass during transport in the SZ. Pu-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. Tc-99, I-129, and Np-237 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 Tc-99 to 1.59×107 years for I-129). The dilution of radionuclides in the SZ and during pumping from wells by the future hypothetical farming community 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 suggests 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 capturing the contaminant plume in 3000 acre-ft/year for use by the hypothetical farming community would be greater than the dilution during transport in the SZ. MDL-NBS-HS-000021, REV 00 138 July, 2003 7. VALIDATION This section of the report documents the validation of both 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 2003 [162419]). 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 2003 [162419]). In both cases, the validations of these models are performed for a range of behavior that is representative of the uncertainties being evaluated for the TSPA analyses. 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 2003 [162419]). 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 Figure 6-28 and Figure 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 2003 [162419]) 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 2003 [162649]) to equilibrium with the specified values of the parameters GWSPD and HAVO. The particle-tracking algorithm in the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [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. MDL-NBS-HS-000021, REV 00 139 July, 2003 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 (1.29x10-4) -1.50 (0.0316) DCVO Effective diffusion coefficient in volcanic units -10.3 (5.0x10-11 m2/s) -10.68 (2.08x10-11 m2/s) -9.65 (2.22x10-10 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. MDL-NBS-HS-000021, REV 00 140 July, 2003 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 2003 [162419]). The SZ Transport Abstraction Model uses the convolution integral method as implemented by the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [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. Note that model validation tests were performed with the SZ_Convolute v. 2.2 software code (STN: 10207-2.2-00, SNL 2003 [163344]). For the first validation test, a constant input of 1 g/year from the UZ is applied at the upstream boundary of the SZ Transport Abstraction Model. This is essentially the same transport boundary condition used in the SZ Site-Scale Transport Model (BSC 2003 [162419]) 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 non-sorbing species and for neptunium. The validation test is also 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 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 1000 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 1000 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 1000 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 v. 2.2 software code (STN: 10207-2.2-00, SNL 2003 [163344]) have been conducted for the purposes of software verification (BSC 2003, Validation Test Report for SZ_Convolute, V 2.2, SDN: 10207-VTR-2.2- 00, MOL.20021202.0341 [163587]). These tests verify the ability of the convolution integral method, as implemented by the SZ_Convolute v. 2.2 software code (STN: 10207-2.2-00, SNL 2003 [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 2003 [162419] and DTN: LA0306SK831231.001 [164362]). The SZ 1-D Transport Model is implemented using the MDL-NBS-HS-000021, REV 00 141 July, 2003 GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]). Ultimately, the SZ 1-D Transport Model is fully integrated into the TSPA 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 2003 [162419]). 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 non-sorbing 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 v. 7.50.100-00 software code (STN: 10344-7.50.100-00), BSC 2003 [161572] have been conducted for the purposes of software verification (BSC 2002, Validation Test Report(VTR) for GoldSim, V 7.50.100, SDN: 10344-VTR-7.50.100-00, MOL.20030312.0227 [163962]). These tests verify the ability of the GoldSim v. 7.50.100-00 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) 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 validity of the model. Groundwater flow rates and flow-path lengths derived from the SZ Site-Scale Transport Model (BSC 2003 [162419]) 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. 7.2 VALIDATION CRITERIA Model validation follows the Technical Work Plan for: Saturated Zone Flow and Transport Modeling and Testing (BSC 2003 [163965], Section 2.5). The TWP states that Level-II validation will be achieved by satisfying the criteria listed as items a) through f) in Appendix B of the Scientific Processes Guidelines Manual (BSC 2002 [160313] and implementing one postdevelopment validation method. In this case, 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 [163965], Section 2.5). 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 (BSC 2003 [162419] and DTN: LA0306SK831231.001 [164362]). The breakthrough curves are compared at 10%, 50%, and 90% mass breakthrough in the evaluation of this criterion. Breakthrough curves are compared for a non-sorbing species and for MDL-NBS-HS-000021, REV 00 142 July, 2003 neptunium. Breakthrough curves for the median, fast, and slow cases outlined above are compared. Qualitative comparison of breakthrough curves is conducted by visual examination of graphs made of the breakthrough curves. 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. 7.3 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 2003 [162419]) for a non-sorbing 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. MDL-NBS-HS-000021, REV 00 143 July, 2003 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 2003 [162419]) 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 Non-Sorbing Radionuclide Visual comparison of the open symbols and the lines in Figure 7-1 indicates very close agreement 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 2003 [162419] and DTN: LA0306SK831231.001 [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 MDL-NBS-HS-000021, REV 00 144 July, 2003 are shown as the open symbols that are superimposed on the breakthrough curves from the sitescale model. 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 2003 [162419]) 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 very close agreement 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 non-sorbing species for the median case. This simulation applies a radionuclide mass influx boundary condition of 1 g/year for the first 1000 years of the simulation, which results in a total mass input of 1000 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% of the input mass. Examination of the simulated breakthrough curve from the SZ Site-Scale Transport Model for the median case indicates that 98 % of the mass has reached the accessible MDL-NBS-HS-000021, REV 00 145 July, 2003 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% and 99.5% 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. 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 Non-Sorbing 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 non-sorbing 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 1D MDL-NBS-HS-000021, REV 00 146 July, 2003 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 non-sorbing 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%, 50%, and 90% 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 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. MDL-NBS-HS-000021, REV 00 147 July, 2003 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 2003 [162419]) 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 Non-Sorbing Radionuclide MDL-NBS-HS-000021, REV 00 148 July, 2003 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 2003 [162419]) 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 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 2003 [162419]). 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 non-sorbing and sorbing radionuclide species for its intended use. MDL-NBS-HS-000021, REV 00 149 July, 2003 It should be noted that the SZ is more effective as a barrier for highly sorbing, short-lived radionuclides such as Sr-90 and Cs-137, 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 Sr-90 and Cs-137 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 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 2003 [162419]). 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 non-sorbing 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 daughter products. The results of the SZ 1-D Transport Model are used only for the daughter products in these decay chains within the TSPA analyses. 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. MDL-NBS-HS-000021, REV 00 150 July, 2003 Considering these factors, the SZ 1-D Transport Model provides a very good approximation of simulated radionuclide transport in the three-dimensional system of the SZ. No future activities are needed to complete this model validation for its intended use. MDL-NBS-HS-000021, REV 00 151 July, 2003 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 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 are conducted for these 200 realizations with the SZ Transport Abstraction Model and the results are documented. 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 model. The simulated radionuclide mass breakthrough curves from the SZ Transport Abstraction Model are coupled to the TSPA analyses using the convolution integral method (via the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180])). In addition, the SZ 1-D Transport Model is developed for direct implementation with the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) in the TSPA. The uncertain input parameters defined for the SZ Transport Abstraction Model are to be used in the SZ 1-D Transport Model for consistency between the two models when used in the probabilistic analyses of TSPA. Both 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 using the convolution integral method. Although the SZ 1-D Transport Model is significantly simplified relative to the three-dimensional SZ Transport Abstraction Model, validation of the SZ 1-D Transport Model indicates close agreement between the models for representative radionuclides over a broad range of uncertainty in SZ transport behavior. The technical bases of FEPs included in the models are presented in this report and related to 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 AMR are related to acceptance criteria specified in the YMRP (NRC 2003 [163274]). Information on the correlation between distribution coefficients (Kd s) used in the sampling of uncertain parameters for the SZ Transport Abstraction Model and the SZ 1-D Transport Model is given in Table 4-1 and Table 6-8. Positive correlation between the distribution coefficient for uranium in volcanic units and alluvium is specified, based on the potentially similar MDL-NBS-HS-000021, REV 00 152 July, 2003 hydrochemical conditions in both aquifers. Positive correlation between the distribution coefficient for neptunium in volcanic units and alluvium is specified, based on the potentially similar hydrochemical conditions in both aquifers. Positive correlation between the distribution coefficient for plutonium in volcanic units and alluvium is specified, based on the potentially similar hydrochemical conditions in both 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 BSC 2003 [162419], Attachment I, Section I.10. Evaluation of uncertainty in horizontal anisotropy of permeability is summarized in Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is given in BSC 2003 [162415], 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 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 BSC 2003 [162419], Attachment I. Information on the geological uncertainty in the location of the contact between tuff and alluvium and the consequent uncertainty in the flow path lengths in the alluvium is presented in Section 6.5.2.2. This evaluation of uncertainty includes currently available 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 relative to the previous evaluation in CRWMS M&O 2000 [147972], Section 6.2. The sensitivity analysis of matrix diffusion in the SZ Transport Abstraction Model is presented in the assessment of alternative conceptual models 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. MDL-NBS-HS-000021, REV 00 153 July, 2003 8.2 MODEL OUTPUTS 8.2.1 Developed Output The technical output from this report is contained in four DTNs that are summarized in Table 8-1. Table 8-1. Summary of Developed Output Output DTN Description SN0306T0502103.007 Uncertainty distributions for parameters used in the SZ Transport Abstraction Model. Sampling output of uncertain parameters for 200 realizations is also included (see Attachment I). This DTN also includes a description of each uncertain parameter. SN0306T0502103.008 Input and output files for the SZ Transport Abstraction Model. This DTN also contains the output breakthrough curves for use in the TSPA analyses. SN0306T0502103.005 Input and output files for the SZ 1-D Transport Model. SN0306T0502103.006 Data spreadsheets to support data uncertainty development. Results of the parameter uncertainty analyses from this AMR are contained in DTN: SN0306T0502103.007. 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 v. 7.50.100 software code (STN: 10344-7.50.100-00) for sampling 200 realizations from these uncertainty distributions. This DTN also contains the output file from the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00) containing the parameter vectors to be used in the SZ Transport Abstraction Model. Results of the SZ Transport Abstraction Model from this AMR are contained in DTN: SN0306T0502103.008. These results consist of the input and output files from the FEHM v. 2.20 software code (STN: 10086-2.20-00), the SZ_Pre v. 2.0 software code (STN: 10914-2.0- 00), and the SZ_Post v. 3.0 software code (STN: 10915-3.0-00) used in the analyses. The results that form a direct input to the TSPA model are the files containing the breakthrough curves from the SZ Transport Abstraction Model for the 200 realizations of radionuclide transport. The breakthrough curves for use in the TSPA model (i.e., the breakthrough curves at the regulatory boundary of the accessible environment) are defined by the first column (time) and the third column (relative mass) in the output files. MDL-NBS-HS-000021, REV 00 154 July, 2003 The input and output files for the SZ 1-D Transport Model are contained in DTN: SN0306T0502103.005. The input file of the SZ 1-D Transport Model for the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) is intended for incorporation into the TSPA model. The data spreadsheets contained in DTN: SN0306T0502103.006 contain the data used and support the analyses of parameter uncertainty summarized in this report and in DTN: SN0306T0502103.007. The spreadsheets mentioned by filename in this report are contained in DTN: SN0306T0502103.006. 8.2.2 Output Uncertainties and Limitations The assessment of uncertainty in model parameters and model outputs is an integral part of the analyses performed in this AMR. Uncertainty in model parameters is quantitatively represented with the statistical distributions developed and contained in DTN: SN0306T0502103.007. Uncertainty in radionuclide transport in the SZ Transport Abstraction Model is embodied in the breakthrough curves for the 200 realizations contained in DTN: SN0306T0502103.008. The SZ 1-D Transport Model is intended for incorporation into the TSPA Model, with which uncertainty will be assessed using Monte Carlo probabilistic analyses. All relevant uncertainties in data and model parameters, as they affect groundwater flow and radionuclide transport, have been included in 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 meet the YMRP (NRC 2003 [163274]) acceptance criterion 3 for the propagation of data uncertainty through model abstraction for flow paths in the saturated zone and for radionuclide transport in the saturated zone. 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 model report. Limitations in knowledge of specific parameter values are addressed in the analysis of parameter uncertainties in this report. 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 model 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 model would be significantly less than 100,000 years. If the glacial-transition climate state is applied for most of simulation period in the TSPA model, the SZ breakthrough curves would be scaled by a factor of approximately 4, limiting the TSPA model simulation time to about 25,000 years. MDL-NBS-HS-000021, REV 00 155 July, 2003 9. INPUTS AND REFERENCES 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] BSC (Bechtel SAIC Company) 2001. Data Qualification Report: Matrix Hydrologic Properties and Alcove 1 Inflitration 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] MDL-NBS-HS-000021, REV 00 156 July, 2003 BSC (Bechtel SAIC Company) 2001. FY 01 Supplemental Science and Performance Analyses, Volume 1: Scientific Bases and Analyses. TDR-MGR-MD-000007 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010801.0404; MOL.20010712.0062; MOL.20010815.0001. [155950] BSC (Bechtel SAIC Company) 2001. Probability Distribution for Flowing Interval Spacing. ANL-NBS-MD-000003 REV 00 ICN 02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010625.0304. [156965] BSC (Bechtel SAIC Company) 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 (Bechtel SAIC Company) 2002. Rock Properties Model Analysis Model Report. MDLNBS- GS-000004 REV 00 ICN 03. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20020429.0086. [159530] BSC (Bechtel SAIC Company) 2002. Scientific Processes Guidelines Manual. MIS-WIS-MD- 000001 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20020923.0176. [160313] BSC (Bechtel SAIC Company) 2002. The Enhanced Plan for Features, Events, and Processes (FEPs) at Yucca Mountain. TDR-WIS-PA-000005 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20020417.0385. [158966] BSC (Bechtel SAIC Company) 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 (Bechtel SAIC Company) 2003. Analysis of Hydrologic Properties Data. MDL-NBS-HS- 000014 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030404.0004. [161773] BSC (Bechtel SAIC Company) 2003. PRELIMINARY DRAFT OF MODEL COVER SHEET FOR MODEL REPORT UZ FLOW MODELS AND SUBMODELS, MDL-NBS-HS-000006, REVISION 01D, BY YU-SHU WU (C). Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030615.0113. [164431] BSC (Bechtel SAIC Company) 2003. Repository Design, Repository/PA IED Subsurface Facilities. 800-IED-EBS0-00401-000-00C. Las Vegas, Nevada: Bechtel SAIC Company. ACC: ENG.20030303.0002. [162289] BSC (Bechtel SAIC Company) 2003. Repository Design, Repository/PA IED Subsurface Facilities. 800-IED-EBS0-00402-000-00B. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030109.0146. [161727] MDL-NBS-HS-000021, REV 00 157 July, 2003 BSC (Bechtel SAIC Company) 2003. Saturated Zone Colloid Transport. ANL-NBS-HS- 000031 REV 01A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030602.0288. TBV-5180 [163932] BSC (Bechtel SAIC Company) 2003. Saturated Zone In-Situ Testing. ANL-NBS-HS-000039 REV 00A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030602.0291. [162415] BSC (Bechtel SAIC Company) 2003. Site-Scale Saturated Zone Flow Model. MDL-NBS-HS- 000011 REV 01A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030626.0296. TBV-5203 [162649] BSC (Bechtel SAIC Company) 2003. Site-Scale Saturated Zone Transport. MDL-NBS-HS- 000010 REV 01A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20030626.0180. [162419] BSC (Bechtel SAIC Company) 2003. Technical Work Plan for: Saturated Zone Flow and Transport Modeling and Testing. TWP-NBS-MD-000002 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030618.0021. [163965] BSC (Bechtel SAIC Company) 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 (Bechtel SAIC Company) 2003. Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and Summary. MDL-EBS-PA-000004 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030626.0006. [161620] 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] MDL-NBS-HS-000021, REV 00 158 July, 2003 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. TER-MGR-MD- 000001 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20030404.0003. [161770] Coen, K. 1987. "Policy Review." Memorandum from K. Coen (LANL) to D. Norton, January 26, 1987, TWS-INC7-1/87-10, with attachment. ACC: NNA.19900112.0339; MOL.19980625.0239. [162960] 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 M&O 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 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 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] MDL-NBS-HS-000021, REV 00 159 July, 2003 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] CRWMS M&O 2000. UZ Flow Models and Submodels. MDL-NBS-HS-000006 REV 00. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19990721.0527. [122797] CRWMS M&O 2001. Features, Events, and Processes in SZ Flow and Transport. ANL-NBSMD- 000002 REV 01. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.20010214.0230. [153931] 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] 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, G.A.; Brodsky, N.S.; and Swift, P.N. 2001. The Development of Information Catalogued in REV00 of the YMP FEP Database. TDR-WIS-MD-000003 REV 00 ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: MOL.20010301.0237. [154365] MDL-NBS-HS-000021, REV 00 160 July, 2003 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] 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] Kotra, J.P.; Lee, M.P.; Eisenberg, N.A.; and DeWispelare, A.R. 1996. Branch Technical Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program. NUREG-1563. Washington, D.C.: U.S. Nuclear Regulatory Commission. TIC: 226832. [100909] 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] MDL-NBS-HS-000021, REV 00 161 July, 2003 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] Reimus, Paul W.; M. J. Haga; A. I. Adams; T. J. Callahan; H.J. Turin; and D. A. Counce 2003. "Testing and Parameterizing a Conceptual Solute Transport Model in Saturated Fractured Tuffs Using Sorbing and Nonsorbing Tracers in Cross-Hole Tracer Tests." Journal of Contaminant Hydrology, 62-63, (April - May 2003), 613-636. New York, New York: Elsevier. [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 {superscript 3}H, {superscript 14}C, and {superscript 99}Tc 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] Sandia National Laboratories 2003. SZ_Convolute. V 3.0-00. PC. 10207-3.0-00. [164180] 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] MDL-NBS-HS-000021, REV 00 162 July, 2003 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] USGS (U.S. Geological Survey) 2001. Hydrogeologic Framework Model for the Saturated- Zone Site-Scale Flow and Transport Model. ANL-NBS-HS-000033 REV 00 ICN 02. Denver, Colorado: U.S. Geological Survey. ACC: MOL.20011112.0070. [158608] USGS (U.S. Geological Survey) 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 (U.S. Geological Survey) 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. Readily available. [156605] AP-2.22Q, Rev. 0, ICN 1. Classification Criteria and Maintenance of the Monitored Geologic Repository Q-List. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20030422.0009. [163021] MDL-NBS-HS-000021, REV 00 163 July, 2003 AP-AC.1Q, Rev. 0, ICN 0. Expert Elicitation. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.19991019.0014. [138711] AP-SI.1Q, Rev. 5, ICN 0. Software Management. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20030422.0012. [163085] AP-SIII.10Q, Rev. 1, ICN 2. Models. Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20030627.0003. [164074] 9.3 SOFTWARE BSC (Bechtel SAIC Company) 2003. Software Code: GoldSim. 7.50.100. PC. 10344- 7.50.100-00. [161572] LANL (Los Alamos National Laboratory) 2001. Software Code: CORPSCON. V5.11.08. 10547-5.11.08-00. [155082] LANL (Los Alamos National Laboratory) 2003. Software Code: FEHM. V2.20. SUN, PC. 10086-2.20-00. [161725] Sandia National Laboratories (SNL) 2003. Software Code: SZ_Convolute. V2.2. PC, Windows 2000. 10207-2.2-00. [163344] Sandia National Laboratories (SNL) 2003. Software Code: SZ_Post. V3.0. Sun, SunO.S. 5.7. 10915-3.0-00. [163571] Sandia National Laboratories (SNL) 2003. Software Code: SZ_Pre. V2.0. Sun, Solaris 7. 10914-2.0-00. [163281] 9.4 SOURCE DATA, LISTED BY DATA TRACKING NUMBER GS010908312332.002. Borehole Data from Water-Level Data Analsis 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, NC-EWDP-19IM1A, and NCEWDP- 19IM2A, Nye County Early Warning Drilling Program, Phase III. Submittal date: 02/11/2003. [163483] LA0002JC831341.001. Depth Intervals and Bulk Densities of Alluviums. Submittal date: 03/08/2000. [147081] MDL-NBS-HS-000021, REV 00 164 July, 2003 LA0302AM831341.001. Saturated Zone Distribution Coefficents (KDS) for U, NP, PU, CS, AM, PA, SR, TH, RA, C, TC, AND I. Submittal date: 02/04/2003. [163556] 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] LA0306SK831231.001. SZ Site-Scale Transport Model, FEHM Files for Base Case. Submittal date: 06/25/2003. [164362] LB990801233129.004. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and Submodels" (Flow Field #4). Submittal date: 11/29/1999. [117129] LB990801233129.009. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and Submodels" (Flow Field #9). Submittal date: 11/29/1999. [118717] LB990801233129.015. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and Submodels" (Flow Field #15). Submittal date: 11/29/1999. [118730] 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] SN0004T0501399.002. Correlation of RH (Relative Humidity) Porosity and Bulk Density. Submittal date: 04/13/2000. [155046] MDL-NBS-HS-000021, REV 00 165 July, 2003 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] 9.5 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER SN0306T0502103.005. SATURATED ZONE (SZ) 1-D TRANSPORT MODEL. Submittal date: 06/05/2003. SN0306T0502103.006. DATA SPREADSHEETS TO SUPPORT PARAMETER UNCERTAINTY DEVELOPMENT. Submittal date: 06/05/2003. SN0306T0502103.007. UPDATED SATURATED ZONE TRANSPORT ABSTRACTION MODEL UNCERTAIN INPUTS. Submittal date: 06/12/2003. SN0306T0502103.008. UPDATED SATURATED ZONE TRANSPORT ABSTRACTION MODEL INPUTS AND RESULTS. Submittal date: 06/12/2003. MDL-NBS-HS-000021, REV 00 166 July, 2003 10. ATTACHMENTS ATTACHMENT I – Stochastic Parameter Values MDL-NBS-HS-000021, REV 00 I-1 July, 2003 ATTACHMENT I Table I-1. Stochastic Parameter Values DTN: SN0306T0502103.007 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 1.5616 6.3364 268.07 259.27 2 0.61702 0.70184 0.11408 0.081329 0.84234 -3.0161 -10.116 1.1722 4.8505 258.99 113.51 3 0.35217 0.61633 0.083152 0.20585 1.0234 -3.3666 -10.146 1.0715 4.2112 113.11 290.67 4 0.43734 0.35304 0.20587 0.19441 0.83422 -3.8921 -10.539 1.2255 7.6552 290.9 159.82 5 0.3726 0.4368 0.19441 0.16058 0.92304 -4.461 -10.042 1.3846 6.1118 160.14 199.68 6 0.38137 0.37493 0.16033 0.17169 1.4084 -2.3306 -10.426 1.1451 6.4302 200.28 240.98 7 0.96095 0.38323 0.17133 0.16309 0.81193 -2.6095 -10.325 1.4043 5.7365 240.86 85.61 8 0.96721 0.96199 0.1631 0.16459 1.1285 -3.3333 -10.197 1.2161 7.73 86.233 122.88 9 0.063508 0.96547 0.16442 0.26596 1.3996 -3.1397 -10.612 1.098 4.6382 122.69 82.931 10 0.39763 0.063782 0.26525 0.26907 1.2126 -3.2812 -10.518 1.176 7.7179 83.165 99.983 11 0.12641 0.39708 0.26845 0.1011 0.63908 -3.2658 -10.619 1.1747 6.2902 100.11 249.1 12 0.83363 0.12855 0.10207 0.16643 1.5206 -1.199 -10.572 1.5992 7.5701 248.31 79.438 13 0.82638 0.83084 0.16658 0.12153 1.3272 -1.15 -10.174 1.2055 6.451 79.842 156.96 14 0.46725 0.82571 0.12117 0.22766 0.62506 -3.976 -10.626 1.1643 4.9316 156.83 245.64 15 0.11482 0.46679 0.2272 0.22709 1.6764 -3.2319 -10.431 1.3064 6.8839 244.94 185.29 16 0.24233 0.11166 0.22688 0.17505 1.0682 -3.8285 -10.185 1.4173 7.3231 183.88 46.974 17 0.8055 0.24472 0.17513 0.11746 1.2021 -1.8383 -10.366 1.4534 7.8869 47.598 285.48 18 0.1329 0.80984 0.11813 0.14376 1.0712 -1.8602 -10.758 1.2152 5.1106 284.54 222.27 19 0.73058 0.13299 0.14387 0.22266 1.4018 -3.0689 -10.059 1.5123 5.8951 223.16 46.513 20 0.34072 0.73141 0.22261 0.12312 1.3451 -3.856 -10.26 1.5542 8.6697 45.328 329.38 21 0.048591 0.34315 0.12247 0.21023 1.0043 -3.5674 -10.801 1.405 7.4175 327.85 136.96 22 0.74837 0.048613 0.21035 0.15875 1.4574 -1.9719 -9.921 1.4846 7.7301 137.24 181.17 23 0.93881 0.74785 0.15923 0.093691 1.2402 -3.8166 -10.485 1.4062 6.4626 180.92 138.35 24 0.55458 0.93563 0.09379 0.21283 1.1247 -2.2296 -10.372 1.0732 1.9633 139.62 247.14 25 0.79283 0.55378 0.21273 0.25453 1.668 -3.3458 -10.476 1.5309 6.3834 246.15 228.25 26 0.37734 0.79098 0.25543 0.18598 1.816 -4.0395 -10.185 5.9009 7.6101 227.35 115.13 MDL-NBS-HS-000021, REV 00 I-2 July, 2003 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 1.4036 7.8466 116.36 264.39 28 0.65266 0.67222 0.22046 0.16351 1.6175 -1.3137 -10.538 0.84532 6.7485 264.74 194.12 29 0.62918 0.65188 0.1638 0.20193 1.5918 -2.8203 -10.13 1.4983 10.779 194.18 155.64 30 0.24883 0.62618 0.20225 0.199 1.3545 -2.032 -10.341 1.1036 2.4415 156.36 325.19 31 0.71164 0.2459 0.19922 0.19577 0.76344 -3.2677 -10.437 1.2579 6.4552 325.42 362 32 0.36584 0.7122 0.1961 0.14524 2.4058 -2.4327 -9.9314 1.3744 6.5489 361.97 105.28 33 0.47113 0.36787 0.14464 0.20748 1.2638 -2.4921 -9.6565 1.3692 6.2446 103.82 313.97 34 0.58157 0.47388 0.20749 0.16199 1.8275 -2.5698 -10.565 1.03 5.3839 313.5 308.63 35 0.17154 0.58391 0.16242 0.17587 1.381 -3.5586 -9.9702 1.0949 4.5499 307.59 232.62 36 0.27276 0.17077 0.17593 0.19016 1.7866 -2.2884 -9.9878 1.1672 6.5466 230.98 72.64 37 0.16841 0.2727 0.18985 0.13151 1.3153 -3.2946 -10.231 1.3467 5.7734 71.65 395.34 38 0.21269 0.16757 0.13141 0.14914 1.5424 -3.0598 -10.645 1.0592 4.3751 395.81 200.88 39 0.60151 0.21358 0.14881 0.13017 1.6877 -2.7243 -9.3455 1.1259 4.6523 201.21 362.94 40 0.15729 0.60256 0.13036 0.13857 1.4451 -3.7297 -10.322 1.2168 5.863 363.36 239.29 41 0.3647 0.15605 0.13923 0.19281 1.2456 -3.5069 -9.6366 1.2943 7.3494 238.67 353.32 42 0.59284 0.36398 0.19225 0.12862 1.5022 -3.7412 -10.208 1.0945 6.6715 353.63 219.29 43 0.43429 0.59413 0.1289 0.16172 1.0933 -3.6399 -9.7391 1.5736 4.4304 218.86 293.52 44 0.074964 0.43453 0.1616 0.1909 1.3933 -2.6663 -10.274 1.189 6.7603 293.54 329.87 45 0.69768 0.072714 0.19154 0.17113 1.7338 -3.7591 -10.037 1.0416 4.24 329.95 260.63 46 0.53002 0.69555 0.17083 0.10469 0.60159 -3.3102 -9.9122 5.9456 12.998 260.58 195.92 47 0.066897 0.53497 0.10634 0.20539 1.5563 -2.6836 -10.14 1.2551 6.3144 195.81 278.81 48 0.81253 0.067039 0.20548 0.18333 1.629 -3.1487 -10.338 1.5648 8.2368 279.26 147.09 49 0.307 0.81175 0.18364 0.10332 1.1917 -3.954 -10.079 1.1086 5.1387 146.39 242.3 50 0.42421 0.30885 0.10441 0.2239 1.6554 -2.3446 -10.461 5.8907 12.116 242.61 342.55 51 0.31471 0.42162 0.22428 0.15377 1.015 -2.8939 -10.193 1.5497 7.6537 342.37 42.645 52 0.59783 0.31468 0.15362 0.16942 1.0887 -3.9623 -9.8347 1.2477 6.3723 41.049 296.42 53 0.54881 0.59673 0.16958 0.15458 0.92816 -1.937 -10.881 1.5972 5.3289 296.98 317.67 54 0.25186 0.54916 0.15499 0.19171 1.3722 -3.4313 -10.022 2.8263 10.605 316.68 177.7 55 0.64107 0.25325 0.19159 0.18521 0.58809 -3.1758 -9.9578 1.3281 6.9642 177.84 322.55 56 0.45988 0.64197 0.18541 0.14594 0.70644 -3.4213 -10.38 1.2863 5.5995 322.77 120.09 57 0.35868 0.45653 0.14567 0.19779 1.1816 -2.6824 -9.9416 1.593 8.3781 119.49 144.75 58 0.80213 0.35725 0.19771 0.17377 1.8448 -2.8405 -10.526 1.3237 8.2585 144.07 102.59 MDL-NBS-HS-000021, REV 00 I-3 July, 2003 real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 59 0.89925 0.80492 0.17397 0.16094 1.8056 -3.5446 -10.465 1.5431 8.3775 102.46 238.09 60 0.22248 0.89986 0.16077 0.22181 0.8828 -2.5185 -10.569 1.818 7.6319 238.24 40.481 61 0.77121 0.22433 0.22181 0.24279 1.776 -3.0919 -10.209 4.5641 8.5555 39.125 60.504 62 0.75746 0.77304 0.24181 0.14055 1.4833 -3.3141 -10.914 1.2771 5.6484 61.745 174.98 63 0.55579 0.75953 0.14106 0.21688 0.29449 -1.9893 -10.676 1.4246 6.0788 175.27 368.07 64 0.13508 0.5581 0.2173 0.2146 0.97023 -1.5186 -10.388 1.4437 7.9421 368.85 358.4 65 0.9875 0.13511 0.21415 0.18662 0.67711 -3.6141 -9.5831 1.3231 7.3588 358.6 93.383 66 0.47965 0.98618 0.18644 0.12437 1.0221 -2.0912 -9.6872 1.4713 6.3947 93.089 351.55 67 0.90123 0.47822 0.12407 0.28381 1.3397 -2.146 -10.594 1.2995 4.8544 350.82 273.61 68 0.57866 0.90303 0.28224 0.17637 1.1865 -2.81 -9.7422 1.3853 7.097 272.91 29.222 69 0.87669 0.57844 0.17686 0.24362 1.3222 -3.8028 -10.099 1.554 8.2015 29.194 109.73 70 0.52246 0.87687 0.24338 0.18948 1.4151 -1.0566 -11.127 1.4993 7.9085 110.4 55.672 71 0.71788 0.52221 0.18946 0.23674 1.8942 -3.0485 -10.55 1.3887 7.2882 54.464 122.53 72 0.81847 0.71882 0.23781 0.182 1.7624 -1.4862 -10.686 1.0413 4.0931 122.07 225.24 73 0.63474 0.81922 0.18229 0.20867 0.738 -2.7404 -10.522 1.2817 5.8392 225.84 177.4 74 0.46117 0.63266 0.20818 0.22519 1.7318 -1.6079 -10.25 1.089 5.563 177.5 220.21 75 0.68208 0.46283 0.22459 0.19667 1.533 -2.9264 -10.382 1.3449 4.6409 220.36 251.38 76 0.33346 0.68422 0.19617 0.1746 1.7237 -2.2736 -10.267 3.7206 5.4484 250.42 379.89 77 0.58661 0.33143 0.17454 0.2033 2.5288 -1.9123 -10.169 1.0843 5.8758 379.91 348.05 78 0.84781 0.58957 0.20353 0.15752 0.18779 -2.5558 -9.4799 3.5283 8.1698 347.72 65.785 79 0.055061 0.84838 0.15727 0.1908 1.4319 -3.0857 -9.7859 1.5113 8.3184 65.77 340.28 80 0.72545 0.059548 0.19074 0.23065 0.65772 -2.3987 -10.66 1.041 6.9709 340.32 288.61 81 0.78233 0.72652 0.23023 0.09896 1.0081 -3.3729 -9.8592 4.6835 7.3093 288.29 337.65 82 0.41537 0.78383 0.10033 0.21009 1.5687 -2.7055 -10.051 1.2534 4.2383 338.42 396.46 83 0.79615 0.4153 0.21009 0.21848 0.1867 -1.7701 -9.868 1.09 4.5096 396.97 24.361 84 0.26279 0.79769 0.21877 0.169 1.8692 -3.9839 -9.3285 1.2688 6.2532 24.087 256.82 85 0.32585 0.26149 0.16913 0.22126 1.0848 -2.2475 -11.197 3.1158 8.0548 257.05 51.292 86 0.21935 0.32771 0.22133 0.14731 0.43697 -2.0638 -10.149 1.2095 6.8038 50.403 118.69 87 0.57287 0.21868 0.14692 0.15714 1.0417 -3.1822 -10.698 1.0986 5.642 117.57 303.07 88 0.05408 0.5743 0.15668 0.14015 0.69929 -2.0111 -10.532 1.3984 6.9799 302.88 23.539 89 0.10576 0.054487 0.13962 0.18832 1.2717 -3.5333 -10.005 1.4976 5.067 22.372 375.01 90 0.40754 0.10529 0.18845 0.096424 1.6977 -3.3872 -11.258 2.503 8.1054 374.3 142.05 MDL-NBS-HS-000021, REV 00 I-4 July, 2003 real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 91 0.91603 0.40782 0.098203 0.11647 0.90599 -3.6232 -9.5364 1.2184 7.3349 143.11 32.802 92 0.89135 0.91567 0.11686 0.16758 1.7454 -2.7577 -10.47 1.5155 6.3243 33.088 128.36 93 0.19019 0.89023 0.16751 0.24842 0.46766 -3.9928 -11.072 1.4338 5.532 129.99 59.201 94 0.87315 0.19372 0.24868 0.24104 1.2729 -3.8725 -10.503 1.3253 8.2211 58.595 204.12 95 0.66517 0.87134 0.24128 0.13522 1.7668 -3.2063 -10.678 1.2312 6.3196 203.25 333.28 96 0.024123 0.66764 0.13509 0.2357 0.79926 -1.415 -10.318 1.2901 5.1403 333.2 96.423 97 0.23899 0.022985 0.23591 0.20122 0.78641 -1.5294 -9.9071 1.4917 10.47 96.617 343.73 98 0.093079 0.23563 0.20126 0.079449 0.50753 -3.6823 -10.585 1.3754 6.2799 344.24 33.838 99 0.26953 0.090888 0.078007 0.14284 1.6105 -1.6374 -9.8223 1.7885 12.343 33.832 205.03 100 0.54079 0.26698 0.14297 0.1121 0.7266 -2.4384 -11.023 1.2352 4.8847 205.87 348.78 101 0.41165 0.54048 0.11173 0.14771 1.2905 -4.5523 -10.31 1.0886 5.4429 349.62 77.497 102 0.52854 0.41152 0.14803 0.18493 1.053 -3.5782 -9.7593 5.288 7.4087 77.534 76.842 103 0.60808 0.52661 0.18474 0.16809 1.8672 -3.9083 -10.633 1.4495 5.0404 76.359 36.081 104 0.94548 0.60856 0.1683 0.18302 1.8887 -3.5167 -10.633 1.0081 4.9632 36.121 311.98 105 0.86326 0.94988 0.18294 0.19313 1.9802 -2.8632 -10.973 1.2061 5.8423 312.49 63.968 106 0.12173 0.86184 0.19307 0.25889 2.2252 -3.196 -9.9776 1.3673 8.3694 64.993 210.78 107 0.84161 0.12403 0.259 0.23369 0.81543 -2.9144 -10.666 1.0087 4.0211 210.19 132.5 108 0.70681 0.84374 0.23391 0.12085 1.0518 -2.6365 -10.296 1.4823 8.0432 133.56 371.99 109 0.83677 0.70737 0.12071 0.22943 1.0756 -1.2562 -10.492 1.2957 7.1784 372.31 378.64 110 0.99128 0.83905 0.22953 0.20708 1.0619 -1.6871 -9.5526 1.5849 6.2277 377.8 384.4 111 0.010519 0.99171 0.20724 0.2288 1.1152 -3.8399 -9.5112 1.3726 8.0958 383.78 389.32 112 0.62269 0.011542 0.22836 0.28924 1.5627 -1.7758 -9.4549 0.47367 2.0554 388.62 81.669 113 0.084204 0.62223 0.29036 0.067107 1.1593 -2.3046 -9.3949 1.2838 5.0674 81.049 131.2 114 0.25597 0.083179 0.063538 0.19537 1.7925 -1.8199 -10.623 1.0259 4.8538 131.47 141.54 115 0.74132 0.25944 0.19539 0.10837 1.8399 -1.0372 -10.499 1.3325 4.3711 140.73 134.5 116 0.007434 0.74115 0.10822 0.14618 1.3104 -4.793 -10.473 1.326 4.6318 135.74 152.57 117 0.93236 0.008269 0.14655 0.21192 1.0318 -2.5914 -10.486 1.192 4.8102 151.56 300.09 118 0.32035 0.93043 0.21235 0.049913 0.25923 -3.925 -10.447 1.5052 8.4928 299.64 166.3 119 0.030233 0.32271 0.054478 0.25292 1.8314 -3.5417 -10.015 1.2865 6.5942 167.99 355.78 120 0.28508 0.034057 0.25215 0.15635 1.6384 -2.197 -10.408 1.0441 4.3142 355.96 366.8 121 0.10144 0.28681 0.15579 0.084439 1.4232 -4.8885 -9.7061 4.0179 8.6042 365.99 216.81 122 0.48434 0.10353 0.087276 0.15092 1.2272 -1.3375 -9.6162 1.5659 10.632 216.07 125.11 MDL-NBS-HS-000021, REV 00 I-5 July, 2003 real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 123 0.82334 0.4826 0.15078 0.11532 1.2217 -3.394 -10.28 1.144 6.8495 126.33 25.85 124 0.20394 0.82124 0.1155 0.17726 1.8577 -4.3628 -10.513 0.56195 5.2954 25.77 364.38 125 0.8532 0.20325 0.1773 0.2256 0.64581 -3.4685 -11.163 0.61438 5.5611 364.43 319.08 126 0.037624 0.85435 0.22552 0.13752 2.2805 -3.8812 -9.6208 1.4824 8.6597 318.59 252.72 127 0.48593 0.038573 0.1374 0.23209 1.8027 -3.0395 -9.9522 1.1054 4.852 253.06 189.7 128 0.86876 0.48711 0.2322 0.090398 1.4724 -1.8783 -10.167 1.426 7.4125 189.11 188.25 129 0.1544 0.86639 0.087853 0.17752 0.8727 -3.6625 -10.349 1.1896 6.6315 189 371.09 130 0.14816 0.15141 0.17766 0.23528 1.4626 -1.7361 -10.354 1.5565 6.1952 371.34 48.507 131 0.043598 0.14898 0.2347 0.12704 0.8525 -4.2851 -9.5649 0.57803 6.1647 49.552 391 132 0.76846 0.043645 0.12788 0.12639 1.9175 -3.0322 -10.707 1.3923 8.5753 392.36 358.05 133 0.11602 0.76916 0.12658 0.091042 0.77682 -1.663 -9.3758 1.4028 6.1291 357.09 270.33 134 0.50019 0.11576 0.091188 0.21608 1.5858 -3.7717 -9.697 1.3106 5.1128 268.94 91.21 135 0.29848 0.50385 0.21619 0.11938 0.66707 -3.782 -10.108 1.5452 7.8604 91.012 266.13 136 0.92706 0.29908 0.11876 0.1795 0.9665 -4.1659 -10.598 1.2378 6.3067 266.24 87.774 137 0.94102 0.92914 0.17972 0.15236 1.6015 -2.1023 -10.123 1.2967 4.568 87.49 381.85 138 0.95563 0.94338 0.1525 0.25203 1.0371 -3.8468 -10.607 1.2594 6.9416 382.11 73.304 139 0.97152 0.95988 0.25117 0.25751 1.4984 -2.9884 -9.4764 1.3533 7.5599 75.05 305.76 140 0.16243 0.97467 0.25758 0.26263 1.3352 -3.4489 -10.64 1.318 6.1782 306.58 52.742 141 0.29141 0.16433 0.26227 0.27269 1.3693 -1.3574 -9.9925 1.009 4.2885 52.555 108.71 142 0.31613 0.29468 0.27054 0.12983 0.90791 -1.2856 -10.691 1.2243 5.0186 107.51 310.21 143 0.30444 0.31977 0.12929 0.1517 1.1741 -1.2235 -10.553 1.2052 6.5328 309.31 127.74 144 0.34719 0.30198 0.15141 0.15513 2.5485 -1.1431 -9.9839 1.4527 4.665 126.78 278.2 145 0.73918 0.34993 0.15548 0.15306 1.2035 -3.7544 -10.508 1.386 6.9865 278.09 224.01 146 0.38633 0.73982 0.15327 0.15945 0.94859 -3.4626 -10.086 1.5271 6.2592 223.97 234.71 147 0.88281 0.38841 0.15936 0.21123 1.7483 -3.4067 -10.258 1.2929 7.0045 235.6 98.655 148 0.91034 0.88286 0.21103 0.16498 1.5123 -3.4429 -10.217 1.0004 2.7287 98.884 173.85 149 0.51841 0.91188 0.16505 0.2382 0.12866 -3.3353 -10.578 0.97924 3.0842 172.58 398.45 150 0.27749 0.51972 0.23803 0.24697 1.4763 -2.2129 -10.391 1.5883 7.36 399.04 182.7 151 0.018691 0.27629 0.2464 0.18134 1.6242 -3.245 -9.3007 1.4981 6.8565 182.75 106.24 152 0.90977 0.017058 0.18162 0.14925 0.88989 -1.5786 -10.367 1.4556 7.3442 106.39 346.76 153 0.78691 0.90918 0.14972 0.071036 1.1644 -1.444 -10.56 1.5135 8.5463 345.34 282.36 154 0.61273 0.78833 0.073847 0.24478 1.5462 -2.9437 -9.806 1.3871 4.5883 283.74 20.174 MDL-NBS-HS-000021, REV 00 I-6 July, 2003 real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 155 0.44835 0.61154 0.24491 0.21959 1.509 -3.4983 -10.066 1.4672 6.1311 20.054 272.36 156 0.44417 0.44562 0.21926 0.19385 2.3672 -4.6266 -11.292 1.42 7.6511 270.96 316.33 157 0.92465 0.44049 0.19402 0.17247 1.2376 -1.4517 -10.102 1.4229 7.0916 315.47 94.793 158 0.076609 0.92395 0.17275 0.17226 1.297 -2.0342 -9.9661 1.0329 4.1036 95.841 169.24 159 0.97647 0.077995 0.17184 0.25011 1.2888 -2.622 -10.589 1.5898 6.7876 169.73 294.38 160 0.88672 0.97946 0.24939 0.10731 1.3071 -3.1179 -10.4 1.3553 6.203 294.14 280.49 161 0.65647 0.88508 0.10708 0.27559 1.3647 -3.1224 -10.027 1.3538 7.3059 281.47 392.49 162 0.18665 0.65755 0.2747 0.2403 1.4503 -1.3913 -10.072 1.2711 4.7212 392.92 192.19 163 0.64606 0.18543 0.23956 0.19953 0.86176 -3.9385 -9.369 5.6619 11.544 192.4 212.7 164 0.17568 0.6463 0.19972 0.13401 1.2833 -1.1169 -10.347 1.0227 5.7699 212.65 209.44 165 0.95061 0.17555 0.13472 0.19829 1.1026 -1.5522 -10.29 3.1197 12.928 209.18 215.42 166 0.14335 0.95267 0.19855 0.13239 0.68419 -2.4821 -10.302 1.1126 4.9715 215.41 233.45 167 0.75389 0.14211 0.13248 0.26065 0.35455 -3.6937 -10.285 1.3633 6.0234 233.3 262.83 168 0.088815 0.75375 0.26063 0.12567 1.5235 -2.5044 -10.222 1.5655 7.7213 262.21 88.429 169 0.23232 0.08869 0.12491 0.21379 1.4276 -3.7156 -10.133 1.1445 5.8916 89.341 207.49 170 0.76434 0.23274 0.21353 0.11061 1.1196 -1.2367 -10.602 1.0316 6.3693 207.28 148.16 171 0.28202 0.7616 0.11071 0.14232 1.2168 -3.7935 -10.308 1.2806 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 1.2576 7.8087 30.992 286.7 174 0.56885 0.53997 0.15046 0.20288 2.0937 -3.5938 -11.111 5.5411 10.593 286.98 254.82 175 0.20533 0.5681 0.20264 0.18426 2.1634 -2.1331 -10.054 5.042 12.993 254.19 153.59 176 0.40471 0.20916 0.18434 0.18769 0.61684 -3.4847 -10.156 1.0129 2.0458 153.92 185.52 177 0.9995 0.40055 0.18774 0.13838 1.1696 -2.4075 -10.442 1.3699 6.559 186.74 162.09 178 0.42544 0.99674 0.13813 0.1669 0.74682 -2.8729 -10.359 1.55 6.093 160.92 166.26 179 0.22637 0.42607 0.16701 0.29202 1.7114 -2.7766 -10.421 1.5916 8.4675 165.99 386.06 180 0.85993 0.22959 0.29861 0.17001 1.7077 -3.649 -10.414 0.38221 4.25 385.73 387.44 181 0.69081 0.85616 0.17039 0.14118 1.2552 -3.218 -9.4402 1.3926 6.3219 388.13 42.922 182 0.000316 0.69391 0.14143 0.23223 0.71843 -1.0082 -9.4219 1.4937 7.6176 44.051 170.83 183 0.66425 0.000898 0.23224 0.20456 0.98249 -3.165 -10.84 0.8293 1.8184 170.21 68.282 184 0.77963 0.6644 0.20481 0.02251 1.6687 -3.6051 -10.4 1.1766 4.7156 67.757 336.51 185 0.19856 0.77701 0.026558 0.20066 0.75819 -1.714 -10.656 1.3618 5.9137 336.43 333.76 186 0.39325 0.19937 0.2007 0.21764 1.5619 -2.3599 -9.8929 1.2442 6.6568 334.86 197.72 MDL-NBS-HS-000021, REV 00 I-7 July, 2003 real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 187 0.72376 0.39066 0.21781 0.13599 1.1067 -4.9164 -9.9021 4.357 10.666 197.9 62.435 188 0.68892 0.7222 0.13594 0.16567 0.55484 -2.4516 -10.331 1.0521 4.4061 61.878 112.56 189 0.98274 0.6877 0.1656 0.2091 1.5759 -2.0718 -10.67 3.9188 8.2587 112.62 326.39 190 0.45275 0.98273 0.20896 0.20396 1.8807 -3.6752 -10.546 1.5064 8.1244 326.54 71.187 191 0.50526 0.45272 0.20412 0.28052 1.3502 -3.2414 -9.9247 1.237 7.4539 70.071 298.21 192 0.49598 0.50781 0.27675 0.17357 1.6501 -2.2593 -10.652 1.3048 6.163 298.79 151.05 193 0.51183 0.49782 0.17314 0.18015 1.1476 -2.3726 -10.017 1.3812 4.1231 150.2 38.786 194 0.56134 0.51179 0.18047 0.17902 1.4929 -1.0761 -10.45 0.037042 6.0078 38.545 304.18 195 0.63937 0.56322 0.17911 0.18073 1.469 -3.1087 -10.948 1.3798 5.8151 303.54 376.34 196 0.18288 0.63794 0.18074 0.18708 1.4386 -2.9756 -9.9997 1.063 4.5618 376.21 230.27 197 0.49279 0.18439 0.18748 0.19706 0.99788 -3.0038 -9.5125 1.1799 5.6844 229.91 321.71 198 0.33957 0.49261 0.19742 0.13392 1.5377 -2.9649 -10.239 1.1972 7.7128 321.32 162.65 199 0.097933 0.33587 0.13394 0.17855 1.1373 -2.7936 -9.9428 1.1266 5.5324 163.61 275.46 200 0.02951 0.098121 0.17837 0.15841 1.2559 -2.5445 -10.415 0.38035 1.9883 274.65 268.56 MDL-NBS-HS-000021, REV 00 I-8 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 1 5.9431 4.0476 0.8181 1791.7 1.0875 1.0042 0.39801 0.12912 0.82832 0.11435 0.46636 2 5.4182 4.3547 -0.85495 1889.7 3.5582 1.6714 0.12714 0.83286 0.46792 0.2438 0.11184 3 5.7796 4.121 -0.1215 1820.9 3.5695 1.1986 0.83439 0.82826 0.11009 0.80568 0.24456 4 5.7825 4.1487 -0.44224 1984.5 0.90319 1.3675 0.82819 0.4672 0.24114 0.13093 0.80542 5 6.5266 6.9729 0.39432 1983.7 1.1434 1.5138 0.46584 0.11053 0.80879 0.73468 0.13052 6 6.5841 7.1394 0.3885 1904.1 0.90338 0.83369 0.11165 0.24447 0.13119 0.34017 0.73259 7 6.1287 2.9464 -0.03684 1815.2 2.9725 1.0459 0.24061 0.80742 0.73112 0.046301 0.34463 8 6.2574 4.2057 -0.46085 1855.7 2.9604 0.81838 0.80897 0.13118 0.34463 0.7483 0.04631 9 5.4494 3.1882 -0.30786 1978.3 1.4071 0.91882 0.13468 0.73388 0.04603 0.93663 0.74671 10 5.7923 5.8512 0.36448 1823.5 0.90334 1.5367 0.73421 0.34146 0.74618 0.55383 0.93928 11 6.8214 5.8404 -0.43612 1957.8 0.90373 0.79926 0.34235 0.045831 0.93877 0.79495 0.55274 12 6.4371 4.4718 0.27522 1878.4 2.8768 1.1894 0.049235 0.74967 0.55011 0.37712 0.79438 13 5.5876 3.13 -0.19072 1777.8 0.9034 1.5267 0.74852 0.93563 0.79164 0.67425 0.37882 14 5.9414 3.6295 -0.97733 1961.7 2.5538 1.3075 0.93625 0.55419 0.37553 0.65406 0.67351 15 6.8651 5.7631 0.29233 2028.3 0.94105 0.77849 0.55335 0.79368 0.67241 0.62614 0.65251 16 5.4152 3.2064 0.66404 1920 0.90314 1.6522 0.79004 0.37616 0.65068 0.24578 0.62768 17 6.3998 5.4719 0.059967 1973.9 2.6065 1.4544 0.37912 0.67379 0.62866 0.7112 0.24627 18 5.8912 3.9963 0.3514 1885.7 3.4344 0.77844 0.67485 0.65038 0.24892 0.3687 0.71087 19 5.8133 2.8633 -0.14488 1944.9 1.7505 1.8446 0.65415 0.62701 0.711 0.47078 0.36665 20 5.9168 5.5418 0.20717 1940.3 2.8112 1.0993 0.62895 0.24539 0.36569 0.58084 0.47477 21 6.4056 6.249 0.18479 1935.4 1.0695 1.288 0.24752 0.71071 0.47397 0.17007 0.5826 22 6.0838 4.799 0.15118 1856.8 2.2828 1.1135 0.71398 0.36774 0.58472 0.27474 0.1718 23 6.3714 5.711 -0.30353 1953.7 2.2025 1.5333 0.36813 0.47456 0.17021 0.1663 0.27316 24 5.9413 4.1293 0.25181 1883.7 2.0793 1.4721 0.47446 0.58489 0.27248 0.21154 0.16614 25 6.2597 5.251 -0.15875 1904.5 0.90375 1.0179 0.58135 0.17051 0.16512 0.60233 0.21337 26 13.877 5.1801 -0.03341 1925.9 2.4697 1.5852 0.17104 0.27259 0.21288 0.15556 0.60328 27 5.5811 5.0737 0.099475 1836.3 1.04 1.3493 0.27161 0.1696 0.60274 0.36263 0.15521 28 5.4277 3.6421 -0.38882 1862.7 1.4328 1.1809 0.16813 0.2111 0.15655 0.59017 0.36338 29 6.4587 5.3989 -0.27169 1834.9 1.8884 1.7837 0.21312 0.60029 0.36028 0.43416 0.59491 30 6.0631 4.1024 -0.39819 1847.3 0.90353 2.3132 0.60039 0.15621 0.59053 0.070562 0.43237 MDL-NBS-HS-000021, REV 00 I-9 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 31 5.9779 4.4969 -0.34483 1930.7 0.90382 0.94597 0.15578 0.36256 0.43289 0.69568 0.072704 32 6.1335 4.9141 0.11944 1831.2 0.90351 1.7452 0.36078 0.59297 0.074871 0.53396 0.69861 33 6.0066 3.3664 -0.41112 1882.9 0.90364 1.7258 0.59401 0.43237 0.69566 0.066305 0.53255 34 5.914 3.7497 -0.16609 1928.7 1.9686 1.4833 0.43426 0.073074 0.53246 0.81035 0.069985 35 5.7302 3.344 0.10967 1896.5 0.90348 0.77891 0.073323 0.6975 0.067696 0.30531 0.81321 36 5.7065 3.508 -0.07847 1796.8 1.0186 2.8271 0.6963 0.53488 0.81113 0.42313 0.30702 37 6.6832 4.9963 -0.76296 1950.8 1.9415 1.3809 0.53406 0.06581 0.30994 0.3125 0.42397 38 5.417 3.3073 0.23755 1916.7 1.2853 2.3632 0.065321 0.81078 0.4221 0.59713 0.31337 39 6.585 4.0865 0.037959 1792.3 0.90322 1.5062 0.81429 0.30812 0.31475 0.54755 0.59695 40 6.1896 4.9427 -0.81314 1978.7 2.3987 2.2149 0.30883 0.42455 0.59518 0.25434 0.54791 41 5.9651 4.348 0.37313 1870.6 1.6641 1.4434 0.42078 0.31241 0.54998 0.64335 0.25415 42 5.713 2.9858 -0.23107 1894.9 0.9032 1.6805 0.31042 0.59809 0.25497 0.45955 0.64074 43 6.6462 5.3518 -0.08994 1872.4 2.8904 1.8892 0.59966 0.549 0.64079 0.35531 0.45927 44 6.0208 4.7282 -0.2259 1929.2 0.90393 1.5782 0.54701 0.25493 0.45549 0.80303 0.35881 45 3.906 2.9717 0.11488 1919 1.2471 1.3553 0.25287 0.64012 0.35869 0.89767 0.8011 46 6.6834 5.7864 0.054703 1857.7 0.90394 1.634 0.64341 0.45504 0.80265 0.22022 0.89575 47 6.2498 3.8645 -0.29576 1938.4 1.9461 1.1435 0.45681 0.35554 0.89736 0.77279 0.22201 48 5.894 4.2993 0.16765 1902 1.729 1.5204 0.35767 0.8033 0.22106 0.75653 0.7745 49 6.3263 3.8948 -0.05232 1881.8 0.90376 2.0395 0.80219 0.8976 0.77391 0.55844 0.75595 50 6.4312 4.9688 -0.17085 1976.9 2.1536 0.77839 0.89527 0.22021 0.75624 0.13669 0.55693 51 6.2701 4.7739 0.35802 2009.1 1.3766 1.6906 0.22262 0.77394 0.55501 0.98761 0.13778 52 5.7903 3.6678 0.4722 1850.2 1.0029 1.7566 0.77311 0.75559 0.136 0.47673 0.98982 53 5.4627 5.1336 -0.32842 1968.2 2.8598 1.2814 0.75897 0.55733 0.98911 0.90165 0.47795 54 6.8287 4.4488 0.3249 1965 3.2589 1.7758 0.55928 0.13643 0.47798 0.57992 0.9017 55 6.3603 4.0579 0.30516 1921.4 0.90367 1.0305 0.13924 0.9852 0.90361 0.87597 0.57623 56 6.6608 5.7363 0.069194 1824.4 2.7248 1.1388 0.98859 0.47716 0.57516 0.52119 0.8799 57 16.607 6.1005 -0.43183 2082 2.6468 0.93337 0.47781 0.9021 0.87838 0.71927 0.52202 58 5.9294 3.5446 0.92526 1905.5 1.7898 1.5033 0.90019 0.57664 0.52429 0.81645 0.71732 59 6.8208 5.6306 -0.02427 2011 0.90342 0.77833 0.57734 0.87993 0.7155 0.63189 0.8157 60 6.5861 5.5676 0.47755 1925.5 3.6555 0.77871 0.87726 0.52225 0.81696 0.46085 0.63455 61 6.7075 4.8121 0.093825 2000.3 1.4533 1.2651 0.52405 0.71818 0.63403 0.6836 0.4645 62 6.1671 3.2399 0.44786 1914.8 3.2957 2.4448 0.71743 0.81913 0.46208 0.33488 0.68352 MDL-NBS-HS-000021, REV 00 I-10 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 63 6.7063 8.2148 0.027231 1955.4 1.8794 2.2914 0.81684 0.63478 0.68113 0.58819 0.33071 64 5.9284 4.5135 0.26113 1979.9 3.1858 0.87284 0.63336 0.46033 0.33102 0.84547 0.58869 65 6.0769 6.1286 0.38063 1936 1.6237 2.1973 0.46483 0.68187 0.58955 0.056247 0.84656 66 6.8568 4.8948 0.15618 1902.7 2.4911 1.6189 0.68036 0.33279 0.84721 0.72827 0.058062 67 6.5521 6.0288 -0.04535 1947.4 2.9073 0.77816 0.33359 0.58683 0.055556 0.78499 0.72763 68 5.8885 4.6899 0.21756 1876.5 2.1063 0.98331 0.5888 0.84941 0.72882 0.41564 0.78044 69 6.7622 5.4261 -0.19898 1927.3 1.3901 0.77861 0.84696 0.057968 0.78458 0.79874 0.41834 70 6.6141 5.7935 0.10325 1990.4 2.3218 1.0352 0.059202 0.72741 0.41612 0.26343 0.79713 71 6.4774 5.1016 0.41512 1786.2 0.91759 1.4684 0.72908 0.783 0.79694 0.32595 0.26112 72 6.0152 4.4622 -0.90291 1957.5 1.9062 1.2751 0.78309 0.41711 0.26183 0.21814 0.32885 73 6.6337 5.2846 0.2696 1971.2 3.0586 1.4506 0.41849 0.79753 0.3285 0.57109 0.21954 74 5.7281 3.9643 0.33449 1893.6 0.90317 1.5424 0.79539 0.26215 0.21556 0.051789 0.57407 75 5.9141 4.9391 -0.0988 1974.5 2.5336 2.6217 0.26288 0.32672 0.57298 0.10611 0.052027 76 6.614 5.9195 0.3558 1860.1 2.769 2.1371 0.32568 0.21746 0.053163 0.40591 0.10719 77 5.583 2.9262 -0.2854 1874.8 1.2181 0.7788 0.21624 0.57483 0.10741 0.91972 0.40777 78 6.4587 5.4588 -0.20391 1849.7 2.8383 2.0286 0.57311 0.052277 0.40829 0.8908 0.91655 79 6.7143 5.6723 -0.33597 1924.3 0.90379 1.6683 0.05449 0.10898 0.91926 0.19459 0.89262 80 6.4207 4.293 0.088795 1785.3 0.90398 1.9847 0.10825 0.4085 0.89123 0.87371 0.19373 81 13.178 5.7162 -0.95629 1813.8 0.90365 2.8559 0.40932 0.91507 0.19271 0.66865 0.87036 82 6.2222 3.6944 -0.46886 1891.7 1.847 0.77807 0.91592 0.89045 0.87402 0.022481 0.66851 83 5.874 3.9482 -0.11054 2018.2 0.90316 1.5616 0.89293 0.19045 0.66901 0.23693 0.024774 84 5.4575 3.5414 0.57263 2006.8 0.90333 0.77854 0.19004 0.87062 0.023309 0.091047 0.2352 85 6.6604 4.87 0.47059 1842.7 1.1819 1.0206 0.87302 0.66938 0.2368 0.26906 0.091802 86 5.6849 2.9113 -0.3659 1998.4 3.3469 1.7082 0.6656 0.024152 0.090667 0.54398 0.26823 87 5.6681 3.1148 0.44164 1944.2 3.2399 0.77803 0.023333 0.23528 0.26661 0.41455 0.54303 88 6.0094 4.2502 0.19729 1751.8 0.90358 2.5253 0.23803 0.090919 0.54429 0.52672 0.41381 89 18.764 6.1699 -1.2709 1853.8 3.1498 1.1287 0.093541 0.26709 0.4112 0.6066 0.52874 90 6.5229 6.0913 -0.31499 1806.3 2.2535 0.77822 0.26696 0.54419 0.52817 0.94606 0.60614 91 5.49 3.4321 -0.57236 1861.2 0.90307 1.0671 0.54172 0.41108 0.60997 0.86265 0.94816 92 14.607 6.0081 -0.27432 1917.9 0.90372 0.77868 0.41491 0.52686 0.94891 0.12263 0.86301 93 6.5563 5.2247 0.050354 1892.7 0.90328 1.3907 0.52942 0.60533 0.86005 0.84008 0.12295 94 5.7647 2.2972 -0.10337 1915.2 0.9038 1.9143 0.60947 0.9471 0.12418 0.70779 0.84136 MDL-NBS-HS-000021, REV 00 I-11 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 95 5.7985 3.6118 0.032758 1931.1 1.7069 0.90439 0.94625 0.86346 0.84482 0.83642 0.70974 96 5.7406 3.0688 0.13087 2035.9 1.2067 2.0823 0.86403 0.12324 0.70673 0.9929 0.83838 97 6.1417 3.7298 0.73013 1995.7 1.6498 0.77824 0.12021 0.84037 0.83719 0.014448 0.9937 98 6.0823 4.7642 0.43066 1819 1.9956 1.3968 0.84499 0.70858 0.99258 0.62177 0.010011 99 6.3706 4.2707 -0.45167 1988.1 3.4882 2.1656 0.70993 0.83907 0.011816 0.080484 0.62177 100 5.9745 4.6949 0.40649 1952.6 3.1045 0.7812 0.83656 0.99291 0.62029 0.25668 0.084052 101 6.4906 4.9982 0.24501 1986.7 0.90337 0.77897 0.99369 0.011109 0.084139 0.74363 0.25783 102 6.53 6.296 0.40263 2096.8 3.03 0.77829 0.012139 0.6206 0.25558 0.008536 0.74421 103 6.2966 5.9683 0.9646 1736.1 2.4303 1.7389 0.62312 0.083331 0.74082 0.93232 0.008844 104 5.5766 3.1765 -1.3741 1934.3 2.9977 0.77877 0.082851 0.25726 0.005755 0.32377 0.93333 105 5.7063 5.8845 0.14663 1800.5 3.6849 1.4182 0.25651 0.74433 0.93264 0.031595 0.32274 106 6.2582 5.3933 -0.65556 1859.7 0.90304 1.0833 0.74383 0.008921 0.32254 0.28928 0.032629 107 7.7608 5.8838 -0.29014 1960.3 2.0719 2.503 0.007082 0.93162 0.032139 0.10235 0.28732 108 10.662 8.4623 0.28677 1711.5 0.90325 2.5914 0.9343 0.32226 0.28774 0.48315 0.10135 109 5.7953 1.9755 -1.4049 2027.8 0.90377 2.6724 0.32398 0.033875 0.10227 0.82137 0.48128 110 6.2488 5.0698 0.65206 1874.1 2.5889 2.7358 0.034804 0.28617 0.48419 0.20142 0.82385 111 5.5802 3.0312 -0.2145 1765.8 0.90302 0.8074 0.28713 0.10452 0.82206 0.85408 0.20133 112 5.4934 3.6783 -1.1351 1866.8 3.4201 1.0809 0.10321 0.48255 0.20087 0.03713 0.85191 113 6.4423 5.5068 -0.25443 1811.7 0.90397 1.1169 0.48009 0.82013 0.85325 0.48798 0.038156 114 5.9016 1.9046 -0.47282 1906.2 0.9031 1.0955 0.82478 0.20143 0.036873 0.86745 0.48608 115 6.5925 6.2268 -0.02221 1981.5 0.90386 1.1662 0.20399 0.85208 0.48667 0.15011 0.86707 116 5.5144 3.9339 0.38733 1845.1 0.90331 1.7033 0.85464 0.036304 0.86896 0.14649 0.15383 117 1.2386 2.4753 -0.35313 1991.5 1.4715 1.2305 0.038431 0.48549 0.15269 0.041893 0.14705 118 6.0572 3.7894 0.42255 1773.4 2.934 2.2435 0.4888 0.86597 0.1496 0.76799 0.042585 119 5.5503 3.1009 -1.0969 1907.4 0.90361 2.4104 0.86947 0.1505 0.041331 0.11687 0.76983 120 6.8224 4.5391 -0.01547 1997.7 3.0755 1.434 0.15471 0.14696 0.76917 0.50225 0.11804 121 6.7078 5.8264 0.4368 1830.6 0.90311 1.0568 0.1482 0.041927 0.11919 0.29972 0.50172 122 6.4723 3.4667 -0.41438 1827.8 1.4778 0.77813 0.043749 0.76965 0.50249 0.92993 0.29938 123 6.1209 5.929 -0.41778 1776.7 3.1256 2.3797 0.76795 0.11768 0.29931 0.94398 0.92995 124 4.3387 2.6339 -1.0303 1966.5 0.90346 1.7621 0.11763 0.50186 0.92988 0.9591 0.94279 125 5.8421 4.5436 0.31744 1818.1 0.90345 1.5484 0.50125 0.29969 0.9417 0.9723 0.95904 126 6.6251 5.9877 -0.45746 1910.2 0.90312 1.3264 0.29829 0.92712 0.95959 0.16336 0.9735 MDL-NBS-HS-000021, REV 00 I-12 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 127 5.4937 3.2852 0.001514 1868.8 2.6949 1.3193 0.92626 0.94495 0.97011 0.29355 0.16075 128 5.8027 3.2702 -0.24028 2024.4 0.90336 2.4598 0.94317 0.95688 0.16089 0.31924 0.29198 129 5.9088 2.6876 0.63084 2032.1 1.5522 0.77853 0.95718 0.97024 0.29356 0.30068 0.31688 130 6.8267 5.6069 0.70954 2044.3 0.9039 2.7802 0.97338 0.16089 0.31924 0.34894 0.30226 131 5.6516 3.1558 0.77432 2060.7 3.4028 2.2586 0.16471 0.29112 0.30169 0.73742 0.34723 132 6.1835 4.6179 0.8669 1834 3.4585 1.6053 0.2919 0.31659 0.34685 0.38542 0.73879 133 6.2919 3.8323 -0.40523 1867.7 3.5324 0.86487 0.31639 0.30034 0.7382 0.8844 0.38707 134 6.8574 6.22 -0.24736 1873.1 3.5873 1.5948 0.30114 0.34737 0.38911 0.91417 0.88103 135 6.6929 6.2657 -0.21795 1869.7 0.9035 0.84208 0.34709 0.7389 0.8827 0.51527 0.91491 136 6.8367 6.5706 -0.23599 1879.7 0.90388 2.6439 0.73959 0.38723 0.91191 0.27739 0.51637 137 6.3765 7.4878 -0.18222 1959.9 0.90395 0.77896 0.3856 0.88123 0.51821 0.01555 0.27512 138 5.4213 3.3293 0.28472 1888.1 0.90392 1.721 0.8846 0.91276 0.27884 0.90859 0.015142 139 6.5404 3.8249 -0.13344 2003.3 0.96295 0.77857 0.91058 0.51807 0.019829 0.78559 0.9075 140 6.3039 3.9127 0.45875 2015.8 2.5618 0.96496 0.51863 0.27877 0.90669 0.61248 0.78753 141 5.6224 3.847 0.55231 1913.2 1.1215 1.7325 0.27928 0.018004 0.78506 0.44553 0.6123 142 6.2112 4.0184 0.022971 1864.3 3.212 1.0603 0.017035 0.90513 0.61484 0.44206 0.44827 143 6.5305 5.5041 -0.26788 1747.7 3.339 1.6273 0.90617 0.7874 0.44935 0.92037 0.44137 144 6.6787 4.1826 -1.319 2012.9 1.6067 1.4599 0.78778 0.61244 0.44289 0.077399 0.92211 145 6.4408 6.0396 0.51974 1971.7 0.90383 1.4942 0.61002 0.44738 0.92177 0.9795 0.075209 146 13.65 6.1585 0.34072 1931.8 0.90305 0.9128 0.44868 0.44026 0.078919 0.88632 0.9771 147 6.1936 4.6736 0.13291 1900.1 3.3213 1.2546 0.44447 0.92422 0.97874 0.65608 0.88741 148 5.7435 3.7619 -0.06401 1898.7 2.7905 2.8905 0.92373 0.077673 0.88803 0.18793 0.65881 149 5.4669 2.0896 -0.07036 2019.6 2.0286 1.2974 0.076063 0.97623 0.65712 0.646 0.1872 150 8.9403 6.1315 0.60144 1800.4 1.3319 0.95621 0.977 0.88897 0.18621 0.17963 0.6468 151 6.4227 5.6864 -0.70644 2065.3 1.3096 2.1114 0.88659 0.65894 0.64638 0.9533 0.17576 152 6.3057 5.0306 0.88838 2004.3 3.3771 1.6455 0.65842 0.18734 0.17977 0.14185 0.9527 153 6.478 4.394 0.46244 1941.7 0.90323 0.77801 0.18664 0.64891 0.95287 0.75049 0.14379 154 5.4622 4.3793 0.1871 1840.8 3.6119 1.6096 0.64507 0.17691 0.14233 0.086316 0.75248 155 6.5647 6.1992 -0.37093 1939.2 3.2128 1.7536 0.17711 0.95118 0.75482 0.23203 0.087912 156 5.9147 2.9992 0.17419 1838.4 2.2216 0.88998 0.95059 0.14242 0.086579 0.7641 0.23087 157 5.7989 7.8565 -0.38192 2039.2 0.90356 1.2436 0.14252 0.75409 0.23232 0.28118 0.76162 158 6.2505 6.0621 0.75051 1826.1 2.1818 1.6866 0.75153 0.088803 0.76344 0.67984 0.28492 MDL-NBS-HS-000021, REV 00 I-13 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 159 6.8844 5.1999 -0.42699 1963.6 0.90353 1.6433 0.08683 0.2337 0.28051 0.53945 0.67884 160 5.5314 3.4208 0.29815 1803.9 3.5015 2.797 0.23407 0.76141 0.67786 0.56739 0.53767 161 6.5527 5.1585 -0.61352 1852.5 0.90344 1.3361 0.76128 0.2824 0.53504 0.20679 0.5676 162 6.4007 3.3742 -0.3168 1966.2 2.6324 1.4226 0.28348 0.67679 0.56754 0.4036 0.20555 163 6.8426 6.3283 0.31264 1864.5 0.90326 1.4115 0.6774 0.5359 0.20907 0.99995 0.40382 164 1.2468 3.2461 -0.26077 1945.8 0.9037 1.4326 0.53853 0.56976 0.40303 0.42927 0.99514 165 6.6391 5.5608 0.21202 1917.8 2.6793 1.4902 0.56716 0.20581 0.99747 0.22505 0.42972 166 4.298 3.0393 0.042953 1923.5 0.90386 1.5815 0.20914 0.40267 0.42578 0.85881 0.22675 167 6.3136 3.5934 0.082558 1846.9 2.304 0.85035 0.40148 0.99633 0.22882 0.69465 0.85692 168 6.8724 5.5989 -0.3463 1890.8 1.6854 1.4043 0.99946 0.429 0.85968 0.002816 0.69442 169 6.0327 3.7778 -0.11436 2150 1.8197 1.1554 0.42931 0.22809 0.69398 0.66467 0.004499 170 6.6137 5.2625 0.9848 1896.2 0.90363 0.77864 0.22617 0.85547 0.000323 0.77513 0.66304 171 6.133 4.737 -0.08534 1851.6 1.1755 0.77818 0.85851 0.69354 0.66257 0.19757 0.77725 172 5.5432 4.8472 -0.32558 1992.9 3.6966 1.6616 0.69111 0.003257 0.77945 0.39292 0.19571 173 5.7763 3.487 0.42615 1949.6 1.2557 1.5596 0.003656 0.66345 0.19765 0.72304 0.3905 174 9.6773 4.2364 0.23043 1675.6 0.90369 1.1742 0.66204 0.77506 0.39062 0.68608 0.72139 175 19.99 8.772 -1.4274 1942.6 3.1009 1.3104 0.77547 0.19838 0.72232 0.98368 0.68895 176 5.5716 4.3221 0.1918 1969.8 2.3748 1.2113 0.19977 0.39453 0.68752 0.45485 0.98231 177 5.6452 3.5686 0.32826 1844.1 0.903 1.2221 0.39164 0.72283 0.98031 0.50929 0.45473 178 13.398 5.9529 -0.36243 1888.8 2.2491 2.6986 0.72173 0.68745 0.45427 0.49792 0.50512 179 6.2551 5.3194 -0.1308 1955.7 2.7377 2.7263 0.68811 0.98268 0.5089 0.51067 0.49559 180 4.8797 1.7248 0.26453 1948.5 0.90359 0.77843 0.98291 0.45113 0.49716 0.56127 0.51465 181 6.4204 5.2177 0.22384 2076 1.14 1.249 0.45143 0.50761 0.51411 0.63635 0.56495 182 13.365 5.6477 0.90461 1900.3 2.4991 0.77886 0.50641 0.4978 0.56414 0.18298 0.63987 183 5.4669 3.4549 -0.05683 1911.2 2.3608 1.9716 0.49998 0.51184 0.63908 0.49347 0.18035 184 6.527 4.1951 0.010673 1909.7 3.6328 1.9303 0.51124 0.56314 0.18468 0.33757 0.49318 185 6.1383 5.4358 -0.00257 1912.2 1.3576 1.3653 0.56096 0.63868 0.49378 0.095147 0.339 186 6.6416 5.3098 0.015309 1922.2 1.5741 0.77876 0.63832 0.18425 0.33664 0.02893 0.098947 187 6.891 7.9127 0.072474 1937 1.5171 0.98742 0.18035 0.4943 0.0968 0.70491 0.029299 188 6.1474 4.4289 0.16452 1839.5 1.5859 1.8086 0.49056 0.33741 0.026781 0.61604 0.70419 189 6.525 4.637 -0.37947 1909 1.7945 0.77888 0.33874 0.096534 0.70431 0.35289 0.61966 190 6.2508 4.5943 -0.00717 1877.3 2.1272 1.6963 0.096831 0.029759 0.61591 0.43939 0.35146 MDL-NBS-HS-000021, REV 00 I-14 July, 2003 real. # KDUVO KDUAL GWSPD BULKDEN SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 191 6.0393 4.6492 -0.19088 1809 0.90355 1.1569 0.028917 0.70069 0.35311 0.37338 0.43794 192 5.9913 4.8274 -0.50508 1763.2 1.5065 0.77832 0.70456 0.6185 0.43943 0.38091 0.37255 193 5.878 5.1259 -1.2166 1951.2 0.921 1.7169 0.61513 0.35035 0.37237 0.96251 0.38203 194 2.3362 3.4099 0.23869 1933.3 0.9033 2.5605 0.35362 0.43951 0.38267 0.96816 0.96337 195 6.1 4.5729 0.13794 1880 0.90309 1.4774 0.43658 0.37213 0.96475 0.063027 0.96716 196 5.9918 3.9869 -0.176 1897.5 2.4068 1.766 0.37128 0.38098 0.96775 0.39953 0.061097 197 5.605 3.0866 -0.07449 1884.9 2.0457 1.2188 0.38369 0.964 0.061914 0.1285 0.3971 198 5.7889 2.3548 -0.15273 1887.1 0.98501 1.6249 0.96476 0.96823 0.39947 0.83442 0.12711 199 6.0367 5.3679 -0.14182 2047.7 1.3082 1.601 0.96697 0.061409 0.12965 0.82773 0.83158 200 6.1339 5.0355 0.79534 2055 1.0649 1.5667 0.061482 0.39772 0.83314 0.46639 0.82855 MDL-NBS-HS-000021, REV 00 I-15 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 1 0.83233 0.24005 0.80624 17.732 1.9903 812.85 440.3 87.238 108.87 4.8775 2 0.82718 0.80526 0.13308 4.6087 1.6863 438.05 704.33 99.833 92.939 5.0531 3 0.46566 0.13442 0.73247 12.27 1.0289 707.27 688.4 33.356 77.02 4.2620 4 0.11361 0.73275 0.34383 3.2112 0.54985 688.19 663.39 66.542 109.71 4.5371 5 0.24003 0.34009 0.049709 7.6813 2.4022 663.62 323.7 77.052 124.51 4.2375 6 0.80576 0.046205 0.7459 6.9906 2.2194 321.01 742.97 82.59 100.9 4.3941 7 0.13452 0.74864 0.93901 6.0614 1.7185 741.48 430.16 81.992 112.08 5.1399 8 0.73186 0.93694 0.55457 2.18 1.8825 429.34 525.79 79.222 94.367 4.2041 9 0.34145 0.55106 0.79371 9.1734 1.7536 526.19 626.36 91.596 106.1 4.6918 10 0.047266 0.79274 0.37606 3.1527 1.7716 626.1 256.08 77.994 105.03 5.1004 11 0.74875 0.37598 0.67186 3.965 3.3158 255.36 346.45 78.102 104.08 4.8134 12 0.9384 0.67431 0.65349 4.8648 3.4105 344.48 252.75 86.185 89.193 3.8495 13 0.55426 0.65427 0.62915 1.5987 0.85794 250.6 293.32 95.152 107.76 5.3892 14 0.79285 0.62833 0.24857 2.3803 1.8079 289.57 644.32 83.888 93.974 4.9578 15 0.37977 0.24591 0.71151 1.5328 1.1538 644.32 240.83 49.263 97.825 3.8205 16 0.67304 0.71226 0.36864 1.9111 2.7247 241.27 425.57 88.886 102.21 5.5740 17 0.65016 0.36852 0.47149 5.1696 2.7109 426.26 632.99 79.081 85.471 4.6028 18 0.62547 0.47303 0.58007 1.4755 1.9399 631.8 489.65 90.427 90.109 4.8036 19 0.24894 0.58477 0.17326 3.117 1.099 489.47 166.43 80.258 85.408 4.6142 20 0.71268 0.17148 0.2719 4.9406 1.4758 166.72 727.65 87.551 87.421 5.1106 21 0.36671 0.27358 0.16723 3.6422 2.6485 726.02 580.16 56.616 102.9 4.9749 22 0.47389 0.16561 0.2131 0.74358 1.1613 578.39 161.12 95.787 84.683 4.4990 23 0.58452 0.21367 0.60303 8.6622 2.4699 159.62 829.77 75.98 93.664 5.2601 24 0.17185 0.60264 0.15762 4.4577 1.6923 830.57 376.18 78.857 102.68 4.8586 25 0.27162 0.15986 0.36181 0.70371 0.73272 375.4 481.98 75.926 96.375 4.6846 26 0.16981 0.36202 0.59096 13.014 2.4972 479.18 381.72 79.314 79.051 5.5658 27 0.21102 0.59494 0.43437 2.6796 3.1595 381.7 638.55 99.785 107.22 5.6739 28 0.60015 0.43132 0.070798 3.5794 2.1024 638.67 590.61 75.657 100.17 4.4166 29 0.15677 0.070876 0.69583 2.6814 2.615 593.85 328.84 89.188 78.996 5.5237 30 0.36158 0.69708 0.53266 4.9996 1.7618 326.95 678.7 86.55 113.21 5.4983 MDL-NBS-HS-000021, REV 00 I-16 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 31 0.59138 0.53117 0.065333 4.5813 2.3314 677.42 509.58 78.09 91.582 4.9849 32 0.43049 0.068262 0.81193 2.2104 2.2912 511.98 422.18 75.186 96.013 4.1083 33 0.074454 0.81122 0.30876 6.6744 2.2459 422.1 820.66 49.841 91.679 5.9685 34 0.6978 0.3088 0.42281 3.8414 1.4862 822.12 909.44 87.598 102.71 4.8878 35 0.53021 0.42103 0.3129 3.0765 2.4162 909.46 300.12 97.988 100.7 5.6821 36 0.068291 0.31034 0.59624 12.605 1.7497 298.61 796.55 77.33 89.246 5.0253 37 0.81435 0.59788 0.5451 16.073 1.9504 794.22 779.79 83.752 104.64 5.6522 38 0.30796 0.54611 0.25403 1.9833 2.1609 779.57 599.93 94.378 97.323 4.9442 39 0.42208 0.25262 0.64219 11.416 1.2938 599.68 224.14 61.75 93.554 5.4314 40 0.31087 0.64499 0.45689 10.91 1.5451 222.51 987.6 172.18 112.55 5.5843 41 0.59771 0.45948 0.35958 4.6453 1.2728 987.07 529.6 96.635 119.63 5.2355 42 0.54692 0.35889 0.80226 1.2839 1.4037 530.28 914.05 77.52 87.977 4.8650 43 0.2541 0.80481 0.89657 19.479 2.1923 910.33 620.16 157.77 110.89 5.3636 44 0.64387 0.89955 0.2211 4.0008 1.2504 620.04 891.15 96.594 110 4.6416 45 0.45648 0.22056 0.77458 16.385 1.7351 891.41 571.89 46.513 101.28 5.0719 46 0.35594 0.77106 0.75751 4.8125 2.1801 571.12 746.07 85.511 83.562 5.6180 47 0.8044 0.75705 0.55876 15.444 1.8744 747.9 837.75 88.67 135.96 3.7922 48 0.89716 0.55861 0.13615 4.3716 0.91376 835.64 667.68 76.295 98.093 5.4487 49 0.22083 0.1361 0.98634 9.4864 2.3907 670.09 514.51 80.551 120.19 5.5328 50 0.7728 0.98683 0.4783 13.063 2.0576 514.64 715.01 98.197 102.03 4.7887 51 0.75745 0.47635 0.90182 6.2683 0.88603 712.87 399.44 70.169 118.01 5.5539 52 0.5575 0.90124 0.57823 3.9013 2.6678 399.58 628.62 89.094 99.752 4.5138 53 0.13948 0.57826 0.87579 8.0909 1.6269 627.55 864.64 98.041 107.99 4.6338 54 0.9886 0.87902 0.52465 2.8593 1.849 864.15 150.75 250.9 113.65 4.4139 55 0.47636 0.52426 0.71777 4.9025 1.6384 151.12 756.56 92.821 104.29 5.0128 56 0.90226 0.71853 0.81891 14.232 2.1894 754.26 803.41 98.759 97.509 3.7624 57 0.57565 0.81586 0.63343 0.60484 2.0898 806.44 474.02 99.074 106.51 3.9613 58 0.87726 0.63481 0.46333 9.816 1.5057 476.79 818.8 70.063 92.659 4.7692 59 0.52271 0.46349 0.68074 11.868 2.2752 818.62 336.85 73.661 102.42 5.6955 60 0.71539 0.68244 0.33489 3.5262 1.9216 336.49 394.56 95.558 115.57 5.6712 61 0.81858 0.33278 0.58895 12.424 1.7264 394.68 294.57 68.061 78.053 4.3374 62 0.63424 0.58517 0.84543 2.2896 2.6399 296.99 615.74 81.64 108.66 5.6464 MDL-NBS-HS-000021, REV 00 I-17 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 63 0.46136 0.84982 0.056311 2.8305 2.956 613.08 148.46 94.821 111.49 5.3243 64 0.68066 0.057841 0.72978 1.9279 1.426 145.92 195.85 63.426 95.797 3.5267 65 0.33153 0.72969 0.78261 4.7985 2.5599 198.3 467.99 86.455 112.44 4.4555 66 0.58726 0.78325 0.4167 0.53612 2.5179 465.66 924.72 78.976 89.718 3.9177 67 0.84941 0.41653 0.79797 1.0404 2.1075 926.22 903.86 84.916 92.376 4.5297 68 0.058578 0.79803 0.26066 3.4568 1.1735 903.5 273.95 82.841 87.717 4.9694 69 0.728 0.26347 0.32972 16.911 3.6979 272.15 883.85 38.951 101.83 4.7835 70 0.78038 0.32548 0.21687 16.014 1.9618 885.32 702.03 37.268 77.264 4.9502 71 0.41596 0.21798 0.57346 1.7511 2.9809 700.89 121.54 84.703 81.802 5.1614 72 0.79808 0.57228 0.054074 15.225 2.1481 119.34 314.87 78.102 95.495 5.8209 73 0.26002 0.052024 0.10657 7.5336 2.8736 311.66 183.97 86.508 121.95 5.6385 74 0.32626 0.10795 0.40776 0.24534 2.039 183.08 339.8 90.516 119.24 4.0269 75 0.21674 0.40841 0.91631 2.0967 2.4268 339.18 589.62 53.927 86.459 5.6138 76 0.57425 0.91592 0.89188 0.92987 2.6786 588.04 473.21 99.006 117.71 5.4099 77 0.053163 0.89356 0.19002 2.3237 2.2583 471.84 575.22 70.292 105.81 5.6053 78 0.10825 0.19055 0.87486 4.5209 1.933 572.68 648.88 89.226 73.738 5.9754 79 0.40749 0.87385 0.66564 3.5023 2.361 646.51 950.64 63.707 88.667 3.3825 80 0.91533 0.66936 0.024592 4.4069 1.6742 952.86 877.79 14.829 80.824 5.1987 81 0.89182 0.024802 0.238 5.2885 2.1683 877.91 212.04 75.662 89.887 3.8823 82 0.19247 0.23768 0.092733 18.024 2.7659 208.9 860.23 97.057 100.63 4.5064 83 0.8716 0.093798 0.2697 14.834 0.82441 860.11 736.5 77.366 95.705 5.4698 84 0.66663 0.26782 0.54484 1.1753 2.4578 738.68 855.93 95.89 100.03 3.2578 85 0.022039 0.54487 0.41286 14.054 2.5864 854.64 993.11 90.006 103.17 5.7672 86 0.23834 0.41297 0.5255 9.0438 1.8464 994.47 110.54 92.685 126.14 4.6235 87 0.09303 0.52693 0.60617 13.953 2.6304 110.62 659.13 299.77 116.81 3.6374 88 0.26994 0.6098 0.94768 19.747 1.5209 658.39 174.16 94.012 82.794 4.5614 89 0.54397 0.94692 0.8623 0.17871 1.6666 172.55 331.74 94.101 115.37 3.9564 90 0.41441 0.86116 0.12201 5.8295 1.4188 329.82 767.45 85.307 107.69 4.8941 91 0.52656 0.12189 0.84487 0.84378 2.1415 766.83 108.83 84.217 115.02 5.5922 92 0.60929 0.84095 0.70556 2.267 0.76916 108.02 939.97 156.24 139.22 4.3696 93 0.94947 0.70568 0.83988 10.333 1.062 937.88 389.58 81.663 71.507 5.6284 94 0.8607 0.83864 0.99131 0.11614 1.8277 388.79 129.98 76.875 103.93 3.6732 MDL-NBS-HS-000021, REV 00 I-18 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 95 0.12496 0.99254 0.012151 17.474 3.0474 127.83 358.17 89.827 80.093 4.8986 96 0.84424 0.014322 0.6206 2.7787 2.9291 359.12 191.36 97.079 89.546 5.6454 97 0.70863 0.62212 0.081579 0.34647 1.3502 192.1 534.33 96.311 109.3 4.1823 98 0.83814 0.081611 0.25537 2.5184 2.8488 534.89 840.2 58.463 68.715 4.1468 99 0.99153 0.25963 0.74219 1.0399 2.3268 841.52 281.38 92.69 124.07 3.7073 100 0.01084 0.74266 0.00638 4.0701 0.4986 282.1 868.25 77.692 92.211 5.5092 101 0.6226 0.008537 0.9333 13.369 1.4611 866.27 135.17 29.459 74.655 3.9941 102 0.082755 0.93024 0.32214 1.8159 1.0042 131.91 540.77 67.995 90.751 4.9205 103 0.25772 0.32134 0.031583 14.474 1.5392 539 882.9 15.984 81.538 4.5873 104 0.74379 0.031874 0.28828 0.39787 2.0766 880.48 236.85 78.325 98.315 5.7497 105 0.0066 0.28693 0.10244 4.0921 1.833 238.35 232.4 94.807 113.88 5.8007 106 0.9304 0.10181 0.48385 14.975 2.0524 232.95 136.31 30.253 86.943 5.8716 107 0.32214 0.48365 0.82219 1.4235 2.2089 139.73 790.5 87.018 116.02 5.9238 108 0.034931 0.82127 0.20133 1.3614 3.2142 789.56 205.25 15.295 75.807 4.2303 109 0.28848 0.20343 0.85064 0.47523 2.8115 204.97 554.05 69.971 98.454 4.5744 110 0.10153 0.85494 0.037852 11.212 1.131 552.51 367.97 85.61 117.35 4.6150 111 0.48488 0.039425 0.48927 1.1337 2.7541 369.82 936.25 45.83 84.514 4.5945 112 0.82181 0.48703 0.86816 4.2122 2.4064 935.32 947.4 82.043 84.306 4.6692 113 0.20309 0.86964 0.15423 2.581 2.735 949.48 963.04 80.577 76.071 5.4624 114 0.85318 0.15153 0.14775 17.239 3.9162 960.13 975.53 98.014 110.59 4.7348 115 0.037029 0.14723 0.043615 17.784 0.28545 973.13 244.95 67.66 82.558 5.6580 116 0.48919 0.044629 0.76977 18.48 2.2311 247.87 362.6 94.324 98.991 5.6920 117 0.86816 0.76877 0.11639 19.016 0.96482 361.16 385.18 76.984 91.229 4.9390 118 0.15324 0.11722 0.50208 1.5062 1.5153 386.4 373.33 94.706 123.17 4.5446 119 0.14901 0.50107 0.29533 2.5563 2.4838 370.58 412.47 90.755 124.87 3.4129 120 0.042737 0.29727 0.92996 2.7567 0.24038 414.2 765.76 79.187 127.87 5.6875 121 0.76893 0.92623 0.94325 2.6167 3.1079 763.07 449.47 187.93 130.96 5.5441 122 0.11682 0.94167 0.9558 2.9723 1.6573 450.84 893.8 80.185 85.118 5.1761 123 0.50185 0.95667 0.97337 10.141 0.63252 896.39 919.94 75.516 90.898 4.8374 124 0.29877 0.97469 0.16451 3.2972 1.5766 920.24 564.89 68.053 92.057 4.8294 125 0.9262 0.16335 0.29046 15.653 1.0562 566.15 347.78 84.548 91.285 5.7118 126 0.94249 0.29347 0.31994 16.673 1.963 349.81 116.51 77.995 93.119 3.8728 MDL-NBS-HS-000021, REV 00 I-19 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 127 0.95651 0.31629 0.30057 4.3587 2.6953 115.03 915.08 80.543 109.14 5.9370 128 0.97227 0.30062 0.34665 2.4069 1.3783 917.36 808.56 94.029 94.609 5.6665 129 0.16375 0.34816 0.73806 0.20749 2.7931 807.17 653.26 47.702 118.5 5.3010 130 0.2908 0.73514 0.38982 16.487 0.64424 650.78 504.69 95.675 121.56 4.3202 131 0.31825 0.38902 0.88375 12.122 1.9739 502.29 497.53 79.084 99.609 5.2718 132 0.30346 0.8811 0.91445 5.5165 2.8316 497.26 928.08 87.425 90.397 4.2901 133 0.34536 0.91351 0.51775 3.7934 1.2279 932.09 167.74 78.926 71.682 5.8432 134 0.73979 0.51891 0.27618 3.7533 1.2149 170.49 978.15 53.697 120.69 4.1248 135 0.38918 0.27944 0.017364 17.149 0.71527 981.81 900.52 29.152 111.8 5.4871 136 0.88142 0.018064 0.90692 0.80096 2.5438 899.31 692.85 85.375 103.46 3.9044 137 0.91369 0.90812 0.78832 19.129 1.1016 691.49 268.16 75.06 96.932 4.4487 138 0.51854 0.78574 0.61055 15.729 2.0081 266.74 684.08 95.652 96.697 5.5024 139 0.27967 0.61066 0.44885 7.1148 1.6021 682.82 261.21 86.741 122.43 4.5558 140 0.018437 0.44944 0.44473 1.6814 3.1047 259.8 957.8 52.56 79.558 5.3464 141 0.90992 0.44492 0.92486 6.8321 3.1925 959.02 228.62 92.132 132.79 4.9658 142 0.78977 0.92496 0.077725 1.6259 3.2736 228.36 778.38 90.726 118.79 4.9995 143 0.61162 0.077621 0.97922 18.18 3.4137 776.75 180.78 84.511 105.23 4.3784 144 0.44672 0.97709 0.88689 1.3552 1.2599 177.45 308.05 79.546 86.269 4.7661 145 0.44483 0.88694 0.65537 10.812 1.5851 307.83 787.18 26.188 104.91 5.9886 146 0.92381 0.65965 0.18644 0.89423 1.6389 788.47 355.4 77.964 85.829 4.8111 147 0.077437 0.18566 0.64725 2.0794 1.6102 354.67 709.36 97.694 127.33 4.4372 148 0.97688 0.64518 0.17796 11.024 1.7018 710.03 584.97 89.418 83.89 5.6345 149 0.88764 0.17513 0.95462 2.4793 2.4779 585.05 611.31 87.727 109.74 5.3747 150 0.65902 0.95013 0.14251 7.9905 1.7862 610.1 285.37 44.46 80.593 3.1110 151 0.18671 0.14065 0.75367 4.4803 2.8909 285.78 461.67 19.323 88.309 5.3096 152 0.64903 0.75082 0.085452 4.7229 3.0224 462.78 999.51 90.311 110.43 5.5276 153 0.17695 0.087076 0.23365 1.8713 2.0351 999.67 483.77 77.454 90.563 4.3465 154 0.9512 0.23467 0.76487 3.4203 1.5586 484.97 306.89 89.845 106.18 4.7466 155 0.14091 0.76127 0.2801 19.848 0.38107 306.1 872.4 98.457 100.45 5.4393 156 0.75336 0.28179 0.67652 3.6112 3.0035 871.12 725.39 91.867 101.58 5.3692 157 0.08953 0.67582 0.53817 2.0206 2.5998 721.14 103.99 60.614 87.341 5.9484 158 0.23059 0.53548 0.56945 14.703 2.2116 101.08 695.4 34.592 95.224 4.8526 MDL-NBS-HS-000021, REV 00 I-20 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 159 0.7646 0.56552 0.20822 8.3977 1.8999 698.34 798.89 86.608 148.17 4.9279 160 0.28497 0.20529 0.40255 0.08363 1.8931 798.55 277.25 179.31 96.195 4.9132 161 0.67504 0.40101 0.99992 7.3602 3.0661 275.58 455.23 83.162 88.301 4.9346 162 0.53552 0.99938 0.42575 11.705 0.9365 455.05 748.2 88.263 116.45 4.9929 163 0.56653 0.42685 0.22858 1.7744 3.5397 751.7 720.14 53.479 106.92 5.2455 164 0.20863 0.22935 0.85861 3.3344 2.9012 718.67 983.76 95.995 63.959 4.3054 165 0.40195 0.85843 0.69288 9.6034 2.3059 984.15 509.34 92.983 105.54 4.9098 166 0.99884 0.69375 0.001538 8.2444 1.3307 505.59 556.96 91.708 111.26 4.6501 167 0.4295 0.00151 0.66146 19.375 2.2877 556.95 548.66 57.505 86.894 3.9386 168 0.22599 0.66498 0.77751 3.8245 1.3026 547.43 562.63 88.128 94.915 3.5547 169 0.8586 0.77867 0.19755 4.2764 3.2398 561.48 608.45 81.325 108.24 5.4048 170 0.69437 0.1954 0.39244 4.1922 1.1982 608.46 671.99 80.933 106.64 5.1931 171 0.001231 0.39299 0.72459 4.3053 2.514 671.82 265.99 219.94 134.49 4.6748 172 0.6606 0.72016 0.68846 4.6899 0.97624 262.5 541.5 94.211 97.076 4.8286 173 0.77628 0.68789 0.98023 6.4311 1.4467 545.05 402.29 89.533 99.164 4.7081 174 0.19637 0.98146 0.45478 1.6777 2.5403 403.25 185.89 45.799 98.867 4.7295 175 0.39311 0.45483 0.50829 4.1271 1.5639 189.74 125.45 95.51 99.409 5.8882 176 0.72453 0.50536 0.49776 2.8941 2.3457 124.24 734.44 81.464 101.46 5.9004 177 0.68917 0.49845 0.51009 0.98473 2.0682 731.22 654.92 78.815 104.55 3.8036 178 0.98396 0.51107 0.56335 0.29817 2.1292 653.57 416.24 91.501 86.075 4.7517 179 0.45418 0.56394 0.63905 8.9345 1.394 416.08 492.31 83.816 98.647 4.0583 180 0.50686 0.6384 0.18176 5.6614 1.8196 493.18 435.53 93.055 92.833 5.6042 181 0.49959 0.18351 0.49236 3.0019 4.0513 437.08 445.56 29.693 81.084 5.5955 182 0.51036 0.49117 0.33981 3.713 1.862 446.28 964.34 84.386 74.407 4.8724 183 0.56418 0.33823 0.098419 3.1858 1.4389 965.64 970.23 96.859 107.46 3.9848 184 0.63522 0.098359 0.029148 3.28 2.8066 970.12 157.45 77.974 103.63 4.4748 185 0.18001 0.028657 0.7049 18.674 2.3825 155.45 458.25 53.3 93.339 5.5682 186 0.49328 0.70242 0.61821 18.723 -0.00165 458.27 216.04 85.497 96.562 4.0889 187 0.33932 0.6174 0.35471 0.66095 2.3105 213.33 848.03 91.901 94.132 5.4564 188 0.095855 0.35206 0.43994 3.3711 2.5777 848.42 845.9 99.622 94.576 4.6564 189 0.025006 0.43563 0.37403 1.2357 1.3627 843.72 521.17 94.301 129.18 3.7290 190 0.70291 0.37478 0.38384 13.799 1.7917 519.67 200.06 94.397 130.24 5.4786 MDL-NBS-HS-000021, REV 00 I-21 July, 2003 real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 191 0.61896 0.38398 0.96484 13.577 2.4475 199.43 316.94 83.555 78.41 5.7810 192 0.35329 0.96202 0.96738 3.9583 2.3695 320.09 827.3 90.094 95.042 4.9796 193 0.43628 0.9654 0.062055 1.0922 3.5458 826.09 219 71.043 83.247 5.5478 194 0.37169 0.061335 0.39868 2.1208 1.9109 218.91 760.81 77.053 114.66 4.7098 195 0.38195 0.39667 0.12538 12.783 2.0123 761.17 408.2 77.048 114.11 5.3385 196 0.96264 0.12797 0.83326 1.2474 1.9917 406.69 142.25 85.209 97.678 5.2878 197 0.96574 0.8321 0.82688 9.9052 2.0208 144.67 773.83 25.382 82.048 5.2122 198 0.063634 0.82798 0.46962 2.9301 2.1217 772.31 943.72 77.31 88.773 4.4856 199 0.39766 0.46669 0.11218 0.49962 2.2674 943.38 595.47 90.686 113.09 5.4216 200 0.12612 0.1129 0.24114 10.512 1.3256 596.34 813.08 87.434 83.544 4.6979 MDL-NBS-HS-000021, REV 00 I-22 July, 2003 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 4872.9 178.08 3.4892 -4.4407 2 7769.2 6721 5.8331 3409.9 799.65 2.9211 -4.4107 3 5702.4 5037 5.9814 6484.7 945 3.0682 -8.7573 4 6712.4 6161.5 5.0086 7258 653.54 3.3114 -7.4077 5 5039.6 6078.9 5.4456 5715.2 833.8 2.6497 -8.4926 6 6166.2 5984.6 4.9920 6664.5 521.65 2.8072 -5.4465 7 6096 4478.6 5.2380 5017.9 744.24 2.6360 -5.476 8 5984.4 6343.7 6.0000 6186.1 729.51 2.7197 -7.1382 9 4483.4 4998.1 4.9762 6100 710.35 3.3486 -8.5426 10 6347.6 5398.5 5.6375 6006.7 405.6 2.6160 -8.0268 11 5003.5 5816.1 5.9903 4489.1 773.96 2.9143 -5.6308 12 5395.8 4080.1 5.7619 6352.7 512.41 3.3299 -8.4685 13 5804 4586.6 4.7149 4963.6 596.07 2.9856 -6.0663 14 4084.8 4056 6.3464 5395.2 676.07 2.3959 -7.6293 15 4591.2 4298.1 5.9175 5837.1 330.43 3.4717 -8.8063 16 4071.1 5882.9 4.6899 4195.7 431.82 3.2197 -6.018 17 4312.5 3986.6 6.5623 4585.8 328.73 2.3635 -4.6686 18 5887.7 4981.3 5.5315 4172.6 371.58 3.5901 -6.7922 19 3997.5 5842.8 5.7451 4359.4 692.74 2.8522 -5.715 20 4964.8 5254.5 5.5465 5916.5 318.51 2.9747 -7.4927 21 5841.3 3352.8 5.9978 4126.1 509.22 2.8589 -6.3092 22 5249.8 6267.7 5.9360 4951.4 684.76 3.3399 -6.3854 23 3350.7 5629.4 5.3838 5874.4 563.37 3.2550 -6.4937 24 6266.9 3265 6.1931 5239 211.99 2.7812 -8.015 25 5614 6838 5.8089 3793.7 761.1 3.4056 -6.1406 26 3268.8 4754.3 5.6274 6280.4 639.2 3.0266 -7.5392 27 6830 5203.4 6.5441 5626 203.9 2.9089 -7.1142 28 4752.1 4769.3 6.6739 3767.1 847.86 3.5824 -6.6703 29 5208.6 5863.3 5.2765 6755.6 461.44 3.6609 -8.3015 30 4760.6 5676.8 6.5011 4739.6 556.39 2.7344 -7.9093 MDL-NBS-HS-000021, REV 00 I-23 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 31 5868 4504.5 6.4728 5197.2 466.35 3.5520 -8.3327 32 5686.4 6049.8 5.9494 4743.8 688.99 3.5412 -8.1408 33 4496.5 5340.1 4.9233 5883.1 651.93 3.2668 -6.5819 34 6054.1 4946 6.9605 5687.4 411.96 2.5760 -8.3777 35 5335.9 6784.5 5.8382 4503.1 720.52 3.9447 -7.556 36 4954.1 7395.9 6.6776 6060.6 582.95 3.0918 -6.6373 37 6768.2 4367.7 5.9759 5335 502.03 3.6629 -7.2777 38 7399.6 6606.1 6.6522 4938.2 839.43 3.3045 -8.7023 39 4349 6544.1 5.9085 6713.1 916.61 3.6457 -6.2199 40 6613.4 5717.4 6.3962 7092.6 383.48 3.2028 -6.8793 41 6556 3873.3 6.5717 4394.2 818.98 3.4953 -8.7381 42 5719.5 8732.1 6.1461 6584.6 808.27 3.5966 -5.5862 43 3858.1 5413.4 5.8195 6537.3 660.06 3.3930 -7.7721 44 8721.8 7419.7 6.3075 5735 294.01 3.0345 -7.3063 45 5413.9 5800.7 5.5809 4050.8 991.22 3.4557 -7.745 46 7437.8 7226.2 5.9859 7456.3 598.1 2.8849 -6.6174 47 5796.5 5589.3 6.6128 5412.2 919.06 3.3241 -6.8126 48 7243.6 6357.7 4.6388 7113.4 672.8 3.6195 -7.9985 49 5589.2 6861.8 6.4183 5814 899.64 2.3345 -6.4285 50 6364.8 6003.9 6.5159 7016.9 634.71 3.5066 -7.1708 51 6866 5353.2 5.7348 5591.9 777.9 3.5638 -7.5752 52 6008.3 6205.2 6.5366 6368.3 852.87 2.9709 -5.6643 53 5358 4858.7 5.4150 6771.1 712.71 3.5795 -5.0276 54 6218.9 5834.7 5.5775 6020.5 586.49 2.7970 -8.1064 55 4843 7046.9 5.2695 5349.7 750.31 2.8776 -5.8657 56 5831.9 3132.8 5.9717 6230.5 484.63 2.7310 -5.9515 57 7035.9 6410 4.6104 4835.7 681.99 3.2964 -6.7658 58 3173.9 6675 4.8343 5843.3 873.87 2.3122 -8.4411 59 6397.3 5193.9 5.7110 6889.5 194.82 2.4968 -4.1002 60 6670.5 6733.1 6.6972 3735.9 784.86 2.9609 -7.0941 61 5191.2 4558.9 6.6712 6400 825.8 3.6766 -4.9691 62 6755 4836.8 5.1367 6624.1 550.47 3.6582 -6.6998 MDL-NBS-HS-000021, REV 00 I-24 July, 2003 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 5174.8 836.11 2.6876 -5.161 64 4826 5767.5 6.2577 6690.1 421.28 3.6429 -6.9188 65 4342.6 3093.2 4.3501 4540.6 477.44 3.4355 -6.1259 66 5774 3650.4 5.3404 4806.1 378.03 2.1519 -5.5367 67 3112.8 5143.1 4.7901 4379.9 668.9 2.7602 -6.4733 68 3652.9 7554.3 5.4249 5797.2 186.91 2.4561 -7.1524 69 5141.2 7336 5.9355 3717.8 260.88 2.8035 -6.2729 70 7565.7 4199.1 5.7202 3931.1 545.33 3.2382 -7.6777 71 7361.4 7210.9 5.9101 5128.2 931.75 2.9685 -6.6509 72 4211.5 6137.8 6.0374 7176.3 911.36 3.2124 -5.3511 73 7212.3 2536.1 6.8306 7063.8 351.33 3.3517 -8.7724 74 6144.2 4428.3 6.6335 4262.8 896.71 3.6989 -6.0952 75 2583 3502.6 4.8833 6998.7 739.45 3.6343 -5.7992 76 4435.6 4576.3 6.6053 6177.4 142.3 2.5393 -7.3313 77 3519.2 5666.3 6.3674 1630.1 399.64 3.6162 -5.6828 78 4580.1 5162 6.5966 4446.5 241.47 3.4880 -7.9519 79 5656.1 5596.2 6.9741 3863.3 426.23 3.6116 -7.6875 80 5172.4 5914 4.2386 4561.9 647.46 3.9614 -8.1309 81 5609.8 7944.5 6.1038 5665.9 550.07 2.0951 -6.7135 82 5912.4 7132.6 4.7531 5155 634.96 3.3796 -8.7844 83 7914.7 3773.6 5.4065 5601.3 697.02 2.4256 -8.5657 84 7132.3 7012.5 6.4456 5928.7 955.7 2.7860 -7.3649 85 3753.5 6324.4 4.1847 7282.4 885.57 3.5229 -4.8334 86 6986.5 6980.9 6.7505 6948.9 276.95 2.0594 -5.0489 87 6306.8 8979.8 5.5658 3996.8 872.71 3.6879 -8.2303 88 6979.8 2198.1 4.4545 6867.5 769.22 2.8735 -5.1937 89 9020.7 5962.9 5.4814 6321.5 868.01 2.2234 -6.3262 90 2223.7 3419.5 4.8231 6843.4 995.38 2.8308 -8.9159 91 5959.5 4534.1 5.8457 7477.5 122.28 2.4814 -8.049 92 3435.1 6465.6 6.5752 843.23 707.86 3.1066 -8.6293 93 4518.4 1938.8 5.1959 5997.2 226.24 3.6012 -7.9308 94 6479.5 7749.4 6.6201 3826.2 418.09 2.7010 -6.8351 MDL-NBS-HS-000021, REV 00 I-25 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 95 1944.9 4815.2 4.4834 4532.5 794.98 3.6242 -7.3558 96 7738.3 2757.9 5.8567 6475 116.33 2.2479 -6.8801 97 4813.7 4650.8 6.6405 806.35 943.93 3.1094 -6.5674 98 2752.3 3626 4.9596 7234.3 474.28 3.6371 -4.579 99 4668.5 5430.8 4.9532 4783 156.07 2.6025 -5.2514 100 3590.2 6886.2 4.5261 2517 445.26 2.5987 -8.5003 101 5437.2 4246.3 6.4871 4659 253.85 2.2623 -5.3798 102 6878.3 7050 4.8636 3907.8 602.23 3.5479 -6.1694 103 4242.2 2836.9 5.8808 5432.1 855.89 2.5293 -5.4229 104 7071.8 5458.1 5.5038 6785.3 365.43 3.1555 -3.9017 105 2849 7165.5 6.7372 4317.5 879.29 2.8449 -8.9485 106 5452 3968.1 6.8082 6918.2 161.11 3.6822 -6.5045 107 7180.6 3947.5 6.8733 2847.2 607.45 3.6947 -8.6754 108 3975.9 2963 6.9243 5458 889.84 3.7506 -7.9714 109 3949.9 6585 4.9802 6969.8 310.82 3.8465 -6.0296 110 2961.6 3722.4 5.4942 4106.8 306.56 2.6266 -8.9706 111 6583.9 5508.2 5.5563 4097.8 167.18 2.8365 -4.7113 112 3744.8 4713.2 5.5211 3160.9 815.33 2.8642 -7.7037 113 5502.7 7651.4 5.6117 6571.9 271.76 2.8499 -8.8791 114 4707.5 7827.8 6.4298 3976.7 619.25 2.9020 -7.8504 115 7668.2 8061.2 5.6812 5508.9 451.04 3.5209 -8.5921 116 7875.1 8371.1 6.6551 4689.3 937.03 2.9405 -7.0702 117 8054.6 4033.3 6.6920 7214.6 952.66 3.6481 -5.5235 118 8382.8 4674.7 5.9025 7266.2 965.4 3.6725 -8.1812 119 4032.2 4794.8 5.4548 7329.4 975.16 3.1876 -5.3301 120 4682.7 4727.1 4.3159 7382.2 320.43 2.8162 -8.8483 121 4789.7 4923.1 6.6857 4150.1 446.62 2.1361 -7.0482 122 4733.6 6446.1 6.5263 4664.8 470.86 3.6683 -5.226 123 4918.3 5066.3 6.0719 4768.9 456.71 3.5702 -8.3913 124 6457.4 7265.2 5.7917 4718.2 493.65 3.3600 -8.4006 125 5073.8 7501.7 5.7853 4895.3 792.72 2.9976 -8.8265 126 7269 5566.2 6.7024 6440.7 527.66 2.9937 -5.8902 MDL-NBS-HS-000021, REV 00 I-26 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 127 7503.6 4620.7 4.7329 5055.9 902.78 3.6804 -8.5362 128 5573.1 2382.2 6.9325 7040 928.67 2.4095 -6.9813 129 4622.1 7497.1 6.6599 7141.5 629.98 3.8979 -7.8073 130 2420.4 6694.9 6.2405 5575.8 435.71 3.6530 -4.7451 131 7457.5 5934.5 5.1173 4611.9 127.29 3.4250 -4.6212 132 6679.9 5310 6.1987 1210.9 924.13 2.6807 -4.4973 133 5936.4 5289 5.0374 7129.5 830.59 3.4087 -4.3664 134 5304.7 7600.3 6.8506 6653.7 698.01 2.6538 -8.3547 135 5285.5 3394.1 4.9341 5942.9 575.88 3.7269 -7.8364 136 7609.5 8528.2 6.4669 5294.8 572.62 2.5810 -7.7319 137 3398.2 7310.8 4.7676 5273.1 934.01 3.5342 -7.7884 138 8495.8 6104.3 5.3160 7196.6 220.56 2.4374 -7.6139 139 7329.9 4160.2 6.4786 3800.3 981.25 2.7538 -6.0479 140 6102.7 6062.9 5.4698 7409.7 907.73 3.5430 -7.4548 141 4166.5 4117.4 6.2900 7052.7 733.62 2.8222 -5.1313 142 6062 7991.4 5.9253 6133.5 349.23 3.4512 -4.9116 143 4131.1 3906.2 5.9633 4248.9 726.94 3.2263 -6.9204 144 8021.9 6524.3 5.2175 6094.7 336.27 3.2910 -7.891 145 3903.4 3468.8 5.7076 4211.3 960.78 2.7132 -8.9265 146 6511.8 4418.7 6.9969 7302.3 300.53 2.9582 -4.9539 147 3457.3 6579.8 5.7505 4060.9 803.03 3.9972 -5.7348 148 4404.6 4630.4 5.2945 6516.3 232.94 2.9797 -6.5489 149 6571.7 6183.3 6.6243 3847.7 394.75 2.7420 -7.2133 150 4650.1 5637.9 6.3304 4437.2 809.21 3.6309 -7.225 151 6185.5 5757.9 4.0403 6552.9 439.43 3.4709 -4.7824 152 5645.3 4276.8 6.2553 4633.2 747.16 2.0382 -8.6861 153 5748.4 5137.6 6.5065 6203.2 644.24 3.4298 -4.3303 154 4277.4 9300.6 5.1614 5653.3 668.14 3.5591 -5.0869 155 5131 5222.6 5.6857 5764.9 369.36 2.6922 -6.3617 156 9534.9 4376.2 6.3997 4330.4 540.59 2.9465 -8.2544 157 5223.8 7111.8 6.3160 5103.9 998.61 3.5045 -6.4036 158 4371.9 6245.4 6.9528 7495.5 559.62 3.4647 -8.2975 MDL-NBS-HS-000021, REV 00 I-27 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 159 7107.4 1511.6 5.8035 5212.8 387.34 3.9291 -4.5372 160 6262.1 6123.3 5.8876 4412.8 884.11 3.0123 -8.4216 161 1345 6652.3 5.8745 6936.4 759.54 3.1609 -5.9679 162 6117.2 4216 5.8954 6265.1 106.16 3.1339 -8.6561 163 6648.8 5090.8 5.9552 141.74 737.64 3.1759 -8.0717 164 4235.5 6390.9 6.1584 6148.5 821.88 3.2811 -5.909 165 5089.3 6227.3 5.0969 6608.2 357.82 3.3966 -7.878 166 6385.7 8608 5.8603 4287.7 532.58 2.6703 -6.2949 167 6223.2 5321.4 5.5933 5062.6 781.14 3.1305 -6.8452 168 8546.8 5534.4 4.8125 6381.6 755.11 2.8881 -6.7339 169 5319.2 5483.1 4.4143 6249.8 983.03 2.4729 -8.1665 170 5521.6 5542.5 6.3617 7434.5 580.56 2.1921 -7.3829 171 5495.8 5731.1 6.0755 5315.5 622.03 3.4794 -3.6765 172 5549.6 6033.4 5.6232 5524.1 613.79 3.3727 -7.2856 173 5727.9 4140 5.7782 5490.6 623.75 2.9066 -8.0952 174 6023.7 5477.9 5.6590 5551.3 664.5 2.9908 -5.2724 175 4148.4 4872.6 5.6693 5750.9 719.54 2.9265 -6.2288 176 5479.6 3549.9 6.8814 6054.3 343.37 2.9380 -8.9859 177 4879.1 2624.6 6.9058 4235.9 608.71 3.8063 -6.3475 178 3562.2 6292.3 4.6491 5471.9 488.67 3.8289 -5.8284 179 2691.1 5944.7 5.6981 4848.9 248.32 2.3548 -8.2179 180 6293.7 4927.5 4.8968 3891 150.62 2.9539 -7.4396 181 5941.6 5265.2 6.5944 2083 766.1 2.5494 -6.1073 182 4940.1 5004.8 6.5843 6317.7 701.74 3.6094 -6.2584 183 5261.6 5043.6 5.8215 5961.4 497.44 3.6051 -4.1654 184 5020.3 8191.8 4.8495 4914.6 568.89 3.0603 -7.1812 185 5060.4 8242.6 5.3579 5258.4 517.51 2.5082 -6.9617 186 8136.4 3206.1 6.5563 4998.6 522.73 2.7668 -7.0139 187 8289.8 5112.5 4.9119 5032.3 967.88 3.5857 -6.9487 188 3212.5 3783.9 6.4232 7341.4 972.79 2.5597 -6.7548 189 5101.7 6943.9 5.6010 7371 199 3.5129 -6.4514 190 3797.2 6920.3 4.5707 3740.7 535.96 2.8922 -8.267 MDL-NBS-HS-000021, REV 00 I-28 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 191 6929.3 5377.6 6.4533 5083.1 283.4 2.2913 -7.0285 192 6916.6 3672.1 6.7846 4020 863.42 3.5281 -7.651 193 5384 4451.3 5.9450 6825.5 861.69 3.6906 -8.615 194 3694.1 6790.8 6.5366 6810.5 590.15 3.2638 -8.8951 195 4459 3827.5 5.6646 5375.4 262.72 3.5723 -6.1974 196 6789.6 6419 6.2765 3949.1 403.04 2.9325 -6.5318 197 3839.3 4891.3 6.2175 4465.3 844.46 3.4436 -7.5985 198 6419.4 3017.7 6.1335 6728.3 285.99 3.4185 -7.2599 199 4889 6501.1 5.3766 4030.4 788.24 3.3858 -7.5095 200 3037 7780.9 6.3784 6433.3 489.71 2.7745 -7.4663 MDL-NBS-HS-000021, REV 00 I-28 July, 2003 real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 191 6929.3 5377.6 6.4533 5083.1 283.4 2.2913 -7.0285 192 6916.6 3672.1 6.7846 4020 863.42 3.5281 -7.651 193 5384 4451.3 5.9450 6825.5 861.69 3.6906 -8.615 194 3694.1 6790.8 6.5366 6810.5 590.15 3.2638 -8.8951 195 4459 3827.5 5.6646 5375.4 262.72 3.5723 -6.1974 196 6789.6 6419 6.2765 3949.1 403.04 2.9325 -6.5318 197 3839.3 4891.3 6.2175 4465.3 844.46 3.4436 -7.5985 198 6419.4 3017.7 6.1335 6728.3 285.99 3.4185 -7.2599 199 4889 6501.1 5.3766 4030.4 788.24 3.3858 -7.5095 200 3037 7780.9 6.3784 6433.3 489.71 2.7745 -7.4663