Saturated Zone Flow and Transport Model Abstraction Rev 02, ICN 00
 
MDL-NBS-HS-000021

October 2004

1. PURPOSE 
The purpose of the saturated zone (SZ) flow and transport model abstraction task is to provide 
radionuclide-transport simulation results for use in the total system performance assessment 
(TSPA) for license application (LA) calculations. This task includes assessment of uncertainty 
in parameters that pertain to both groundwater flow and radionuclide transport in the models 
used for this purpose. This model report documents the following: 
 The SZ transport abstraction model, which consists of a set of radionuclide breakthrough 
curves at the accessible environment for use in the TSPA-LA simulations of 
radionuclide releases into the biosphere. These radionuclide breakthrough curves 
contain information on radionuclide-transport times through the SZ. 
 The SZ one-dimensional (1-D) transport model, which is incorporated in the TSPA-LA 
model to simulate the transport, decay, and ingrowth of radionuclide decay chains in 
the SZ. 
 The analysis of uncertainty in groundwater-flow and radionuclide-transport input 
parameters for the SZ transport abstraction model and the SZ 1-D transport model. 
 The analysis of the background concentration of alpha-emitting species in the 
groundwater of the SZ. 
Figure 1-1 shows the relationship of this report to other model reports that also pertain to flow 
and transport in the SZ. Figure 1-1 also shows the flow of key information among the SZ 
reports. It should be noted that Figure 1-1 does not contain a complete representation of the data 
and parameter inputs and outputs of all SZ reports, nor does it show inputs external to this suite 
of SZ reports. The primary input model to this report is the SZ site-scale transport model, which 
forms the basis for the SZ transport abstraction model and the SZ 1-D transport model, as 
developed in this report. The output models from this report are direct feeds to the TSPA-LA 
model. Several other SZ reports provide information used to define the uncertainty distributions 
for groundwater flow and radionuclide transport parameters. 
The following reports, through their output DTNs, provide direct input to this report: 
 Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and Transport Model 
(BSC 2004 [DIRS 170009]) 
 Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036]) 
 Probability Distributions for Flowing Interval Spacing (BSC 2004 [DIRS 170014]) 
 Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006]) 
 Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010]) 
 Analysis of Hydrologic Properties Data (BSC 2004 [DIRS 170038]) 
 UZ Flow Models and Submodels (BSC 2004 [DIRS 169861]) 
 Rock Properties Model (BSC 2004 [DIRS 170032]) 
 Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction 
and Summary (BSC 2004 [DIRS 170025]). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 1-2 October 2004 
The following reports use this report or its output DTNs as direct input: 
 Total System Performance Assessment (TSPA) Model/Analysis for the License 
Application 
 Drift-Scale Radionuclide Transport 
 Features, Events, and Processes in SZ Flow and Transport 
 Features, Events, and Processes: Disruptive Events. 
Revision 02 of this report includes several changes relative to Revision 01 [Saturated Zone Flow 
and Transport Model Abstraction (BSC 2003 [DIRS 167651])]. Numerous comments from the 
Regulatory Integration Team have been addressed in this revision of the report. Additional 
simulations and corrections are presented, which compare the SZ site-scale transport model to 
the SZ 1-D transport model, to clarify the correspondence of these models to each other on a 
realization-by-realization basis. Using a re-sampling of the input parameters, the entire suite of 
radionuclide transport simulations from the SZ transport abstraction model is presented. 
Regeneration of the transport simulation results is performed as an impact analysis, to address 
CR (Condition Report) 2222 (Evaluate Revised LH Sampling Algorithm on the Results of 
ANL-EBS-PA-000009). Documentation of this impact analysis for CR 2222 is contained in 
Appendix B of this report. 
This model report provides the technical basis for SZ-related features, events, and processes 
(FEPs) included in the TSPA-LA model, and contributes to the characterization of the SZ as part 
of the natural barrier below the repository. The natural-barrier characterization provides 
evidence pertaining to the capability of the SZ to delay movement of radionuclides through the 
SZ to the accessible environment. This report also contributes to the technical basis for the SZ 
transport-system description that is used in the LA, and provides evidence for the acceptance 
criteria specified in the Yucca Mountain Review Plan, Final Report (YMRP) (NRC 2003 
[DIRS 163274]). The scope of this model report is limited to adaptation of an existing model 
(the SZ site-scale transport model) for the uncertainty analysis, as reflected in the SZ 
radionuclide breakthrough curves developed in this model report. 
Use of the SZ transport abstraction model and the SZ 1-D transport model in this report and in 
the TSPA-LA is subject to the limitations imposed by the assumptions listed in Section 5 of this 
report. Limitations in knowledge of specific parameter values are addressed in this report in the 
analysis of parameter uncertainties in Section 6.5.2. The radionuclide breakthrough curves 
generated for the SZ transport abstraction model are limited to a simulation period of 
100,000 years, for present-day climatic conditions. This limits the time period that can be 
simulated with the TSPA-LA model when using these breakthrough curves for the SZ. Because 
the SZ breakthrough curves are scaled for higher groundwater flow rates under future climatic 
conditions (i.e., the time scale of the breakthrough curve is divided by the multiplier of 
groundwater flux), the time period that can be simulated with the TSPA-LA model would be 
significantly less than 100,000 years. If the glacial-transition climate state is applied for most of 
the simulation period in the TSPA-LA model, the SZ breakthrough curves would be scaled by a 
factor of approximately four, thereby limiting the TSPA-LA model simulation time to about 
25,000 years. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 1-3 October 2004 
Information on the correlation between distribution coefficients (Kds) used in the sampling of 
uncertain parameters for the SZ transport abstraction model and for the SZ 1-D transport model 
is provided in Table 4-3 and Table 6-8. The technical bases for correlations between distribution 
coefficients (or the lack thereof) are documented in Site-Scale Saturated Zone Transport (BSC 
2004 [DIRS 170036], Section C1.2.1). 
Evaluation of uncertainty in horizontal anisotropy in permeability is summarized in 
Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of 
uncertainty is given in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6). 
Implementation of uncertainty in horizontal anisotropy in the SZ transport abstraction model and 
in the SZ 1-D transport model is discussed in Section 6.5.3.1 and Section 6.5.1.2, respectively. 
The impacts of spatial variability of parameters that affect radionuclide transport in the alluvium 
are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, 
Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. The technical bases for 
uncertainty in distribution coefficients are documented in Site-Scale Saturated Zone Transport 
(BSC 2004 [DIRS 170036], Appendix C). 
Information on geological uncertainty in the location of the contact between tuff and alluvium, 
and the consequent uncertainty in flow-path lengths in the alluvium, is presented in 
Section 6.5.2.2. This evaluation of uncertainty includes information from the Nye County early 
warning drilling program. 
The sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in 
the assessment of alternative conceptual models (ACMs) in Section 6.4. 
This model report is governed by Technical Work Plan For: Natural System  Saturated Zone 
Analysis and Model Report Integration (BSC 2004 [DIRS 171421], Work Package ARTM01). 
The work documented in this model report was conducted in accordance with the quality 
assurance (QA) procedure AP-SIII.10Q, Models. 
In this report, a unique six-digit numerical identifier (the Document Input Reference System 
(DIRS) number) is placed in the text after the reference callout (e.g., BSC 2001 [DIRS 163566]). 
The DIRS numbers are provided to assist readers to locate specific references in the DIRS 
database. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 1-4 October 2004 
NOTE: This figure is a simplified representation of the flow of information among SZ reports. See the DIRS of each 
report for a complete listing of data and parameter inputs. This figure does not show inputs external to this 
suite of SZ reports. 
Figure 1-1. Generalized Flow of Information Among Reports Pertaining to Flow and Transport in the SZ 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 2-1 October 2004 
2. QUALITY ASSURANCE 
Development of this model report and the supporting modeling activities is subject to the 
Yucca Mountain Project (YMP) QA program (BSC 2004 [DIRS 171421], Section 8, Work 
Package ARTM01). Approved QA procedures identified in the technical work plan (BSC 2004 
[DIRS 171421], Section 4) have been used to conduct and document the activities described in 
this model report. The technical work plan also identifies the methods used to control the 
electronic management of data (BSC 2004 [DIRS 171421], Section 8). 
This model report provides values for hydrologic properties of the SZ as part of the natural 
barrier below the repository that is important to the demonstration of compliance with the 
postclosure performance objectives prescribed in 10 CFR 63.113 [DIRS 156605]. Therefore, it 
is classified on the Q-List (BSC 2004 [DIRS 168361]) as SC (Safety Category), reflecting its 
importance to waste isolation, as defined in AP-2.22Q, Classification Analyses and Maintenance 
of the Q-List [DIRS 170665]. The report contributes to the analysis and modeling data used to 
support postclosure performance assessment; the conclusions do not directly impact preclosureengineered 
features important to safety, as defined in AP-2.22Q [DIRS 170665]. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 2-2 October 2004 
INTENTIONALLY LEFT BLANK 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 3-1 October 2004 
3. USE OF SOFTWARE 
3.1 SOFTWARE TRACKED BY CONFIGURATION MANAGEMENT 
The computer software codes used directly in this model report are listed in Table 3-1. The 
qualification status of the software is noted in the Software Configuration Management database. 
All software was obtained from Software Configuration Management and is appropriate for the 
application, considering the simulation capabilities of the software, the range of inputs, and the 
functionality required by the computational task. Qualified codes were used only within the 
range of validation as required by LP-SI.11Q-BSC, Software Management. 
Table 3-1. Computer Software Used in This Model Report 
Software Name 
and Version (V) 
Software 
Tracking 
Number 
(STN) Description 
Computer Type, 
Platform, and 
Location 
Date 
Baselined 
FEHM (finite 
element heat 
and mass 
model) V2.20 
[DIRS 161725] 
10086-2.20- 
00 
This code is a finite-element heat- and 
mass-transport code that simulates 
nonisothermal, multiphase, 
multicomponent flow, and solute 
transport in porous media. 
Sun UltraSPARC - 
SunOS 5.7 
Sandia National 
Laboratories 
01/28/2003 
GoldSim 
V7.50.100 
[DIRS 161572] 
10344- 
7.50.100-00 
This code is the modeling software used 
in the TSPA-LA. Probabilistic 
simulations are represented graphically 
in GoldSim. 
Dell OptiPlex GX260 
Windows 2000 
Professional 
5.0.2195 
Sandia National 
Laboratories 
01/07/2003 
GoldSim V8.01 
SP4 
[DIRS 169695] 
10344- 
8.01SP4-00 
GoldSim (GS) is a Windows-2000based 
program that provides the following 
general capabilities: 
 Quantitatively address the inherent 
variability. 
 Superimposes the occurrence and 
consequences of discrete events 
onto continuously varying systems. 
 Builds top-down models, dynamically 
links external programs or 
spreadsheets directly to the GS 
model. 
 Directly exchanges data between 
any ODBC-compliant database to 
the GS model. 
Computer: Master 
06 
Windows 2000 
Advanced Server 
YMP Offices, Las 
Vegas, Building 3 
04/01/2004 
SZ_Pre V2.0 
[DIRS 163281] 
10914-2.0- 
00 
This software is an automated method 
for preparing the FEHM input files for the 
SZ site-scale flow and transport model a 
for use in TSPA-LA analyses. 
Sun UltraSPARC - 
SunOS 5.7 
Sandia National 
Laboratories 
04/28/2003 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 3-2 October 2004 
Table 3-1. Computer Software Used in This Model Report (Continued) 
Software Name 
and Version (V) 
Software 
Tracking 
Number 
(STN) Description 
Computer Type, 
Platform, and 
Location 
Date 
Baselined 
SZ_Post V3.0 
[DIRS 163571] 
10915-3.0- 
00 
This software is used to translate the 
output files from the SZ site-scale 
model b into the format used by the 
SZ_Convolute software code. SZ_Post 
reads the output files from the FEHM 
software code and writes the 
breakthrough curve data for radionuclide 
transport in the SZ. 
Sun UltraSPARC - 
SunOS 5.7, Solaris 
2.7 
Sandia National 
Laboratories 
05/22/2003 
CORPSCON 
V 5.11.08 
[DIRS 155082] 
10547- 
5.11.08-00 
This software is used to convert 
coordinate data to the Universal 
Transverse Mercator (UTM) coordinate 
system. 
IBM Thinkpad 770Z - 
Windows NT 4.0 
Sandia National 
Laboratories 
08/27/2001 
SZ_Convolute 
V2.2 
[DIRS 163344] 
10207-2.2- 
00 
This software is used to calculate SZ 
response curves based on unsaturated 
zone (UZ) radionuclide source terms, 
generic SZ responses, and climate 
scenarios for the YMP. 
Dell OptiPlex GX260 
- Windows 2000 
Professional 
5.0.2195 
Sandia National 
Laboratories 
01/13/2003 
a SZ site-scale flow and transport model refers to the SZ transport abstraction model. 
b SZ site-scale model refers to the SZ transport abstraction model. 
NOTE: The SZ_Convolute V2.2 software code (STN: 10207-2.2-00, SNL 2003 [DIRS 163344]) was used in the 
modeling and analyses in this report. SZ_Convolute V3.0 (STN: 10207-3.0-00, SNL 2003 [DIRS 
164180]) will be used for implementation of the SZ transport abstraction model in TSPA-LA. The 
summary description of the changes in the SZ_Convolute software code in the software baseline report 
between versions 2.2 and 3.0 gives no indication that the changes in functionality would have any impact 
on the model validation performed in this report. Software descriptions are taken directly from the 
software baseline report. 
FEHM=finite element heat and mass model; LA=license application; ODBC=Open Database Connectivity; 
SZ=Saturated Zone; TSPA=Total System Performance Assessment; UZ=Unsaturated Zone; YMP=Yucca 
Mountain Project 
3.2 EXEMPT SOFTWARE 
The commercially available software cited in this section is appropriate for use in this 
application, considering the functionality required for the computational tasks. These software 
products were used primarily for plotting of graphs and the visualization of modeling results, and 
for simple spreadsheet operations. Different graphical software programs were used for different 
plotting requirements, as appropriate. The results were spot-checked by hand to ensure the 
results were correct. The computer that was used was a Dell OptiPlex GX1 with Pentium II 
processor, running Microsoft Windows 2000 Version 5.0.2195. The range of validation for 
Excel, Surfer, and Grapher is the set of real numbers. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 3-3 October 2004 
Commercially available software: 
 Excel 2000: Used for simple spreadsheet calculations in support of plotting and 
visualization. The formulas, listing of inputs, listing of outputs, and other required 
information can be found in the following spreadsheets: Eff_MtrxDif_11.xls, 
bulkd_matr_eff_La.xls, and geonames.xls. These spreadsheets can be found in DTN 
(data tracking number): SN0306T0502103.006. 
 Surfer 8.0: Used for plotting and visualization. 
 Grapher 4.0: Used for plotting graphs. 
 Igor 4.07: Used for plotting graphs. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 3-4 October 2004 
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Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-1 October 2004 
4. INPUTS 
4.1 DIRECT INPUT 
All data, parameters, and other model inputs documented in Section 4.1 are used as direct inputs 
to the analyses of parameter uncertainty and/or the SZ transport abstraction model and SZ 1-D 
transport model. 
4.1.1 Data and Other Model Inputs 
The data providing input for the development of parameters used in the models documented in 
this report are identified in Table 4-1. 
These input data are considered appropriate for the development of uncertain parameters for the 
SZ transport abstraction model and the SZ 1-D transport model, considering the processes being 
simulated and the geological material in the model domain. The data that are used as direct input 
to the models developed in this report are the best relevant qualified data because they are taken 
from the Yucca Mountain site and region. Where available and appropriate, nonqualified data 
are used to corroborate those data that are used as direct input (see Section 6.5.2). 
Table 4-1. Direct Inputs 
Data Name Originating Report DTN 
Matrix Porosity in the Volcanic Units 
(HFM Units 15-8) MDL-NBS-GS-000004 (HFM Units 
15-13, 10-8) (BSC 2004 
[DIRS 170032]) 
OFR 94-469 (Buesch et al. 1996 
[DIRS 100106]); Flint 1998 [DIRS 
100033]; OFR 94-460 (Moyer and 
Geslin 1995 [DIRS 101269]); (HFM 
Units 12 and 11) 
TDR-NBS-HS-000014 (BSC 2001 
[DIRS 163566]) 
TDR-NBS-GS-000020, BSC 2001 
[DIRS 163479] (HFM Units 12 
and 11) 
SN0004T0501399.003 
[DIRS 155045] 
(HFM Units 15-13, 10-8) 
MO0109HYMXPROP.001 
[DIRS 155989] 
(HFM Units 12 and 11) 
MO0010CPORGLOG.002 
[DIRS 155229] 
(HFM Units 12 and 11) 
Effective Porosity Alluvium Bedinger, et al. 1989 [DIRS 129676], 
p. A18, Table 1 (HFM Units 19 and 
7) 
EDCON 2000 [DIRS 154704] (HFM 
Units 19 and 7) 
Burbey and Wheatcraft 1986 [DIRS 
129679] (HFM Units 19 and 7) 
DOE (U. S. Department of Energy) 
1997 [DIRS 103021], Table 8-2, 
p. 8-6, Table 8-1 p. 8-5 (HFM Units 
19 and 7) 
MO0105HCONEPOR.000 
[DIRS 155044] 
(HFM Units 19 and 7) 
MO0105GPLOG19D.000 
[DIRS 163480] 
(HFM Units 19 and 7) 
Burbey and Wheatcraft 1986 
[DIRS 129679] is an outside source 
of direct input (see table note). 
(HFM Units 19 and 7) 
DOE 1997 [DIRS 103021] is an 
outside source of direct input (see 
table note). 
(HFM Units 19 and 7) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-2 October 2004 
Table 4-1. Direct Inputs (Continued) 
Data Name Originating Report DTN 
Effective Porosity in the Other Units Bedinger, et al. 1989 DIRS 129676] 
(HFM Units, 18, 17, 16, 6-2, 1) 
MO0105HCONEPOR.000 
[DIRS 155044] 
(HFM Units, 18, 17, 16, 6-2, 1) 
Bulk Density in the Volcanic Units MDL-NBS-GS-000004 (HFM Units 
15-13, 10-8) (BSC 2004 [DIRS 
170032]) 
OFR 94-469 (Buesch et al. 1996 
[DIRS 100106]); Flint 1998 
[DIRS 100033]; OFR 94-460 (Moyer 
and Geslin 1995 [DIRS 101269]), 
(HFM Units 12, 11, and 9) 
TDR-NBS-HS-000014, (BSC 2001 
[DIRS 163566]) 
TDR-NBS-GS-000020, BSC 2001 
[DIRS 163479] (HFM Units 17, 12, 
11, 6-2) 
SN0004T0501399.002 
[DIRS 155046] 
(HFM Units 15-13, 10, 8) 
SN0004T0501399.003 
[DIRS 155045] 
(HFM Units 15-13, 10-8) 
MO0109HYMXPROP.001 
[DIRS 155989] 
(HFM Units 12, 11, and 9) 
MO0010CPORGLOG.002 
[DIRS 155229] 
(HFM Units 17, 12, and 11, 6-2) 
Effective Diffusion Coefficient BSC 2001 [DIRS 163566] (HFM 
Units 8-15) 
MO0109HYMXPROP.001 
[DIRS 155989] (HFM Units 8-15) 
Bulk Density - Alluvium EDCON 2000 [DIRS 154704] (HFM 
Units 19 and 7) 
MO0105GPLOG19D.000 
[DIRS 163480] (HFM Units 19 and 7) 
Flowing Interval Porosity in the 
Volcanic Units 
BSC 2004 [DIRS 170038], Section 
6.1.3 (HFM Units 8-15) 
BSC 2004 [DIRS 170010] 
DOE 1997 [DIRS 103021], p. 5-14 
(HFM Units 8-15) 
LB0205REVUZPRP.001 
[DIRS 159525] (HFM Units 8-15) 
LA0303PR831231.005 
[DIRS 166259] 
GS031008312315.002 
[DIRS 166261] 
DOE 1997 [DIRS 103021] is an 
outside source of direct input (see 
table note). (HFM Units 8-15) 
Lithostratigraphy in Wells EWDP- 
10SA and EWDP-22SA 
N/A GS030108314211.001 [DIRS 
163483] 
Coordinates of Well Locations and 
Depth to Water Table 
USGS 2001 [DIRS 157611] GS010908312332.002 
[DIRS 163555] 
Uncertainty in Groundwater Specific 
Discharge 
CRWMS M&O 1998 [DIRS 100353] MO0003SZFWTEEP.000 
[DIRS 148744] 
Uncertainty in Groundwater Specific 
Discharge at the Alluvial Tracer 
Complex (ATC) 
BSC 2004 [DIRS 170010] LA0303PR831231.002 
[DIRS 163561] 
UZ Site-Scale Model Flow Fields  
Infiltration for Climate States 
BSC 2004 [DIRS 169861] LB03023DSSCP9I.001 
[DIRS 163044] 
Gross Alpha Concentrations in 
Groundwater 
CRWMS M&O 1999 [DIRS 150420], 
Section 3.2.1, Table 3 
MO9904RWSJJS98.000 
[DIRS 165866] 
NOTE: The column containing the originating report is provided for reference only. The direct source of the data 
used in this report is listed in the DTN column. The given HFM Unit numbers refer to the unit definitions in 
Table 6-9. 
DTN=Data Tracking Number; HFM=hydrogeologic framework model; UZ=Unsaturated Zone 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-3 October 2004 
The data on effective porosity in alluvium from the Burbey and Wheatcraft report (1986 
DIRS 129679]) are obtained from an outside source and are not established fact. The suitability 
of these data is justified for this specific application, as outlined in AP-SIII.10Q, Section 5.2.1. 
U. S. Department of Energy (DOE) directed the collection of these data as part of the 
investigation of contaminant migration from underground nuclear testing at the Nevada Test Site 
(NTS). The porosity data in the alluvium were collected in Frenchman Flat from below the 
water table. That these data come from an area near Yucca Mountain and in a similar 
physiographic and hydrogeologic setting provides confidence that the data demonstrate the 
property of interest. The model of contaminant transport presented in the 1986 Burbey and 
Wheatcraft report was calibrated with measurements of contaminant concentrations during 
pumping near the Cambric nuclear test and no changes to the values of porosity were suggested 
as a result of the calibration process. This supports the values of porosity measured in the 
alluvium at the site. These porosity data generally are corroborated by comparison with other 
data sources, as discussed in Section 6.5.2.3, and fall within the total range of estimates from 
other sources. 
The data on effective porosity in alluvium from Regional Groundwater Flow and Tritium 
Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, 
Nevada (DOE 1997 DIRS 103021]) are obtained from an outside source and are not established 
fact. The suitability of these data is justified for this specific application, as outlined in 
AP-SIII.10Q. DOE directed the analyses of these data as part of a study of regional groundwater 
flow and tritium migration at the NTS. That these data come from an area near Yucca Mountain 
and in a similar hydrogeologic setting provides confidence that the data demonstrate the property 
of interest. The data on porosity in alluvium presented in the 1997 DOE report are based on a 
statistical analysis of measurements by several different methods and at different locations in the 
NTS. The average value of porosity is corroborated by comparison with another source in 
Table 8-2 of the 1997 DOE report, and the comparison for porosity in alluvium is very close. 
These porosity data generally are corroborated by comparison with other data sources, as 
discussed in Section 6.5.2.3, and fall within the total range of estimates from other sources. 
The data on fracture spacing and aperture from Regional Groundwater Flow and Tritium 
Transport Modeling and Risk Assessment of the Underground Test Area, Nevada Test Site, 
Nevada (DOE 1997 [DIRS 103021]) used to estimate flowing interval porosity are obtained from 
an outside source and are not established fact. The suitability of these data is justified for this 
specific application, as outlined in AP-SIII.10Q. DOE directed the analyses of these data as part 
of a study of regional groundwater flow and tritium migration at the NTS. The data used in the 
1997 DOE study were from seven cores from Pahute Mesa on the NTS, and were taken for 
volcanic rocks that are analogous to the volcanic units in the SZ at Yucca Mountain, providing 
confidence that the data demonstrate the property of interest. The resulting range of estimated 
fracture porosity is broad and generally is corroborated by comparison to other sources of 
information in Section 5.5.2.2 of the 1997 DOE report. These data also are corroborated by 
comparison to estimates of fracture porosity in Total-System Performance Assessment for Yucca 
Mountain  SNL Second Iteration (TSPA-1993) (Wilson et al. 1994 [DIRS 100191], Volume 1, 
Table 7-19), as described in Section 6.5.2.5 of this report. 
Uncertainty associated with the model, including development of parameter values and their 
implementation in the SZ transport abstraction model and the SZ 1-D transport model, is 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-4 October 2004 
discussed in Sections 6.5.1 and 6.5.2. Parameter uncertainties are addressed by providing 
ranges, probability distributions, and bounding assumptions, as appropriate for each parameter. 
Other model, analysis, design, and regulatory input information is listed in Table 4-2. 
Table 4-2. Other Direct Inputs (Model, Analysis, Design, and Regulations) 
Input Name Input Description DTN/IED 
Site-Scale 
Saturated Zone 
Transport Model 
The SZ site-scale model that forms the basis of the SZ 
transport abstraction model. 
LA0306SK831231.001 
[DIRS 164362] 
Matrix Diffusion 
Type Curves 
The analytical solution type curves for matrix diffusion in 
fractured media. These type curves are used in the particletracking 
algorithm of the FEHM software to simulate 
radionuclide transport in fractured porous media. 
LA0302RP831228.001 
[DIRS 163557] 
Repository 
Design 
The coordinates of the outline of the repository design are 
used in defining the SZ source regions at the water table 
below the repository. 
800-IED-WIS0-00101-000-00A 
(BSC 2004 [DIRS 164519]) 
Boundary of 
Accessible 
Environment 
Latitude of the accessible environment, as defined by 
regulation. 
10 CFR 63.302 [DIRS 156605] 
(regulatory input, technical 
information, no DTN) 
DTN=Data Tracking Number; FEHM=finite element heat and mass model; IED=information exchange drawing; 
SZ=Saturated Zone 
4.1.2 Parameters and Parameter Uncertainty 
The parameters and parameter uncertainties from external sources used directly in the modeling 
documented in this report are shown in Table 4-3. Parameters are those variables that are used as 
direct inputs to the models documented in this report. 
The input parameters are considered appropriate as direct input to the SZ transport abstraction 
model and the SZ 1-D transport model. The data used in this report are appropriate for this study 
because they represent various parameter properties of the SZ at Yucca Mountain. 
Table 4-3. Direct Input (Parameter Uncertainty) 
Parameter 
Name 
Parameter 
Source DTN Value(s) Units 
Parameter 
Type 
KDNPVO 
(neptunium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF (cumulative distribution 
function): 
Probability Value 
0.0 0.0 
0.05 0.99 
0.90 1.83 
1.0 6.0 
mL/g Distribution 
KDNPAL 
(neptunium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 1.8 
0.05 4.0 
0.95 8.7 
1.0 13.0 
mL/g Distribution 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-5 October 2004 
Table 4-3. Direct Input (Parameter Uncertainty) (Continued) 
Parameter 
Name 
Parameter 
Source DTN Value(s) Units 
Parameter 
Type 
KDSRVO 
(strontium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 20. 
Maximum 400. 
mL/g Distribution 
KDSRAL 
(strontium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 20. 
Maximum 400. 
mL/g Distribution 
KDUVO 
(uranium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 0.0 
0.05 5.39 
0.95 8.16 
1.0 20.0 
mL/g Distribution 
KDUAL 
(uranium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 1.7 
0.05 2.9 
0.95 6.3 
1.0 8.9 
mL/g Distribution 
KDRAVO 
(radium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 100. 
Maximum 1000. 
mL/g Distribution 
KDRAAL 
(radium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 100. 
Maximum 1000. 
mL/g Distribution 
KD_Pu_Vo 
(plutonium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 10. 
0.25 89.9 
0.95 129.87 
1.0 300. 
mL/g Distribution 
KD_Pu_Al 
(plutonium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Beta: 
Mean 100. 
Standard Deviation 15. 
Minimum 50. 
Maximum 300. 
mL/g Distribution 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-6 October 2004 
Table 4-3. Direct Input (Parameter Uncertainty) (Continued) 
Parameter 
Name 
Parameter 
Source DTN Value(s) Units 
Parameter 
Type 
KD_Am_Vo 
(americium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
mL/g Distribution 
KD_Am_Al 
(americium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
mL/g Distribution 
KD_Cs_Vo 
(cesium 
sorption 
coefficient in 
volcanic units) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 100. 
0.05 3000.59 
1.0 6782.92 
mL/g Distribution 
KD_Cs_Al 
(cesium 
sorption 
coefficient in 
alluvium) 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 728. 
Standard Deviation 464. 
Minimum 100. 
Maximum 1000. 
mL/g Distribution 
FISVO 
(flowing 
interval 
spacing in the 
volcanic units) 
BSC 2004 
[DIRS 
170014] 
SN9907T0571599.001 
[DIRS 122261] 
CDF: (Log10-transformed) 
Probability Value 
0.0 0.087 
0.05 0.588 
0.25 1.00 
0.50 1.29 
0.75 1.58 
0.95 1.90 
1.0 2.62 
m Distribution 
CORAL 
(colloid 
retardation 
factor in the 
alluvium) 
BSC 2004 
[DIRS 
170006] 
LA0303HV831352.004 
[DIRS 163559] 
CDF : (Log10-transformed) 
Probability Value 
0.0 0.903 
0.331 0.904 
0.50 1.531 
1.0 3.715 
N/A Distribution 
CORVO 
(colloid 
retardation 
factor in the 
volcanic units) 
BSC 2004 
[DIRS 
170006] 
LA0303HV831352.002 
[DIRS 163558] 
CDF : (Log10-transformed) 
Probability Value 
0.0 0.778 
0.15 0.779 
0.25 1.010 
0.50 1.415 
0.80 1.778 
1.0 2.903 
N/A Distribution 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-7 October 2004 
Table 4-3. Direct Input (Parameter Uncertainty) (Continued) 
Parameter 
Name 
Parameter 
Source DTN Value(s) Units 
Parameter 
Type 
HAVO 
(ratio of 
horizontal 
anisotropy in 
permeability) 
BSC 2004 
[DIRS 
170010] 
SN0302T0502203.001 
[DIRS 163563] 
CDF : 
Probability Value 
0.0 0.05 
0.10 1.0 
0.60 5. 
1.0 20. 
N/A Distribution 
LDISP 
(longitudinal 
dispersivity) 
CRWMS 
M&O 1998 
[DIRS 
100353] 
MO0003SZFWTEEP.000 
[DIRS 148744] 
Truncated Normal: (Log10- 
transformed) 
Mean 2.0 
Standard Deviation 0.75 
m Distribution 
Kd_Pu_Col 
(plutonium 
sorption 
coefficient 
onto colloids) 
BSC 2004 
[DIRS 
170025] 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e3 
0.04 5.e3 
0.12 1.e4 
0.37 5.e4 
0.57 1.e5 
0.92 5.e5 
1.0 1.e6 
mL/g Distribution 
Kd_Am_Col 
(americium 
sorption 
coefficient 
onto colloids) 
BSC 2004 
[DIRS 
170025] 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e4 
0.07 5.e4 
0.17 1.e5 
0.40 5.e5 
0.60 1.e6 
0.92 5.e6 
1.0 1.e7 
mL/g Distribution 
Kd_Cs_Col 
(cesium 
sorption 
coefficient 
onto colloids) 
BSC 2004 
[DIRS 
170025] 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e2 
0.2 5.e2 
0.45 1.e3 
0.95 5.e3 
1.0 1.e4 
mL/g Distribution 
Conc_Col 
(groundwater 
concentration 
of colloids) 
BSC 2004 
[DIRS 
170025] 
SN0306T0504103.005 
[DIRS 164132] 
CDF: (Log10-transformed) 
Probability Value 
0.0 -9.0 
0.50 -7.0 
0.75 -6.0 
0.90 -5.0 
0.98 -4.3 
1.0 -3.7 
g/mL Distribution 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-8 October 2004 
Table 4-3. Direct Input (Parameter Uncertainty) (Continued) 
Parameter 
Name 
Parameter 
Source DTN Value(s) Units 
Parameter 
Type 
Correlation 
coefficient for 
U Kd in 
volcanic units 
and alluvium 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
0.75 N/A Single Value 
Correlation 
coefficient for 
Np Kd in 
volcanic units 
and alluvium 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
0.75 N/A Single Value 
Correlation 
coefficient for 
Pu Kd in 
volcanic units 
and alluvium 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
0.50 N/A Single Value 
Correlation 
coefficient for 
U Kd and Np 
Kd 
BSC 2004 
[DIRS 
170036] 
LA0310AM831341.002 
[DIRS 165891] 
0.50 N/A Single Value 
NOTE: DTN: MO0003SZFWTEEP.000 [DIRS 148744] contains qualified data from an expert elicitation that was 
determined to comply with expert elicitation procedure AP-AC.1Q, which is consistent with the branch 
technical position on expert elicitation, NUREG-1563 (Kotra et al. 1996 [DIRS 100909]). 
4.2 CRITERIA 
The general requirements to be satisfied by the TSPA-LA are stated in 10 CFR 63.114 
(10 CFR 63 [DIRS 156605]). Technical requirements to be satisfied by the TSPA-LA are 
identified in the Yucca Mountain Project Requirements Document (Canori and Leitner 2003 
[DIRS 166275], Section 3). The acceptance criteria that will be used by the U.S. Nuclear 
Regulatory Commission (NRC) to determine whether the technical requirements have been met 
are identified in the Yucca Mountain Review Plan, Final Report (YMRP) (NRC 2003 
[DIRS 163274]). The pertinent requirements and criteria for this report are summarized in 
Table 4-4. 
Table 4-4. Project Requirements for This Model Report 
Requirement 
Numbera Requirement Titlea 10 CFR 63 Link 
YMRP Acceptance 
Criteriab 
PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 
[DIRS 156605] 
2.2.1.3.8.3, criteria 1 to 5; 
2.2.1.3.9.3, criteria 1 to 5 
a Canori and Leitner 2003 [DIRS 166275]. 
b NRC 2003 [DIRS 163274]. 
YMRP=Yucca Mountain Review Plan 
In this section, the acceptance criteria identified in Sections 2.2.1.3.8.3, and 2.2.1.3.9.3 of the 
YMRP (NRC 2003 [DIRS 163274]) are given below. In cases where subsidiary criteria are 
listed in the YMRP for a given criterion, only the subsidiary criteria addressed by this model 
report are listed below. Where a subcriterion includes several components, only some of those 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-9 October 2004 
components may be addressed. How these components are addressed is summarized in 
Section 8.3 of this report. 
Acceptance criteria from Section 2.2.1.3.8, Flow Paths in the Saturated Zone 
Acceptance Criterion 1, System Description and Model Integration are Adequate: 
(1) Total system performance assessment adequately incorporates important 
design features, physical phenomena, and couplings, and uses consistent 
and appropriate assumptions, throughout the flow paths in the SZ 
abstraction process. 
(2) The description of the aspects of hydrology, geology, geochemistry, 
design features, physical phenomena, and couplings that may affect flow 
paths in the SZ is adequate. Conditions and assumptions in the abstraction 
of flow paths in the SZ are readily identified and consistent with the body 
of data presented in the description. 
(3) The abstraction of flow paths in the SZ uses assumptions, technical bases, 
data, and models that are appropriate and consistent with other related 
DOE abstractions. For example, the assumptions used for flow paths in 
the SZ are consistent with the total system performance assessment 
abstraction of representative volume (Section 2.2.1.3.12 of NRC 2003 
[DIRS 163274]). The descriptions and technical bases provide transparent 
and traceable support for the abstraction of flow paths in the SZ. 
(4) Boundary and initial conditions used in the total system performance 
assessment abstraction of flow paths in the SZ are propagated throughout 
its abstraction approaches. For example, abstractions are based on initial 
and boundary conditions consistent with site-scale modeling and regional 
models of the Death Valley groundwater flow system. 
(5) Sufficient data and technical bases to assess the extent to which features, 
events, and processes have been included in this abstraction are provided. 
(7) Long-term climate change, based on known patterns of climatic cycles 
during the Quaternary period, particularly the last 500,000 years, and other 
paleoclimate data, are adequately evaluated. 
(9) The impact of the expected water table rise on potentiometric heads and 
flow directions, and consequently on repository performance, is 
adequately considered. 
(10) Guidance in NUREG-1297 (Altman et al. 1988 [DIRS 103597]) and 
NUREG-1298 (Altman et al. 1988 [DIRS 103750]) or other acceptable 
approaches for peer review and data qualification is followed. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-10 October 2004 
Acceptance Criterion 2, Data are Sufficient for Model Justification: 
(1) Geological, hydrological, and geochemical values used in the license 
application to evaluate flow paths in the SZ are adequately justified. 
Adequate descriptions of how the data were used, interpreted, and 
appropriately synthesized into the parameters are provided. 
(3) Data on the geology, hydrology, and geochemistry of the SZ used in the 
total system performance assessment abstraction are based on appropriate 
techniques. These techniques may include laboratory experiments, 
site-specific field measurements, natural analogue research, and processlevel 
modeling studies. As appropriate, sensitivity or uncertainty analyses 
used to support the U.S. Department of Energy total system performance 
assessment abstraction are adequate to determine the possible need for 
additional data. 
Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
(1) Models use parameter values, assumed ranges, probability distributions, 
and/or bounding assumptions that are technically defensible, and 
reasonably account for uncertainties and variabilities, and do not result in 
an under-representation of the risk estimate. 
(2) Uncertainty is appropriately incorporated in model abstractions of 
hydrologic effects of climate change, based on a reasonably complete 
search of paleoclimate data. 
(3) Uncertainty is adequately represented in parameter development for 
conceptual models, process-level models, and ACMs considered in 
developing the abstraction of flow paths in the SZ. This may be done 
either through sensitivity analyses or use of conservative limits. For 
example, sensitivity analyses and/or similar analyses are sufficient to 
identify saturated zone flow parameters that are expected to significantly 
affect the abstraction model outcome. 
(4) Where sufficient data do not exist, the definition of parameter values and 
conceptual models is based on appropriate use of expert elicitation, 
conducted in accordance with NUREG-1563 (Kotra et al. 1996 
[DIRS 100909]). If other approaches are used, the U.S. Department of 
Energy adequately justifies their uses. 
Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through 
the Model Abstraction: 
(1) Alternative modeling approaches of features, events, and processes are 
considered and are consistent with available data and current scientific 
understanding, and the results and limitations are appropriately considered 
in the abstraction. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-11 October 2004 
(2) Conceptual model uncertainties are adequately defined and documented, 
and effects on conclusions regarding performance are properly assessed. 
For example, uncertainty in data interpretations is considered by analyzing 
reasonable conceptual flow models that are supported by site data, or by 
demonstrating through sensitivity studies that the uncertainties have little 
impact on repository performance. 
(3) Consideration of conceptual model uncertainty is consistent with available 
site characterization data, laboratory experiments, field measurements, 
natural analog information and process-level modeling studies; and the 
treatment of conceptual model uncertainty does not result in an 
under-representation of the risk estimate; and 
(4) Appropriate alternative modeling approaches are consistent with available 
data and current scientific knowledge and appropriately consider their 
results and limitations, using tests and analyses that are sensitive to the 
processes modeled. 
Acceptance Criterion 5, Model Abstraction Output Is Supported by Objective 
Comparisons: 
(1) The models implemented in this total system performance assessment 
abstraction provide results consistent with output from detailed 
process-level models and/or empirical observations (laboratory and field 
testing and/or natural analogues). 
(2) Outputs of flow paths in the SZ abstractions reasonably produce or bound 
the results of corresponding process-level models, empirical observations, 
or both. 
(3) Well-documented procedures that have been accepted by the scientific 
community for the construction and testing of the mathematical and 
numerical models are used to simulate flow paths in the SZ. 
(4) Sensitivity analyses or bounding analyses are provided to support the 
abstraction of flow paths in the saturated zone that cover ranges consistent 
with site data, field or laboratory experiments and tests, and natural analog 
research. 
Acceptance criteria from Section 2.2.1.3.9, Radionuclide Transport in the Saturated Zone 
Acceptance Criterion 1, System Description and Model Integration are Adequate: 
(1) Total system performance assessment adequately incorporates important 
design features, physical phenomena, and couplings, and uses consistent 
and appropriate assumptions throughout the radionuclide transport in the 
saturated zone abstraction process. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-12 October 2004 
(2) The description of the aspects of hydrology, geology, geochemistry, 
design features, physical phenomena, and couplings that may affect 
radionuclide transport in the SZ is adequate. For example, the description 
includes changes into transport properties in the saturated zone, from 
water-rock interaction. Conditions and assumptions in the abstraction of 
radionuclide transport in the saturated zone are readily identified, and 
consistent with the body of data presented in the description. 
(3) The abstraction of radionuclide transport in the SZ uses assumptions, 
technical bases, data, and models that are appropriate and consistent with 
other related DOE abstractions. For example, assumptions used for 
radionuclide transport in the saturated zone are consistent with the total 
system performance assessment abstractions of radionuclide release rates 
and solubility limits, and flow paths in the saturated zone (Sections 
2.2.1.3.4 and 2.2.1.3.8 of the Yucca Mountain Review Plan, respectively). 
The descriptions and technical bases provide transparent and traceable 
support for the abstraction of radionuclide transport in the saturated zone. 
(4) Boundary and initial conditions used in the abstraction of radionuclide 
transport in the SZ are propagated throughout its abstraction approaches. 
For example, the conditions and assumptions used to generate transport 
parameter values are consistent with other geological, hydrological, and 
geochemical conditions in the total system performance assessment 
abstraction of the saturated zone. 
(5) Sufficient data and technical bases for the inclusion of features, events, 
and processes related to radionuclide transport in the SZ in the total 
system performance assessment abstraction are provided. 
(6) Guidance in NUREG-1297 (Altman et al. 1988 [DIRS 103597]) and 
NUREG-1298 (Altman et al. 1988 [DIRS 103750]) or other acceptable 
approaches for peer review and data qualification is followed. 
Acceptance Criterion 2, Data are Sufficient for Model Justification: 
(1) Geological, hydrological, and geochemical values used in the license 
application are adequately justified (e.g., flow path lengths, sorption 
coefficients, retardation factors, colloid concentrations, etc.). Adequate 
descriptions of how the data were used, interpreted, and appropriately 
synthesized into the parameters are provided 
(2) Sufficient data have been collected on the characteristics of the natural 
system toestablish initial and boundary conditions for the total system 
performance assessmentabstraction of radionuclide transport in the 
saturated zone 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-13 October 2004 
Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
(1) Models use parameter values, assumed ranges, probability distributions, 
and/or bounding assumptions that are technically defensible, and 
reasonably account for uncertainties and variabilities, and do not result in 
an under-representation of the risk estimate. 
(4) Parameter values for processes, such as matrix diffusion, dispersion, and 
groundwater mixing, are based on reasonable assumptions about climate, 
aquifer properties, and groundwater volumetric fluxes (Section 2.2.1.3.8 
of NRC 2003 [DIRS 163274]). 
(5) Uncertainty is adequately represented in parameter development for 
conceptual models, process-level models, and ACMs considered in 
developing the abstraction of radionuclide transport in the SZ. This may 
be done either through sensitivity analyses or use of conservative limits. 
(6) Where sufficient data do not exist, the definition of parameter values and 
conceptual models is based on appropriate use of expert elicitation, 
conducted in accordance with NUREG-1563 (Kotra et al. 1996 
[DIRS 100909]). If other approaches are used, the U.S. Department of 
Energy adequately justifies their use. 
Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through 
the Model Abstraction: 
(1) Alternative modeling approaches of features, events, and processes are 
considered and are consistent with available data and current scientific 
understanding, and the results and limitations are appropriately considered 
in the abstraction. 
(2) Conceptual model uncertainties are adequately defined and documented, 
and effects on conclusions regarding performance are properly assessed. 
(3) Consideration of conceptual model uncertainty is consistent with available 
site characterization data, laboratory experiments, field measurements, 
natural analog information and process-level modeling studies; and the 
treatment of conceptual model uncertainty does not result in an 
under-representation of the risk estimate; and 
(4) Appropriate alternative modeling approaches are consistent with available 
data and current scientific knowledge and appropriately consider their 
results and limitations, using tests and analyses that are sensitive to the 
processes modeled. For example, for radionuclide transport through 
fractures, the U.S. Department of Energy adequately considers alternative 
modeling approaches to develop its understanding of fracture distributions 
and ranges of fracture flow and transport properties in the saturated zone. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 4-14 October 2004 
Acceptance Criterion 5, Model Abstraction Output is Supported by Objective 
Comparisons: 
(1) The models implemented in this total system performance assessment 
abstraction provide results consistent with output from detailed 
process-level models and/or empirical observations (laboratory and field 
testing and/or natural analogs); 
(2) Outputs of radionuclide transport in the SZ abstractions reasonably 
produce or bound the results of coresponding process-level models, 
empirical observations, or both. The U.S. Department of Energyabstracted 
models for radionuclide transport in the saturated zone are 
based on the same hydrological, geological, and geochemical assumptions 
and approximations shown to be appropriate for closely analogous natural 
systems or laboratory experimental systems. 
(3) Well-documented procedures that have been accepted by the scientific 
community for the construction and testing of the mathematical and 
numerical models are used to simulate radionuclide transport through the 
SZ. 
(4) Sensitivity analyses or bounding analyses are provided, to support the total 
system performance assessment abstraction of radionuclide transport in 
the SZ, that cover ranges consistent with site data, field or laboratory 
experiments and tests, and natural analogue research. 
4.3 CODES, STANDARDS, AND REGULATIONS 
No codes, standards, or regulations other than those identified in the Project Requirements 
Document (Canori and Leitner 2003 [DIRS 166275], Table 2-3) and determined to be applicable 
(Table 4-4) were used in this analysis. 

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 5-1 October 2004 
5. ASSUMPTIONS 
Several types of assumptions pertain to model development. The assumptions listed in this 
section of the report are restricted to those that meet the definition given in the QA procedure 
AP-SIII.10Q, Models. This definition states that an assumption is a statement or proposition 
that is taken to be true or representative in the absence of direct confirming data or evidence. 
Additional technical modeling bases (assumptions) pertaining to the modeling framework are 
documented in Section 6 of this report (primarily in Section 6.3). 
1. For the transport of radionuclides irreversibly attached to colloids in the SZ, it is assumed 
that radionuclides will not desorb from colloids. This assumption is carried forward from 
the scientific analysis report Saturated Zone Colloid Transport (BSC 2004 
[DIRS 170006], Section 6.3) and is consistent with the mineralogic characteristics of 
colloids from the degradation of the glass waste form. This assumption is also 
conservative with regard to repository performance due to the comparatively high 
mobility of colloids in the SZ relative to the sorptive characteristics of the radionuclides 
(Pu and Am) that are subject to colloid-facilitated transport. This assumption is used in 
Sections 6.3.1, 6.3.2, 6.5.1, and 6.5.2.11. This assumption needs no further confirmation, 
given that it is a bounding assumption that maximizes the rate of radionuclide migration 
in the SZ. 
2. Colloids with irreversibly attached radionuclides are assumed to be subject to attachment 
and detachment to mineral grains in the aquifer, but not to be subject to permanent 
filtration from the groundwater of the SZ. This assumption is carried forward from the 
scientific analysis report Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], 
Section 6.3). The kinetically controlled attachment and detachment of colloids in the 
aquifer is consistent with tracer testing in the SZ using microspheres. The permanent 
filtration of colloids in the SZ has not been demonstrated by field-testing, although this 
process can occur. This assumptions alternative, in which permanent filtration were 
simulated to occur, would lead to significant attenuation of the migration of radionuclides 
irreversibly attached to colloids. This assumption is used in Sections 6.3.1, 6.3.2, 6.5.1, 
and 6.5.2.11. This assumption needs no further confirmation, given that it is a bounding 
assumption that maximizes the migration of radionuclides in the SZ. 
3. The assumption is made that the average concentration of radionuclides in the 
groundwater supply of the hypothetical community in which the reasonably maximally 
exposed individual (RMEI) resides is an appropriate estimate of radionuclide 
concentration for the calculation of radiological dose. This assumption applies to the 
calculation of radionuclide concentrations for evaluation of compliance with 
10 CFR 63.332 (10 CFR 63 [DIRS 156605]) and with groundwater protection in 
10 CFR 63.331. Realistically, the concentrations of radionuclides encountered by wells 
in the hypothetical community in which the RMEI resides would vary from location to 
location within the contaminant plume in the SZ. However, radionuclide transfer 
processes within the biosphere (e.g., redistribution of agricultural products, communal 
water supplies, etc.) would tend to average the overall dose received by the population of 
the community in which the RMEI resides. This assumption is used in Section 6.3.3. 
This assumption needs no further confirmation, given that there is a regulatory basis for 

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 5-2 October 2004 
this approach to calculating average concentrations of radionuclides and radiological 
dose in 10 CFR 63.332 (10 CFR 63 [DIRS 156605]). 
4. The assumption is made that the horizontal anisotropy in permeability applies to the 
fractured and faulted volcanic units of the SZ system along the groundwater flow path 
from the repository to the south and east of Yucca Mountain. This assumption is carried 
forward from the scientific analysis report Saturated Zone In-Situ Testing (BSC 2004 
[DIRS 170010], Section 6.2.6). The inferred flow path from beneath the repository 
extends to the south and east. This is the area in which pumping tests were conducted at 
the C-holes well complex (BSC 2004 [DIRS 170010]), from which horizontal anisotropy 
was inferred. Given the conceptual basis for the anisotropy model, it is appropriate to 
apply anisotropy only to those hydrogeologic units that are dominated by groundwater 
flow in fractures because it is the preferential orientations of open fractures that impart 
anisotropy in the system. This assumption is used in Section 6.5.2.10. This assumption 
needs no further confirmation, given the wide range of uncertainty in horizontal 
anisotropy used in the SZ transport abstraction model. 
5. It is assumed that the change in groundwater flow in the SZ from one climatic state to 
another occurs rapidly and is approximated by an instantaneous shift from one 
steady-state flow condition to another steady-state flow condition. In actuality, even an 
extremely rapid shift in climatic conditions would result in a transient response of the SZ 
flow system because of changes in groundwater storage associated with water table rise 
or fall and because of the response time in the unsaturated zone (UZ) flow system. The 
assumption of instantaneous shifts to new steady-state conditions would tend to 
overestimate the rate of radionuclide transport in the TSPA-LA calculations. The 
progression of climate states in the 10,000 years following repository closure is 
anticipated to be from drier to wetter climatic conditions and thus from slower to more 
rapid groundwater flow in the SZ. By assuming an instantaneous shift to higher 
groundwater flux in the SZ, the simulations tend to overestimate the radionuclide 
transport velocities during the period of transition from drier conditions to wetter 
conditions. This assumption is used in Section 6.5. This assumption needs no further 
confirmation, given that this simplified approach underestimates the transport times for 
radionuclides in the SZ and is thus pessimistic with regard to repository performance. 
6. Groundwater flow pathways in the SZ from beneath the repository to the accessible 
environment are assumed not to be significantly altered for wetter climatic states. 
Scaling of present-day groundwater flux and radionuclide mass breakthrough curves by a 
proportionality factor implies that only the groundwater velocities are changed in the 
SZ system in response to climate change. This assumption is supported by the 
observation that the shape of the simulated potentiometric surface downgradient from 
Yucca Mountain remains essentially the same under glacial-transition climatic conditions 
in simulations using the Death Valley regional flow model (DAgnese et al. 1999 
[DIRS 120425], p. 30). Water table rise directly beneath the repository under wetter 
climatic conditions would tend to place volcanic units higher in the stratigraphic 
sequence at or just below the water table. These higher volcanic units (Prow Pass Tuff 
and Calico Hills Formation) have lower values of permeability than the underlying 
Bullfrog Tuff. This approximation of climate change with unaltered SZ flow paths is 

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 5-3 October 2004 
shown to underestimate radionuclide transport times in sensitivity studies documented in 
Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix E). This 
assumption is used in Section 6.5. This assumption needs no further confirmation, given 
that this simplified approach tends to underestimate the transport times for radionuclides 
in the SZ. 

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 5-4 October 2004 
INTENTIONALLY LEFT BLANK

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 6-1 October 2004 
6. MODEL DISCUSSION 
6.1 MODELING OBJECTIVES 
The primary objective of the SZ transport abstraction model and the SZ 1-D transport model is to 
provide a method of simulating radionuclide transport in the SZ for use in the TSPA-LA model 
of repository performance. Analyses of parameter uncertainty and multiple realizations of the 
SZ system using the SZ transport abstraction model constitute an assessment of uncertainty in 
the SZ system for direct implementation in the TSPA-LA model. Model uncertainty is addressed 
by generating a suite of radionuclide breakthrough curves based on the multiple realizations of 
the SZ system. The general approach to modeling radionuclide migration and the assessment of 
uncertainty in the SZ is also described by Arnold et al. in Radionuclide Transport Simulation 
and Uncertainty Analyses with the Saturated-Zone Site-Scale Model at Yucca Mountain, 
Nevada (2003 [DIRS 163857]). The objective of the SZ 1-D transport model is to provide a 
simplified, yet accurate, representation of SZ transport for the simulation of four radionuclide 
decay chains for implementation with the TSPA-LA model. Figure 1-1 shows the flow of 
information among the SZ reports used in the development of the SZ transport abstraction model 
and the SZ 1-D transport model as outputs from this report. 
In the TSPA-LA analyses, the convolution integral method is used by the SZ transport 
abstraction model to determine the radionuclide mass flux at the SZ/biosphere interface, 18 km 
downgradient of the repository at 3640'13.6661 north latitude (10 CFR 63.302 [DIRS 156605]) 
as a function of the transient radionuclide mass flux at the water table beneath the repository. 
This computationally efficient method combines information about the unit response of the 
system, as simulated by the SZ transport abstraction model, with the radionuclide source history 
from the UZ, to calculate transient system behavior. The fundamental concepts of the 
convolution integral method, as applied to solute transport in groundwater, are presented by Jury 
et al. (1986 [DIRS 164314]), in which the method is called the transfer function model. The 
most important assumptions of the convolution method are linear system behavior and steadystate 
flow conditions in the SZ. 
The SZ 1-D transport model is used in the TSPA-LA analyses for the purpose of simulating 
radioactive decay and ingrowth for four decay chains. This simplified model is required because 
the radionuclide transport methodology used in the SZ transport abstraction model is not capable 
of simulating ingrowth by radioactive decay. Although it is not anticipated that the decay 
products generated from these radioactive decay chains during transport in the SZ are significant 
contributors to the total radiological dose, regulations concerning groundwater protection 
contained in 10 CFR 63.331 (10 CFR 63 [DIRS 156605]) require explicit analysis of the total 
concentrations of 226Ra plus 228Ra, gross alpha emitters, and beta plus photon emitters in the 
water supply of the RMEI. Consequently, only the results for decay product-radionuclides from 
the SZ 1-D transport model are input to the TSPA-LA simulations. Although transport of the 
parent radionuclides is also included in the SZ 1-D transport model, the results for 
parent-radionuclides input to the TSPA-LA simulations are those derived from the SZ transport 
abstraction model. The SZ 1-D transport model for TSPA-LA differs in implementation from 
the SZ transport abstraction model in that it is constructed directly within the GoldSim 
V7.50.100 software code (GoldSim V7.50.100, STN: 10344-7.50.100-00 [DIRS 161572]) in the 
TSPA-LA model. It should be noted that transport of the first-generation decay products in the 

Saturated Zone Flow and Transport Abstraction 
MDL-NBS-HS-0000021 REV 02 6-2 October 2004 
four decay chains is simulated with the SZ transport abstraction model using a simplified method 
of inventory boosting, as described in Section 6.3.1. 
6.2 FEATURES, EVENTS, AND PROCESSES FOR THIS MODEL REPORT 
As stipulated in Technical Work Plan For: Natural System - Saturated Zone Analysis Model 
Report Integration (BSC 2004 [DIRS 171421], Section 2.1.5) this model report addresses the SZ 
FEPs pertaining to the abstraction of SZ flow and transport that are included in the TSPA-LA 
model (Table 6-1). Table 6-1 provides a list of FEPs that are relevant to the models documented 
in this report, in accordance with their assignment in the LA FEP list 
(DTN: MO0407SEPFEPLA.000 ([DIRS 170760]). Specific reference to the various sections 
within this document where issues related to each FEP are addressed is provided in Table 6-1. 
The detailed discussions of these FEPs and their implementation in TSPA-LA are documented in 
the Features, Events, and Processes in SZ Flow and Transport (BSC 2004 [DIRS 170013]) 
report. Saturated zone FEPs that were excluded from the TSPA-LA modeling also are described 
in Features, Events, and Processes in SZ Flow and Transport. 
Table 6-1. Features, Events, and Processes Included in TSPA-LA and Relevant to This Model Report 
FEP No. FEP Name 
Sections Where 
Disposition is 
Supported 
FEP Topic Addressed in Other SZ Analysis 
or Model Reports 
1.2.02.01.0A Fractures 6.5.2.1, 6.5.2.4, 
6.5.2.5, 6.5.2.9, 
6.5.2.10, 6.5.2.11, 
6.5.2.12, 6.5.2.15 
Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170014] 
CorroboratingbBSC 2004 [DIRS 170010] 
1.2.02.02.0A Faults 6.3.1, 6.5.2.1, 
6.5.2.10 
Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170037], BSC 2004 [DIRS 170008] 
CorroboratingbBSC 2004 [DIRS 170010] 
1.3.07.02.0A Water table rise affects 
SZ 
5 Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170009] 
1.4.07.01.0A Water management 
activities 
6.3.3, 6.7.2 Upstream FeedsaBSC 2004 [DIRS 170009] 
1.4.07.02.0A Wells 6.3.3 Upstream FeedsaBSC 2004 [DIRS 170009] 
2.2.03.01.0A Stratigraphy 6.5.2, 6.5.2.1, 6.5.2.2, 
6.5.2.3, 6.5.2.6, 
6.5.2.18, 6.5.2.19 
Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170008], BSC 2004 [DIRS 170037] 
CorroboratingbBSC 2004 [DIRS 170010], 
BSC 2004 [DIRS 170014] 
2.2.03.02.0A Rock properties of 
host rock and other 
units 
6.5.2.1, 6.5.2.2, 
6.5.2.3, 6.5.2.4, 
6.5.2.5, 6.5.2.7, 
6.5.2.8, 6.5.2.9, 
6.5.2.10, 6.5.2.14, 
6.5.2.15, 6.5.2.16, 
6.5.2.17, 6.5.2.18, 
6.5.2.19, 6.5.2.20 
Upstream FeedsaBSC 2004 [DIRS 170036] 
CorroboratingbBSC 2004 [DIRS 170010], 
BSC 2004 [DIRS 170014], BSC 2004 
[DIRS 170008] 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-3 October 2004 
Table 6-1. Features, Events, and Processes Included in TSPA-LA and Relevant to This Model Report 
(Continued) 
FEP No. FEP Name 
Sections Where 
Disposition is 
Supported 
FEP Topic Addressed in Other SZ Analysis or 
Model Reports 
2.2.07.12.0A Saturated groundwater 
flow in the geosphere 
6.3, 6.5, 6.5.2.1, 
6.5.2.10 
Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170037] 
CorroboratingbBSC 2004 [DIRS 170010], BSC 
2004 [DIRS 170037], BSC 2004 [DIRS 170014] 
2.2.07.13.0A Water-conducting 
features in the SZ 
6.5.2.1, 6.5.2.4, 
6.5.2.5, 6.5.2.9, 
6.5.2.10 
Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170037] 
CorroboratingbBSC 2004 [DIRS 170014], 
BSC 2004 [DIRS 170010] 
2.2.07.15.0A Advection and 
dispersion in the SZ 
6.3, 6.5.2.1, 6.5.2.9, 
6.5.2.10 
Upstream FeedsaBSC 2004 [DIRS 170036] 
CorroboratingbBSC 2004 [DIRS 170010] 
2.2.07.16.0A Dilution of radionuclides 
in groundwater 
6.5.2.9, 6.7.2 Upstream FeedsaBSC 2004 [DIRS 170036] 
2.2.07.17.0A Diffusion in the SZ 6.3, 6.5.2.6 Upstream FeedsaBSC 2004 [DIRS 170036] 
CorroboratingbBSC 2004 [DIRS 170010], 
BSC 2004 [DIRS 170006] 
2.2.08.01.0A Chemical characteristics 
of groundwater in the SZ 
6.5.2.8, 6.5.2.11, 
6.5.2.12 
Upstream FeedsaBSC 2004 [DIRS 170036] 
CorroboratingbBSC 2004 [DIRS 170037] 
2.2.08.06.0A Complexation in the SZ 6.5.2.8, 6.5.2.11, 
6.5.2.12 
Upstream FeedsaBSC 2004 [DIRS 170036] 
2.2.08.08.0A Matrix diffusion in the SZ 6.3, 6.5.2.4, 6.5.2.5, 
6.5.2.6 
Upstream FeedsaBSC 2004 [DIRS 170036] 
CorroboratingbBSC 2004 [DIRS 170010], 
BSC 2004 [DIRS 170014], BSC 2004 
[DIRS 170006] 
2.2.08.09.0A Sorption in the SZ 6.3, 6.5.2.8, 6.5.2.11, 
6.5.2.12 
Upstream FeedsaBSC 2004 [DIRS 170036] 
2.2.08.10.0A Colloidal transport in the 
SZ 
6.3.1, 6.5.1, 6.5.2.11, 
6.5.2.12 
Upstream FeedsaBSC 2004 [DIRS 170036], 
BSC 2004 [DIRS 170006] 
2.2.10.03.0A Natural geothermal 
effects on flow in the SZ 
6.5.2.6 Upstream FeedsaBSC 2004 [DIRS 170036] 
Expanded DiscussioncBSC 2004 
[DIRS 170037] 
2.2.12.00.0B Undetected features in 
the SZ 
6.5.2.1, 6.5.2.3, 
6.5.2.4, 6.5.2.10 
Upstream FeedsaBSC 2004 [DIRS 170036], 
BSC 2004 [DIRS 170014] 
CorroboratingbBSC 2004 [DIRS 170010], BSC 
2004 [DIRS 170037] 
3.1.01.01.0A Radioactive decay and 
in-growth 
6.3.1, 6.5, 6.5.1 Upstream FeedsaN/A 
a Upstream Feeds  Aspects of the SZ FEP discussion adopted in this report are a result of SZ analyses performed in a 
directly upstream SZ model or analyses. 
b Corroborating  Corroborative aspect(s) of the FEP topic is (are) discussed in a SZ analysis report. 
c Expanded Discussion  The primary discussion of the FEP topic is discussed in the referenced SZ report. 
NOTE: See Table 6-2 for key to SZ Analysis and Model Reports (e.g., BSC 2004 [DIRS 170036]) 
FEP=feature, event, or process; SZ=saturated zone 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-4 October 2004 
Table 6-2 provides a key to the SZ analysis and model reports listed in Table 6-1. SZ FEPs that 
are excluded from the models in the SZ are listed in Table 6-3. Screening arguments for the 
exclusion of the excluded FEPs are provided in Features, Events, and Processes in SZ Flow and 
Transport (BSC 2004 [DIRS 170013]. 
Table 6-2. SZ Analysis and Model Reports 
SZ Analysis or Model 
Report Number Report Title 
Document 
Identification Number 
BSC 2004 [DIRS 170008] Hydrogeologic Framework Model for the Saturated Zone Site 
Scale Flow and Transport Model 
MDL-NBS-HS-000024 
BSC 2004 [DIRS 170009] Water-Level Data Analysis for the Saturated Zone Site-Scale 
Flow and Transport Model 
ANL-NBS-HS-000034 
BSC 2004 [DIRS 170015] Recharge and Lateral Groundwater Flow Boundary Conditions 
for the Saturated Zone Site-Scale Flow and Transport Model 
ANL-NBS-MD-000010 
BSC 2004 [DIRS 170036] Site-Scale Saturated Zone Transport MDL-NBS-HS-000010 
BSC 2004 [DIRS 170014] Probability Distribution for Flowing Interval Spacing ANL-NBS-MD-000003 
BSC 2004 [DIRS 170006] Saturated Zone Colloid Transport ANL-NBS-HS-000003 
BSC 2004 [DIRS 170037] Saturated Zone Site-Scale Flow Model MDL-NBS-HS-000011 
BSC 2004 [DIRS 170042] Saturated Zone Flow and Transport Model Abstraction MDL-NBS-HS-000021 
BSC 2004 [DIRS 170013] Features, Events, and Processes in SZ Flow and Transport ANL-NBS-MD-000002 
BSC 2004 [DIRS 170010] Saturated Zone In-Situ Testing ANL-NBS-HS-000039 
SZ=saturated zone 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-5 October 2004 
Table 6-3. SZ Excluded FEPs 
FEP Number FEP Name 
1.2.04.02.0A Igneous activity changes rock properties 
1.2.04.07.0B Ash redistribution in groundwater 
1.2.06.00.0A Hydrothermal activity 
1.2.09.02.0A Large-scale dissolution 
1.2.10.01.0A Hydrologic response to seismic activity 
1.2.10.02.0A Hydrologic response to igneous activity 
1.3.07.01.0A Water table decline 
1.4.07.03.0A Recycling of accumulated radionuclides from soils to groundwater 
2.1.09.21.0B Transport of particles larger than colloids in the SZ 
2.2.06.01.0A Seismic activity changes porosity and permeability of rock 
2.2.06.02.0A Seismic activity changes porosity and permeability of faults 
2.2.06.02.0B Seismic activity changes porosity and permeability of fractures 
2.2.07.14.0A Chemically-induced density effects on groundwater flow 
2.2.08.03.0A Geochemical interactions and evolution in the SZ 
2.2.08.07.0A Radionuclide solubility limits in the SZ 
2.2.08.11.0A Groundwater discharge to surface within the reference biosphere 
2.2.09.01.0A Microbial activity in the SZ 
2.2.10.02.0A Thermal convection cell develops in SZ 
2.2.10.04.0A Thermo-mechanical stresses alter characteristics of fractures near repository 
2.2.10.04.0B Thermo-mechanical stresses alter characteristics of faults near repository 
2.2.10.05.0A Thermo-mechanical stresses alter characteristics of rocks near repository 
2.2.10.08.0A Thermo-Chemical Alteration in the SZ (Solubility, Speciation, Phase 
Changes, Precipitation/Dissolution 
2.2.10.13.0A Repository-induced thermal effects on flow in the SZ 
2.2.11.01.0A Gas effects in the SZ 
2.3.11.04.0A Groundwater discharge to surface outside the reference biosphere 
3.2.07.01.0A Isotopic dilution 
FEP=feature, event, or process; SZ=saturated zone 
6.3 BASE-CASE CONCEPTUAL MODEL 
The base-case conceptual model for radionuclide transport, as implemented in the SZ transport 
abstraction model, implicitly includes the conceptual models of groundwater flow and transport 
incorporated in the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.3) and the SZ 
site-scale transport model (BSC 2004 [DIRS 170036], Sections 6.3). The SZ site-scale flow 
model and alternative conceptualizations of groundwater flow are also described by Zyvoloski et 
al. (2003 [DIRS 163341]). The base-case conceptual model for the SZ 1-D transport model also 
implicitly includes the conceptual models in these underlying models, with the conceptual 
simplifications in flow associated with representation by 1-D groundwater flow. The SZ 
transport abstraction model and the SZ 1-D transport model also include the concept of 
uncertainty in key model parameters. The probabilistic analysis of uncertainty is implemented 
through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent 
with the TSPA-LA simulations. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-6 October 2004 
6.3.1 SZ Transport Abstraction Model 
The conceptual model of groundwater flow in the SZ includes steady-state flow conditions in a 
three-dimensional (3-D) flow system (BSC 2004 [DIRS 170037], Section 6.3.3). Groundwater 
flow occurs in a continuum fracture network in the fractured volcanic rocks beneath the 
repository site, at the scale of individual grid blocks in the SZ transport abstraction model. The 
effective continuum conceptual model is appropriate, given the relatively large horizontal scale 
(500 m by 500 m) of the grid in the model. Grid resolution studies with the SZ site-scale flow 
model indicate that the 500 m grid resolution and the effective continuum conceptual model are 
adequate to capture the flow behavior of the SZ system and to calibrate the model (Bower et al. 
2000 [DIRS 149161]). Groundwater flow is conceptualized to occur in a continuum porous 
medium in the alluvium and valley-fill units of the SZ transport abstraction model. Contrasting 
values of average permeability among hydrogeologic units influence the patterns of groundwater 
flow in the SZ (BSC 2004 [DIRS 170037], Sections 6.3 and 6.6). 
Some of the major faults and other discrete geological features are conceptualized to impact the 
groundwater flow due to contrasts in permeability with surrounding hydrogeologic units. In 
addition, the prevailing structural fabric in the volcanic hydrogeologic units near 
Yucca Mountain can possibly impart horizontal anisotropy in the permeability between the major 
faults in this area of the SZ system. Significant variations in the hydraulic gradient near 
Yucca Mountain occur to the north of Yucca Mountain at the Large Hydraulic Gradient and to 
the west of Yucca Mountain at the Moderate Hydraulic Gradient, corresponding to the Solitario 
Canyon fault (Luckey et al. 1996 [DIRS 100465], pp. 21 to 26). Analysis of the different 
conceptualizations of the Large Hydraulic Gradient showed that the specific discharge was only 
mildly sensitive to choice of conceptual model if the hydraulic head measurements along the 
flow path were reasonably well matched by the numerical model (BSC 2004 [DIRS 170037], 
Section 6.4.1). 
Groundwater flow enters the SZ site-scale flow system primarily as underflow at the lateral 
boundaries of the model domain (BSC 2004 [DIRS 170037], Section 6.3.2). The conceptual 
model of recharge to the SZ includes distributed recharge, primarily in the northern part of the 
model domain, and focused recharge along the Fortymile Wash channel (BSC 2004 
[DIRS 170037], Section 6.3.2). Recharge within the area of the SZ transport abstraction model 
domain constitutes a small fraction of the entire groundwater budget of the site-scale flow 
system. Groundwater flow paths from beneath Yucca Mountain to the south are conceptualized 
to occur near the water table, due to the generally small amount of recharge in this area. 
The conceptual model of the SZ flow system for future climatic conditions includes significant 
changes in the groundwater flow rates for potential wetter, cooler climate states. Increases in 
recharge at both the local and regional scales for monsoonal and glacial-transition climatic 
conditions would increase the specific discharge of groundwater in the SZ. Given the likelihood 
of such climatic variations within the 10,000-year period of regulatory concern, the conceptual 
model of SZ flow includes higher groundwater fluxes for the future. 
The conceptual model of radionuclide transport in the SZ includes the processes of advection, 
dispersion, matrix diffusion in fractured volcanic units, sorption, and colloid-facilitated transport 
(BSC 2004 [DIRS 170036], Section 6.3). In addition, radionuclides are subject to radioactive 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-7 October 2004 
decay and ingrowth during migration in the SZ in the TSPA-LA analyses. These processes are 
illustrated in Figures 6-1 and 6-2. 
Figure 6-1. Illustration of the Conceptual Model of Radionuclide Transport Processes in the SZ 
Groundwater advection is the primary mechanism to drive the migration of contaminants from 
the SZ beneath the repository to the accessible environment. Advective transport of 
radionuclides is conceptualized to occur primarily within the fracture network of the volcanic 
hydrogeologic units (BSC 2004 [DIRS 170036], Section 6.3) due to the very high contrast in 
permeability between the fractures and the rock matrix. The conceptual model of advection 
within the porous medium of the alluvium units envisions the flow of groundwater to be much 
more widely distributed, but excludes groundwater flow from zones or sedimentary facies of 
lower permeability material within the alluvium. 
Dispersion of contaminant mass during transport in the SZ is conceptualized to occur because of 
hydrodynamic dispersion and molecular diffusion. Hydrodynamic dispersion is the result of 
variations in groundwater flow rates induced by heterogeneities within the aquifer, both in 
fractured and porous media. The conceptual model of hydrodynamic dispersion distinguishes 
between longitudinal dispersion, which occurs in the direction of groundwater flow, and 
transverse dispersion, which occurs perpendicular to the direction of groundwater flow. 
Longitudinal dispersion is typically much greater than transverse dispersion 
(see Section 6.5.2.9). Molecular diffusion also contributes to dispersion in radionuclide transport 
in the advective domain, but to a much lesser degree than hydrodynamic dispersion. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-8 October 2004 
The dual-porosity conceptual model of matrix diffusion in fractured media describes the transfer 
of radionuclide mass from the flowing groundwater within the fractures to the relatively stagnant 
groundwater contained in the pores of the rock matrix. This mass transfer, either into or out of 
the rock matrix, occurs by molecular diffusion, which is driven by differences in the 
concentration of the contaminant in the fractures and matrix. The simplified conceptual model 
of the spatial distribution of groundwater-conducting fractures and matrix is a set of parallel, 
uniformly spaced fractures, separated by blocks of porous matrix (BSC 2004 [DIRS 170036], 
Section 6.4.2.4). This conceptual model considers that groundwater flow occurs only in the 
fractures and that the groundwater in the rock matrix has no advective groundwater movement. 
Although this aspect of the dual-porosity conceptual model is difficult to confirm, the contrast in 
permeability between the rock matrix and the fracture network in fractured tuff supports this 
approach. Groundwater flow is conceptualized to not necessarily occur in all fractures of the 
system, but is limited to those fractures that are interconnected in the through-going fracture 
network. The matrix diffusion process is controlled primarily by the effective diffusion 
coefficient in the rock matrix, the spacing between fractures carrying flowing groundwater, and 
the aperture of the fractures. 
The conceptual model of matrix diffusion also recognizes the possibility of groundwater flow in 
fracture zones, in which numerous, closely spaced fractures can possibly transmit groundwater. 
Such fracture zones could exist along faults, which have experienced multiple episodes of 
displacement and potentially contain zones of rubblized bedrock. Diffusion of contaminants into 
the relatively small blocks of matrix within a fracture zone would be rapid in comparison to the 
matrix diffusion that would occur into the large blocks that exist between such zones. The 
contaminant storage capacity of the small blocks within such a fracture zone would be the total 
matrix porosity (and sorption capacity of mineral grains) of the blocks, corresponding to 
essentially complete matrix diffusion within the small matrix blocks. 
The conceptual model of radionuclide sorption in the SZ is local equilibrium distribution of 
radionuclide mass between the aqueous phase and the mineral grains of the aquifer. This 
equilibrium distribution of contaminant mass is defined by the linear sorption coefficient 
relationship (BSC 2004 [DIRS 170036], Section 6.4.2.5). In fractured media, sorption is 
conceptualized to occur in the rock matrix; no sorption of solutes is conceptualized to occur on 
the fracture surfaces or coatings. Although sorption can possibly occur on fracture surfaces or 
coatings, there are no definitive measurements of this process. Discounting possible sorption on 
fracture surfaces in the conceptual model results in more rapid radionuclide migration in 
numerical simulations of transport in the SZ. In the porous media of the alluvium, sorption is 
conceptualized to occur in that portion of the aquifer corresponding to the effective porosity of 
the alluvium. In other words, sorption can occur in that part of the alluvium through which 
significant groundwater flow occurs; zones or layers of low permeability are effectively excluded 
from the sorption process. 
In the conceptual model of colloid-facilitated transport radionuclide migration associated with 
colloids can occur by two modes (BSC 2004 [DIRS 170006], Section 6.3), as illustrated in 
Figure 6-2. In the first mode, radionuclides that are reversibly attached to colloids are in 
equilibrium with the aqueous phase and the aquifer material. In this mode of transport, the 
effective retardation of these radionuclides during transport in the SZ is dependent on the 
sorption coefficient of the radionuclide onto colloids, the concentration of colloids in the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-9 October 2004 
groundwater, and the sorption coefficient of the radionuclide onto the aquifer material. In the 
second mode, radionuclides that are irreversibly attached to colloids are transported at the same 
rate as the colloids. The colloids with the irreversibly attached radionuclides are themselves 
retarded by interaction (attachment and detachment) with the aquifer material. Specifically, the 
colloids undergo reversible filtration, which is represented by a retardation factor in the model. 
This conceptual model also recognizes that a small fraction of colloids with irreversibly attached 
radionuclides could be transported through the SZ with no retardation, due to kinetic effects of 
colloid attachment and detachment. This fast fraction of the colloids with irreversibly attached 
radionuclides is transported with no retardation in the SZ (similar to nonsorbing solutes), but 
without diffusion into the matrix of the volcanic units. 
The conceptual model of radioactive decay in the SZ transport abstraction model is that 
radionuclides experience a decrease in mass during transport time using the first-order decay 
constant for that radionuclide. Because the ingrowth of radionuclides is not explicitly included 
in the SZ transport abstraction model, a simplified approach is used to account for this process 
for some of the radionuclides that have parent radionuclides. In this simplified approach, the 
mass of the decay product-radionuclide is boosted by the maximum mass of the parent 
radionuclide that would decay over the remaining TSPA-LA simulation time (BSC 2004 
[DIRS 168504], Section 6.3.10). The boosting of the decay product-radionuclide mass occurs 
for the input to the SZ transport abstraction model (i.e., at the UZ-SZ interface). The decay 
product-radionuclides that are boosted in this manner are 239Pu (from 243Am), 237Np (from 
241Am), 236U (from 240Pu), 238U (from 242Pu), and 234U (from 238U and 238Pu). It should be noted 
that the parent radionuclides of these boosted decay products are not diminished and that, 
consequently, this approach overestimates the mass of radionuclides being transported in the SZ. 
Transport of subsequent decay products in the four decay chains is explicitly simulated using the 
SZ 1-D transport model, as described in Section 6.3.2. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-10 October 2004 
Figure 6-2. Illustration of the Conceptual Model of Colloid-Facilitated Radionuclide Transport in Fractured 
Tuff in the SZ 
Homogeneous material properties are assigned to individual hydrogeologic units. The 
assumption of intra-unit homogeneity is justified primarily on the basis of scale in the 
SZ transport abstraction model. The horizontal grid resolution of 500 m implies averaging of 
spatially variable properties over a very large volume. In addition, variations among realizations 
for stochastic parameters in the analysis encompass probable spatial variations in material 
properties within the model domain. 
The groundwater flow conditions in the SZ system are also assumed to be in steady state. This 
approach is carried forward from the SZ site-scale flow model (BSC 2004 [DIRS 170037], 
Section 5). The site-scale SZ flow model is a steady-state model of the flow conditions, 
reflecting the conclusion that a steady-state representation of the SZ system is accurate. This 
conclusion is supported by the lack of consistent, large-magnitude variations in water levels 
observed in wells near Yucca Mountain (Luckey et al. 1996 [DIRS 100465], pp. 29 to 32). The 
convolution integral method has been extended to incorporate multiple steady-state flow 
conditions for future climate states in the TSPA-LA analyses. 
The conceptual model of matrix diffusion in the fractured volcanic units of the SZ assumes 
groundwater flow in evenly spaced, parallel-walled fractures separated by impermeable matrix 
(BSC 2004 [DIRS 170036], Section 6.4.2.4). Although this dual-porosity conceptual model of 
radionuclide transport represents a significant simplification of the complex fracture network 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-11 October 2004 
observed in fractured volcanic rocks at the site, it is an acceptable approximation at the scale of 
individual grid blocks in the SZ transport abstraction model. Individual grid blocks in the 
transport model have horizontal dimensions of 500 m by 500 m, in comparison to a geometric 
mean flowing interval spacing of approximately 21 m. This comparison indicates that the grid 
blocks in the numerical model are more than an order of magnitude larger than the expected 
spacing between fracture zones that contain flowing groundwater. In addition, the relatively 
broad range of uncertainty in the flowing interval spacing used in this analysis encompasses the 
variability in spacing of the actual fracture network. Thus, the variability in flowing interval 
spacing among stochastic realizations in the TSPA-LA simulations captures the impact of 
variable spacing between fractures in an ensemble fashion. 
For transport of radionuclides reversibly attached to colloids in the SZ, it is assumed that 
equilibrium conditions exist among radionuclides sorbed onto colloids, the aqueous phase 
concentration, and those sorbed onto the aquifer material. This approach is carried forward from 
the SZ site-scale transport model (BSC 2004 [DIRS 170036], Section 6.3) and is related to the 
general assumption regarding linear, equilibrium sorption presented in Section 5. This approach 
is consistent with laboratory observations of sorption onto colloids, particularly given the time 
scales of transport in the SZ. This modeling approach is appropriate, given the broad ranges of 
uncertainty applied to parameters underlying the simulated transport of radionuclides reversibly 
attached to colloids in the SZ. 
Pumping of groundwater by the hypothetical community in which the RMEI resides is assumed 
not to alter significantly the groundwater pathways or radionuclide travel times in the SZ. 
Calibration of the SZ site-scale flow model is based on the present-day potentiometric surface 
observed in the model domain. Whereas the SZ site-scale model does not explicitly include the 
withdrawal of groundwater by pumping at the location of the hypothetical community in which 
the RMEI resides, the model does implicitly account for the drawdown of water levels associated 
with pumping at the southern boundary of the model domain. The values of specified head along 
the western part of the southern boundary reflect the lower water levels resulting from pumping 
in the Amargosa Farms region. Consequently, the model does implicitly include the influence of 
pumping in terms of increased hydraulic head gradients. 
6.3.2 SZ 1-D Transport Model 
Many components of the conceptual model for the SZ transport abstraction model also apply to 
the SZ 1-D transport model. Representation of the groundwater flow processes in the 3-D SZ 
transport abstraction model is simplified to 1-D streamtubes in the SZ 1-D transport model. 
However, characteristics of the conceptual model of groundwater flow in the SZ transport 
abstraction model are implicitly included in the SZ 1-D transport model because the average 
values of groundwater flow rate used in the SZ 1-D transport model are extracted from the three 
dimensional (3-D) flow model. The conceptual model of aquifer properties has also been 
simplified in the SZ 1-D transport model, relative to the SZ transport abstraction model. 
Material properties in the SZ 1-D transport model streamtubes are for average fractured tuff or 
for alluvium; no distinctions among volcanic hydrogeologic units are made. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-12 October 2004 
The conceptual model of radionuclide transport in the SZ 1-D transport model includes the same 
processes of advection, dispersion, matrix diffusion in fractured volcanic units, sorption, and 
colloid-facilitated transport described in the previous section. The conceptualization of 
dispersion in the SZ 1-D transport model is simplified to the extent that transverse dispersion is 
precluded in the streamtube representation of the SZ system. The conceptual model of 
radionuclide decay in the SZ 1-D transport model includes both decay and ingrowth of 
radionuclides in decay chains. 
The final radionuclide decay product in three of the radionuclide decay chains simulated in the 
1-D radionuclide transport model is calculated to be in secular equilibrium with its parent 
radionuclide (see Section 6.5.1.2). This is a reasonable approach because it simplifies the 
analysis and the final decay product-radionuclides have relatively short half-lives (less than 
25 years). This approach overestimates the concentration of decay products because it implies 
an instantaneous increase in the mass of the final decay product to be in equilibrium with the 
mass of parent radionuclide present. 
The groundwater flux within each 1-D pipe segment used in the model is assumed to be 
constant along the length of the pipe. Each pipe segment used in the model consists of 
homogenous material properties, for which the radionuclide transport process is simulated. This 
constitutes a reasonable approach because the average groundwater flux along that portion of the 
radionuclide flow path is derived from the corresponding region of the 3-D SZ transport 
abstraction model. 
6.3.3 Interfaces with the UZ and the Biosphere 
The source of radionuclides in the SZ transport abstraction model is conceptualized to be a point 
source from the UZ transport model. The location of this source is treated as uncertain and 
constant for a given realization of the system. This conceptual model is consistent with a 
contaminant source to the SZ resulting from a single leaking waste package, focused 
groundwater flow in the UZ, or the human intrusion scenario in which a borehole intersects a 
waste package and extends to the water table (CRWMS M&O 2000 [DIRS 153246], 
Section 4.4). 
The conceptual model of radionuclide releases from the SZ to the biosphere includes discharge 
of groundwater from wells to the hypothetical community in which the RMEI resides. The 
extent of the controlled area is specified in the regulations for the Yucca Mountain site (10 CFR 
63.302 (10 CFR 63 [DIRS 156605])) and the location of the hypothetical community in which 
the RMEI resides is taken to be adjacent to the controlled area. In addition, the quantity of 
groundwater in the representative volume from which contaminated water is withdrawn by the 
RMEI is specified by the regulations to be 3,000 acre-ft/year (10 CFR 63.332 (10 CFR 63 
[DIRS 156605])). The conceptualization of the SZ system is that the entire mass flux of 
radionuclides that crosses the regulatory boundary in the SZ would be contained in the 
representative volume of groundwater from which the RMEI obtains water and that these 
contaminants would be homogeneously distributed in the specified volume of groundwater. 
The interface between radionuclide transport in the UZ and the SZ is assumed to be a point 
source near the water table. This approach is physically consistent with a single leaking waste 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-13 October 2004 
package and highly focused transport of radionuclides in the UZ flow system, as can possibly 
occur early in the history of the repository. This approach is also consistent with the human 
intrusion scenario, in which a borehole penetrates a waste package and provides a direct pathway 
for radionuclide migration to the SZ. The approach of a point source for radionuclides in the 
SZ transport simulations, while not physically realistic for the situation in which multiple, 
dispersed leaking waste packages exist, provides a generally conservative approximation of the 
source term to the SZ. This approximation results in less dispersion of the radionuclide transport 
times through the SZ and thus to less attenuation of peaks in radionuclide discharge. Although 
in situ concentrations of radionuclides are not utilized in the analysis of SZ transport, a point 
source maximizes the simulated concentrations of radionuclides at the outlet to the accessible 
environment. 
The location of the point source of radionuclides for transport in the SZ site-scale flow and 
transport model is assumed to be randomly located within the four source regions defined at the 
water table (Section 6.5.2.13). This approach implies that there are no consistent spatial patterns 
of waste package failure or delivery of radionuclides at the water table within each of the four 
source regions. Many of the processes that may lead to waste package failure are spatially 
random (e.g., manufacturing defects, seepage onto waste packages, etc.). The spatial pattern of 
preferential groundwater flow pathways in the UZ flow model is represented in a general sense 
by the locations of the four source regions (e.g., the southeastern source region corresponds to 
focused vertical groundwater flow along the Ghost Dance fault). 
An assumption inherent to the convolution integral method is that the system being simulated 
exhibits a linear response to the input function. In the case of solute transport in the SZ system, 
this approach implies, for example, that a doubling of the input mass flux results in a doubling of 
the output mass flux. This approach is valid for the SZ transport abstraction model because the 
underlying transport processes (e.g., advection and sorption) are all linear with respect to solute 
mass (BSC 2004 [DIRS 170036], Section 6.4.2). The processes of colloid filtration and sorption 
are both represented as equilibrium retardation processes. Simple retardation affects the timing 
of the release of radionuclides from the SZ, but still constitutes a linear relationship between 
mass input and mass output to the SZ. 
It is assumed that all radionuclide mass crossing the regulatory boundary at approximately 18 km 
distance from the repository at the boundary of the controlled area (10 CFR 63.302 (10 CFR 63 
[DIRS 156605])) in the SZ is contained in the representative volume of groundwater, which 
serves as a source of water to the RMEI, based on 10 CFR 63.332 (10 CFR 63 [DIRS 156605]). 
This approach implies that the representative volume of groundwater is large relative to the 
volumetric flow in the plume of contaminated groundwater in the SZ. This approach is justified 
on the basis of conservatism with respect to the analysis of repository performance. The total 
mass of radionuclides released to the biosphere for a given time period cannot be larger than the 
amount of radionuclide mass delivered by groundwater flow (for the nominal case). 
6.4 CONSIDERATION OF ALTERNATIVE CONCEPTUAL MODELS 
Two significant ACMs regarding groundwater flow and radionuclide transport in the SZ have 
been considered in this report. Both of these ACMs are encompassed in the range of uncertainty 
evaluated in the SZ transport abstraction model and the SZ 1-D Transport model and are thus 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-14 October 2004 
implicitly carried forward to the TSPA-LA modeling analyses. Consequently, these ACMs need 
not be separately evaluated from the base case. Information on ACMs is summarized in Table 
6-4. The ACMs are consistent with available data and current scientific knowledge and 
appropriately consider their results and limitations. 
Table 6-4. ACMs Considered 
ACM Key Assumptions Screening Assessment and Basis 
Minimal Matrix 
Diffusion 
Diffusion of radionuclides into the pore 
space of the rock matrix in the fractured 
volcanic units is extremely limited due 
to highly channelized groundwater flow, 
fracture coatings, or other factors. 
This ACM is implicitly included in the SZ 
transport abstraction model and in the SZ 1-D 
transport model through the range of 
uncertainty in key input parameters. The 
uncertain input parameters influencing matrix 
diffusion include effective diffusion coefficient 
(DCVO), flowing interval spacing (FISVO), and 
flowing interval porosity (FPVO). 
Horizontal 
Anisotropy in 
Permeability 
Alternative interpretations of pump test 
results in the fractured volcanic units 
indicate preferential permeability along 
structural features oriented in the NNESSW 
direction or in the WNW-ESE 
direction. 
This ACM is implicitly included in the SZ 
transport abstraction model and in the SZ 1-D 
transport model through the range of 
uncertainty in an input parameter. The 
uncertain input parameter influencing horizontal 
anisotropy in permeability in the volcanic units 
near Yucca Mountain is the ratio of N-S to E-W 
permeability (HAVO, see Section 6.5.2.10). 
This continuously distributed parameter varies 
from less than one to greater than one with 
most of the realizations greater than one. 
ACM=alternative conceptual model; SZ=saturated zone 
A sensitivity analysis using the SZ transport abstraction model was conducted to show that the 
minimal matrix diffusion ACM is included within the range of parameter uncertainties 
considered. Figure 6-3 shows the solute mass breakthrough curves for a nonsorbing tracer, using 
the expected values of flow and transport parameters. The short-dashed line shows the simulated 
breakthrough curve for transport with no diffusion into the matrix of the fractured volcanic units, 
and the long-dashed line shows the breakthrough curve for maximum matrix diffusion. The 
solid line shows the simulated breakthrough curve using the 95th percentile value for flowing 
interval spacing (79.4 m) from the uncertainty distribution in this parameter. These results 
indicate that the breakthrough curve using the 95th percentile value of flowing interval spacing is 
very near the bounding case of no matrix diffusion. Similarly, low values of effective diffusion 
coefficient and low values of flowing interval porosity would produce breakthrough curves 
tending toward the no-matrix-diffusion case. This sensitivity analysis demonstrates that the 
minimal matrix diffusion ACM is captured within the range of uncertainty used in the model. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-15 October 2004 
10 100 1000 10000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: The case of no matrix diffusion is shown with the short-dashed line. The case of maximum matrix diffusion 
is shown with the long-dashed line. The case for which flowing interval spacing is set to its 95th percentile 
value (79.4 m) is shown with the solid line. Mass breakthrough curves are for present climate and do not 
include radionuclide decay. 
Figure 6-3. Mass Breakthrough Curves at 18-km Distance Showing Sensitivity to Matrix Diffusion for a 
Non-Sorbing Radionuclide 
The incorporation of the horizontal anisotropy ACM into the SZ transport abstraction model is 
inherent in the range of parameter values used for the parameter HAVO in the analyses. 
A complete discussion of uncertainty in horizontal anisotropy of permeability and the basis for 
the uncertainty distribution are provided in the Saturated Zone In Situ Testing scientific analysis 
report (BSC 2004 [DIRS 170010], Section 6.2.6). The uncertainty distribution for HAVO 
indicates that there is a 10 percent probability that the direction of maximum horizontal 
permeability is east-west with a ratio between 1 and 20. The uncertainty distribution also 
indicates that there is a 90 percent probability that the direction of maximum horizontal 
permeability is north-south with a ratio between 1 and 20. The isotropic case, corresponding to a 
horizontal permeability ratio of one, is included in this continuous uncertainty distribution for the 
parameter HAVO. 
6.5 MODEL FORMULATION FOR BASE-CASE MODELS 
SZ Transport Abstraction Model 
The SZ site-scale flow model (BSC 2004 [DIRS 170037]) and the SZ site-scale transport model 
(BSC 2004 [DIRS 170036]) form the bases for the SZ transport abstraction model. The 
progression in the development of models is from the SZ site-scale flow model to the SZ 
site-scale transport model to the SZ transport abstraction model. The SZ site-scale flow model 
includes the implementation of the hydrogeologic framework, the numerical grid, and the 
boundary conditions for steady-state groundwater flow. The SZ site-scale flow model is 
calibrated to water-level measurements in wells and estimates of groundwater flow rates at the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-16 October 2004 
lateral boundaries. The SZ site-scale transport model begins with the SZ site-scale flow model 
and adds the model input files required for the simulation of radionuclide transport using the 
particle-tracking method. A set of representative parameter values for radionuclide transport is 
included in the SZ site-scale transport model and the range of behavior associated with parameter 
uncertainty is examined. Finally, the SZ transport abstraction model begins with the SZ 
site-scale transport model and adds the capability to perform probabilistic uncertainty analyses 
using multiple Monte Carlo realizations of the SZ flow and transport system. The resulting 
radionuclide breakthrough curves are then used in the convolution integral method to couple the 
SZ transport abstraction model with the TSPA-LA model. 
The SZ site-scale flow model, the SZ site-scale transport model, and the SZ transport abstraction 
model share a common model domain, hydrogeologic framework, numerical grid, and 
groundwater flow boundary conditions. The model domain is shown in Figure 6-4 with the blue 
dashed line overlain on a shaded relief map of the surface topography. The nodes that constitute 
the model grid form an orthogonal mesh with 500-m spacing in the north-south and east-west 
directions. The repository outline is shown with the bold blue line and the nodes that occur 
along the regulatory boundary of the accessible environment are shown as overlapping red 
crosses. 
The groundwater flow boundary conditions for the SZ site-scale flow model, the SZ site-scale 
transport model, and the SZ transport abstraction model are specified head at the lateral 
boundaries and specified groundwater flux for recharge at the upper boundary. These boundary 
conditions are described in detail in Site-Scale Saturated Zone Flow Model (BSC 2004 
[DIRS 170037], Section 6.3.2) and are the same for all three models with the following 
exception: for the SZ transport abstraction model, the specified flux for recharge is scaled in 
proportion to the uncertainty in groundwater specific discharge (see Section 6.5.2.1). Scaling the 
recharge flux and the values of permeability in proportion to the groundwater specific discharge 
uncertainty factor maintains the calibration of the flow model with regard to water-level 
measurements. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-17 October 2004 
530000 535000 540000 545000 550000 555000 560000 565000 
UTM Easting (m) 
4045000 
4050000 
4055000 
4060000 
4065000 
4070000 
4075000 
4080000 
4085000 
4090000 
UTM Northing (m) 
Source: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]). 
NOTE: The dashed blue line indicates the boundaries of the SZ transport abstraction model, the solid blue line 
shows the outline of the repository, and the red crosses indicate the boundary to the accessible 
environment for radionuclide transport in the SZ. 
Figure 6-4. Model Domain of the SZ Site-Scale Flow Model, SZ Site-Scale Transport Model, and the SZ 
Transport Abstraction Model 
Radionuclide transport is simulated in the SZ transport abstraction model using a particle 
tracking method. This method, as implemented by the FEHM (finite element heat and mass 
model) V2.20 software code (FEHM V2.20 STN: 10086-2.20-00 [DIRS 161725]), simulates 
advection along groundwater streamlines, random-walk dispersion, retardation due to sorption, 
and matrix diffusion. Each simulation uses 500 particles, which results in a continuous, 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-18 October 2004 
generally smooth cumulative mass breakthrough curve at the boundary of the accessible 
environment. The time-step size that determines output intervals varies from 10 years to 
100 years, depending on the radionuclide. Internally, the simulation uses local flow conditions 
to determine time steps for dispersion and matrix diffusion calculations. This internal time step 
is controlled such that the particles take approximately 20 internal time steps to traverse each cell 
in the model. 
The convolution integral method used in the SZ transport abstraction model for the TSPA-LA 
analyses provides an approximation of the transient radionuclide mass flux at a specific point 
downgradient in the SZ in response to the transient radionuclide mass flux from transport in the 
UZ. This coupling method makes full use of detailed SZ flow and transport simulations for a 
given realization of the system, without requiring complete numerical simulation of the SZ for 
the duration of each TSPA-LA realization. The two input functions to the convolution integral 
method are: 
1) a unit radionuclide mass breakthrough curve in response to a step-function mass flux 
source as simulated by the SZ transport abstraction model. 
2) the radionuclide mass flux history as simulated for transport in the UZ. The output 
function is the radionuclide mass flux history downgradient in the SZ. 
There are several important assumptions in the use of the convolution integral method. 
Groundwater flow in the SZ is assumed to be steady state. The transport processes in the SZ 
must be linear with respect to the solute source term (i.e., a doubling of the solute mass source 
results in a doubling of mass flux). In addition, the flow and transport processes in the UZ and 
the SZ must be independent of one another. 
Radioactive decay is also applied to radionuclide mass flux calculated with the convolution 
integral computer code SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 
[DIRS 164180]) in the TSPA-LA analyses. The convolution integral method consists of 
numerical integration that accounts for the contributions to the outlet radionuclide mass flux 
from a series of time intervals. Because the travel time for each contribution to radionuclide 
mass flux is known, the loss of radionuclide mass (and consequent decrease in mass flux) during 
transport is calculated by first-order decay for that time interval. 
The effects of climate change on radionuclide transport in the SZ are incorporated into the 
convolution integral analysis in the TSPA-LA by assuming instantaneous change from one 
steady-state flow condition to another steady-state condition in the SZ. A description of the 
mathematical and numerical implementation of multiple steady-state flow conditions is given in 
DOE 2003 [DIRS 167588], Equation 3. Changes in climate state are assumed to affect the 
magnitude of groundwater flux through the SZ system but have a negligible impact on flow 
paths. The effect of changes in groundwater flux is incorporated into the convolution method by 
scaling the timing of radionuclide mass breakthrough curves proportionally to the change in 
SZ-specific discharge. 
For the base-case TSPA-LA analyses, present-day climatic conditions are modeled to occur from 
the time of repository closure and to be followed by monsoonal conditions and glacial-transition 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-19 October 2004 
climatic conditions. The monsoonal climatic state is wetter than present-day conditions and the 
glacial-transition state is conceptualized to be wetter and cooler than present-day conditions 
(BSC 2004 [DIRS 170002]). Note that the glacial-transition climate state is approximately 
equivalent to the long-term average climate state, as referenced in Total System Performance 
Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis Document (CRWMS 
M&O 1998 [DIRS 100365], Table 8-16, p. T8-20). 
Estimates of the scaling factors for groundwater flux in the SZ under alternative climatic 
conditions are based on simulations using the Death Valley regional flow model 
(DAgnese et al., 1999 [DIRS 120425]; CRWMS M&O 1998 [DIRS 100365]) and on the 
infiltration for the UZ site-scale flow model (BSC 2004 [DIRS 169861], Section 6.1.4). 
Simulations using the Death Valley regional flow model were conducted for the past-climate 
state that likely existed about 21,000 years ago (DAgnese et al., 1999 [DIRS 120425]). This 
climatic state approximately corresponds to the glacial-transition state, as defined for TSPA-LA 
calculations. A comparison of the groundwater flux in the SZ near Yucca Mountain under pastclimate 
conditions (i.e., 21,000 years ago) using the Death Valley regional flow model indicates 
that the simulated flux under the past-climate conditions was approximately 3.9 times the flux of 
present-day simulations, as shown in Table 6-5. 
Simulations of SZ flow under monsoonal climatic conditions have not been performed using the 
Death Valley regional flow model. Information on the increased infiltration through the UZ 
site-scale flow model is used as the basis for estimating flux increases in the SZ for monsoonal 
conditions (DTN: LB03023DSSCP9I.001 [DIRS 163044]) (see also UZ Flow Models and 
Submodels (BSC 2004 [DIRS 169861], Table 6.1-2)). Values of average infiltration in the 
model domain of the UZ site-scale flow model (second column of Table 6-5) are taken from the 
GENER card of the TOUGH2 input files preq_mA.dat, glaq_mA.dat, and 
monq_mA.dat. This value of average infiltration is the mean groundwater flux at the upper 
boundary of the UZ site-scale flow model, as stated in the three input files named above. 
Similarly, the total infiltration through the UZ site-scale flow model for present and glacialtransition 
climatic conditions is calculated (DTN: LB03023DSSCP9I.001 [DIRS 163044]). 
Note in Table 6-5 that the ratio of glacial-transition infiltration in the UZ model to the presentday 
infiltration (a factor of 3.8) is approximately the same value as the estimate of increased SZ 
groundwater flux from the Death Valley regional flow model (i.e., 3.9). This correspondence 
suggests that the UZ infiltration ratio provides a reasonable estimate of the flux ratio for the SZ. 
Thus, the values of the SZ groundwater flux ratio for TSPA-LA simulations of future climatic 
states are derived from the estimates of increased UZ infiltration at Yucca Mountain. For 
monsoonal climatic conditions, the ratio of UZ infiltration to the infiltration for present-day 
conditions is 2.7 (see Table 6-5) and this value is applied to the SZ flux as well. The values of 
flux ratio used as scaling factors of SZ flow and transport for alternative climate states are given 
in the last column of Table 6-5. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-20 October 2004 
Table 6-5. Groundwater Flow Scaling Factors for Climate Change 
Climate State 
Average 
Infiltration, 
UZ Model 
(Mean Case) 
(mm/year) a 
Ratio to 
Present 
Climate, 
UZ Model 
SZ Groundwater 
Flux Ratio 
from 
Death Valley Regional 
Flow Model 
SZ Groundwater 
Flux Ratio 
for 
TSPA-LA 
Simulations 
Present-Day 4.43 1.0 1.0 1.0 
Glacial- 
Transition 17.0 3.8 3.9 b 3.9 
Monsoonal 11.8 2.7 N/A 2.7 
a Source: DTN: LB03023DSSCP9I.001 [DIRS 163044]. 
b Total System Performance Assessment-Viability Assessment (TSPA-VA) Analyses Technical Basis 
Document (CRWMS M&O 1998 [DIRS 100365], Table 8-16, p. T8-20). 
SZ 1-D Transport Model 
The SZ 1-D transport model is a simplified model of radionuclide transport for the purpose of 
simulating decay chains and is implemented with the GoldSim V7.50.100 software code in the 
TSPA-LA simulator as a series of pipes. The same radionuclide transport processes that are 
simulated in the 3-D SZ transport abstraction model (e.g., sorption, matrix diffusion in fractured 
units, and colloid-facilitated transport) are analyzed in the pipe segments, with the exception of 
transverse dispersion. Transverse dispersion is not very important to the modeling results, given 
the assumption that all radionuclide mass is captured by the wells of the receptor group. 
Although strict consistency between the SZ 1-D transport model and the 3-D SZ transport 
abstraction model is not possible, average groundwater flow and transport characteristics of the 
SZ transport abstraction model are used to define flow and transport properties within the pipe 
segments of the 1-D model. Average specific discharge along different segments of the flow 
path is estimated using the 3-D SZ transport abstraction model. The resulting values of average 
specific discharge are applied to the individual pipe segments in the 1-D transport model. 
6.5.1 Mathematical Description of Base-Case Conceptual Model 
6.5.1.1 SZ Transport Abstraction Model 
The mathematical descriptions of the processes of groundwater flow and radionuclide transport 
in the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.5) and the SZ site-scale 
transport model (BSC 2004 [DIRS 170036], Section 6.4.2) are presented in the corresponding 
reports for these models. The SZ site-scale flow model forms the direct basis for the SZ 
site-scale transport model, which forms the direct basis for the SZ transport abstraction model. 
Therefore, the mathematical bases for those models, as implemented by the FEHM V2.20 
software code [DIRS 161725], apply to the SZ transport abstraction model and are not 
reproduced here. 
The particle tracking method is used to simulate radionuclide transport in the SZ transport 
abstraction model (see Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036], 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-21 October 2004 
Section 6.4.2) for a description of the particle tracking method). This method exhibits very 
limited numerical dispersion relative to standard finite-difference and finite-element methods of 
solute transport simulation. Consequently, particle tracking is appropriate for use in the SZ 
transport abstraction model, in which the spatial discretization (500 m) exceeds the values of 
dispersivity being simulated for many of the model realizations. 
Convolution Integral 
The convolution integral method is used to couple the radionuclide transport in the UZ with the 
simulations of mass transport in the SZ in the TSPA-LA analyses. The convolution integral 
method takes the radionuclide mass breakthrough curve for a continuous, unitary mass source 
(step function input of mass) from the SZ and the time-varying radionuclide mass from the UZ as 
inputs. The output is the time-varying radionuclide mass exiting the SZ. 
The mathematical expression for the convolution integral method is written as: 
. ' 
' 
' - = 
t 
p 
sz 
uz sz t d 
m 
t M t t m t M 
0 
) ( 
) ( ) ( & (Eq. 6-1) 
where 
Msz(t) = radionuclide mass flux downstream in the SZ [M] 
t = time [T], 
) (t mUZ & = time dependent radionuclide mass flux entering the SZ from the UZ [M] 
t' = time lag [T] 
) (t M ' = derivative of the downstream radionuclide mass flux-time response curve [M] to a 
step input of mass mp [M] 
Note that symbols in brackets are generalized dimensions with T denoting time and M denoting 
mass. 
This expression is taken from the convolution integral for concentration (CRWMS M&O 1998 
[DIRS 100365], p. 8-39) and rewritten in terms of radionuclide mass. A description of the 
mathematical implementation of multiple steady-state flow conditions for alternative climate 
states is given in DOE 2003 [DIRS 167588], Equation 3. 
Correction of Retardation 
The retardation factor for linear sorption of radionuclides during transport in porous media is 
defined (Freeze and Cherry 1979 [DIRS 101173], p. 404) as: 
d 
b 
f K R 
f 
. 
+ = 1 (Eq. 6-2) 
where Rf is the retardation factor in the porous media [-] (the symbol - denotes a dimensionless 
parameter), .b 
is the bulk density [M/L3], f is the porosity of the porous media [-], and Kd is the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-22 October 2004 
distribution coefficient [L3/M]. The FEHM V2.20 software code [DIRS 161725] to be used in 
the SZ transport abstraction model automatically calculates Rf based on input values of .b 
, f, and 
Kd. 
Effective porosity ( fe 
) [-] is a macroscopic parameter that helps account for discrete flow paths 
and channelized flow in the porous medium of the alluvium (see Section 6.5.2.3). The effective 
porosity is defined as the fraction of the total volume of the medium through which significant 
groundwater flow occurs. The effective porosity parameter in the alluvium is used to correctly 
calculate the pore velocity of groundwater. Effective porosity is not intended to be used to 
estimate surface areas in Equation 6-2. Therefore, it is necessary to adjust another parameter in 
the equation to compensate for the lower effective porosity that is entered. If this were not done, 
then the calculated values of Rf would be overestimated, given that values of Kd used in Equation 
6-2 are based on laboratory-scale measurements. For the SZ transport abstraction model and the 
SZ 1-D transport model, the Kd values for the alluvium are adjusted according to the following 
relationship (CRWMS M&O 1998 [DIRS 100365], Equation 8-4, p. 8-55): 
T
e 
d 
new 
d K K 
f
f 
 = (Eq. 6-3) 
where Kd
new is the adjusted distribution coefficient [L3/M] and fT is the total porosity [-]. The 
total porosity is 0.30, which is the upper bound of the effective porosity uncertainty distribution 
and also documented in Section 6.5.2.14. 
Colloid-Facilitated Transport 
For colloid-facilitated radionuclide transport in which radionuclides are reversibly attached to 
colloids, a partition coefficient is defined to represent the potential for enhanced migration of 
radionuclides in association with colloids. This unitless constant, Kc, is defined as: 
coll 
coll 
d c C K K = (Eq. 6-4) 
where Kd
coll is the sorption coefficient for the radionuclide onto colloids [L3/M] and Ccoll is the 
concentration of colloids in the groundwater [M/L3]. The conceptual model of colloid-facilitated 
transport of reversibly sorbed radionuclides is described in Section 6.3, and the underlying 
theoretical derivation of the model is presented in The Site-Scale Unsaturated Zone Transport 
Model of Yucca Mountain (CRWMS M&O 1997 [DIRS 124052], pp. 8-32 to 8-36). 
For equilibrium conditions in a porous medium, the effective sorptive capacity of the aquifer is 
reduced when the groundwater colloids carry a significant fraction of radionuclide mass in the 
system. The values of the sorption coefficient in the alluvium and undifferentiated valley fill 
hydrogeologic units for the colloid-facilitated transport of radionuclides with the Kc model are 
modified by the value of Kc, according to the relationship: 
) 1 ( c 
new 
d adjusted 
d K 
K K 
+ 
= (Eq. 6-5) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-23 October 2004 
as derived from Equation 6-2 and Total System Performance Assessment-Viability Assessment 
(TSPA-VA) Analyses Technical Basis Document (CRWMS M&O 1998 [DIRS 100365], 
Equation 8-8, pp. 8-54 and 8-56), and assigning the retardation factor for colloids with reversibly 
attached radionuclides a value of one. Kd
adjusted is the adjusted distribution coefficient [L3/M] to 
account for reversible sorption onto colloids. 
For transport in fractured media, the effective diffusion coefficient into the rock matrix is 
reduced due to the affinity of radionuclides for sorption onto colloids in the fractures. To 
evaluate this effect with constant velocity and dispersion, consider the 1-D advection-dispersion 
equation for a solute in the fractures (BSC 2004 [DIRS 170036], Section 6.4.2) with a term for 
retardation and a final term added for diffusion into the matrix: 
b
q 
x
C v 
x
C D 
t 
C R f f - 
. 
. 
- 
. 
. 
= 
. 
. 
2 
2 
, (Eq. 6-6) 
where f f R , is the retardation factor in the fractures [-], D is the dispersion coefficient in the 
fracture [L2/T], C is aqueous concentration of the solute [M/L3], t is time [T], x is distance [L], 
v is groundwater velocity in the fractures [L/T], q is the diffusive flux into the rock matrix 
[M/L2T], and b is the half-aperture of the fracture [L]. For that part of the solute mass that is 
sorbed onto colloids the advection-dispersion equation is: 
x 
C v 
x 
C D 
t 
C R 
coll coll coll 
col . 
. - 
. 
. = 
. 
. 
2 
2 
(Eq. 6-7) 
where Rcol is the retardation factor of the colloids in the fractures [-] and coll C is the concentration 
of the solute in the groundwater [M/L3]. Adding the two advection dispersion equations and 
using the relationship that Kc = coll C /C, the combined advection-dispersion equation for 
colloid-facilitated transport of radionuclides reversibly sorbed onto colloids can be written as: 
) 1 ( 1 2 
2 
, 
c c 
col c f f 
K b 
q 
x
C v 
x
C D 
t 
C 
K 
R K R 
+ 
- 
. 
. - 
. 
. = 
. 
. 
. 
. 
. . 
. 
. 
+ 
+ 
(Eq. 6-8) 
As seen by comparing this equation with Equation 6-6, the term for diffusive mass flux into the 
rock matrix is modified by dividing by the factor (1 + Kc) to account for the equilibrium 
colloid-facilitated transport. One approach would be to adjust the value of fracture half-aperture 
by multiplying by the factor (1 + Kc). An alternative approach is possible based on examination 
of the . term in the analytical solution for transport in fractures with matrix diffusion by 
Sudicky and Frind (1982 [DIRS 105043], Equation 34, p. 1638). In the . term, adjusting the 
value of b by multiplying it by the factor (1 + Kc) is equivalent to dividing the effective diffusion 
coefficient in the matrix by the factor (1 + Kc)2. In the SZ transport abstraction model and the SZ 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-24 October 2004 
1-D transport model, the values of effective diffusion coefficient for radionuclides subject to the 
Kc model of colloid-facilitated transport are adjusted according to the relationship: 
2 ) 1 ( c 
e adjusted 
e K 
D D 
+ 
= (Eq. 6-9) 
where De
adjusted is the adjusted effective diffusion coefficient in the rock matrix [L2/T], and De is 
the effective diffusion coefficient in the rock matrix [L2/T]. It should be noted that this approach 
to adjusting the effective diffusion coefficient to account for colloid-facilitated transport in 
fractured media is not exact. The s term of the Sudicky and Frind analytical solution also 
contains the variable b and the adjustment to the effective diffusion coefficient does not scale the 
variable b in the same manner as in the . term. However, the variable b is a minor contributor 
in the expression for the s term (i.e., value of b is much smaller than the value of B, which is the 
half fracture spacing). In addition, the adjusted diffusion coefficient, as applied in the s term, is 
equivalent to increasing the value of B and a higher value of B underestimates the mass transfer 
to the matrix and overestimates the rate of migration of radionuclides through the SZ. The 
approach of adjusting the effective diffusion coefficient is thus an acceptable approximation for 
use in the SZ transport simulations. 
For colloid-facilitated radionuclide transport in which radionuclides are irreversibly attached to 
colloids, most of the colloids (and attached radionuclides) are delayed during transport in the SZ 
by a retardation factor. A small fraction of colloids with irreversibly attached radionuclides is 
subject to rapid transport without retardation, as described in Saturated Zone Colloid Transport 
(BSC 2004 [DIRS 170006], Section 6.6). In fractured volcanic units, the retardation factor for 
the majority of colloids is applied directly in the SZ transport abstraction model input files as an 
input parameter. In porous media, it is not possible to directly specify a retardation factor in the 
SZ transport abstraction model; therefore, an effective sorption coefficient is specified that 
results in the sampled value of the retardation factor. In the porous medium of the alluvium, the 
colloid retardation factor in the alluvium units is converted to a value of effective sorption 
coefficient according to the relationship: 
b 
e f eff 
d 
R 
K 
. 
f ) 1 ( - 
= (Eq. 6-10) 
where Kd
eff is the effective Kd in the porous media [L3/M]. 
Retardation in Fracture Zones 
As described in the conceptual model of transport in fractured media of the SZ (Section 6.3.1), 
relatively small blocks of rock matrix or rubblized material in fracture zones may participate in 
radionuclide transport via diffusion on a short time scale. The impact of rapid diffusion into 
small matrix blocks on the calculation of average linear velocity of groundwater is captured with 
a correspondingly larger value of flowing interval porosity for the volcanic units. In this 
conceptualization, the flowing interval porosity includes the fracture porosity with flowing 
groundwater plus it may include the matrix porosity of the small matrix blocks within the 
fracture zones. The possibility of small matrix blocks within fracture zones is encompassed 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-25 October 2004 
within a range of uncertainty in transport behavior in fractured tuff. If this process of rapid 
diffusion occurs, the sorptive capacity of the small matrix blocks would also be important to the 
transport of sorbing radionuclides. This is handled in the following way: if the flowing interval 
porosity ( ff 
) [-] is less than the average fracture porosity ( avg 
f f) [-], then groundwater flow is 
conceptualized to occur only in fractures, and no retardation due to sorption within small matrix 
blocks occurs. If the flowing interval porosity is greater than the average fracture porosity, then 
the portion of the flowing interval porosity in excess of the average fracture porosity corresponds 
to the matrix porosity of the small matrix blocks within the fracture zones. If the flowing 
interval porosity is greater than the average fracture porosity, then the retardation factor within 
the fracture domain due to sorption within small matrix blocks ( f R' ) is calculated as: 
m 
dm b 
f 
K fraction 
R 
f 
. ) * ( 
1+ = ' (Eq. 6-11) 
where Kdm is the sorption coefficient in the rock matrix [L3/M], fm is the rock matrix 
porosity [-], and fraction is calculated as: 
) ( 
) ( 
avg 
f m 
avg 
f f fraction 
f f 
f f 
-
- 
= (Eq. 6-12) 
The term fraction [-] describes the fraction of the entire rock matrix that is accessible to rapid 
matrix diffusion within the small matrix blocks of the fracture zone. Typically, the value of 
fraction would be small for the range of uncertainty in flowing interval porosity. For example, if 
the flowing interval porosity is 0.01 (80th percentile from Figure 6-13), the rock matrix porosity 
is 0.20, and the average fracture porosity is 0.001, then the value of fraction is 0.045. This 
means that 4.5 percent of the total rock matrix is available for direct interaction with radionuclide 
advection and sorption. 
6.5.1.2 SZ 1-D Transport Model 
The SZ 1-D transport model provides simulation results for several radionuclide chains that are 
not simulated in the SZ transport abstraction model. The simplified decay chains considered 
(CRWMS M&O 2000 [DIRS 153246], Figure 3.5-5, p. F3-67) consist of the following. 
1. Actinium series: 
Pa U Pu Am 231 235 239 243 . . . 
2. Neptunium Series: 
Th U Np Am 229 233 237 241 . . . 
3. Thorium Series: 
Th U Pu 232 236 240 . . 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-26 October 2004 
4. Uranium Series: 
Ra Th U 
Pu 
U Pu 226 230 234 
238 
238 242 
. . . 
. . .
. 
The radionuclide decay chain analysis is simplified in a manner that overestimates the 
concentration of decay product-radionuclides by calculating secular equilibrium between the 
final decay products and their parents in three of these chains. 227Ac is in secular equilibrium 
with 231Pa in the actinium chain at the downstream end of the SZ analysis. Radium-228 is in 
secular equilibrium with 232Th in the thorium series. Lead-210 is in secular equilibrium with 
226Ra in the uranium series. The mass of the final daughter in the neptunium series is explicitly 
simulated. In the model setup, radioisotopes of Am and Pu are subject to transport as 
irreversibly attached to colloids; and radioisotopes of Am, Pu, Th, Pa, and Cs are subject to the 
equilibrium colloid-facilitated transport mode. The 1-D model is set up using the Pathway 
Component of the Contaminant Transport Module in the GoldSim Graphical Simulation 
Environment. The pipe component is able to simulate advection, longitudinal dispersion, 
retardation, decay and ingrowth, and matrix diffusion (Figure 6-5) (Miller and Kossik 1998 
[DIRS 100449]). 
Sources: GoldSim V7.50.100; figure from Miller and Kossik 1998 [DIRS 100449]. 
Figure 6-5. Transport Processes Simulated in 1-D Pipe Pathways in the GoldSim V7.50.100 
Software Code 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-27 October 2004 
Each pipe in the GoldSim V7.50.100 software code represents a 1-D mass transport model with 
uniform properties, as illustrated conceptually in Figure 6-5. The ratio of the volumetric outflow 
rate to the cross-sectional area of each pipe pathway represents the specific discharge in the pipe. 
A mass flux loading at the beginning of the first pipe is the source of the radionuclides that are 
transported along the connected pipes. The GoldSim V7.50.100 software code also provides a 
graphical container that isolates all of the model components in one compartment, to better 
organize the model components graphically on screen. 
Transport from the four source regions in the SZ is represented by four sets of connected pipes in 
the SZ 1-D transport model. Each set of pipes consists of three pipe segments. The first segment 
extends from the center of the corresponding source region beneath the repository to a distance 
of 5 km. The second pipe segment extends from 5 km to the contact between the volcanic 
aquifer and the alluvium. The third pipe segment extends from the contact between the volcanic 
aquifer and the alluvium to the regulatory boundary with the accessible environment. 
The mathematical representation of radionuclide transport in the SZ 1-D transport model is the 
same as that in the SZ transport abstraction model, as presented in Equation 6-2 to Equation 6-5 
and Equation 6-9. There are some differences in the mathematical implementation between the 
models with regard to retardation in fractures, as described below. 
In the SZ 1-D transport model the retardation factor in fractures cannot be directly specified. 
The retardation in fractures for colloids with irreversibly attached radionuclides is calculated 
according to the retardation factor (CORVO) of the colloids using the fracture coating option in 
the GoldSim V7.50.100 software code. The equation for calculating the retardation factor in the 
fracture with the coating on the fracture surface is: 
) ( 1 , , c s c c 
p m 
s m K 
A
PT R f . 
f 
+ + = (Eq. 6-13) 
where Rm,s is the retardation factor due to the coating [-], P is the perimeter of the fracture 
pathway [L], T is the thickness of the coating [L], Am is the cross-sectional area of the mobile 
zone [L2], p f is the porosity in the pipe (equal to 1.0 for fractures) [-], .c 
is the dry bulk density 
of the coating material [M/L3], Kc,s is the sorption coefficient of the coating [L3/M], and c f is the 
porosity of the coating material [-]. For a given value of Rm,s, the sorption coefficient is specified 
by rearranging Equation 6-13: 
( ) .. 
. 
.. 
. 
- - = c s m 
p m 
c 
s c R 
PT 
A 
K f 
f 
. 
1 1 
, , (Eq. 6-14) 
It should be noted that representation of retardation in the fractures using the coating option in 
the GoldSim V7.50.100 software code is for mathematical convenience only. The retardation 
factor for colloids with irreversibly attached radionuclides is specified as an input parameter in 
the SZ 1-D transport model, and a corresponding value of the sorption coefficient of the fracture 
coating is calculated using Equation 6-14 within the parameter definitions used in the model. 
This does not constitute an inconsistency in the conceptual model between the SZ 1-D transport 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-28 October 2004 
model and the SZ transport abstraction model. The values of the parameters T (0.0001 m) and 
c f (0.01) are chosen to be realistic, but are essentially irrelevant because they are only used to 
back-calculate the value of Kc,s. The value of the fracture perimeter is 2 m because the cross 
section of the pipes in the SZ 1-D transport model is specified as 1 m by 1m, and a single 
fracture within the pipe would have a corresponding perimeter of 2 m. 
There is no matrix diffusion in fractured media for colloids with irreversibly attached 
radionuclides. Consequently, there is no sorption in the matrix for radionuclides irreversibly 
attached to colloids. This is simulated by specifying an arbitrarily small value of matrix porosity 
(approximately 10-10) and zero sorption coefficients for these species in the volcanic matrix. The 
matrix diffusion coefficient for those radionuclides that do experience matrix diffusion is 
implemented by calculating an effective tortuosity, based on the sampled value of effective 
diffusion coefficient and the free water diffusion coefficient. The free water diffusion coefficient 
is adjusted by a factor approximately equivalent to the volcanic matrix porosity, using the 
parameter Adjusted_Diffusion_Free to match results from the 3-D SZ site-scale transport 
model. 
Values of specific discharge for segments represented by pipe pathways in the SZ 1-D transport 
model vary along the flow path from the repository. A plot of the particle paths in the SZ 
transport abstraction model indicates that the flow path length through the alluvium varies, 
depending on uncertainty in the SZ flow field (see Figure 6-6). This uncertainty is represented 
by variation in the geometry of the alluvial uncertainty zone in the SZ transport abstraction 
model. Specifically, the lengths of the flow paths in the volcanic units and the alluvium are 
functions of the western boundary of the alluvial uncertainty zone (as controlled by the FPLAW 
stochastic parameter). Secondarily, this variability is the result of different flow paths 
(i.e., width of the plume). The lengths of the flow paths are also functions of the anisotropy ratio 
in horizontal permeability of the volcanic units (as controlled by the HAVO stochastic 
parameter) (see Figure 6-6). In the 1-D radionuclide transport model, the length of the alluvium 
(out to an 18-km distance) is varied from 2 km to 10 km as functions of the FPLAW and HAVO 
parameter values and the source region beneath the repository (see Table 6-7 and 
supporting text). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-29 October 2004 
535000 540000 545000 550000 555000 560000 
UTM Easting (m) 
4050000 
4055000 
4060000 
4065000 
4070000 
4075000 
4080000 
4085000 
4090000 
UTM Northing (m) 
Source: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]). 
NOTE: Green lines, purple lines, blue lines, yellow lines, and red lines show simulated particle paths for horizontal 
anisotropy values of 0.05, 0.20, 1.0, 5.0, and 20.0, respectively. 
Figure 6-6. Simulated Particle Paths for Different Values of Horizontal Anisotropy in Permeability 
The SZ 1-D transport model represents a significant simplification of the 3-D groundwater flow 
system, relative to the SZ transport abstraction model. To accurately capture the 3-D 
characteristics of the SZ flow and transport system in this 1-D model, the SZ 1-D transport 
model is divided into three sets of pipe segments. The lengths and groundwater flow rates of 
these pipe segments are estimated from the SZ transport abstraction model. 
Average specific discharge along different segments of the flow path is estimated using the 
SZ transport abstraction model in the following way: 1,000 particles are released from a point 
beneath the repository (as shown in Figure 6-6) in the simulation, matrix diffusion is not used, 
and all porosities are assigned a value of 1.0 for the assessment of average specific discharge. 
The average specific discharge is calculated by dividing the flow path length by the 
50th percentile of travel times among the particles, for that flow path segment. The average 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-30 October 2004 
specific discharge also varies as a function of the horizontal anisotropy (parameter HAVO). The 
resulting values of average specific discharge, as used in the SZ 1-D transport model, are shown 
in Table 6-6. The values in Table 6-6 are input as a GoldSim V7.50.100 software code look-up 
table in the SZ 1-D transport model. Note that the values of specific discharge scale linearly 
with the groundwater specific discharge-scaling factor (parameter GWSPD) for the consideration 
of uncertainty in specific discharge. The values of specific discharge within the three pipe 
segments are calculated within the model by interpolating between the values of HAVO and 
scaling by the value of GWSPD. The volumetric flow rate is the same for all segments in the SZ 
1-D transport model, and the variations in specific discharge along the flow path are incorporated 
by varying the cross-sectional areas of the pipe segments. 
Table 6-6. Average Specific Discharge in Flow Path Segments 
HAVO Average Specific Discharge (m/year) 
0-5 km 5-13 km 13-18 km 
0.05 0.312 7.50 1.936 
1.00 0.536 1.824 2.357 
5.00 0.722 2.694 2.793 
20.00 0.870 4.465 3.183 
The impacts of different climate states are implemented in the SZ 1-D transport model in a 
manner similar to the SZ transport abstraction model. The specific discharge within all pipe 
segments of the SZ 1-D transport model is scaled by the groundwater flow factors given in 
Table 6-5 for the monsoonal and glacial-transition climate states. Application of this scaling 
begins at the time of climate change. However, an important limitation of the Laplace transform 
solution used for radionuclide transport simulation within the pipe segments in the SZ 1-D 
transport model should be noted. Radionuclide mass already within a given pipe segment of the 
SZ 1-D transport model does not increase in velocity in response to increased specific discharge 
resulting from climate change. Radionuclide mass introduced after the change in specific 
discharge is transported at the proper, correspondingly faster rate. The impacts of this limitation 
to calculations of peak dose in the TSPA-LA model are not large due to the following 
considerations: the SZ 1-D transport model results are used only for the daughter products of the 
decay chains in the TSPA-LA calculations and these daughter products are only minor 
contributors to total simulated dose. This limitation applies only to radionuclide mass that enters 
a given pipe segment prior to 2,000 years, after which glacial-transition climatic conditions 
continue unchanged. In addition, only radionuclide mass that enters the SZ 1-D transport model 
prior to 600 years, at the time of change from present to monsoonal conditions, would experience 
this limitation to a large extent. Finally, this limitation applies only to an individual pipe 
segment, and the entire SZ 1-D transport model is composed of three pipe segments. This 
computational limitation thus applies only to a part of the total transport pathway in the SZ for 
any given unit of radionuclide mass. 
The flow path length of each pipe segment in the SZ 1-D transport model varies as a function of 
FPLAW, HAVO, and the source region from which the radionuclide source originates beneath 
the repository. The first pipe segment is 5 km in length for all cases. The second pipe segment 
represents that portion of the flow path from the 5-km distance to the contact between the 
volcanic units and the alluvium in the SZ. The third pipe segment represents the portion of the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-31 October 2004 
flow path from the contact between the volcanic units and the alluvium out to the regulatory 
boundary to the accessible environment. The lengths of the second and third pipe segments were 
estimated from the particle tracking results of the 3-D SZ transport abstraction model, as shown 
in Figure 6-6 and as summarized in Table 6-7. The estimated pipe segment lengths are shown in 
Table 6-7 for differing values of HAVO and for the four source regions. Each entry in the table 
contains a range of values in length, where the minimum value shown for the 5-to-13-km pipe 
segment (second pipe segment) corresponds to FPLAW equal to 1.0 and the maximum value 
corresponds to FPLAW equal to 0.0. By contrast, the minimum value of length for the 
13-to-18-km pipe segment (third pipe segment) corresponds to FPLAW equal to 0.0 and the 
maximum value corresponds to FPLAW equal to 1.0. In other words, the maximum length of 
the flow path in the alluvium corresponds to the maximum westerly extent of the alluvium 
uncertainty zone, and the minimum length of the flow path in the alluvium corresponds to the 
minimum westerly extent of the alluvium uncertainty zone. The values in Table 6-7 are input as 
a GoldSim V7.50.100 software code look-up table in the SZ 1-D transport model. 
Table 6-7. Flow Path Lengths of Pipe Segments 
Minimum and Maximum Flow Path Lengths of Pipe Segments (km) 
Source Region 1 Source Region 2 Source Region 3 Source Region 4 
HAVO 5  13 km 13  18 km 5  13 km 13  18 km 5  13 km 13  18 km 5  13 km 13  18 km 
0.05 12.0  14.5 7.5  10.0 12.0  14.0 7.0  9.0 13.0  16.0 3.0  6.0 12.5  15.0 3.5  6.0 
1.00 12.0  14.0 5.5  7.5 12.0  14.5 4.5  7.0 10.0  13.5 2.0  5.5 10.0  12.0 3.0  5.0 
5.00 12.5  14.5 3.0  5.0 11.5  14.0 3.0  5.5 10.5  14.0 1.0  4.5 10.5  12.5 2.0  4.0 
20.00 12.5  14.5 2.5  4.5 11.5  14.0 3.0  5.5 10.5  14.0 1.0  4.5 10.5  12.5 2.0  4.0 
HAVO=horizontal anisotropy 
6.5.2 Base-Case Model Inputs 
The SZ transport abstraction model and the SZ 1-D transport model include uncertainty through 
stochastic simulations of uncertain parameters. Parameter uncertainties are quantified through 
uncertainty distributions, which numerically represent our state of knowledge about a particular 
parameter on a scale of the model domain. The uncertainty distribution (either cumulative 
distribution function (CDF) or probability density function (PDF)) of a parameter, represents 
what is known and what is unknown about the parameter, and reflects the current knowledge of 
the range and likelihood of the appropriate parameter values when used in these models 
(BSC 2002 [DIRS 158794], p. 45). The uncertainty distributions incorporate uncertainties 
associated with field or laboratory data, knowledge of how the parameter will be used in the 
model, and theoretical considerations. Geologic uncertainty is incorporated with regard to the 
location of the contact between the tuff and alluvium at the water table (see Section 6.5.2.2). In 
some cases, parameters are assigned constant values because radionuclide transport is relatively 
insensitive to the parameter, or the uncertainty is relatively small. Constant parameters are 
defined to vary from one hydrogeologic unit to another, but for a given hydrogeologic unit, the 
parameter remains constant for all realizations. The development and justification for the 
parameter uncertainty distributions are discussed below. See Table 6-8 for a comprehensive list 
of the models/analyses inputs used in the SZ transport abstraction model and the 
SZ 1-D transport model. The unit numbers given in Table 6-8 are defined by hydrogeologic unit 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-32 October 2004 
in Table 6-9. Please note that parameter values are developed for the 19 hydrogeologic units in 
Table 6-9 for completeness; however, 18 units are included in the SZ site-scale flow model, the 
SZ site-scale transport model, and the SZ transport abstraction model. The valley-fill confining 
unit has a very small volume relative to other units in the model domain, and there are no 
occurrences of this unit along the flow path from the repository. Consequently, it is not included 
in the models as a separate unit. 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
KDNPVO Neptunium 
sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 0.0 
0.05 0.99 
0.90 1.83 
1.0 6.0 
mL/g Epistemic 
KDNPAL 
Neptunium 
sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 1.8 
0.05 4.0 
0.95 8.7 
1.0 13.0 
mL/g Epistemic 
KDSRVO 
Strontium sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 20. 
Maximum 400. 
mL/g Epistemic 
KDSRAL 
Strontium sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 20. 
Maximum 400. 
mL/g Epistemic 
KDUVO 
Uranium sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 0.0 
0.05 5.39 
0.95 8.16 
1.0 20.0 
mL/g Epistemic 
KDUAL 
Uranium sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 1.7 
0.05 2.9 
0.95 6.3 
1.0 8.9 
mL/g Epistemic 
KDRAVO 
Radium sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 100. 
Maximum 1000. 
mL/g Epistemic 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-33 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
KDRAAL 
Radium sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
Uniform: 
Minimum 100. 
Maximum 1000. 
mL/g Epistemic 
KD_Pu_Vo 
Plutonium sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 10. 
0.25 89.9 
0.95 129.87 
1.0 300. 
mL/g Epistemic 
KD_Pu_Al 
Plutonium sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
Beta: 
Mean 100. 
Standard Deviation 15. 
Minimum 50. 
Maximum 300. 
mL/g Epistemic 
KD_Am_Vo 
Americium 
sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
mL/g Epistemic 
KD_Am_Al 
Americium 
sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
mL/g Epistemic 
KD_Cs_Vo 
Cesium sorption 
coefficient in 
volcanic units 
LA0310AM831341.002 
[DIRS 165891] 
CDF: 
Probability Value 
0.0 100. 
0.05 3000.59 
1.0 6782.92 
mL/g Epistemic 
KD_Cs_Al 
Cesium sorption 
coefficient in 
alluvium 
LA0310AM831341.002 
[DIRS 165891] 
Truncated Normal: 
Mean 728. 
Standard Deviation 464. 
Minimum 100. 
Maximum 1000. 
mL/g Epistemic 
FISVO Flowing interval 
spacing in 
volcanic units 
SN9907T0571599.001 
[DIRS 122261] 
CDF : (Log10-transformed) 
Probability Value 
0.0 0.087 
0.05 0.588 
0.25 1.00 
0.50 1.29 
0.75 1.58 
0.95 1.90 
1.0 2.62 
m Epistemic 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-34 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
CORAL Colloid retardation 
factor in alluvium 
LA0303HV831352.004 
[DIRS 163559] 
CDF : (Log10-transformed) 
Probability Value 
0.0 0.903 
0.331 0.904 
0.50 1.531 
1.0 3.715 
N/A Epistemic 
CORVO Colloid retardation 
factor in volcanic 
units 
LA0303HV831352.002 
[DIRS 163558] 
CDF : (Log10-transformed) 
Probability Value 
0.0 0.778 
0.15 0.779 
0.25 1.010 
0.50 1.415 
0.80 1.778 
1.0 2.903 
N/A Epistemic 
HAVO 
Ratio of horizontal 
anisotropy in 
permeability 
SN0302T0502203.001 
[DIRS 163563] 
CDF: 
Probability Value 
0.0 0.05 
0.0042 0.2 
0.0168 0.4 
0.0379 0.6 
0.0674 0.8 
0.10 1.0 
0.60 5. 
0.744 8. 
0.856 11. 
0.936 14. 
0.984 17. 
1.0 20. 
N/A Epistemic 
LDISP 
Longitudinal 
dispersivity 
MO0003SZFWTEEP.000 
[DIRS 148744] 
Truncated Normal: (Log10- 
transformed) 
Mean 2.0 
Standard Deviation 0.75 
m Epistemic 
Kd_Pu_Col 
Plutonium sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e3 
0.04 5.e3 
0.12 1.e4 
0.37 5.e4 
0.57 1.e5 
0.92 5.e5 
1.0 1.e6 
mL/g Epistemic 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-35 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
Kd_Am_Col 
Americium 
sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e4 
0.07 5.e4 
0.17 1.e5 
0.40 5.e5 
0.60 1.e6 
0.92 5.e6 
1.0 1.e7 
mL/g Epistemic 
Kd_Cs_Col 
Cesium sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[DIRS 164131] 
CDF: 
Probability Value 
0.0 1.e2 
0.2 5.e2 
0.45 1.e3 
0.95 5.e3 
1.0 1.e4 
mL/g Epistemic 
Conc_Col 
Groundwater 
concentration of 
colloids 
SN0306T0504103.005 
[DIRS 164132] 
CDF : (Log10-transformed) 
Probability Value 
0.0 -9.0 
0.50 -7.0 
0.75 -6.0 
0.90 -5.0 
0.98 -4.3 
1.0 -3.7 
g/mL Epistemic 
R_U_Kd Correlation 
coefficient for U Kd 
in volcanic units 
and alluvium 
LA0310AM831341.002 
[DIRS 165891] 
0.75 N/A N/A 
R_Np_Kd Correlation 
coefficient for Np 
Kd in volcanic 
units and alluvium 
LA0310AM831341.002 
[DIRS 165891] 
0.75 N/A N/A 
R_Pu_Kd Correlation 
coefficient for Pu 
Kd in volcanic 
units and alluvium 
LA0310AM831341.002 
[DIRS 165891] 
0.50 N/A N/A 
R_U_Np Correlation 
coefficient for U Kd 
and Np Kd 
LA0310AM831341.002 
[DIRS 165891] 
0.50 N/A N/A 
FPLAW Western boundary 
of alluvial 
uncertainty zone 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 
FPLAN Northern 
boundary of 
alluvial uncertainty 
zone 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-36 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
NVF19 Effective porosity 
in shallow 
alluvium 
Internal to this report Truncated Normal: 
Mean 0.18 
Standard Deviation 0.051 
Minimum 0.00 
Maximum 0.30 
N/A Epistemic 
NVF7 Effective porosity 
in undifferentiated 
valley fill 
Internal to this report Truncated Normal: 
Mean 0.18 
Standard Deviation 0.051 
Minimum 0.00 
Maximum 0.30 
N/A Epistemic 
FPVO Fracture porosity 
in volcanic units 
Internal to this report CDF: (Log10-transformed) 
Probability Value 
0.0 -5.0 
0.05 -4.0 
0.50 -3.0 
0.80 -2.0 
1.0 -1.0 
N/A Epistemic 
DCVO Effective diffusion 
coefficient in 
volcanic units 
Internal to this report CDF: (Log10-transformed) 
Probability Value 
0.0 -11.3 
0.08 -10.7 
0.50 -10.3 
0.83 -9.9 
1.0 -9.3 
m2/s Epistemic 
GWSPD Groundwater 
specific discharge 
multiplier 
Internal to this report CDF: (Log10-transformed) 
Probability Value 
0.0 -1.477 
0.10 -0.477 
0.50 0.0 
0.90 0.477 
1.0 1.0 
N/A Epistemic 
bulkdensity Bulk density of 
alluvium 
Internal to this report Normal: 
Mean 1910 
Standard Deviation 78 
kg/m3 Epistemic 
SRC1X 
SRC1Y 
SRC2X 
SRC2Y 
SRC3X 
SRC3Y 
SRC4X 
SRC4Y 
Source regions 
beneath the 
repository 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 
and Aleatory 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-37 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
Alluv_xmin1 UTM minimum 
easting, SW 
corner alluvial 
uncertainty zone 
Internal to this report 548285. m N/A 
Alluv_xmax1 UTM maximum 
easting, SW 
corner alluvial 
uncertainty zone 
Internal to this report 546669. m N/A 
Alluv_ymin1 UTM minimum 
northing, SW 
corner alluvial 
uncertainty zone 
Internal to this report 4057240. m N/A 
Alluv_ymax1 UTM maximum 
northing, SW 
corner alluvial 
uncertainty zone 
Internal to this report 4057620. m N/A 
Alluv_xmin2 UTM minimum 
easting, SE corner 
alluvial uncertainty 
zone 
Internal to this report 555550. m N/A 
Alluv_xmax2 UTM maximum 
easting, SE corner 
alluvial uncertainty 
zone 
Internal to this report 555550. m N/A 
Alluv_ymin2 UTM minimum 
northing, SE 
corner alluvial 
uncertainty zone 
Internal to this report 4055400. m N/A 
Alluv_ymax2 UTM maximum 
northing, SE 
corner alluvial 
uncertainty zone 
Internal to this report 4055400. m N/A 
Alluv_xmin3 UTM minimum 
easting, NE corner 
alluvial uncertainty 
zone 
Internal to this report 557424. m N/A 
Alluv_xmax3 UTM maximum 
easting, NE corner 
alluvial uncertainty 
zone 
Internal to this report 557758. m N/A 
Alluv_ymin3 UTM minimum 
northing, NE 
corner alluvial 
uncertainty zone 
Internal to this report 4065430. m N/A 
Alluv_ymax3 UTM maximum 
northing, NE 
corner alluvial 
uncertainty zone 
Internal to this report 4067430. m N/A 
Alluv_xmin4 UTM minimum 
easting, NW 
corner alluvial 
uncertainty zone 
Internal to this report 554192. m N/A 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-38 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
Alluv_xmax4 UTM maximum 
easting, NW 
corner alluvial 
uncertainty zone 
Internal to this report 553579. m N/A 
Alluv_ymin4 UTM minimum 
northing, NW 
corner alluvial 
uncertainty zone 
Internal to this report 4065430. m N/A 
Alluv_ymax4 UTM maximum 
northing, NW 
corner alluvial 
uncertainty zone 
Internal to this report 4067430. m N/A 
A1_1_x UTM easting, SW 
corner source 
zone 1 
Internal to this report 547570. m N/A 
A1_1_y UTM northing, SW 
corner source 
zone 1 
Internal to this report 4078630. m N/A 
A1_2_x UTM easting, SE 
corner source 
zone 1 
Internal to this report 548500. m N/A 
A1_2_y UTM northing, SE 
corner source 
zone 1 
Internal to this report 4078630. m N/A 
A1_3_x UTM easting, NE 
corner source 
zone 1 
Internal to this report 548500. m N/A 
A1_3_y UTM northing, NE 
corner source 
zone 1 
Internal to this report 4081090. m N/A 
A1_4_x UTM easting, NW 
corner source 
zone 1 
Internal to this report 547570. m N/A 
A1_4_y UTM northing, NW 
corner source 
zone 1 
Internal to this report 4081090. m N/A 
A2_1_x UTM easting, SW 
corner source 
zone 2 
Internal to this report 548500. m N/A 
A2_1_y UTM northing, SW 
corner source 
zone 2 
Internal to this report 4078630. m N/A 
A2_2_x UTM easting, SE 
corner source 
zone 2 
Internal to this report 549320. m N/A 
A2_2_y UTM northing, SE 
corner source 
zone 2 
Internal to this report 4078630. m N/A 
A2_3_x UTM easting, NE 
corner source 
zone 2 
Internal to this report 549320. m N/A 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-39 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
A2_3_y UTM northing, NE 
corner source 
zone 2 
Internal to this report 4081210 m N/A 
A2_4_x UTM easting, NW 
corner source 
zone 2 
Internal to this report 548500. m N/A 
A2_4_y UTM northing, NW 
corner source 
zone 2 
Internal to this report 4081210. m N/A 
A3_1_x UTM easting, SW 
corner source 
zone 3 
Internal to this report 547720. m N/A 
A3_1_y UTM northing, SW 
corner source 
zone 3 
Internal to this report 4076170. m N/A 
A3_2_x UTM easting, SE 
corner source 
zone 3 
Internal to this report 548500. m N/A 
A3_2_y UTM northing, SE 
corner source 
zone 3 
Internal to this report 4076170. m N/A 
A3_3_x UTM easting, NE 
corner source 
zone 3 
Internal to this report 548500. m N/A 
A3_3_y UTM northing, NE 
corner source 
zone 3 
Internal to this report 4078630. m N/A 
A3_4_x UTM easting, NW 
corner source 
zone 3 
Internal to this report 547720. m N/A 
A3_4_y UTM northing, NW 
corner source 
zone 3 
Internal to this report 4078630. m N/A 
A4_1_x UTM easting, SW 
corner source 
zone 4 
Internal to this report 548500. m N/A 
A4_1_y UTM northing, SW 
corner source 
zone 4 
Internal to this report 4076170. m N/A 
A4_2_x UTM easting, SE 
corner source 
zone 4 
Internal to this report 548890. m N/A 
A4_2_y UTM northing, SE 
corner source 
zone 4 
Internal to this report 4076170. m N/A 
A4_3_x UTM easting, NE 
corner source 
zone 4 
Internal to this report 548890. m N/A 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-40 October 2004 
Table 6-8. Models/Analyses Inputs Used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model (Continued) 
Input Name Input Description 
Input Source 
(DTN, if applicable) Value or Distribution Units 
Type of 
Uncertainty 
A4_3_y UTM northing, NE 
corner source 
zone 4 
Internal to this report 4078630. m N/A 
A4_4_x UTM easting, NW 
corner source 
zone 4 
Internal to this report 548500. m N/A 
A4_4_y UTM northing, NW 
corner source 
zone 4 
Internal to this report 4078630. m N/A 
Max_al_por Total alluvium 
porosity 
Internal to this report 0.30 N/A N/A 
Fpor Average fracture 
porosity in 
volcanic units 
Internal to this report 0.001 N/A N/A 
Mpor Average matrix 
porosity in 
volcanic units 
Internal to this report 0.22 N/A N/A 
Bdens Average bulk 
density in volcanic 
units 
Internal to this report 1.88 g/mL N/A 
Matrix 
porosity 
Expected values 
for matrix porosity 
per volcanic unit 
SN0004T0501399.003 
[DIRS 155045] Units 15- 
13, 10 and 8 
Units 12, 11, and 9 are 
internal to this report 
Unit 15: 0.15 
Unit 14, 10, and 8: 0.25 
Unit 13: 0.23 
Unit 12: 0.18 
Unit 11: 0.21 
Unit 9: 0.21 
N/A N/A 
Bulk Density Expected bulk 
density values per 
volcanic unit 
Units 15-13, 10, 8; DTN: 
SN0004T0501399.002 
[DIRS 155046] and 
SN0004T0501399.003 
[DIRS 155045] 
Units 17, 12, 11, 9, and 
6-2 are internal to this 
report 
Unit 18: 2.50 
Unit 17, 6, 5, and 3: 2.77 
Unit 16: 2.44 
Unit 15: 2.08 
Unit 14, 10 and 8: 1.77 
Unit 13: 1.84 
Unit 12: 2.19 
Unit 11: 2.11 
Unit 9: 2.05 
Unit 4 and 2: 2.55 
Unit 1: 2.65 
g/cm3 N/A 
Effective 
Porosity 
Expected effective 
porosity values for 
other units (see 
Section 6.5.2.20) 
Units 18-16 and 1: DTN: 
MO0105HCONEPOR.00 
0 [DIRS 155044] 
Units 6-2 Internal to this 
report 
Unit 18: 0.32 
Unit 17: 0.01 
Unit 16: 0.08 
Unit 6,5 and 3: 0.01 
Unit 4: 0.18 
Unit 2: 0.18 
Unit 1: 0.0001 
N/A N/A 
CDF=cumulative distribution function; UTM=Universal Transverse Mercator 
NOTE: Unit numbers refer to hydrogeologic units in Table 6-9 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-41 October 2004 
Table 6-9. Hydrogeologic Unit Definition 
Hydrogeologic Unit 
Hydrogeologic 
Unit Identification 
Number 
Valley Fill 19 
Valley Fill Confining Unit 18 
Cenozoic Limestones 17 
Lava Flows 16 
Upper Volcanic Aquifer 15 
Upper Volcanic Confining Unit 14 
Lower Volcanic Aquifer Prow Pass 13 
Lower Volcanic Aquifer Bullfrog 12 
Lower Volcanic Aquifer Tram 11 
Lower Volcanic Confining Unit 10 
Older Volcanic Aquifer 9 
Older Volcanic Confining Unit 8 
Undifferentiated Valley Fill 7 
Upper Carbonate Aquifer 6 
Lower Carbonate Aquifer Thrust 5 
Upper Clastic Confining Unit 4 
Lower Carbonate Aquifer 3 
Lower Clastic Confining Unit 2 
Granites 1 
NOTE: Hydrogeologic Units adapted from Hydrogeologic 
Framework Model for the Saturated-Zone Site- 
Scale Flow and Transport Model (BSC 2004 [DIRS 
170008], Table 6-1). 
6.5.2.1 Groundwater Specific Discharge 
Uncertainty exists in the groundwater specific discharge in the SZ along the flow path from 
beneath the repository to the hypothetical point of release into the biosphere. This uncertainty 
was quantified as a distribution of specific discharge in the volcanic aquifer near Yucca 
Mountain by the SZ expert elicitation (CRWMS M&O 1998 [DIRS 100353], p. 3-43). This 
expert elicitation was conducted in a manner consistent with Branch Technical Position on the 
Use of Expert Elicitation in the High-Level Radioactive Waste Program (NUREG-1563) (Kotra 
et al. 1996 [DIRS 100909]). Conclusions regarding the uncertainty in specific discharge by the 
expert elicitation panel primarily were based on single- and multi-well hydraulic testing of wells 
in the fractured volcanic units near Yucca Mountain. The aggregate uncertainty distribution of 
specific discharge in the SZ from the expert elicitation had a median value of about 0.6 m/year, 
with a range of values from less than 0.01 m/year to about 10 m/year (CRWMS M&O 1998 
[DIRS 100353], p. 3-43). It should be noted that the experts in the SZ expert elicitation were 
only elicited regarding uncertainty in specific discharge within about 5 km of the repository. 
More recently, estimates of groundwater specific discharge in the SZ have been obtained at 
another location in the SZ system: from field-testing at the alluvial tracer complex (ATC) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-42 October 2004 
(BSC 2004 [DIRS 170010], Section 6.5.4.3). The ATC is approximately located at the boundary 
of the accessible environment, as specified in regulations for the Yucca Mountain project, 
10 CFR 63.302 (10 CFR 63 [DIRS 156605]). The location of the ATC is approximately 18 km 
from Yucca Mountain, and testing was performed in the alluvium aquifer. Estimates of 
groundwater specific discharge at the ATC range from 1.2 m/year to 9.4 m/year 
(DTN: LA0303PR831231.002, [DIRS 163561]), using alternative means of analyzing the 
single-well tracer testing results. The simulated average specific discharge in this region of the 
SZ system using the SZ transport abstraction model ranges from 1.9 m/year to 3.2 m/year for 
differing values of horizontal anisotropy in permeability, as shown in Table 6-6. 
Correspondingly, the simulated average specific discharge in the volcanic aquifer near Yucca 
Mountain using the SZ transport abstraction model ranges from 0.31 m/year to 0.87 m/year for 
differing values of horizontal anisotropy in permeability. These results show that the average 
groundwater specific discharge tends to increase along the flow path from beneath Yucca 
Mountain to the south. This increase in the specific discharge is due to convergent groundwater 
flow in this region of the SZ system. These results also indicate that there is general consistency 
between the simulated specific discharge and the median values of uncertainty ranges estimated 
for the volcanic aquifer and the alluvial aquifer along the flow path. 
The additional data from the ATC constitutes new information on the specific discharge in the 
SZ, and significantly reduces uncertainty in the specific discharge relative to the assessment by 
the expert elicitation panel. Estimates of specific discharge at the ATC range from 1.2 m/year to 
9.4 m/year; the upper end of the range is 7.8 times the lower end of the range. This range of 
uncertainty in specific discharge is somewhat less than one order of magnitude, which is 
considerably less than the degree of uncertainty from the SZ expert elicitation project (CRWMS 
M&O 1998 [DIRS 100353]). Consequently, the uncertainty distribution for the groundwater 
specific discharge factor (GWSPD) is reevaluated to reflect the reduced uncertainty. From this 
information, a discrete CDF of uncertainty in specific discharge is constructed, in which 
80 percent of the probability is between 1/3 and 3 times the best estimate of specific discharge. 
The lower tail of the uncertainty distribution extends to 1/30 of the expected value and 
10 percent of the probability is assigned to this lower tail. The upper tail of the uncertainty 
distribution extends to 10 times the expected value and 10 percent of the probability is assigned 
to this upper tail. The lower and upper tails of the uncertainty distribution approximately 
correspond to the greater uncertainty reflected in the SZ expert elicitation results. The resulting 
wide total range of uncertainty in specific discharge implicitly includes the potential existence of 
undetected features in the SZ, such as fault and fracture zones that could significantly impact 
groundwater flow. 
Uncertainty in the groundwater specific discharge is incorporated into the SZ transport 
abstraction model using the continuously distributed GWSPD parameter. This parameter is a 
multiplication factor that is applied to all values of permeability and values of specified boundary 
fluxes in the SZ transport abstraction model to effectively scale the simulated specific discharge 
in the model. Note that a separate steady-state groundwater flow field is simulated for each 
realization of the system, using the value of GWSPD (and the value of HAVO, for horizontal 
anisotropy). The sampling of GWSPD is performed on the log-transformed values of the 
specific discharge multiplication factor, as indicated in Table 6-8. The CDF of uncertainty in the 
groundwater specific discharge multiplier is shown in Figure 6-7. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-43 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 1.0 
Cumulative Probability 
Log Groundwater Specific Discharge Multiplier 
Output DTN: SN0310T0502103.009. 
Figure 6-7. CDF of Uncertainty in Groundwater Specific Discharge Multiplier 
6.5.2.2 Alluvium Uncertainty Zone 
Uncertainty exists in the geology below the water table, along the inferred flow path from the 
repository at distances of approximately 10 km to 20 km downgradient of the repository. The 
location at which groundwater flow moves from fractured volcanic rocks to alluvium is of 
particular significance from the perspective of repository performance assessment. This is 
because of contrasts between the fractured volcanic units and the alluvium in terms of 
groundwater flow (fracture-dominated flow versus porous medium flow) and in terms of sorptive 
properties of the media for some radionuclides. 
The uncertainty in the northerly extent of the alluvium in the SZ of the site-scale flow and 
transport simulations is abstracted as a polygonal region that is assigned radionuclide transport 
properties representative of the valley-fill aquifer hydrogeologic unit (Table 6-9). The 
dimensions of the polygonal region are randomly varied in the SZ transport abstraction model for 
the multiple realizations. The northern boundary of the uncertainty zone is varied between the 
dashed lines at the northern end of the polygonal area shown in Figure 6-8. The western 
boundary of the uncertainty zone is varied between the dashed lines along the western side of the 
polygonal area shown in the figure. 
The uncertainty in the contact between volcanic rocks and alluvium at the water table along the 
northern part of the uncertainty zone is approximately bounded by the location of well 
UE-25 JF#3, in which the water table is below the contact between the volcanic rocks and the 
overlying alluvium, and by the location of well EWDP-10S, in which the water table is above the 
contact between the volcanic rocks and the alluvium. The uncertainty in the contact along the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-44 October 2004 
western part of the uncertainty zone is defined by the locations of wells EWDP-10S, EWDP-22S, 
and EWDP-19D1, in which the water table is above the contact between volcanic rocks and the 
overlying alluvium, and outcrops of volcanic bedrock to the west. 
The lower boundary of the alluvium uncertainty zone varies from an elevation of 670 m in the 
northwestern corner of the uncertainty zone to 400 m along the southern edge of the uncertainty 
zone. This corresponds to a saturated alluvium thickness of approximately 50 m in the 
northwestern corner varying to about 300 m along the southern boundary of the uncertainty zone. 
The boundaries of the alluvium uncertainty zone are determined for a particular realization by 
the parameters FPLAW and FPLAN. These parameters have uniform distributions from 0.0 to 
1.0, where a value of 0.0 corresponds to the minimum extent of the uncertainty zone and 1.0 
corresponds to the maximum extent of the uncertainty zone in a westerly direction and northerly 
direction, respectively. A uniform distribution is appropriate for these uncertainty distributions 
because only the bounding values are known. A uniform distribution is the best statistically 
unbiased choice in this situation. These parameters are used to independently and uniformly 
vary the northern and western contacts of the volcanic rocks and alluvium at the water table. The 
maximum and minimum coordinates of the alluvium uncertainty zone, corresponding to the plot 
shown in Figure 6-8, are given in Table 6-8 (Alluv_xmin1 to Alluv_ymax4). 
6.5.2.3 Effective Porosity of Alluvium 
For the TSPA Site Recommendation (SR) calculations, effective porosity in the alluvium was a 
truncated normal distribution with a mean of 0.18, a standard deviation of 0.051, a lower bound 
of 0, and an upper bound of 0.35 (CRWMS M&O 2000 [DIRS 153246], Table 3.8-3). The basis 
for this parameter is from Bedinger et al. (1989 [DIRS 129676], p. A18, Table 1). There were no 
site-specific data for effective porosity in the alluvium at the time of the TSPA-SR. Bedinger 
et al. (1989 [DIRS 129676]) include a study of hydraulic characteristics of alluvium within the 
Basin and Range Province of the Southwestern U.S. This study is relevant to the local basin fill 
conditions, and provides values for effective porosity as a stochastic parameter. Since the 
TSPA-SR, a site-specific value was determined for effective (or flow) porosity from well 
EWDP-19D1 at the ATC, based on a single-well pumping test (BSC 2004 [DIRS 170010], 
Section 6.5.4.2.4). There are also total porosity values from the same well based on borehole 
gravimeter surveys, which are used in developing the upper bound of the effective porosity in the 
alluvium uncertainty distribution. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-45 October 2004 
Sources: Repository outline is from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]); well locations are 
from DTNs: GS010908312332.002 [DIRS 163555]; GS030108314211.001 [DIRS 163483]. 
NOTE: The repository outline is shown by the solid line, and the minimum and maximum boundaries of the alluvium 
uncertainty zone are shown by the dashed lines. Key well locations and well numbers are shown with the 
cross symbols. 
Figure 6-8. Minimum and Maximum Extent of the Alluvium Uncertainty Zone 
Effective porosity is important for determining the average linear groundwater velocities used in 
the simulation of radionuclide transport. They are customarily calculated by dividing the 
specific discharge of groundwater through a model grid cell by the porosity, fe 
. Groundwater 
velocities are rendered more accurate when dead-end pores are eliminated from consideration 
because they do not transmit water. The effective porosity results from that elimination. As a 
result fe 
will always be less than or equal to total porosity, fT. The retardation coefficient, Rf, is 
also a function of porosity. Reducing total porosity to fe 
can erroneously raise the magnitude of 
this value within the model. The correction for this is detailed in the Equation 6-3 discussion in 
Section 6.5.1. 
Effective porosity is treated as an uncertain parameter for the two alluvium units (19 and 7) of 
the nineteen SZ model hydrogeologic units. Uncertain, in this sense, means that fe 
will be 
constant spatially for each unit for any particular model realization, but that value will vary from 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-46 October 2004 
one realization to the next. In comparison, constant parameters are constant spatially and do not 
change from realization to realization. 
The parameter input sources used in this analysis are described in Table 4-1, and corroborative 
data are discussed in this section. The uncertainty distribution used for the analysis is the 
distribution used for TSPA-SR, with a change to the upper bound. The effective porosity 
uncertainty distribution is shown in Figure 6-9. Figure 6-9 compares the distribution of Bedinger 
et al. (1989 [DIRS 129676]) (DTN: MO0105HCONEPOR.000 [DIRS 155044]) to distributions, 
ranges, and values from the other sources that were considered to develop the uncertainty 
distribution. The site-specific effective porosity data point of 0.1 from well EWDP-19D1 
(BSC 2004 [DIRS 170010], Section 6.5) is shown on Figure 6-9. This is considered a 
corroborative data point, and falls within the uncertainty distribution. 
The upper bound of the uncertainty distribution for effective porosity is re-evaluated because of 
new site-specific data obtained after TSPA-SR. The new upper bound is based on the total 
porosity values from well EWDP-19D1 and the average of the total porosity values from the 
Cambric study (Burbey and Wheatcraft 1986 [DIRS 129679], pp. 23 and 24) within the NTS but 
several kilometers to the east, in Frenchman Flat; and total porosity shown in Tables 8-1 and 8-2 
of Regional Groundwater Flow and Tritium Transport Modeling and Risk Assessment of the 
Underground Test Area, Nevada Test Site, Nevada (DOE 1997 [DIRS 103021], pp. 8-5 and 8-6, 
see Table 6-10). The computed total porosity values from EWDP-19D1 are shown in 
Table 6-11, and have an average value of 0.24. 
The average of the total porosity values in Table 6-10 and the average of the site-specific data 
from well EWDP-19D1 were used to develop the upper bound of the effective porosity 
uncertainty distribution. Although there is considerable variability in measured total porosity 
within alluvial strata (see Table 6-11), an average value to define the upper bound of the 
uncertainty distribution is appropriate because of scaling considerations. The grid cells in the SZ 
site-scale transport model are 500 m by 500 m and smaller scale variations in total porosity 
would be averaged over this large volume of alluvium. The average total porosity value of 0.35 
and the average value from EWDP-19D1 of 0.24 result in a mean of 0.30. Figure 6-10 shows the 
truncated normal distribution developed in this analysis for effective porosity in the alluvium 
(parameter NVF19 and NVF7) with a mean of 0.18, standard deviation of 0.051, a lower bound 
of 0, and an upper bound of 0.30. Note that parameter NVF7 has the same distribution as 
NVF19, and is sampled independently. The hydrogeologic units corresponding to the parameters 
NVF19 and NVF7 (Units 19 and 7) developed at different geologic times and under potentially 
differing tectonic conditions. Consequently, they may have different characteristics with regard 
to effective porosity and the parameters are not correlated in the sampling process. The resulting 
range of uncertainty in effective porosity of the alluvium implicitly accounts for the potential 
existence of undetected stratigraphic and sedimentological features, such as fine-grained, 
low-permeability facies, that could exclude groundwater flow through the alluvium aquifer. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-47 October 2004 
0
1 
2
3
4
5
6
7
8
9 
10 
0 0.1 0.2 0.3 0.4 0.5 0.6 
Porosity (effective or 'total') 
Frequency 
Sources: DTN: MO0003SZFWTEEP.000 [DIRS 148744]; BSC 2004 [DIRS 170010], Section 6.5; Burbey and 
Wheatcraft 1986 [DIRS 129679], pp. 23 to 24; DOE 1997 [DIRS 103021], Table 8-1, p. 8-5, and Table 8-2, 
p. 8-6. 
NOTE: The dashed black line is Neuman (MO0003SZFWTEEP.000 [DIRS 148744]); 
the solid heavy blue line is DTN: MO0105HCONEPOR.000 [DIRS 155044]; 
the solid pink line is Gelhar (DTN: MO0003SZFWTEEP.000 [DIRS 148744]); 
the solid blue block is the effective porosity value calculated from EWDP-19D1 (BSC 2004 [DIRS 170010], 
Section 6.5). 
The single value data points do not have a y-scale value, but do correspond to the x-axis. These points are 
shown for comparison purposes only. 
The solid black triangle is DOE 1997 [DIRS 103021], Table 8-1, mean matrix porosity; 
the diamond outlined shapes are Burbey and Wheatcraft 1986 [DIRS 129679] total porosity; 
the X is DOE 1997 [DIRS 103021], Table 8-2, total porosity; 
and the square outlined shape is DOE 1997 [DIRS 103021], Table 8-1, mean bulk porosity. 
Figure 6-9. Effective Porosity Distributions and Values for Alluvium Compared 
Table 6-10. Total Porosity Summary ( fT) for Alluvium 
Reference Total Porosity Comments 
DOE 1997 [DIRS 103021], Table 
8-1, p. 8-5 0.36 Mean bulk porosity 
DOE 1997 [DIRS 103021], Table 
8-2, p. 8-6 0.35 Total porosity 
Burbey and Wheatcraft 1986 
[DIRS 129679], pp. 23 to 24 0.34 Average of porosity values from 
Table 3 of that study 
Average of above 0.35 N/A 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-48 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.00 0.05 0.10 0.15 0.20 0.25 0.30 
Cumulative Probability 
Effective Porosity in Alluvium 
Output DTN: SN0310T0502103.009. 
Figure 6-10. CDF of Uncertainty in Effective Porosity in Alluvium 
6.5.2.4 Flowing Interval Spacing 
The flowing interval spacing is a key parameter in the dual porosity model that is included in the 
SZ transport abstraction model. A flowing interval is defined as a fractured zone that transmits 
fluid in the SZ, as identified through borehole flow meter surveys (see Figure 6-11). This figure 
shows a borehole that is intersected by multiple, irregularly spaced fractures. The figure also 
shows several black bands, labeled as flowing intervals, in which a flow meter survey has 
detected groundwater flow into (or out of) the borehole. The analysis uses the term flowing 
interval spacing as opposed to fracture spacing, which is typically used in the literature. 
Fracture spacing was not used because field data identified zones (or flowing intervals) that 
contain fluid-conducting fractures but do not distinguish how many or which fractures comprise 
the flowing interval. These data also indicate that numerous fractures between flowing intervals 
do not transmit significant amounts of groundwater. The flowing interval spacing is the distance 
between the midpoints of each flowing interval. The flowing interval approach and the resulting 
uncertainty distribution implicitly accounts for the potential existence of undetected features, 
such as fracture zones through which groundwater flow is channeled, in the fractured volcanic 
units of the SZ. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-49 October 2004 
Source: BSC 2004 [DIRS 170014], Figure 6-1. 
Figure 6-11. Example of Flowing Interval Spacing for a Typical Borehole 
There is considerable uncertainty regarding the flowing interval spacing parameter due to the 
limited number of data points available. The data set used for the analysis consisted of borehole 
flow meter survey data. This analysis is described in detail in Probability Distributions for 
Flowing Interval Spacing (BSC 2004 [DIRS 170014]). 
There are no new data available to reevaluate the uncertainty distribution for this parameter; 
therefore, a CDF based on the lognormal distribution (BSC 2004 [DIRS 170014], Section 7) that 
was used in TSPA-SR is used as input to the TSPA-LA model, and is shown in Figure 6-12. 
The flowing interval spacing parameter is specified for a particular realization by the parameter 
FISVO. See Table 6-8 for the associated probabilities for the flowing interval spacing CDF. 
6.5.2.5 Flowing Interval Porosity 
The flowing interval porosity is defined as the volume of the pore space through which 
significant groundwater flow occurs, relative to the total volume. At Yucca Mountain, rather 
than attempt to define the porosity within all fractures, a flowing interval is defined as the region 
in which significant groundwater flow occurs at a well. The fracture porosity then characterizes 
these flowing intervals rather than all fractures. The advantage to this definition of fracture 
porosity is that in situ well data may be used to characterize the parameter. The flowing interval 
porosity may also include the matrix porosity of small matrix blocks within fracture zones that 
potentially experience rapid matrix diffusion. 
Flowing Interval Spacing 
Flowing interval 
Borehole 
Fractures 
Fracture Spacing 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-50 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 
Cumulative Probability 
Log Flowing Interval Spacing (m) 
Output DTN: SN0310T0502103.009. 
Figure 6-12. CDF of Uncertainty in Flowing Interval Spacing 
For the TSPA-SR calculations, the flowing interval (fracture) porosity probability distribution 
was a uniform distribution with an upper bound of log10 (flowing interval porosity) of -1.0 and a 
lower bound of log10 (flowing interval porosity) of -5.0 (CRWMS M&O 2000 [DIRS 147972], 
Section 6.7). The basis for this uncertainty distribution includes estimates of fracture porosity in 
intact cores of volcanic rock, and the results of pumping tests and tracer tests in the Bullfrog Tuff 
at the C-wells complex (CRWMS M&O 2000 [DIRS 147972], Section 6.7). 
The TSPA-SR probability distribution for the flowing interval porosity has been modified based 
on new sources of information pertaining to flowing interval porosity. New information has 
been derived from tests in unsaturated tuff in the Exploratory Studies Facility (ESF). Fracture 
porosity has been estimated in unsaturated volcanic tuff in the ESF for the middle nonlithophysal 
welded tuff (UZ model layer tsw34) using gas tracer testing. The assumptions used in obtaining 
the fracture porosity from gas tracer tests are that the diffusion of gas into the rock matrix is 
negligible compared to the flow through the fractures, that the fracture network is well 
connected, and that the gas flow is approximately radial toward the pumped borehole. This 
calculation of fracture porosity is documented in the Analysis of Hydrologic Properties Data 
report (BSC 2004 [DIRS 170038], Section 6.1.3) and estimates of fracture porosity in other 
volcanic subunits have been based on these testing results. The estimated average value of 
fracture porosity is on the order of 0.01. 
Fracture porosity has also been estimated using the residence time of conservative tracers during 
cross-hole tracer tests at the C-wells complex (CRWMS M&O 1997 [DIRS 100328], pp. 2 to 4; 
BSC 2004 [DIRS 170010]). This method assumes that the mean tracer arrival time is equal to 
the time required to drain a homogenous, fractured cylinder of rock with a radius equal to the 
distance between the pumping well and the tracer-injection well. A large range in estimated 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-51 October 2004 
fracture porosity for the saturated Bullfrog Tuff resulted from this method because the tracers 
were interpreted to have traveled along two paths with different travel times. The path with the 
longer travel time resulted in a larger estimate of fracture porosity. The resulting lower and 
upper bounds of fracture porosity were 0.003 and 0.10, respectively 
(DTNs: LA0303PR831231.005 [DIRS 166259] and GS031008312315.002 [DIRS 166261]). 
The Department of Energy Nevada Site Office Underground Test Area Project (DOE 1997 
[DIRS 103021]) evaluated the fracture spacing and apertures in seven cores from wells in 
volcanic rocks at Pahute Mesa. The estimated open fracture porosities based on the assumption 
of parallel plates range from 2.6  10-6 to 4.7  10-4 in these cores (DOE 1997 [DIRS 103021], 
p. 5-14). Information compiled for Total-System Performance Assessment for Yucca Mountain  
SNL Second Iteration (TSPA-1993) (Wilson et al. 1994 [DIRS 100191], Volume 1, Chapter 7, 
Table 7-19, p. 7-30) indicates expected values of fracture porosities ranging from 8.1  10-5 to 
2.8  10-3 in core from USW G-1, USW GU-3, USW G-4, and UE25a#1, when parallel plate 
fracture geometry is assumed. This information generally corroborates the estimates of fracture 
porosity from DOE (1997 [DIRS 103021]). There is large uncertainty in the flowing interval 
porosity parameter. 
Given the estimates of this parameter from values based on theoretical models, pumping tests, 
and tracer data, the parameter uncertainty ranges over four orders of magnitude. To estimate the 
lower bound of flowing interval porosity, the estimates of fracture porosity of intact cores of 
volcanic rock were used. The upper bound of uncertainty in the flowing interval porosity is 
based on interpretations of pumping test and tracer data. The new data from the ESF provide an 
estimate of flowing interval porosity that falls in the upper half of the distribution used for this 
parameter (CRWMS M&O 2000 [DIRS 147972], Section 6.7) in the TSPA-SR. 
For the TSPA-LA calculations, a cumulative distribution with a lower bound of log10 (flowing 
interval porosity) equal to -5.0, and an upper bound of log10 (flowing interval porosity) equalt to 
-1.0 is selected for this parameter, as shown in Figure 6-13. This distribution places more 
weight in the middle of the distribution range in comparison to the TSPA-SR uniform 
distribution (CRWMS M&O 2000 [DIRS 147972], Section 6.7) that results in equal probabilities 
for the given range. The 0.5 probability value of -3.0 is representative of the smallest values of 
fracture porosity estimated from the new data from the ESF and previous field tests. See 
Table 6-8 for the associated probabilities for the flowing interval porosity CDF. The flowing 
interval porosity parameter is specified for a particular realization by the parameter FPVO. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-52 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-5 -4 -3 -2 -1 
Cumulative Probability 
Log Flowing Interval Porosity in Volcanic Units 
Output DTN: SN0310T0502103.009. 
Figure 6-13. CDF of Uncertainty in Flowing Interval Porosity 
6.5.2.6 Effective Diffusion Coefficient 
Matrix diffusion is a process in which diffusing particles move, via Brownian motion, through 
both mobile and immobile fluids. Diffusion is a Fickian process; that is, diffusing species move 
from high to low concentrations. It is dependent on the free water molecular diffusion 
coefficient for individual constituents and the characteristics of the flow path in which the 
diffusing species passes. Because diffusion through porous media is less than free water 
molecular diffusion, it is quantitatively defined as the effective diffusion coefficient, De. 
Matrix diffusion has been demonstrated to occur in the volcanic rocks within the vicinity of 
Yucca Mountain (Reimus et al. 2002 [DIRS 162956]; Reimus et al. 2002 [DIRS 163008]). 
Thus, it is modeled in the volcanic units of the SZ transport abstraction model and the SZ 1-D 
transport model for TSPA-LA. It is the transport mechanism that occurs in the rock matrix 
portion of the volcanic units. Consequently, it can be an important process that physically 
retards net radionuclide transport in fractured media. 
The variability in De in saturated media is caused by the variability in: 
1. The individual constituents size (atom, ion, or molecule) and charge 
2. Fluid temperature 
3. The unique properties of a porous medias lithology at a microscopic scale. 
The contribution of these uncertainties and variabilities to deriving a value of De is evaluated in 
the following subsections. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-53 October 2004 
Variability between Lithologic Units 
There are several derived lumped parameters, used as adjustments to the free water molecular 
diffusion, to account for the impact of lithology on molecular diffusion. Tortuosity, formation, 
and constrictivity factors are common adjustment parameters. These lumped parameters are 
based on various linear regression models, fit to field and laboratory experimental results and 
measured properties of the host rock, such as porosity, permeability, and formation electrical 
resistivity (from geophysical logs). 
Diffusion cell experiments have demonstrated that De is affected more by the structural 
properties of the porous medium, such as permeability, porosity, pore size distribution, and pore 
geometry, than by the mineralogy or geochemistry (Skagius and Neretnieks 1986 
[DIRS 156862], pp. 389 to 398). Specific to Yucca Mountain, diffusion cell experiments 
documented in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010], Section E.2) on dilute 
bromide solutions diffusing through Yucca Mountain tuff samples demonstrated De was directly 
proportional to the variability in permeability. Buchholtz ten Brink et al. (1991 [DIRS 162954]) 
found De for 238U on various Yucca Mountain tuff samples to be dependent on the pore size 
distribution of the hydrostratigraphic units. 
Many mathematical models have been formulated to derive a value of De. Most, if not all, rely 
on porosity, with some adding other lumped parameters. For example, Dynamics of Fluids in 
Porous Media (Bear 1972 [DIRS 156269], Sections 4.8.2 and 4.8.3) relates effective matrix 
diffusion to porosity, formation factor (derived from geophysical logs), and the free water 
molecular diffusion coefficient as follows: 
F 
D De f
0 = 
(Eq. 6-15) 
where De is the effective diffusion coefficient in a porous medium [L2/T], 0 D is the diffusion 
coefficient in water [L2/T], and F is the formation factor [-]. The formation factor is defined by 
the electrical resistivity of the porous medium saturated with electrolyte divided by the resistivity 
of the electrolyte. This method has limitations, in that it relies on formation factor 
measurements. 
Domenico and Schwartz (1990 [DIRS 100569], p. 368) document the relationship between 
porosity and effective diffusion with the following: 
0 ) / ( D Dm t f = (Eq. 6-16) 
where t (= Le/L) is the tortuosity [-], Le is the length of the channel for the fluid particle [L], and 
L is the length of the porous media channel [L]. This method has limitations, in that it relies on 
multiple diffusion cell measurements on a wide variety of rock samples to derive a global value 
for t. 
Domenico and Schwartz (1990 [DIRS 100569], p. 368) define a range for Dm with the following 
empirical equation: 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-54 October 2004 
Dm = 
2
0 Df 
to 
2 
0 2 . .. 
. 
. .. 
. 
- f 
f D (Eq. 6-17) 
Bound 1 Bound 2 
This relationship captures the uncertainty and range of Dm in a heterogeneous system. It is 
dependent only on porosity and, because there are many matrix porosity measurements on 
Yucca Mountain tuffs, site-specific data can be used as input. 
Using Equation 6-17 and site-specific porosity data, a range in the effective diffusion coefficient 
in the volcanic rock matrix (De) can be calculated. Mean porosity values were calculated using 
the relative-humidity porosities found in DTN: MO0109HYMXPROP.001 [DIRS 155989] for 
the SZ hydrostratigraphic units defined in Characterization of Hydrogeologic Units Using 
Matrix Properties, Yucca Mountain, Nevada (Flint 1998 [DIRS 100033]) as input. Relativehumidity 
porosity is measured by drying the sample in an oven for 48 hours at 60C and 
65 percent relative humidity. (Note: Flints hydrostratigraphic units are subunits of the SZ 
hydrogeologic framework models (HFM) units adopted in TSPA-LA.) Using Flints 
hydrostratigraphic units to represent a mean porosity is appropriate for this exercise because 
Flints basis for categorizing the units is heavily based on matrix rather than fracture properties, 
and it is the matrix properties that are important to diffusion in the SZ. 
Using relative-humidity porosity values in DTN: MO0109HYMXPROP.001 [DIRS 155989], 
the minimum average porosity is 0.042, and is located in the Calico Hills-vitric unit (a subunit of 
the SZs Upper Volcanic Confining, Unit 14); the maximum average is 0.321, and is located in 
unit TC (Tiva Canyon Tuff, a subunit of the SZ Upper Volcanic Aquifer, Unit 15). For this 
exercise, 0 D is that of 3HHO (tritiated water), 2.44  105 cm2/s. The resulting range in De is 
between 3.92  10-6 and 1.12  10-8 cm2/s when the largest porosity is used as input in bound 1, 
and the smallest porosity is used as input to bound 2. The variability in De is a factor of: 
350 
/ 10 12 . 1 
/ 10 3.92 
2 8 
2 6 
= 

 
-
- 
s cm 
s cm (Eq. 6-18) 
Reimus et al. (2002 [DIRS 163008]) have developed an empirical relationship between De and 
porosity and permeability measurements based on diffusion cell experiments on rock samples 
from the Yucca Mountain area. Diffusing species used in the experiments are 99Tc (as TcO4
-), 
14C (as HCO3
-) and 3HHO, as well as Br- and I -. Rock samples used were taken from within the 
vicinity of Yucca Mountain, under Pahute Mesa and Area 25 of the NTS. Based on these 
experiments, Reimus et al. (2002 [DIRS 163008]) describe three different approaches to deriving 
De. Two are dependent on linear regression relationships fitting the experimental results to 
diffusion cell measurements for: 
1. Both matrix porosity and permeability 
2. Only matrix porosity measurements. 
The third approach is simply compiling a CDF based on their numerous diffusion cell results. 
Reimus et al. (2002 [DIRS 163008], Section 4) found that differences in rock type account for 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-55 October 2004 
the largest variability in the effective diffusion coefficients, rather than variability between 
diffusing species, size, and charge. The highest predictability in determining a value of De 
occurs when both matrix porosity and log permeability are known, with log permeability the 
most important predictive variable. 
The following equation defines their linear regression relationship based on porosity and 
permeability values and diffusion cell results (Reimus et al. 2002 [DIRS 163008], p. 2.25): 
)(log 165 . 0 38 . 1 49 . 3 ) ( log 10 10 m m e k D + + - = f (Eq. 6-19) 
where e D is in units of cm2/s and m k is matrix permeability [L2] in units of m2. 
Again, using matrix properties based on Flints hydrostratigraphic subdivisions (denoted as 
hydrogeologic units in this report), the variability in De can be calculated using Equation 6-19 
and the following inputs: 
 Find the maximum and minimum geometric mean permeability in 
DTN: MO0109HYMXPROP.001 [DIRS 155989] within the Flint-defined set of 
hydrostratigraphic units (listed as hydraulic conductivities in 
DTN: MO0109HYMXPROP.001 [DIRS 155989], then converted to permeability). 
 Determine the maximum and minimum average porosity within the Flint-defined set of 
hydrostratigraphic units (listed as relative-humidity porosities in 
DTN: MO0109HYMXPROP.001 [DIRS 155989]). 
The highest mean log permeability is -13.25, and is located in the Calico Hill-vitric unit (a 
subunit of the SZ HFM Unit 14), the lowest mean log permeability is -19.39, and is located in 
unit TLL (a subunit of SZ HFM Unit 15). The largest porosity, 0.321, is located in the Calico 
Hill-vitric unit; the smallest porosity, 0.042, is located in unit TC (Tiva Canyon Tuff). 
The variation in De, using Equation 6-19 and average maximum and minimum permeabilities 
and porosities values, expressed as a ratio of maximum to minimum estimated De, is as: 
25 
/ 10 34 . 2 
/ 10 84 . 5 
2 7 
2 6 
= 

 
-
- 
s cm 
s cm (Eq. 6-20) 
Variability from Ionic Radius and Charge 
Empirical correlations exist in the literature to adjust free diffusion coefficients dependent on 
species size and charge. For this analysis, general guidance provided by Newman (1973 
[DIRS 148719], Table 75-1, p. 230), which lists diffusion coefficients for ions and cations of 
varying charges and size, is adopted in the scaling of radionuclide diffusion coefficients. 
Diffusion coefficients listed for the simple monovalent ions Br- and I - are the largest values 
listed by Newman. Consequently, diffusion coefficient scaling factors for all other ions and 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-56 October 2004 
cations are relative to those listed for Br- and I -. The rationale for specific scaling factors is 
given below. 
1. Simple monovalent cations tend to be more hydrated than anions, resulting in 
larger effective radii than anions, and concomitantly, diffusion coefficients are 
about 0.90 and 0.95 times that of simple monovalent anions such as Br- and I -. 
PuO2
+ and NpO2
+ would fall into this category, since they both have relatively 
low charge-to-mass ratios and should not be highly hydrated. 
2. Cations, such as Na+ and Li+, with high charge-to-mass ratios have a diffusion 
coefficient between 0.65 and 0.5 times that of Br- and I -. 
3. Multivalent anions (which are generally multiatom species) tend to have diffusion 
coefficients of 0.4 to 0.6 times that of Br- and I -. 
4. Multivalent cations have diffusion coefficients between 0.3 to 0.4 times that of 
Br- and I -. 
5. Diffusion coefficients of organic molecules can be considered reasonable lower 
bounds for diffusion coefficients of large anionic radionuclide complexes. An 
example is the large monovalent anions, such as pentafluorobenzoate, which have 
diffusion coefficients about 0.33 times that of Br- and I - (Callahan et al. 2000 
[DIRS 156648], Tables 5 and 6, p. 3553). 
6. Cations with charges of +3 typically hydrolyze or form complexes in solution, 
resulting in a lower charge and higher mass species (e.g., hydroxyl or carbonate 
complexes). Consequently, the multivalent and complexed species could diffuse 
between 0.3 and 0.25 times that of Br- and I -. 
Concluding from the above, the variation between the diffusion coefficients for simple and 
relatively small monovalent ions and the larger multivalent complexed cations can be as much 
as: 
0 . 4 
25 . 0
1 = (Eq. 6-21) 
The variability in De due to ionic charge and species size can be as much as a factor of 4.0. 
Variability from Temperature 
The uncertainty and variability in diffusion due solely to temperature variations (over space and 
time) will affect all contaminants equally. Hence, the uncertainty in temperature will not affect 
the decision to use a single diffusion coefficient. The Stokes-Einstein relationship can be used to 
approximate the molecular diffusion of ions in water with concentrations of ions as high as 
seawater and with temperatures ranging from 0C to 100C (Li and Gregory 1974 
[DIRS 129827], p. 704; (Simpson and Carr 1958 [DIRS 139449], p. 1201). Using the 
Stokes-Einstein relationship, the molecular diffusion coefficient for a given temperature can be 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-57 October 2004 
estimated as a function of the diffusion coefficient at a reference absolute temperature ( 0 T ) and 
the relative change in temperature and water viscosity, ( .) [M/(LT)] (Li and Gregory 1974 
[DIRS 129827], p. 704): 
) ( ) ( 0 0 
1
0 
0
1 
1 0 T D 
T
T T D 
.
. 
= (Eq. 6-22) 
Given the maximum potential range in temperature for the Yucca Mountain groundwater along 
the transport pathway of 20C to 50C (293.15 K to 323.15 K), based on the ambient geothermal 
gradient and range in depth to the shallow SZ and the viscosity of water at those temperatures 
(Viswanath and Natarajan 1989 [DIRS 129867], p. 714), Equation 6-22 can be rewritten and 
solved as follows: 
15 . 2 
/ 516 . 0 
/ 007 . 1 
15 . 293 
15 . 323 
) ( 
) ( 
2
2 
1
0 
0
1 
0 0 
1 0 = = = 
m Ns 
m Ns 
K
K 
T
T 
T D 
T D 
.
. 
(Eq. 6-23) 
Thus, 0 D can vary by a factor of about 2.2 due to changes in water temperature. 
Effective Diffusion Coefficients for Yucca Mountain Volcanic Units 
Given the above arguments, it is demonstrated that the largest variability in De is due to 
differences in lithology. The variability in De using Equation 6-19 is not as high as that derived 
using Equation 6-17. However, Equation 6-19 will be adopted in deriving the uncertainty 
distribution of De for the following reasons: 
1. Because Equation 6-19 is derived based on site-specific data, it is more 
appropriate in determining the range of De due to lithology specific to Yucca 
Mountain. 
2. A large number of permeability and porosity measurements are taken from the SZ 
hydrogeologic units where flow is expected to take place. Averages of these 
measurements can be used as input to Equation 6-19. 
3. Using maximum and minimum averages from matrix porosity and permeability as 
input yields a range in De that approaches that of the few laboratory-derived De 
measurements specific to Yucca Mountain tuffs for TcO4
- (1.0  10-7 to 
2.0  10-6) and HTO- (1.2  10-7 to 3.5  10-6) (see Triay et al. 1993 
[DIRS 145123]); Rundberg et al. 1987 [DIRS 106481]) as indicated on the 
Flint_Reim_TrRnd spreadsheet in the EXCEL workbook Eff_MtrxDif_11.xls 
file (DTN: SN0306T0502103.006). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-58 October 2004 
The CDF for uncertainty in the effective diffusion coefficient used in this analysis is derived as 
follows: 
1. Mean porosity and permeability values (calculated from values found in 
DTN: MO0109HYMXPROP.001 [DIRS 155989]) were calculated for the 
volcanic hydrostratigraphic units TC, TR, TUL, TMN, TLL, TM2, TM1, CHV, 
CHZ, PP4, PP3, PP2, PP1, BF3, and BF2, defined by Flint (1998 
[DIRS 100033]). These are subunits of the more broadly defined SZ HFM Units 
11, 12, 13, 14, and 15, and are units where flow and transport are expected to take 
place. Mean porosity and permeability values are given on the spreadsheets 
LVA (12 &11), LVA (13), UVC (14), and UVA (15) in the EXCEL file 
Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 
2. A CDF for De was calculated with Equation 6-19, using the mean permeability 
and porosity values for the above hydrostratigraphic units as input. These values 
are given on the spreadsheet drns_all_straight, (Column AG, Rows 34 through 
49) in the EXCEL file Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 
3. The derived CDF was then scaled down to account for the variability in De (to 
account for ionic charge and size). The scaling factors used are: 1) 0.9, to 
represent diffusion of simple monovalent cations, 2) 0.65 and 0.50, to represent 
cations with a high charge-to-mass ratios, 3) 0.3, to represent large monovalent 
anions, and 4) 0.25, to represent multivalent and complexed cations (Figure 6-14). 
Note the rationale for the above scaling factors is discussed in the subsection 
Variability from Ionic Radius and Charge. These values are given on the 
spreadsheet drns_all_straight in the EXCEL file Eff_MtrxDf_11.xls 
(Column AG, Rows 50 through 109) (DTN: SN0306T0502103.006). The 
resulting CDF yields a distribution given in Figure 6-14, with a range in log space 
of 5.3 to 7.12 cm2/s. The range captures laboratory 3HHO and TcO4
- measured 
values of De on Yucca Mountain tuffs reported by Triay et al. (1993 
[DIRS 145123]) and Rundberg et al. (1987 [DIRS 106481]) and 3HHO, TcO4, and 
14C De reported by Reimus et al. (2002 [DIRS 163008]) and Reimus et al. (2003 
[DIRS 162950]). Additionally, this range incorporates the interpreted diffusion 
coefficients (6.0  10-6 cm2/s and 1.3  10-7 cm2/s) derived from field tests using 
Br-, PFBA (a fluorinated organic acid) as the diffusing species (Reimus et al. 
2003 [DIRS 162950]). 
The distribution for the derived values of effective diffusion coefficient using Equation 6-19 is 
about half an order of magnitude lower than the distribution of values from laboratory and field 
results. This is because the derived distribution scales the effective diffusion coefficient to take 
into account species not measured in laboratory or field experiments, as described in step 3, 
above. The lowest values of effective diffusion coefficient are those for hydrolyzed or 
complexed ions having a low charge and high mass, which would have diffusion coefficients 
about 0.25 times the values for Br- and I- ions. 
To account for uncertainties in De at the lower end, the uncertainty range is expanded to span a 
full 2 orders of magnitude (log De 5.3 to 7.3 with De in units of cm2/s), with the 50-percentile 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-59 October 2004 
log De set at 6.3. When converted to m2/s, it results in a log De (m2/s) range of 9.3 to 11.3, 
with the 50-percentile log De set at 10.3 (see Figure 6-15). The effective matrix diffusion 
coefficient is determined for a particular realization by the parameter DCVO. See Table 6-8 for 
the associated probabilities for the effective matrix diffusion coefficient CDF. 
0.00 
0.20 
0.40 
0.60 
0.80 
1.00
-7.50 -7.00 -6.50 -6.00 -5.50 -5.00 -4.50 
Log Effective Diffusion Coefficient (cm2/sec) 
Cumulative Probability 
TcO4 labmatrix diffusion - 
red dots 
(Rundberg et al. 1987 
[106481] and Triay 1993 
[145126]) 
3HHO lab matrix diffusion - 
green squares 
(Rundberg et al. 1987 
[106481] and Triay 1993 
[145126]) 
Output DTN: SN0306T0502103.006. 
NOTE: The CDF to the left represents values of effective diffusion coefficient derived using Equation 6-19 (black 
asterisks). Included in the plot are laboratory measurements of effective diffusion coefficient from Triay 
1993 [DIRS 145123] and Rundberg et al. 1987 [DIRS 106481] to demonstrate the reasonableness of the 
derived values of effective diffusion coefficient. The CDF to the right represents laboratory and field-derived 
values. 
Yellow Triangles  14C laboratory values; 
Blue Squares  3HHO laboratory values; 
Red Diamonds  TcO4 laboratory values; 
Purple Circles  Br- and PFBA field values 
(Reimus et al. 2002 [DIRS 163008]; Reimus et al. 2003 [DIRS 162950]). 
Figure 6-14. CDFs of Data Used in the Assessment of Uncertainty in Effective Diffusion Coefficient 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-60 October 2004 
Output DTN: SN0310T0502103.009. 
Figure 6-15. CDF of Uncertainty in Effective Diffusion Coefficient 
6.5.2.7 Bulk Density of Alluvium 
For the TSPA-SR, the dry bulk density was considered to be a constant, and set to 1.27 g/cm3 
(CRWMS M&O 2000 [DIRS 147972], Section 6.9). The basis for this parameter value is a set 
of tests performed on four five-foot alluvial intervals from each of the EWDP Boreholes 2D, 9S, 
and 3S, at depths of 395 to 415 feet, 145 to 165 feet, and 60 to 80 feet, respectively 
(DTN: LA0002JC831341.001 [DIRS 147081]). These samples were drill cuttings and thus 
highly disturbed from their condition in the aquifer. The range of the dry bulk density values in 
laboratory columns packed with alluvium from these wells was 1.2 to 1.3 g/cm3. The data are 
presented in Unsaturated Zone and Saturated Zone Transport Properties (U0100) (CRWMS 
M&O 2000 [DIRS 152773], p. 86) with a note stating that densities were measured in the 
laboratory and do not represent in situ conditions. 
The values used in the TSPA-SR were low compared to dry bulk densities measured in alluvium 
at Frenchman Flat and the NTS near Yucca Mountain (Howard 1985 [DIRS 153266], Table 3, 
p. 31, and Table A-1, p. 38). Similarly, a comparison to the range of dry bulk densities of 
alluvial material in general (Manger 1963 [DIRS 154474], pp. E41 to E42) led to the conclusion 
that the values used in the TSPA-SR were likely an underestimate of the true bulk density. 
Consequently, bulk density in the alluvium and its uncertainty has been reevaluated using data 
from the Yucca Mountain area that have been measured at a larger, more representative scale. 
The dry bulk density of the alluvium is used in the computation of the retardation of sorbing 
radionuclides. The dry bulk density is related to the matrix retardation coefficient as indicated in 
Equation 6-2. 
Borehole gravimeter surveys were conducted by EDCON (2000 [DIRS 154704], pp. 1 to 23) at 
well EWDP-19D1 directly south of Yucca Mountain near U.S. Highway 95. A total of 36 values 
of saturated bulk density were estimated, based on the geophysical measurements taken from this 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-61 October 2004 
well (EDCON 2000 [DIRS 154704], p. 3). Seventeen measurements were taken from a depth 
corresponding to the inferred depth of the flow path through the alluvium near Yucca Mountain 
(401.5 to 776 feet). The wet bulk density computed from gravimeter measurements is presented 
in Table 6-11, and also includes the porosity and dry bulk density computed from Freeze and 
Cherry (1979 [DIRS 101173], p. 337): 
grain w 
grain sat 
. . 
. . 
f 
-
- 
= T (Eq. 6-24) 
( ) T f. . - = 1 grain b (Eq. 6-25) 
where .sat is the saturated bulk density [M/L3], .grain is the average grain density for these 
samples [M/L3] (2.52 g/cm3), and .w is the density of water (1.0 g/cm3). 
The average grain density was computed to be 2.52 g/cm3 (2520 kg/m3) from alluvial samples 
from other boreholes in the vicinity of Yucca Mountain (USGS n.d. [DIRS 154495], pp. 3 to 4). 
The grain density varied little (2.49 to 2.55 g/cm3), and so the average was used in the 
computation of the porosity and dry bulk density. 
The mean dry bulk density for this set of measurements was 1.91 g/cm3 (1910 kg/m3). This 
value is close to dry bulk density values previously measured at Frenchman Flat and the NTS in 
similar material at similar depth (Howard 1985 [DIRS 153266], Table 3, p. 31, and Table A-1, 
p. 38), and it is the value used as the mean in the uncertainty distribution. The computed 
standard deviation for these measurements is 0.078 g/cm3. A normal distribution was selected to 
characterize the uncertainty in the dry bulk density based on the frequency plot shown in 
Figure 6-16. The relatively large volume of the medium interrogated by the borehole gravimeter 
method suggests that the variability observed is appropriate for the uncertainty in this parameter 
at the scale of individual grid cells in the SZ transport abstraction model. The CDF of 
uncertainty in bulk density of the alluvium is shown in Figure 6-17. The bulk density in the 
alluvium is specified for a particular realization by the parameter bulk density. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-62 October 2004 
Table 6-11. Measured Saturated Density, Computed Porosity, and Computed Dry Bulk Density for 
Depths from 402 to 776 Feet Below the Surface at the Nye County Well EWDP-19D1 
Sample Depth 
(ft) 
Drift-Corrected Saturated Bulk 
Density, .sat (g/cm3) 
Computed Total 
Porosity, T f 
Computed Dry Bulk 
Density, .b (g/cm3) 
402 2.231 0.190 2.04 
422 2.156 0.239 1.92 
442 2.180 0.224 1.96 
485 2.163 0.235 1.93 
505 2.174 0.228 1.95 
525 2.214 0.201 2.01 
569.95 2.148 0.245 1.90 
589.9 2.142 0.249 1.89 
610 2.105 0.273 1.83 
630 2.079 0.290 1.79 
649.95 2.077 0.291 1.79 
669.95 2.133 0.255 1.88 
690 2.121 0.262 1.86 
715.95 2.158 0.238 1.92 
736 2.143 0.248 1.90 
756 2.105 0.273 1.83 
776 2.239 0.185 2.05 
Source: DTN: MO0105GPLOG19D.000 [DIRS 163480]. 
1.6 1.7 1.8 1.9 2 2.1 2.2 
Dry BulkDensity (g/cm3) 
0
1
2
3
4
5 
Frequency 
NOTE: Normal distribution fit to the data shown with the dashed line. 
Figure 6-16. Histogram of Dry Bulk Density from Borehole Gravimeter Data 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-63 October 2004 
Output DTN: SN0310T0502103.009. 
Figure 6-17. CDF of Uncertainty in Bulk Density of Alluvium 
6.5.2.8 Sorption Coefficients 
Sorption, or adsorption, is the process by which dissolved radionuclides temporarily adhere or 
bond to rock and alluvial substrate along a transport path. Sorption occurs because of the 
electrochemical affinity between the dissolved species and the substrate. The significance of 
sorption to the SZ transport abstraction model and the SZ 1-D transport model is that sorption 
results in a retardation of the radionuclide because part of the radionuclide transport time is spent 
on an immobile surface. 
A linear, equilibrium, sorption coefficient, Kd, is considered appropriate for the radionuclides 
that exhibit sorption during transport because of experimental observations that establish the 
adequacy of this approach. The Kd model also depends on chemical equilibrium between the 
aqueous phase and sorbed phase of a given species. 
The Kd relationship is defined as follows (Domenico and Schwartz 1990 [DIRS 100569], p. 441): 
C K S d = (Eq. 6-26) 
where S [moles/M] is the mass sorbed on the surface of the substrate, and C [moles/L3] is the 
concentration of the dissolved mass. The Kd model determines transport retardation as described 
earlier per Equation 6-2. 
A detailed discussion of the uncertainty distributions for sorption coefficients used in the SZ 
transport abstraction model and the SZ 1-D transport model is given in Site-Scale Saturated Zone 
Transport (BSC 2004 [DIRS 170036], Appendix A). The documentation provided by Site-Scale 
Saturated Zone Transport (BSC 2004 [DIRS 170036], Appendix A) includes the technical bases 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-64 October 2004 
for the values of sorption coefficient for the relevant radionuclides in volcanic units and alluvium 
at Yucca Mountain. 
6.5.2.9 Dispersivity 
Longitudinal dispersion is the mixing of a solute in groundwater that occurs along the direction 
of flow. This mixing is a function of many factors, including the relative concentrations of the 
solute, the velocity pattern within the flow field, and the host rock properties. An important 
component of this dispersion is the dispersivity, a coarse measure of solute (mechanical) 
spreading properties of the rock. The dispersion process causes spreading of the solute in 
directions transverse to the flow path, as well as in the longitudinal flow direction (Freeze and 
Cherry 1979 [DIRS 101173], p. 394). Longitudinal dispersivity will be important only at the 
leading edge of the advancing plume; transverse dispersivity (horizontal transverse and vertical 
transverse) is the strongest control on plume spreading and possible dilution for the 
Yucca Mountain repository (CRWMS M&O 1998 [DIRS 100353], p. LG-12). 
Temporal changes in the groundwater flow field can significantly increase the apparent 
dispersivity displayed by a contaminant plume, particularly with regard to transverse dispersion. 
However, observations of water levels in wells at Yucca Mountain have not indicated large or 
consistent variations (Luckey et al. 1996 [DIRS 100465], pp. 29 to 32), suggesting that 
transience in the SZ flow system would not lead to much greater dispersion. The thick UZ in the 
area of Yucca Mountain likely dampens the response of the SZ flow system to seasonal 
variations or transience in infiltration on time scales of less than centuries. 
These dispersivities (longitudinal, vertical transverse, and horizontal transverse) are used in the 
advection-dispersion equation governing solute transport, and are implemented into the 
SZ transport abstraction model as stochastic parameters. Recommendations from the SZ expert 
elicitation were used as the basis for determining the distribution for longitudinal and transverse 
dispersivity. This expert elicitation was conducted in a manner consistent with Branch Technical 
Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program (Kotra 
et al. 1996 [DIRS 100909]). As part of the expert elicitation, Dr. Lynn Gelhar provided 
statistical distributions for longitudinal dispersivity at 5 km and 30 km (CRWMS M&O 1998 
[DIRS 100353], p. 3-21). These distributions for longitudinal dispersivity are consistent with his 
previous work (Gelhar 1986 [DIRS 101131], pp. 135s to 145s). Modeling Sub Gridblock Scale 
Dispersion in Three-Dimensional Heterogeneous Fractured Media (CRWMS M&O 2000 
[DIRS 152259], p. 53) provided estimates of the transverse and longitudinal dispersion that can 
occur at the subgridblock scale within the SZ site-scale model. The estimation of dispersivity 
using subgridblock scale modeling is also described by McKenna et al. (2003 [DIRS 163578]). 
The results from the subgridblock scale modeling (CRWMS M&O 2000 [DIRS 152259], p. 55) 
are in general agreement with the estimates by the expert elicitation panel (CRWMS M&O 1998 
[DIRS 100353], p. 3-21). However, there is a significant difference in the spatial scale at which 
the analyses in Modeling Sub Gridblock Scale Dispersion in Three-Dimensional Heterogeneous 
Fractured Media (CRWMS M&O 2000 [DIRS 152259]) were conducted (500 m) and the scales 
at which the expert elicitation (CRWMS M&O 1998 [DIRS 100353]) estimates were made 
(5 km and 30 km). Nonetheless, both sources of information on dispersivity are mutually 
supportive. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-65 October 2004 
In the SZ transport abstraction model, the longitudinal dispersivity parameter is sampled as a 
log-transformed parameter, and the transverse dispersivities are then calculated as indicated by 
Saturated Zone Flow and Transport Expert Elicitation Project (CRWMS M&O 1998 
[DIRS 100353], p. 3-21), according to the following relationships: 
200 
L 
h 
a 
a = (Eq. 6-27) 
20000 
L 
v 
a 
a = (Eq. 6-28) 
where L a is the longitudinal dispersivity [L], h a is the transverse horizontal dispersivity [L], and 
v a is transverse vertical dispersivity [L]. 
The longitudinal dispersivity is specified for a particular realization by the parameter LDISP. 
The statistical distribution is a lognormal distribution: E[log10( L a )]: 2.0 and S.D.[log10( L a )]: 
0.75. The CDF of uncertainty in longitudinal dispersivity is shown in Figure 6-18. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-2 -1 0 1 2 3 4 5 6 
Cumulative Probability 
Log Longitudinal Dispersivity (m) 
Output DTN: SN0310T0502103.009. 
Figure 6-18. CDF of Uncertainty in Longitudinal Dispersivity 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-66 October 2004 
Effective Longitudinal Dispersivity in the SZ Transport Abstraction Model 
Longitudinal dispersivity for radionuclide transport simulations in the SZ transport abstraction 
model is specified as a transport parameter. The dispersion process is simulated by the 
random-walk displacement algorithm on the local scale for each time step in the transport 
simulation. In addition, the spatial distribution of hydrogeologic units of contrasting 
permeability within the model imparts additional dispersion to the simulated transport of 
particles as the flow paths diverge to adjacent grid cells of contrasting permeability during 
transport. The effective longitudinal dispersivity simulated by the SZ transport abstraction 
model can be significantly larger than the specified value due to the additive effects of these two 
processes. 
The effective longitudinal dispersivity in the SZ transport abstraction model is analyzed for a 
range of values of specified longitudinal dispersivity to evaluate this effect. A point source 
beneath the repository is used for the analysis. Neither sorption nor matrix diffusion is included 
in the simulations. Effective longitudinal dispersivity is estimated using the relationship from 
Kreft and Zuber (1978 [DIRS 107306]): 
2 
2 . .. 
. 
. .. 
. 
= 
t
t f 
L m 
L s 
a (Eq. 6-29) 
where Lf is the flow path length [L], st 
is the standard deviation in travel time [T], and mt is the 
mean travel time [T]. The standard deviation is estimated from the particle mass breakthrough 
curve at an 18-km distance by taking the difference in time between the arrival of 0.159 fraction 
of the mass (the mean minus one standard deviation for a Gaussian distribution) and the arrival 
of 0.841 fraction of the mass (the mean plus one standard deviation for a Gaussian distribution), 
and dividing by 2. The mean travel time is estimated using the arrival time of 0.500 fraction 
of the mass. 
The results of this analysis are shown in Figure 6-19, with the plotted open circles. The effective 
simulated longitudinal dispersivity is consistently about one order of magnitude higher (bold red 
dashed line) than the specified longitudinal dispersivity (for values of specified longitudinal 
dispersivity of less than 1,000 m). These results indicate that the heterogeneous distribution of 
permeability in the SZ transport abstraction model in the region along the flow path is 
contributing approximately one order of magnitude of dispersivity relative to the specified value. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-67 October 2004 
1 10 100 1000 10000 100000 
Specified Longitudinal Dispersivity (m) 
1 
10 
100 
1000 
10000 
100000 
Effective Simulated Longitudinal Dispersivity (m) 
Figure 6-19. Effective Simulated Longitudinal Dispersivity Versus the Specified Longitudinal Dispersivity 
in the SZ Transport Abstraction Model 
These results indicate that the effective longitudinal dispersivity in the SZ transport abstraction 
model is significantly higher than the value input to the model. In order to avoid the excessive 
effective dispersion in the SZ transport abstraction model, the input value of longitudinal 
dispersivity can be reduced. Based on these results, the value of specified longitudinal 
dispersivity used in the SZ transport abstraction model for the TSPA-LA abstraction simulations 
is adjusted to yield the correct value of effective simulated longitudinal dispersivity. This is 
accomplished by scaling the input value of longitudinal dispersivity down by one order of 
magnitude (i.e., dividing the longitudinal dispersivity by 10) in the input files for each 
realization. 
6.5.2.10 Horizontal Anisotropy in Permeability 
Although a detailed description of the analysis and derivation of the distribution of anisotropy 
ratio in the SZ near the C-wells complex is presented in the Saturated Zone In Situ Testing report 
(BSC 2004 [DIRS 170010], Section 6.2.6), some background information and a short summary 
are presented here. Interpretation of well test data with analytical solutions consists of inferring 
the hydraulic properties of the system from its measured responses, based on an assumed flow 
geometry (i.e., radial). The problem becomes more complicated, however, when the system 
geometry cannot be specified with reasonable certainty. In a layered sedimentary system lacking 
extreme heterogeneity, flow might reasonably be expected to be radial during a hydraulic test. 
When hydraulic tests are conducted at some arbitrary point within a 3-D fractured rock mass, 
however, the flow geometry is complex. Radial flow would occur only if the test were 
performed in a single uniform fracture of effectively infinite extent, or within a network of 
fractures confined to a planar body in which the fractures were so densely interconnected that the 
network behaves like an equivalent porous medium. More likely, flow in fractured tuff is 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-68 October 2004 
nonradial and variable, as fracture terminations and additional fracture intersections were 
reached. Therefore, it must be emphasized that assumptions required in the analytical treatment 
of anisotropy may not be strictly consistent with site geology. 
Through the fractured tuff and alluvium near Yucca Mountain, there is significant heterogeneity 
in hydraulic properties, which not only vary spatially, but also differ depending upon the 
direction in which they are measured (both horizontally and vertically). In the fractured volcanic 
units near Yucca Mountain, preferential orientation of open fractures and/or faults can possibly 
impart significant anisotropy in horizontal permeability to the groundwater flow system. The 
uncertainty in horizontal anisotropy in permeability implicitly accounts for potential undetected 
features, such as fault and fracture zones, that impart preferential directional flow to 
groundwater. In this analysis, transmissivity and storativity are the hydrologic parameters 
required to calculate and define large-scale anisotropy, and their measured values reflect the 
heterogeneity of the media. The concept of anisotropy is typically associated with a 
homogeneous mediuma criterion not met here. Nevertheless, there are clearly spatial and 
directional variations in transmissivity, and the notion remains that, over a large enough 
representative elementary volume, there exists a preferential flow direction that can be termed 
anisotropy. 
Data from the long-term pumping test conducted from May 8, 1996, to November 12, 1997, 
were used to evaluate the anisotropy in the vicinity of the C-wells complex in Saturated Zone 
In-Situ Testing (BSC 2004 [DIRS 170010], Section 6.2.6). After filtering the drawdown data in 
response to pumping at UE-25 c#3, transmissivity and storativity were calculated at four distant 
wells (USW H-4, UE-25 ONC1, UE-25 wt#3, and UE-25 wt#14). 
A distribution of anisotropies must be specified so that an anisotropy ratio can be selected for 
each of the 200 stochastic model realizations used as input to the SZ transport abstraction model. 
Because the current version of the FEHM V2.20 software code [DIRS 161725] can only 
implement anisotropy oriented in alignment with the grid direction, principal directions 
discussed above are not directly applicable in the model. The net result of being unable to 
specify a principal direction is that uncertainty in the anisotropy ratio increases. For example, 
the analytical result for anisotropy using the Cooper-Jacob (1946 [DIRS 150245]) method is a 
ratio of 3.3 in a direction 15 east of north. A projection that orients the principal direction 
north-south (0) results in a new anisotropy ratio of 2.5. In fact, this line of reasoning suggests 
that it is possible for the projected north-south anisotropy ratio to be significantly less than one. 
Based on consultations with USGS staff and with the YMP Parameters Team, and on scientific 
judgment and results from the analytical anisotropy analyses, Figure 6-20a represents the best 
estimate of the PDF for the anisotropy ratio (north-south / east-west) in the SZ near the C-wells 
complex. Figure 6-20b is the corresponding CDF. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-69 October 2004 
Source: DTN: SN0302T0502203.001 [DIRS 163563]. 
Figure 6-20. Probability Density Function (a) and Corresponding CDF (b) for the Uncertainty in 
North-South/East-West Anisotropy Ratio 
There are several noteworthy points based on three distinct regions of the anisotropy ratio 
distribution (DTN: SN0302T0502203.001 [DIRS 163563]). 
 Anisotropy ratio between 5 and 20. The maximum anisotropy ratio of 20:1 is based 
upon the highest calculated anisotropy ratio of 17:1 reported by Ferrill et al. (1999 
[DIRS 118941], p. 7). The maximum reported value of 17:1 was rounded to 20:1 and 
set as the upper limit for horizontal anisotropy. Furthermore, although features such as 
high transmissivity zones and fractures can yield very large anisotropy ratios locally, 
globally, their effects are attenuated, and 20 is a reasonable maximum. The 
5.5 anisotropy ratio calculated by the second approach of the modified 
Papadopulos-PEST method (see Saturated Zone In-Situ Testing (BSC 2004 
[DIRS 170010], Section 6.2.6)) lies in this range, near its highest probability point. 
Therefore, between 5 and 20, a triangular distribution of anisotropy ratio is constructed 
that decreases to zero probability at 20. A 40-percent probability is assigned to this 
portion of the probability density function. 
 Anisotropy ratio between 0.05 and 1. Discussions among Sandia National Laboratories 
(SNL) and USGS staff established that, although it is likely the SZ is anisotropic with a 
principal direction approximately northeast, it is possible the media could be isotropic, 
as well as a small probability that the principal direction could be significantly different 
from north-northeast. Correspondingly, an anisotropy ratio of less than one is possible, 
and the minimum anisotropy ratio is set equal to the inverse of the maximum, 1:20, with 
a triangular distribution of 10 percent probability decreasing to zero at a ratio of 0.05. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-70 October 2004 
An additional Papadopulos solution yielding an anisotropy ratio of 3.5 at 79 west of 
north (BSC 2004 [DIRS 170010], Section 6.2.6) falls in this range. 
 Anisotropy ratio between 1 and 5. A uniformly distributed 50 percent probability is 
assigned to the range of anisotropy ratio between 1 and 5. This interval comprises the 
more likely values of anisotropy ratios, with no specific value more likely than any 
other. It should be noted that in a previous model of the SZ near Yucca Mountain 
(CRWMS M&O 2000 [DIRS 153246], Section 3.8.1.3), anisotropy was binomially 
distributed with a 50 percent probability of isotropy (1:1) and a 50 percent probability of 
a 5:1 ratio. 
It is assumed that the potential anisotropy of permeability in the horizontal direction is 
adequately represented by a permeability tensor that is oriented in the north-south and east-west 
directions. This approach is carried forward from the Saturated Zone In-Situ Testing scientific 
analysis report (BSC 2004 [DIRS 170010], Section 6.2.6). The numerical grid in the SZ 
site-scale flow and transport model is aligned in the north-south and east-west directions, and 
values of permeability may only be specified in directions parallel to the grid. Analysis of the 
probable direction of horizontal anisotropy shows that the direction of maximum transmissivity 
may be about N 15 E, indicating that the anisotropy applied on the SZ transport abstraction 
model grid is within approximately 15 of the inferred anisotropy. 
Figure 6-20(a) and Figure 6-20(b) are the best estimates for the PDF and the CDF, respectively, 
of north-south anisotropy ratios in the SZ to be modeled with the FEHM V2.20 software code 
[DIRS 161725] in the SZ transport abstraction model. Horizontal anisotropy in permeability is 
determined for a particular realization by the parameter HAVO. 
6.5.2.11 Retardation of Colloids with Irreversibly Sorbed Radionuclides 
For TSPA-LA, colloid-facilitated transport of radionuclides in the SZ is simulated to occur by 
two basic modes. In the first mode, radionuclides that are irreversibly attached to colloids are 
transported at the same rate as the colloids, which are themselves retarded by interaction with the 
aquifer material. In the second mode, radionuclides that are reversibly attached to colloids are in 
equilibrium with the aqueous phase and the aquifer material. In this mode of transport, the 
effective retardation of these radionuclides during transport in the SZ is dependent on the 
sorption coefficient of the radionuclide onto colloids, the concentration of colloids, and the 
sorption coefficient of the radionuclide onto the aquifer material. This section deals with the first 
mode of colloid-facilitated transport; Section 6.5.2.12 addresses the second mode. 
The SZ transport simulations of radionuclides that are irreversibly attached to colloids are 
conducted for radioisotopes of Pu and Am. The retardation of colloids with irreversibly attached 
radionuclides is a kinetically controlled process, which approaches equilibrium behavior for long 
transport times. For transport of colloids through the SZ, equilibrium behavior is nearly 
achieved. However, nonequilibrium behavior results in unimpeded migration of some of the 
colloids. Consequently, a small fraction of these colloids is transported through the SZ with no 
retardation, whereas the larger fraction is delayed by a retardation factor. For the SZ transport 
simulations, a small fraction of the radionuclide mass irreversibly attached to colloids is 
transported without retardation, and the remaining fraction of the radionuclide mass is retarded. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-71 October 2004 
A discussion of the fraction of colloids transported with no retardation is in Saturated Zone 
Colloid Transport (BSC 2004 [DIRS 170006], Section 6.6). The fraction of irreversibly sorbed 
to reversibly sorbed radionuclides is determined in the waste-form component of TSPA-LA, and 
is used as input to the SZ transport abstraction model and the SZ 1-D transport model. 
The processes important to the transport of irreversible colloids in the volcanic units of the 
SZ are as follows: advection and dispersion of colloids in the fracture water, exclusion of the 
colloids from the matrix waters, and chemical filtration or adsorption of the colloids onto the 
fracture surfaces. 
Modeling of the advective/dispersive processes is handled as if the colloids were solute in the 
SZ transport abstraction model and the SZ 1-D transport model. Matrix exclusion (i.e., colloid 
transport only in the fractures) in the volcanic units is considered to be appropriate because of the 
large size and small diffusivities of the colloids compared to the solute, plus the possibility of 
similar electrostatic charge of the colloids and the tuff matrix. Matrix exclusion is implemented 
by reducing the values of the effective diffusion coefficients for radionuclides (see 
Section 6.5.2.6 for a discussion of the solute diffusion coefficient) by 10 orders of magnitude, 
thus preventing essentially all matrix diffusion. Chemical (i.e., reversible) filtration of 
irreversible colloids is modeled by applying a retardation factor to the transport in the fractures. 
The implementation of the retardation factor in the SZ transport abstraction model is described in 
Section 6.5.1. 
Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], Section 6.4) describes the 
development of colloid retardation factors for fractured tuff from field and experimental data. 
Figure 6-21 shows the CDF used for retardation factors in the volcanic units for the SZ transport 
abstraction model and Table 6-8 provides the associated probabilities. This CDF is based on the 
uncertainty distribution developed in Saturated Zone Colloid Transport (BSC 2004 
[DIRS 170006], Table 6-2). A log cumulative probability distribution is used because the 
retardation factors span slightly more than two orders of magnitude. Retardation of colloids with 
irreversibly sorbed radionuclides in the volcanic units is specified for a particular realization by 
the parameter CORVO. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-72 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 
Cumulative Probability 
Log Colloid Retardation Factor in Volcanic Units 
Source: DTN: LA0303HV831352.002 [DIRS 163558]. 
Figure 6-21. CDF of Uncertainty in Colloid Retardation Factor in Volcanic Units 
The processes modeled for irreversible colloids in the alluvium are the same as those modeled 
for irreversible colloids in the volcanic units, with the exception of matrix exclusion, because the 
alluvium is modeled as a single porous medium. Saturated Zone Colloid Transport (BSC 2004 
[DIRS 170006], Section 6.5) describes the development of colloid retardation parameters for the 
alluvium using experimental data specific to colloid transport in alluvial material from Yucca 
Mountain, as well as bacteriophage field studies in alluvial material, which are thought to be 
good analogues for colloid transport because of their colloidal size and passive transport 
characteristics. As with irreversible colloids in the volcanic units, filtration in the alluvium is 
modeled by applying a retardation factor to transport in the porous medium. Figure 6-22 shows 
the CDF used for retardation factors in the alluvium for the SZ transport abstraction model, and 
Table 6-8 provides the associated probabilities. This CDF is based on the uncertainty 
distribution developed in Saturated Zone Colloid Transport (BSC 2004 [DIRS 170006], 
Table 6-3). A log cumulative probability distribution is used because the retardation factors span 
slightly more than three orders of magnitude. The implementation of the retardation factor in the 
SZ transport abstraction model is described in Section 6.5.1. Retardation of colloids with 
irreversibly sorbed radionuclides in the alluvium is specified for a particular realization by the 
parameter CORAL. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-73 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.0 1.0 2.0 3.0 4.0 
Cumulative Probability 
Log Colloid Retardation Factor in Alluvium 
Source: DTN: LA0303HV831352.004 [DIRS 163559]. 
Figure 6-22. CDF of Uncertainty in Colloid Retardation Factor in Alluvium 
6.5.2.12 Transport of Radionuclides Reversibly Sorbed on Colloids 
Radionuclides that are reversibly sorbed onto colloids are modeled to be temporarily attached to 
the surface of colloids. Thus, these radionuclides are available for dissolution in the aqueous 
phase, and their transport characteristics are a combination of the transport characteristics of 
solute and colloids. The SZ transport simulations of radionuclides that are reversibly attached to 
colloids are conducted for radioisotopes of Pu, Am, Th, Pa, and Cs, which is consistent with the 
radionuclides selected for reversible sorption (BSC 2004 [DIRS 170025], 6.3.3.1). For these 
transport simulations, radioisotopes of Pu are transported as one group, radioisotopes of Am, Th, 
and Pa are transported as a second group, and Cs is transported as a third species. Americium 
and plutonium can also be transported as irreversibly sorbed onto colloids; see Section 6.5.2.11. 
The Kc parameter is a distribution coefficient that represents the equilibrium partitioning of 
radionuclides between the aqueous phase and the colloidal phase, as given in Equation 6-4. The 
Kc is a function of only radionuclide sorption properties, colloid substrate properties, and colloid 
mass concentration, and not any properties of the immobile media through which transport 
occurs; thus, the same Kc applies to transport of a radionuclide in both the volcanic units and the 
alluvium. 
For TSPA-LA, the coll 
d K uncertainty distributions for Pu, Am, Th, Pa, and Cs were developed in 
Waste Form and In-Drift Colloids-Associated Radionuclide Concentrations: Abstraction and 
Summary (BSC 2004 [DIRS 170025], Table 6-6). Figures 6-23 to 6-25 show the uncertainty 
distributions input to the SZ transport abstraction model for sorption coefficients onto colloids. 
The Ccol uncertainty distribution was also developed in Waste Form and In-Drift 
Colloids-Associated Radionuclide Concentrations: Abstraction and Summary (BSC 2004 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-74 October 2004 
[DIRS 170025], Table 6-4) (see Figure 6-26). Retardation of colloids with reversibly sorbed 
radionuclides is determined for a particular realization by the following uncertain parameters: 
 Conc_Col for groundwater colloid concentrations 
 Kd_Cs_Col for cesium sorption coefficient onto colloids; 
 Kd_Am_Col for americium, thorium, and protactinium sorption coefficients onto 
colloids 
 Kd_Pu_Col for plutonium sorption coefficient onto colloids. 
Implementation of the Kc model in the SZ transport abstraction model is discussed in 
Section 6.5.1. Note that the values given for the parameter vectors of Kd_Pu_Col, Kd_Am_Col, 
and Kd_Cs_Col in Appendix A are the log10-transformed values. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 2.0e05 4.0e05 6.0e05 8.0e05 1.0e06 
Cumulative Probability 
Plutonium Sorption Coefficient onto Colloids ml/g) 
Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. 
Figure 6-23. CDF of Uncertainty in Plutonium Sorption Coefficient onto Colloids 
(mL/g) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-75 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 2.0e06 4.0e06 6.0e06 8.0e06 1.0e07 
Cumulative Probability 
Americium Sorption Coefficient onto Colloids ml/g) 
Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. 
Figure 6-24. CDF of Uncertainty in Americium Sorption Coefficient onto Colloids 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 1.0e03 2.0e03 3.0e03 4.0e03 5.0e03 6.0e03 7.0e03 8.0e03 9.0e03 1.0e04 
Cumulative Probability Cesium Sorption Coefficient onto Colloids (ml/g) 
Source: DTN: SN0306T0504103.006 [DIRS 164131], Table 1. 
Figure 6-25. CDF of Uncertainty in Cesium Sorption Coefficient onto Colloids 
(mL/g) 
(mL/g) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-76 October 2004 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-9 -8 -7 -6 -5 -4 -3 
Cumulative Probability 
Log Groundwater Colloid Concentrations (g/ml) 
Source: DTN: SN0306T0504103.005 [DIRS 164132], Table 3. 
Figure 6-26. CDF of Uncertainty in Groundwater Colloid Concentrations 
Accompanying the Kc model is the partitioning of radionuclides between the aqueous phase and 
the sorbed phase onto the tuff matrix and the alluvium, as described by Kd for the radionuclide 
onto the aquifer material. The Kd uncertainty distributions for americium, plutonium, and cesium 
are described in Table 6-8 (DTN: LA0310AM831341.002, [DIRS 165891]). 
6.5.2.13 Source Regions 
Variations in radionuclide transport pathways and travel times in the SZ from various locations 
beneath the repository are considered by defining four radionuclide source regions at the water 
table. For any particular TSPA-LA realization, a point source of radionuclides is defined within 
each of the four regions for simulation of radionuclide transport in the SZ transport abstraction 
model. A point source of radionuclides in the SZ is appropriate for a single leaking waste 
package or for highly focused groundwater flow along a fault or single fracture in the UZ. 
Whereas a more diffuse source of radionuclides at the water table may be more physically 
realistic for later times when numerous leaking waste packages occur, use of a point source in 
the SZ is an approach that overestimates the concentration of radionuclides near the source. 
The SZ source region locations are based on the extent of the repository design and on the 
general pattern of groundwater flow in the UZ as simulated by the UZ site-scale flow and 
transport model. Variations in the pattern of groundwater flow from the repository to the water 
table exist among infiltration models, ACMs, and climate states for the UZ site-scale model 
(BSC 2004 [DIRS 169861], Section 6.6). The UZ flow and transport simulations indicate 
varying degrees of lateral diversion of groundwater to the east of the repository, and downward 
redirection by interception of flow at major faults. The SZ source region locations are defined to 
accommodate the general range in UZ transport pathways simulated by the suite of UZ site-scale 
flow model simulations. 
(g/mL) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-77 October 2004 
The four SZ radionuclide source regions are shown in Figure 6-27. Note that the CORPSCON 
software code (CORPSCON V5.11.08, STN: 10547-5.11.08-00 [DIRS 155082]) was used to 
convert the coordinates of the repository design (given in state plane coordinates, in meters) to 
Universal Transverse Mercator (UTM) coordinates. The coordinates of the corners of the source 
regions are given in Table 6-8. Source regions 1, 3, and part of 2 are located directly below the 
repository to capture radionuclide transport that occurs vertically downward in the UZ site-scale 
flow and transport model. In addition, regions 1, 2, and 3 are appropriate source locations for 
radionuclides arriving at the water table in the human intrusion scenario (see Total System 
Performance Assessment for the Site Recommendation (CRWMS M&O 2000 [DIRS 153246], 
Section 4.4)), in which a hypothetical borehole penetrates the repository and extends to the SZ. 
Source regions 2 and 4 are located to the east of the repository to capture radionuclide transport 
that is subject to lateral diversion of groundwater to the east along dipping volcanic strata in the 
UZ. Also note, that the northern part of source region 2 underlies a northeasterly extension of 
the repository. 
The random locations of the radionuclide source term for each realization are defined by eight 
stochastic parameters. The parameters SRC1X, SRC1Y, SRC2X, SRC2Y, SRC3X, SRC3Y, 
SRC4X, and SRC4Y determine the x coordinate and y coordinate for the source location within 
regions 1 to 4, respectively. These parameter values are drawn from independent, uniform 
distributions from 0.0 to 1.0. The result is a randomly located point source within each of the 
four source regions for each realization of the SZ transport abstraction model. 
6.5.2.14 Maximum Alluvial Porosity 
The value of maximum or total alluvial porosity is used to calculate the adjusted (or new) Kd 
value in the effective porosity conceptualization of transport in the alluvium (see Equation 6-3). 
The average total porosity of alluvium from corroborative data given in Table 6-10 is 0.35. The 
calculated value of average total porosity in alluvium from the borehole gravimeter data from 
well EWDP-19D1 is significantly lower, as shown in Table 6-11. The approximate average 
value of maximum alluvial porosity from these two sources is 0.30. The uncertainty distribution 
in effective porosity of alluvium is truncated at a maximum value of 0.30 (Figure 6-10). 
6.5.2.15 Average Fracture Porosity 
The value of average fracture porosity of volcanic rocks is used to calculate the retardation factor 
of sorbing radionuclides in the rubblized material of fracture zones. This retardation factor in the 
fracture zones only applies when the flowing interval porosity exceeds the average fracture 
porosity. The average fracture porosity is conceptualized to be the total fracture porosity of the 
volcanic units, not including any matrix porosity in the rubblized material of fracture zones. The 
average fracture porosity is taken as the median of the uncertainty distribution assigned to the 
flowing interval porosity (FPVO) (see Table 6-8), which is equal to 0.001. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-78 October 2004 
Sources: Repository outline from 800-IED-WIS0-00101-000-00A (BSC 2004 [DIRS 164519]) and 800-IED-WIS0- 
00101-000-00A (BSC 2004 [DIRS 164519]). 
NOTE: Repository outline is shown by the solid blue line and the four source regions are shown by the 
dashed red lines. 
Figure 6-27. Source Regions for Radionuclide Release in the SZ Transport Abstraction Model 
6.5.2.16 Average Matrix Porosity 
The value of average matrix porosity of volcanic rocks is used to calculate the retardation factor 
of sorbing radionuclides in the SZ 1-D transport model and in the rubblized material of fracture 
zones. This retardation factor in the fracture zones only applies when the flowing interval 
porosity exceeds the average fracture porosity. The average matrix porosity of volcanic rocks is 
calculated as the average of matrix porosity in hydrogeologic Units 11 through 14, as given in 
Table 6-12. The calculated average matrix porosity is 0.22. 
6.5.2.17 Average Bulk Density of the Volcanic Matrix 
The value of average bulk density of the matrix in volcanic rocks is used to calculate the 
retardation factor of sorbing radionuclides in the SZ 1-D transport model and in the rubblized 
material of fracture zones. This retardation factor in the fracture zones only applies when the 
flowing interval porosity exceeds the average fracture porosity. The average bulk density of the 
volcanic matrix is calculated as the weighted average of bulk density in hydrogeologic Units 13 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-79 October 2004 
through 15, as given in Table 6-13, with double weighting given to Unit 13 because of its 
prominence in the flow path beneath the repository. The calculated average bulk density is 
1.88 g/cm3. 
6.5.2.18 Matrix Porosity of Volcanic Units (Constant) 
Matrix porosity ( fm) is treated as a constant parameter for eight units of the nineteen SZ model 
hydrogeologic units. Constant, in this sense, means that fm will vary from one unit to another 
but, given a particular unit, the porosity is constant for all realizations. The porosity also remains 
spatially constant for each unit. The parameter values and input source(s) are shown in 
Section 4, Table 4-1, and discussed below. 
The following discussion covers data sources used in constant porosity inputs for the affected 
hydrogeologic units. The volcanic Units 11 through 15 do lie in the expected flow paths per the 
SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.6.2). All of the remaining units 
lie outside of any expected SZ model transport paths because they do not exist in this area of the 
model or they occur deeper than the expected flow paths. Thus, the values of matrix porosity 
assigned to the remaining units have no impact on the transport simulations. However, the 
model requires values for fm for all units, regardless of whether they play a role in transport 
simulations; therefore, values as representative as possible were used. 
For the case of Units 15-13, the matrix porosity is based on the values from 
DTN: SN0004T0501399.003. The matrix porosity value for Units 12 and 11 were derived from 
matrix porosity data from the boreholes: UE-25P#1, USW H-3, SD7, USW G-3, USW H-1, 
USW G-4, USW H-5, and USW H-6 (DTNs: SN0004T0501399.003 [DIRS 155045], 
MO0109HYMXPROP.001 [DIRS 155989], MO0010CPORGLOG.002 [DIRS 155229]). Simple 
averages of the wells described above were calculated from the data for Units 12 and 11, as 
shown in spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006). 
Units 10 and 8 are both volcanic confining units. The value of fm for these units was obtained 
from the value for Unit 14, which is a volcanic confining unit for which there are site-specific 
data. The fm value for Unit 9 (volcanic unit) was obtained by averaging the values for the three 
overlying Crater Flat group units (Units 11 - 13). These averages were used as the matrix 
porosity inputs to the SZ site-scale model for their respective units, as shown in Table 6-12. 
6.5.2.19 Bulk Density of the Volcanic Matrix 
Bulk density ( .b 
) is defined by Freeze and Cherry (1979 [DIRS 101173], p. 337) as the 
oven-dried mass of the sample divided by its field volume. It is a factor in Equation 6-2, used 
to determine retardation of a solute due to chemical adsorption in groundwater. That equation is 
employed in the SZ site-scale flow and transport model as part of the FEHM code (Zyvoloski 
et al. 1997 [DIRS 110491], p. 42). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-80 October 2004 
Table 6-12. Values of Matrix Porosity ( fm) for Several Units of the SZ Model 
SZ Unit Name SZ Unit Number Matrix Porosity ( fm) 
Upper Volcanic Aquifer (Topopah) 15 0.15 
Upper Volcanic Confining Unit 
(Calico Hills) 
14 0.25 
Lower Volcanic Aquifer, Prow Pass 13 0.23 
Lower Volcanic Aquifer, Bullfrog 12 0.18 
Lower Volcanic Aquifer, Tram 11 0.21 
Lower Volcanic Confining Unit 10 0.25 
Older Volcanic Aquifer 9 0.21 
Older Volcanic Confining Unit 8 0.25 
Output DTN: SN0310T0502103.010. 
Bulk density is treated as a constant parameter for seventeen of the nineteen units of the 
SZ model hydrogeologic units. Constant, in this sense, means that .b 
varies from one unit to 
another but, given a particular unit, the bulk density stays the same for all realizations. The bulk 
density also remains spatially constant for each unit. Bulk density in hydrogeologic Units 19 and 
7 is treated as an uncertain parameter, and is discussed in Section 6.5.2.7. The parameter values 
and input source(s) are described in Section 4. This section contains a discussion of the analyses 
used to develop the values. The volcanic Units 11 through 15 do lie in the expected flow paths 
per the SZ site-scale flow model (BSC 2004 [DIRS 170037], Section 6.6.2). All of the 
remaining units lie outside of any expected SZ model transport paths, because they do not exist 
in this area of the model or they occur deeper than the expected flow paths. Thus, the values of 
bulk density assigned to the remaining units have no impact on the transport simulations. 
Estimates for bulk density were either based on the use of an analogous unit, or a calculation was 
required, as discussed below. For some units, including part of the volcanic units and the 
carbonate units, the calculation involved averaging a group of referenced bulk density values. 
Some of the volcanic units required the use of a referenced graph to calculate bulk density as a 
certain function of matrix porosity (for which values had already been determined). Finally, two 
units (granite and lava flows) required the use of a general equation that relates bulk density to 
porosity. Many of the calculations required referencing either the matrix porosities or the 
effective porosities that were tabulated in Table 6-12 and Table 6-14, respectively. 
The estimated bulk densities are summarized in Table 6-13, and the methods used to obtain these 
values are summarized in the discussion below. 
Table 6-13. Values of Bulk Density ( .b) for All Units of the SZ Site-Scale Model 
SZ Unit Name SZ Unit Number 
Bulk Density (.b) 
(g/cm3) 
Valley Fill Confining Unit 18 2.50 
Cenozoic Limestone 17 2.77 
Lava Flows 16 2.44 

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MDL-NBS-HS-000021 REV 02 6-81 October 2004 
Table 6-13. Values of Bulk Density ( .b) for All Units of the SZ Site-Scale Model 
(Continued) 
SZ Unit Name SZ Unit Number 
Bulk Density (.b) 
(g/cm3) 
Upper Volcanic Aquifer 
(Topopah) 
15 2.08 
Upper Volcanic Confining Unit 
(Calico Hills) 
14 1.77 
Lower Volcanic Aquifer, Prow Pass 13 1.84 
Lower Volcanic Aquifer, Bullfrog 12 2.19 
Lower Volcanic Aquifer, Tram 11 2.11 
Lower Volcanic Confining Unit 10 1.77 
Older Volcanic Aquifer 9 2.05 
Older Volcanic Confining Unit 8 1.77 
Upper Carbonate Aquifer 6 2.77 
Lower Carbonate Aquifer Thrust 5 2.77 
Upper Clastic Confining Unit 4 2.55 
Lower Carbonate Aquifer 3 2.77 
Lower Clastic Confining Unit 2 2.55 
Granites 1 2.65 
NOTE: Units 19 and 7 are treated as uncertain parameters, and are discussed in 
Section 6.5.2.7. 
Carbonates Units 3, 5, 6, and 17  Bulk density for Units 3, 5, 6, and 17 is determined from an 
average of a series of bulk density values from the Roberts Mountain Formation and the Lone 
Mountain Formation of Borehole UE-25p#1 (DTN: MO0010CPORGLOG.002 [DIRS 155229]). 
A simple average was calculated using these values (see spreadsheet bulkd_matr_eff_La.xls 
[DTN: SN0306T0502103.006]). 
Clastic Units 2, 4, and 18  Bulk density values for Unit 4 are determined from an average of a 
series of sedimentary deposit formation bulk densities from Borehole UE-25P#1 
(DTN: MO0010CPORGLOG.002 [DIRS 155229]). There are no bulk density data available for 
the Clastics hydrogeologic units. A simple average was calculated using these values (see 
spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). The bulk density assigned 
to Unit 4 was used as an analogous value for Unit 2, because Unit 2 is also a clastic confining 
unit. Unit 4 is also used as an analogous unit for Unit 18 because data do not exist for this unit, 
and the value was rounded to 2.5. 
Volcanic Units 8, 10, 13, 14, and 15 - The rock properties model (BSC 2004 [DIRS 170032]) 
contains a graph (Figure 6.4-21) that relates point values of .b 
to fm in volcanic tuff. The graph 
demonstrates a strong linear correlation between the two parameters. The equation for the 
straight-line fit to the scatterplot is shown below (DTN: SN0004T0501399.002 [DIRS 155046]) 
m b f .  - = 8924 . 2 5019 . 2 (Eq. 6-30) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-82 October 2004 
Table 6-8 lists the values of fm for the units (Units 13 - 15) that were used to calculate .b 
. 
Hydrogeologic Units 8 and 10 are volcanic confining units. The value of .b 
for these units was 
obtained from the value for Unit 14, which is a volcanic confining unit for which we have 
site-specific data. 
Volcanic Units 11 and 12  Bulk density for Units 11 and 12 is determined from values of the 
so-called middle volcanic aquifer, which is equivalent to SZ Units 11 and 12 
(DTNs: MO0109HYMXPROP.001 [DIRS 155989] and MO0010CPORGLOG.002 
[DIRS 155229]). The bulk density values come from Boreholes SD7, USW H-1, UE-25b#1, 
J-13, UE-25a#1, USW GU-3, USW G-3, USW G-4, UE-25p#1, and USW G-1. A simple 
average was calculated from those values (see spreadsheet bulkd_matr_eff_La.xls 
[DTN: SN0306T0502103.006]). 
Volcanic Unit 9  Unit 9 is a volcanic aquifer. Its value was obtained by averaging the values 
for the three overlying volcanic Crater Flat group units (Units 11 - 13) and Unit 15. 
Lava Flows (Unit 16) and Granites (Unit 1)  The values of bulk density for these units are 
calculated from Equation 6-25. A representative value that is appropriate for .grain is 2.65g/cm3 
(Hillel 1980 [DIRS 101134], p. 9). As both of these units are not in the transport model path, it 
is suitable to use the particle density value and effective porosity to calculate bulk density 
(Equation 6-31) (see spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). The 
effective porosity values were used for Equation 6-31 because the effective porosity is very 
similar to the total porosity for the lava flow and granite units. The porosity values were taken 
from Table 6-12. The lava flow unit has an effective porosity of 0.08, and the granite unit has a 
porosity of 0.0001. Therefore, the bulk densities assigned for those units are 2.44 and 
2.65 g/cm3, respectively. 
6.5.2.20 Effective Porosity 
Effective porosity ( fe 
) is treated as a constant parameter for nine of the nineteen SZ model 
hydrogeologic units. Constant, in this sense, means that fe 
varies from one unit to another but, 
given a particular unit, the porosity is the same for all realizations. The effective porosity is also 
homogeneous within each unit. The input source(s) are described in Section 4, Table 4-1. 
The nine hydrogeologic units discussed in this section do not occur within the flow path from 
beneath the repository; therefore, these values do not impact the simulated transport of 
radionuclides. However, representative values are used. The Bedinger et al. report (1989 
[DIRS 129676], Table 1, p. A18) includes hydrogeologic data for the Basin and Range Province 
of the Southwestern U.S. The Bedinger et al. report covers a region that extends into eight states 
and includes the Yucca Mountain site. The Bedinger et al. report was used as the source for data 
on the Valley Fill Confining Unit (18), the Cenozoic Limestone Unit (17), Lava Flow Unit (16), 
Upper Carbonate Aquifer Unit (6), Lower Carbonate Aquifer Thrust Unit (5), Upper Clastic 
Confining Unit (4), Lower Carbonate Aquifer Unit (3), Lower Clastic Confining Unit (2) and the 
Granites Unit (1). All of the carbonate units were assigned the same value. 
The effective porosity values (Bedinger et al. 1989 [DIRS 129676], Table 1, page A18; 
DTN: MO0105HCONEPOR.000 [DIRS 155044]) are used for all of the hydrogeologic units 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-83 October 2004 
described in this paragraph. The upper carbonate aquifer, the lower carbonate aquifer, the lower 
carbonate thrust aquifer, and the Cenozoic limestone units (designated as Units 6, 3, 5, and 17 
respectively) use the mean value of Carbonate Rocks. The Cenozoic Limestone Unit is assigned 
the same value as the carbonate units because it is a similar rock type to the carbonate rocks. 
The value for granites (Unit 1) is set equal to the estimate for metamorphic rock with a depth 
more than 300 m. Unit 16 is assigned the average of the Lava Flows, fractured and moderately 
dense, from the DTN: MO0105HCONEPOR.000 [DIRS 155044] source. Units 4 and 2 utilize 
the mean value from the Clastic Sedimentary Units. Unit 18 utilizes the Basin fill mean value 
for fine-grained clay and silt cited by Bedinger et al. (1989 [DIRS 129676], Table 1). This 
information is summarized in the spreadsheet geonames.xls (DTN: SN0306T0502103.006). 
Table 6-14 lists the constant values used for each unit, for the SZ transport abstraction model for 
TSPA-LA. 
Table 6-14. Values of Effective Porosity ( fe) for Several Units of the SZ Transport Abstraction Model 
SZ Unit Name SZ Unit Number Effective Porosity ( fe) 
Valley Fill Confining Unit 18 0.32 
Cenozoic Limestone 17 0.01 
Lava Flows 16 0.08 
Upper Carbonate Aquifer 6 0.01 
Lower Carbonate Aquifer Thrust 5 0.01 
Upper Clastic Confining Unit 4 0.18 
Lower Carbonate Aquifer 3 0.01 
Lower Clastic Confining Unit 2 0.18 
Granites 1 0.0001 
Output DTN: SN0310T0502103.009. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-84 October 2004 
6.5.3 Summary of Computational Models 
Both the SZ transport abstraction model and the SZ 1-D transport model are intended for use in 
the analyses for TSPA-LA. The results of the multiple realizations of SZ transport with the SZ 
transport abstraction model, in the form of multiple breakthrough curves, are coupled with the 
TSPA-LA simulations using the convolution integral method. The SZ 1-D transport model is 
intended for direct incorporation into the TSPA-LA model. The SZ 1-D transport model is 
developed independently of the TSPA-LA model, but contains the elements necessary for 
implementation within the TSPA-LA model. 
The results of the SZ transport abstraction model and the SZ 1-D transport model are combined 
for calculating dose for comparison to the individual protection standard in the following way: 
the mass arriving at the accessible environment of the following radionuclides is simulated, using 
the SZ transport abstraction model: 14C, 90Sr, 99Tc, 129I, 135Cs, 137Cs, 232U, 243Am, 241Am, 240Pu, 
242Pu, 239Pu, 237Np, 236U, 238U, 238Pu, and 234U. Note, transport of the actinides listed above (with 
the exception of 232U) is also simulated with the SZ 1-D transport model, but only the subsequent 
daughter products in the four decay chains are taken as output from the SZ 1-D transport model. 
The mass arriving at the accessible environment of the following radionuclides is simulated with 
the SZ 1-D transport model (or assumed to be in secular equilibrium with their respective 
parents): 235U, 233U, 232Th, 231Pa, 229Th, 229Ra, 230Th, and 226Ra. 
6.5.3.1 SZ Transport Abstraction Model 
The groups of radioelements for simulated transport in the SZ transport abstraction model 
are summarized in Table 6-15. There are 10 groupings of radionuclides noted in the first column 
of Table 6-15. The modes of radionuclide transport are: 
1. As solute, 
2. As colloid-facilitated transport of radionuclides reversibly attached to colloids, and 
3. As colloid-facilitated transport of radionuclides irreversibly attached to colloids. 
As indicated in Table 6-15, the nonsorbing radionuclides of carbon, technetium, and iodine are 
grouped together because their migration is identical. Americium, thorium, and protactinium 
reversibly attached to colloids are grouped together because of their similar sorption 
characteristics. Note that plutonium and americium may be transported both reversibly and 
irreversibly attached to colloids. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-85 October 2004 
Table 6-15. Radioelements Transported in the SZ Transport Abstraction Model 
Radionuclide 
Number Transport Mode Radioelements 
1 Solute Carbon, Technetium, Iodine 
2 Colloid-Facilitated 
(Reversible) 
Americium, Thorium, Protactinium 
3 Colloid-Facilitated 
(Reversible) 
Cesium 
4 Colloid-Facilitated 
(Reversible) 
Plutonium 
5 Solute Neptunium 
6 Colloid-Facilitated 
(Irreversible) 
Plutonium, Americium 
7 Solute Radium 
8 Solute Strontium 
9 Solute Uranium 
10 Colloid-Facilitated 
(Fast Fraction of 
Irreversible) 
Plutonium, Americium 
Output DTNs: SN0310T0502103.010 and SN0310T0502103.012. 
The radionuclide breakthrough curves from the SZ transport abstraction model for the 
200 Monte Carlo realizations of SZ flow and transport are generated as follows: a steady-state 
groundwater flow field is produced for each of the 200 realizations prior to transport simulations. 
Variations in the groundwater specific discharge are included by scaling all values of 
permeability in the base-case SZ site-scale flow model (BSC 2004 [DIRS 170037]) and the 
values of specified recharge, using the value of the GWSPD parameter. Variations in horizontal 
anisotropy in permeability are included by scaling the values of north-south and east-west 
permeability within the zone of volcanic rocks influenced by anisotropy, using the value of the 
HAVO parameter. Each steady-state groundwater flow solution is stored to be used as the initial 
conditions in the radionuclide transport simulations. The SZ_Pre V2.0 software code 
(STN: 10914-2.0-00, SNL 2003 [DIRS 163281]) is a preprocessor that is used to prepare the 
FEHM V2.20 software code [DIRS 161725] input files for each of the 200 realizations. The 
preprocessor reads the values of the parameters from an input file containing a table of values for 
all 200 realizations, performs relevant parameter transformations, and writes the appropriate 
values to the various FEHM V2.20 software code [DIRS 161725] input files. A total of 
7,200 individual simulations (200 realizations  9 radioelement groups  4 source regions) of 
SZ transport are conducted, and the particle tracking output files are saved. The particle tracking 
simulations of matrix diffusion use the type curves of the analytical solution for matrix diffusion 
in DTN: LA0302RP831228.001 [DIRS 163557]. The SZ_Post V3.0 software code 
(STN: 10915-3.0-00, SNL 2003 [DIRS 163571]) is a post-processor that is used to extract the 
breakthrough curves from the FEHM V2.20 software code [DIRS 161725] output files, and 
concatenate all 200 realizations into a single file for input to the SZ_Convolute V3.0 software 
code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]), for use in the TSPA-LA. 
For implementation of the SZ transport abstraction model in the TSPA-LA model, the specific 
radionuclides and the timing of climate change events must be specified in the control file for the 
SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). The 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-86 October 2004 
radionuclides for each radioelement and their corresponding values of half-life are specified in 
order for the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 
[DIRS 164180]) to calculate the decay of these radionuclides during simulated transport in the 
SZ. The number of climate states and the times at which climate changes occur during the 
TSPA-LA model simulation are also specified in the control file for the SZ_Convolute 
V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). The multiplier of 
groundwater flow rate in the SZ (relative to present conditions) for each climate state is also 
specified for the TSPA-LA simulation. The values for this factor are given in Table 6-5. 
6.5.3.2 SZ 1-D Transport Model 
Implementation of the SZ 1-D transport model in the TSPA-LA model requires that the 
stand-alone version of the model developed in this report be correctly integrated into the 
TSPA-LA model. The SZ 1-D transport model was developed in anticipation of integration into 
the TSPA-LA model, but the following aspects of the integration are required for implementation 
in the TSPA-LA model: 
The radionuclide flux into and out of the SZ 1-D transport model must be properly 
linked to the other components of the TSPA-LA model. The radionuclide decay 
and ingrowth chains and the corresponding half-life values of radionuclides must 
be consistent with the other components of the TSPA-LA model. The parameter 
values for the 200 realizations of the SZ transport abstraction model are stored as a 
table in the TSPA-LA model, and the SZ 1-D transport model must be correctly 
linked with this table of values to ensure consistency with the SZ transport 
abstraction model on a realization-by-realization basis. The parameter vectors used 
in the SZ transport abstraction model that need to be incorporated into the table 
values used by the SZ 1-D transport model are contained in Appendix A of this 
report and in DTN: SN0310T0502103.009. The variable controlling changes in 
climate state in the TSPA-LA model must be correctly linked with the SZ 1-D 
transport model. 
6.6 BASE-CASE MODEL RESULTS 
Base-case model results from the SZ transport abstraction model consist of radionuclide mass 
breakthrough curves at the accessible environment of the biosphere, approximately 18 km 
downgradient from the repository. A suite of breakthrough curves is generated for each species 
or class of radionuclides based on multiple realizations of the model. Variability in the results 
among these multiple realizations reflects uncertainty in groundwater flow and radionuclide 
transport behavior in the SZ. Variations in transport behavior among the species are also 
represented in these results. 
6.6.1 Overview 
The results of the 200 SZ transport abstraction model realizations are shown in Figures 6-28 to 
6-36. Each figure shows the relative mass arriving at the accessible environment as a function of 
time and a histogram of median transport times, for a given category of radionuclides from 
Table 6-15. Note that the breakthrough curves and transport times shown in these figures are for 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-87 October 2004 
a continuous, steady source at the water table below the repository (source region 1), initiated at 
time equal to zero. Transport simulation results for source region 1 are representative of results 
for all of the source regions; there are no dramatic variations among the source regions in 
simulated radionuclide transport times for any given realization. Note that the breakthrough 
curves shown in these figures are for present climatic conditions, and do not include the effects 
of radioactive decay. Recall that the process of radioactive decay is implemented in the 
SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 2003 [DIRS 164180]). 
Although individual breakthrough curves can be difficult to discern in some of the figures, both 
the timing and the shapes of the breakthrough curves vary among the realizations. Variability in 
the timing of the breakthrough is reflected in the histograms of median transport time, for the 
bulk of the radionuclide mass arrival at the accessible environment. Variability in the shapes of 
the breakthrough curves is a function of differences in matrix diffusion and dispersivity among 
the realizations. 
The results differ from the results presented in SZ Flow and Transport Model Abstraction 
(BSC 2003 [DIRS 164870], Section 6.6) for neptunium, plutonium reversibly attached to colloid, 
cesium reversibly attached to colloids, and uranium. However, the results presented here for the 
breakthrough curves do not differ significantly from the results in SZ Flow and Transport Model 
Abstraction (BSC 2003 [DIRS 164870]) for transport times of less than 100,000 years, given the 
overall uncertainty among the 200 realizations. 
In addition, simulated breakthrough curves for the fast fraction of plutonium and americium 
irreversibly attached to colloids are developed for this report, as shown in Figure 6-37. 
Transport of these radionuclides in the SZ is simulated to occur with no retardation of colloids in 
the volcanic units or alluvium, and with no matrix diffusion in the volcanic units. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-88 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-28. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Carbon, 
Technetium, and Iodine at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-89 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-29. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Americium, 
Thorium, and Protactinium on Reversible Colloids at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-90 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-30. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Cesium on 
Reversible Colloids at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-91 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-31. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Plutonium on 
Reversible Colloids at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-92 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-32. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Neptunium at 
18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-93 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-33. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Plutonium and 
Americium on Irreversible Colloids at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-94 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-34. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Radium at 
18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-95 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-35. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Strontium at 
18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-96 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.010. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-36. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for Uranium at 
18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-97 October 2004 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
Output DTN: SN0310T0502103.012. 
NOTE: Mass breakthrough curves and median transport times are for present-day climate, and do not include 
radionuclide decay. Results shown for 200 realizations from source region 1. 
Figure 6-37. Mass Breakthrough Curves (upper) and Median Transport Times (lower) for the Fast 
Fraction of Plutonium and Americium on Irreversible Colloids at 18-km Distance 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-98 October 2004 
6.6.2 Summary of Results 
SZ transport simulation results with the SZ transport abstraction model for the nonsorbing 
radionuclides of carbon, technetium, and iodine indicate that variability in simulated median 
transport times to the boundary of the accessible environment ranges from a few tens of years to 
100,000 years. The bulk of the realizations show transport times ranging from a few hundred 
years to a few thousand years for nonsorbing species, and a median transport time among all of 
the realizations of about 640 years. 
Approximately 97 percent of the realizations of americium, protactinium, and thorium 
transported as reversibly sorbed onto colloids have simulated transport times of greater than 
100,000 years. Approximately 99 percent of the realizations of cesium transported as reversibly 
sorbed onto colloids have simulated transport times of greater than 100,000 years. 
Simulated median transport times for plutonium reversibly sorbed on colloids range from a few 
thousand years to greater than 100,000 years, with a majority of the realizations indicating 
transport times of greater than 100,000 years. The simulated breakthrough curves for neptunium 
range from less than 100 years to greater than 100,000 years, with a median transport time 
among the realizations of about 18,000 years. Simulated median transport times for plutonium 
and americium irreversibly attached to colloids range from a few hundred years to greater than 
100,000 years, with a median among the realizations of about 18,000 years. 
About 99 percent of the realizations of radium transport have simulated transport times of greater 
than 100,000 years. Greater than 99 percent of the realizations of strontium transport have 
simulated transport times of greater than 10,000 years, with the majority of the realizations 
having median transport times of greater than 100,000 years. Simulated median transport times 
for uranium range from somewhat less than 1,000 years to greater than 100,000 years, with a 
median transport time among the realizations of about 24,000 years. Simulated median transport 
times for plutonium and americium irreversibly attached to the fast fraction of colloids (i.e., with 
no retardation) range from a few tens of years to greater than 10,000 years, with a median among 
the realizations of about 300 years. 
6.7 DESCRIPTION OF BARRIER CAPABILITY 
The SZ forms a barrier to the migration of radionuclides and to the exposure of the potential 
receptor population to these radionuclides in two ways. Delay in the release of radionuclides to 
the accessible environment during transport in the SZ allows radioactive decay to diminish the 
mass of radionuclides that are ultimately released. Dilution of radionuclide concentrations in 
groundwater used by the potential receptor population occurs during transport in the SZ and in 
the process of producing groundwater from wells. Further discussion of the SZ flow system as a 
barrier to radionuclide migration at Yucca Mountain is found in a report by Eddebbarh et al. 
(2003 [DIRS 163577]). 
6.7.1 Analyses of Barrier Capability 
The simulated transport times of radionuclides in the SZ give a direct indication of the barrier 
capability of the SZ with regard to the delay in the release of radionuclides to the accessible 
environment. Uncertainty in the radionuclide transport times in the SZ is represented in the 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-99 October 2004 
multiple realizations of the SZ system with the SZ transport abstraction model and shown in the 
breakthrough curves for various radionuclides in Figures 6-28 to 6-36. As shown by these 
figures, the effectiveness of the SZ as a barrier to transport varies significantly among the classes 
of radionuclides included in the analyses. The ranges of median transport times and the median 
transport times from all realizations for the various radionuclides are summarized in Table 6-16. 
Variations in the radionuclide transport time among the realizations shown in Figures 6-28 to 
6-36 reflect the aggregate uncertainty in the underlying input parameters to the SZ transport 
abstraction model. Although formal sensitivity analyses have not been applied to these results, 
sensitivity analyses have been performed on similar previous SZ transport modeling results 
(Arnold et al. 2003 [DIRS 163857]). The SZ transport abstraction model has not been 
significantly changed and the parameter uncertainty distributions have not been dramatically 
changed in the present modeling, relative to the modeling analyzed in Arnold et al. (2003 
[DIRS 163857]). Consequently, the general conclusions from the study are expected to apply to 
the current modeling. The analyses in Arnold et al. (2003 [DIRS 163857]) indicate that 
uncertainties in groundwater specific discharge, sorption coefficients, and retardation of colloids 
are major factors in the simulated uncertainty in radionuclide transport times. Parameters related 
to matrix diffusion and geologic uncertainty have significant, but secondary importance with 
regard to the uncertainty in radionuclide transport times. 
For nonsorbing species, such as carbon, technetium, and iodine, the delay afforded by the SZ can 
be less than 100 years to as much as 100,000 years, within the range of uncertainty indicated by 
the simulation results shown in Figure 6-28. The median transport time for nonsorbing species 
among all realizations is about 620 years. For the moderately sorbing species of neptunium, 
simulated median transport times range from about 200 years to greater than 100,000 years, with 
a median transport time among all realizations of 17,100 years (see Table 6-16). For the strongly 
sorbing species of radium, simulated median transport times range from 80,200 to greater than 
100,000 years, with a median transport time among all realizations of greater than 100,000 years 
(see Table 6-16). 
Analyses with the SZ transport abstraction model indicate that there is considerable uncertainty 
in the delay to release of radionuclides to the accessible environment for all radionuclides. The 
upper bounds of uncertainty in the transport times are greater than 100,000 years (the upper limit 
of time in the transport simulations) for all radionuclides, with the exception of the fast fraction 
of plutonium and americium irreversibly attached to colloids. The lower bounds of the 
uncertainty in transport times are indicated by the ranges given in Table 6-16. 
It should be noted that the summary of simulated transport times presented in Table 6-16 is given 
for SZ groundwater flow under present climatic conditions. Under glacial-transition climatic 
conditions that are expected to occur within the next 10,000 years, the groundwater flow rate 
would be significantly higher. Groundwater flow rates in the SZ are estimated to be 3.9 times 
higher under glacial-transition climate conditions (see Section 6.5.1) corresponding to transport 
times of approximately 3.9 shorter than those presented in Table 6-16. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 6-100 October 2004 
Table 6-16. Summary of Simulated Transport Times in the SZ Under Present Climatic Conditions 
Species 
Range of Median Transport 
Time (years) 
Median Transport Time Among 
All Realizations (years) 
Carbon 
Technetium 
Iodine 
20 - >100,000 
620 
Reversible Colloids: 
Americium 
Thorium 
Protactinium 
25,000 - >100,000 
>100,000 
Reversible Colloids: 
Cesium 
80,000 - >100,000 >100,000 
Reversible Colloids: 
Plutonium 
5,000 - >100,000 >100,000 
Neptunium 200 - >100,000 17,100 
Irreversible Colloids: 
Plutonium 
Americium 
200 - >100,000 
19,400 
Radium 80,200 - >100,000 >100,000 
Strontium 3,300 - >100,000 >100,000 
Uranium 600 - >100,000 23,300 
Fast Fraction of Irreversible Colloids: 
Plutonium 
Americium 
20  32,620 310 
6.7.2 Summary of Barrier Capability 
Taken as a whole, these analyses indicate that the SZ is expected to be a significant barrier to the 
transport of radionuclides to the accessible environment within the 10,000-year period of 
regulatory concern for the repository at Yucca Mountain. The expected behavior of the 
SZ system is to delay the transport of sorbing radionuclides and radionuclides associated with 
colloids for many thousands of years, even under future wetter climatic conditions. Nonsorbing 
radionuclides are expected to be delayed for hundreds of years during transport in the SZ. 
However, analyses of uncertainty in radionuclide transport in the SZ indicate that delays in the 
release of nonsorbing radionuclides could be as small as tens of years. The transport times in the 
SZ of neptunium, uranium, and of plutonium and americium irreversibly attached to colloids 
could be as small as hundreds of years, based on the analyses of uncertainty conducted with the 
SZ transport abstraction model. It is important to note that ranges of uncertainty based on 
analyses with 200 Monte Carlo realizations extend to relatively low probability (approximately 
0.5 percent probability) and thus include relatively unlikely results. Nonetheless, lower values in 
the ranges of transport time are possible, given the degree of uncertainty included in the model. 
The radioactive decay of radionuclides during transport in the SZ enhances the barrier capability 
of the SZ by reducing the mass of radionuclides ultimately released to the accessible 
environment. The effectiveness of the decay process in attenuating releases from the SZ is 
related to the delay in the SZ and the half-life of the radionuclide. For radionuclides with longer 

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MDL-NBS-HS-000021 REV 02 6-101 October 2004 
transport times in the SZ and relatively short half-lives, this process renders the SZ an extremely 
effective barrier. Strontium-90 and 137Cs transport times would exceed several thousand 
half-lives, i.e., greater than 100,000 years, based on the median transport time among the 
realizations (Table 6-16). For comparison, the reduction in radioactivity after 20 half-lives is 
more than six orders of magnitude. For some radionuclides, a modest reduction in radionuclide 
mass would occur during transport in the SZ. Plutonium-239 that is irreversibly attached to 
colloids would be expected to experience about 0.8 half-lives, based on the median transport 
time among all realizations (Table 6-16). Several radionuclides would experience little 
attenuation due to radioactive decay during transport in the SZ. Technetium-99, 129I, and 237Np 
would have only very small reductions in mass during the delay in release afforded by the SZ, 
due to their long half-lives (2.13  105 years for 99Tc to 1.59  107 years for 129I). 
The dilution of radionuclides in the SZ and during pumping from wells by the future 
hypothetical community in which the RMEI resides is not quantitatively assessed with the 
transport modeling approach used in the SZ transport abstraction model. The relatively low 
values of transverse dispersivity in the uncertainty distribution for this parameter suggest that a 
large amount of dilution in radionuclide concentration during transport from beneath the 
repository to the accessible environment in the SZ is not expected. It is likely that the amount of 
dilution implicit in averaging the concentration of radionuclides in 3,000 acre-ft/year of the 
representative volume of groundwater would be greater than the dilution during transport in the 
SZ. 
6.8 GROSS ALPHA CONCENTRATION 
Regulations in 10 CFR 63.331 (10 CFR 63 [DIRS 156605]) limit the gross alpha concentration 
and 226Ra and 228Ra concentration in groundwater. These groundwater protection standards 
apply to the accessible environment in the Yucca Mountain region and potential impacts of the 
repository must be compared to them. One aspect of the analysis is an assessment of the natural 
background concentrations in groundwater near the site because the standards for both gross 
alpha activity and combined 226Ra and 228Ra activity concentrations (respectively 15 pCi/L and 
5 pCi/L (picocuries per liter (pCi/L)), 10 CFR 63 [DIRS 156605], Section 63.331, Table 1) are 
inclusive of natural background concentrations. 
6.8.1 Gross Alpha Activity Data 
A testing program to measure ambient radiation levels in groundwater was conducted in 
FY 1998. This work was performed under the YMP QA program. Groundwater samples were 
collected in June, July, and September of 1998 from each of six wells and two springs. The 
details and findings of this evaluation were reported in Radioactivity in FY 1998 Groundwater 
Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420]). 
The data of interest for this study are the reported gross alpha concentrations (picocuries per liter 
(pCi/L)) (CRWMS M&O 1999 [DIRS 150420], Section 3.2.1, Table 3) and submitted, with 
gross beta measurements, to the Total Management Data System as 
DTN: MO9904RWSJJS98.000 [DIRS 165866]. 
In Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near Yucca 
Mountain (CRWMS M&O 1999 [DIRS 150420], p. 9) it was stated that, when gross alpha 

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MDL-NBS-HS-000021 REV 02 6-102 October 2004 
concentrations in groundwater exceed 5 pCi/L, calculation of average combined 226Ra and 228Ra 
concentration was required. However, Radioactivity in FY 1998 Groundwater Samples from 
Wells and Springs Near Yucca Mountain (CRWMS M&O 1999 [DIRS 150420], Section 3.2.1) 
demonstrates the mean gross alpha concentration at each sample location was below 5 pCi/L in 
FY 1998, and continues by stating that in such cases, it was not necessary to calculate combined 
226Ra and 228Ra concentration. As a consequence, data concerning 226Ra and 228Ra 
concentrations were not presented. 
6.8.2 Counting Statistics and Error Prediction 
Because of the random nature of radioactive decay and the relatively low concentrations of alpha 
emitting radionuclides in natural groundwater, it is necessary to understand the statistical 
fluctuations of the analytical method in relation to uncertainty. 
6.8.2.1 Counting Statistics and Uncertainty 
The following discussions on the statistics of radioactive decay measurements are taken from 
Radiation Detection and Measurement (Knoll 1989 [DIRS 161052], Chapter 3). When a counter 
is used to detect the number of radioactive decays in a given period of time, the counts from 
multiple trials have a Poisson distribution. If a single measurement is taken of n counts, then the 
estimate of the actual average number of counts ( n ) in that period is n (Knoll 1989 
[DIRS 161052], p. 84). Furthermore, the sample variance (s2) is also n, implying that the 
standard deviation (s) is n0.5 (Knoll 1989 [DIRS 161052], p. 85). For large values of n, the 
Poisson distribution can be approximated by a normal (i.e., Gaussian) distribution, thereby 
allowing confidence limits for the true mean ( n ) to be established. Measurements involving 
radioactive decay are generally conducted for sufficient time to establish conditions for this 
approximation to be valid. One example given by Knoll 1989 [DIRS 161052], Table 3-6, is for a 
measurement of n = 100, then there is a 90 percent probability that the true mean ( n ) is in the 
interval s  64 . 1 n , or 83.6 to 116.4. The symmetry of the normal distribution indicates that in 
this example, that there is a 5 percent chance of the true mean being below 83.6 and a 5 percent 
chance of it being above 116.4. 
6.8.2.2 Uncertainty Propagation 
Measurements involving the counting of radioactive decay events are subject to spurious counts 
from natural background radiation. The effect of this natural background on the desired results 
can be negated to a certain extent by performing the measurement twice, once with the sample to 
be quantified and once without the sample. The former measurement gives a count of the 
desired signal plus unwanted background noise, while the latter provides an estimate of the 
background noise. If the counting times for both trials are equal, then the net counts from the 
sample to be characterized is then the difference between the two measured counts. 
Following the approach presented by Knoll (1989 [DIRS 161052], p. 88), if there were two 
counts taken the first x being associated with the sample and background noise and the second y 
corresponding to the background noise, then the net counts attributable to the sample being 

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MDL-NBS-HS-000021 REV 02 6-103 October 2004 
assessed is the difference between x and y. The variance (s2) associated with the net value is the 
sum of the variances of the two measurements: 
2 2 2 
y x net s + s = s (Eq. 6-31) 
Because of the stochastic nature of both radioactive decay and background radiation, it is 
possible for a sample of low activity to give rise to a total count that is lower than the 
independently measured background count. These cases produce a negative estimate for the net 
sample activity. If these measurements to quantify a small level of activity were to be repeated 
several times, then the stochastic nature of the processes will result in a range of net activity 
estimates. Some of these results would underestimate the true activity while others would 
overestimate the true value. Combining the data sets allows the random fluctuations observed in 
single measurements to be averaged over multiple measurements and thereby reduce statistical 
variations. This approach is adopted here. 
If there are n measurements of a variable x, where measurement i is denoted by xi having a 
variance of 2
i s (number of counts) then the average ( x ) is given by: 
. = 
n 
i x 
n 
x 
1 
1 (Eq. 6-32) 
Knoll (1989 [DIRS 161052], Equations 3-38 and 3-40) provides an estimate of the standard 
deviation ( x s ) in x as: 
.s = s 
n 
i x n 1 
2 1 (Eq. 6-33) 
6.8.3 Applicable Sample Locations 
Gross alpha concentration data in groundwater from eight locations in the vicinity of the receptor 
were collected in Radioactivity in FY 1998 Groundwater Samples from Wells and Springs Near 
Yucca Mountain (CRWMS M&O 1999 [DIRS 150420]). Six of these locations were identified 
as being in the subbasin (Alkali Flat-Furnace Creek Subbasin) that contains Yucca Mountain, as 
shown in the first column of Table 6-17 (DTN: MO9904RWSJJS98.000 [DIRS 165866]). The 
data from these six locations were selected to be the basis of estimating the groundwater gross 
alpha concentration at the receptors location. The data from the Cherry Patch Well and 
Fairbanks Spring were not used, as these locations are not in the groundwater subbasin 
containing the repository. 
It was appreciated that other weighting schemes to obtain a mean activity level from these data 
were available. Weights could be based on some function of distance of the sampled wells from 
the receptor location or on the uncertainties of the individual measurements. In the interests of 
keeping the analysis simple without having to provide justification from any particular scheme, it 
was elected to use simple averaging. 

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MDL-NBS-HS-000021 REV 02 6-104 October 2004 
6.8.4 Data Analysis 
The calculation of the mean activity values and the estimated standard deviation is shown in 
Table 6-17. It should be noted that the measurements of gross alpha concentrations on these 
groundwater samples are for all alpha emitters, whereas the regulations in 10 CFR 63.331 
(10 CFR 63 [DIRS 156605]) exclude radon and uranium from the standard for gross alpha 
activity. Consequently, the measurements shown in Table 6-17 overestimate the gross alpha 
activity exclusionary of radon and uranium. 
Table 6-17. Data Table Showing Calculation of Mean and Standard Deviation of Gross 
Alpha Concentration 
Gross Alpha 
(xi) 
Uncertaintya 
 
Sigma 
(si) si
2 
Location Date (pCi/L) (pCi/L) (pCi/L) (pCi/L)2 
NDOT Well 24-Jun-98 -0.08 1.56 0.78 0.608 
29-Jul-98 0.32 1.1 0.55 0.303 
23-Sep-98 -1.40 0.79 0.40 0.156 
Gilgan's South 
Well 
24-Jun-98 -0.63 0.86 0.43 0.185 
29-Jul-98 0.64 0.86 0.43 0.185 
23-Sep-98 -0.74 0.69 0.35 0.119 
UE-25 J-12 23-Jun-98 0.06 0.96 0.48 0.230 
28-Jul-98 0.27 0.72 0.36 0.130 
22-Sep-98 0.27 0.8 0.40 0.160 
UE-25 J-13 23-Jun-98 0.05 0.94 0.47 0.221 
28-Jul-98 0.50 0.73 0.37 0.133 
22-Sep-98 -0.18 1.2 0.60 0.360 
UE-25 c#2 23-Jun-98 1.20 1.33 0.67 0.442 
28-Jul-98 1.49 0.94 0.47 0.221 
22-Sep-98 0.73 1.67 0.84 0.697 
Crystal Pool 22-Jun-98 1.04 1.27 0.64 0.403 
27-Jul-98 1.75 1.64 0.82 0.672 
25-Sep-98 -0.85 1.21 0.61 0.366 
Sxi = 4.44 Ssi
2 = 5.59 
Mean Gross 
Alpha x = 0.25 
x s = 0.13 
Source: DTN: MO9904RWSJJS98.000 [DIRS 165866]. 
a Uncertainty is defined as being two standard deviations (sigma) (CRWMS M&O 1999 [DIRS 150420], 
Section 3.2.1, Note to Table 3 given on p. 9). 

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MDL-NBS-HS-000021 REV 02 6-105 October 2004 
6.8.5 Results 
From the discussion in Section 6.8.2 from Knoll (1989 [DIRS 161052], p. 86), there is a 
90 percent chance that the true mean of a parameter () will fall in the interval of x x s  64 .1 and 
that in only 5 percent of the cases will the true value exceed x x s + 64 . 1 . From the values 
presented in Table 6-17 to two decimal places, the best estimate for the mean gross alpha 
concentration in groundwater is 0.25 pCi/L with a 95 percent confidence that the concentration 
will not exceed 0.46 pCi/L. The overall uncertainty in the mean gross alpha concentration has a 
physically defined lower bound of 0.0 pCi/L. The upper bound of the uncertainty in the gross 
alpha concentration can be reasonably defined using a value that is 3 times the standard deviation 
above the expected value, which can be calculated as 0.64 pCi/L. A value that is 3 times the 
standard deviation above the expected value corresponds approximately to the 99.9th percentile 
in a normal distribution. The overall uncertainty distribution of the mean gross alpha 
concentration can thus be defined as a truncated normal distribution with a mean of 0.25 pCi/L, a 
standard deviation of 0.13 pCi/L, a lower bound of 0.0 pCi/L, and an upper bound of 0.64 pCi/L. 
In the absence of data on the combined concentrations of 226Ra and 228Ra, it should be 
conservatively assumed for the standards involving these radionuclides that they are responsible 
for all gross alpha activity. For 226Ra and 228Ra, the mean concentration is 0.25 pCi/L with a 
95 percent confidence that the concentration will not exceed 0.46 pCi/L. These results are 
summarized in Table 6-18. 
Table 6-18. Summary of Alpha Concentration Results in Amargosa Valley Groundwater 
Parameter 
Expected Value 
pCi/L 
Upper (95%) Limit 
pCi/L 
Gross Alpha Concentration 0.25 0.46 
Combined Concentration of 226Ra and 228Ra 0.25 0.46 
6.8.6 Corroborative Data 
Two reports were identified that provided measurements (non-QA) of gross alpha and radium 
concentrations in groundwater in the vicinity of the receptor that could be used to corroborate the 
concentrations derived to demonstrate compliance with the groundwater protection standards. 
These data are discussed below. 
In Yucca Mountain Site Characterization Project Radiological Programs, Radioactivity in FY 
1997 Groundwater Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 
1998 [DIRS 104963]) the closest measurement site to the location of the receptor is the NDOT 
well near the intersection of highways US 95 and Route 373. At this location, the annual 
average gross alpha activity concentration in groundwater during FY 1997 was reported as 
0.54  1.20 pCi/L (CRWMS M&O 1998 [DIRS 104963], Table 5). The format is the mean 
value of 4 quarterly measurements  two standard deviations. Table 4 of Yucca Mountain Site 
Characterization Project Radiological Programs, Radioactivity in FY 1997 Groundwater 
Samples from Wells and Springs Near Yucca Mountain (CRWMS M&O 1998 [DIRS 104963]) 
gives, for the same location and year, an average combined 226Ra and 228Ra concentrations in 

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MDL-NBS-HS-000021 REV 02 6-106 October 2004 
groundwater of 0.32  0.33 pCi/L. Both these measurements of activity concentrations are 
consistent with the values provided in Table 6-18. 
Some additional project data of gross alpha and radium activity concentrations in groundwater 
are reported in Yucca Mountain Site Characterization Project Radiological Programs White 
Paper: Radioactivity in Groundwater in the Vicinity of Yucca Mountain (CRWMS M&O 1997 
[DIRS 147759], Table 4). These data were based on samples taken during the first and second 
quarters of 1997. At each location of interest discussed in Section 6.8.3, gross alpha 
concentrations were reported to be below the detection limit, a limit that was not defined in the 
report. The combined 226Ra and 228Ra activity concentration (rounded here to two significant 
figures) ranged from a low value of 0.29  0.27 pCi/L at the NDOT well to a high value of 
0.70  0.47 pCi/L at Crystal Pool. These values are consistent with those reported in 
Section 6.8.5. 
In Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 
[DIRS 156604], p. 8-1), the preamble to Section 8, Groundwater Monitoring, identifies that for 
the calendar year covered by the report (CY 2000), some results for radioactivity analysis were 
somewhat higher than historical data. It was also mentioned that the (unidentified) organization 
providing oversight of groundwater monitoring activities had also experienced similar difficulty 
in obtaining accurate analytical data. Because, there was no indication as to whether this caveat 
applied to specific data sets or to all data, it must be assumed that all data based on radioactivity 
analysis were systematically biased to higher values. 
The measurement site in Nevada Test Site Annual Site Environmental Report for Calendar Year 
2000 (Townsend 2001 [DIRS 156604], Figure 8.3) that is closest to the point of compliance is 
the Amargosa Valley RV Park, which is shown to be near the intersection of highways US 95 
and Route 373 (i.e., close to the NDOT well of CRWMS M&O (1998 [DIRS 104963])). The 
samples for this site were taken on November 14, 2000, and reported concentrations were based 
on a single measurement. 
In Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 
[DIRS 156604]) the gross alpha concentration in groundwater was reported to be 
0.78  0.50 pCi/L (Table 8.3), the 226Ra concentration was 0.59  0.40 pCi/L (Table 8.6), and the 
228Ra concentration was 0.43  0.79 pCi/L (Table 8.7). By combining the two Ra measurements 
as discussed in Radiation Detection and Measurement (Knoll 1989 [DIRS 161052] 
Equation 3-38, p. 88), the combined concentration of 226Ra and 228Ra is 1.02  0.89 pCi/L. 
Given that for a normal distribution the 95 percent confidence limits are at the mean value 
 2 standard deviations, the following statements can be made for the concentrations reported in 
Nevada Test Site Annual Site Environmental Report for Calendar Year 2000 (Townsend 2001 
[DIRS 156604]). 
Gross alpha: 0.28 pCi/L < actual concentration < 1.28 pCi/L 
226Ra and 228Ra: 0.13 pCi/L < actual concentration < 1.91 pCi/L 

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MDL-NBS-HS-000021 REV 02 6-107 October 2004 
As the data reported by Townsend (2001 [DIRS 156604]) are stated to have systematically 
overestimated the concentrations, the above concentration ranges are not inconsistent with those 
in Table 6-18. 

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INTENTIONALLY LEFT BLANK 

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MDL-NBS-HS-000021 REV 02 7-1 October 2004 
7. VALIDATION 
This section of the report documents the validation of the SZ transport abstraction model and the 
SZ 1-D transport model. For the SZ transport abstraction model, a comparison is made between 
the abstraction model and the underlying process model, which is discussed in the report 
Site-Scale Saturated Zone Transport (BSC 2004 [DIRS 170036]). This comparison tests the 
appropriateness and accuracy of the convolution integral method used in the SZ transport 
abstraction model. Similarly, the validation of the SZ 1-D transport model consists of a 
qualitative comparison between the abstraction model and the site-scale process model 
mentioned above (BSC 2004 [DIRS 170036]). In all cases, the validations of these models are 
performed for a range of behavior that is representative of the uncertainties being evaluated for 
the TSPA-LA analyses. In addition, this section documents corrections to the SZ 1-D transport 
model and evaluates the impacts of these corrections (see Section 7.5). 
7.1 VALIDATION PROCEDURES 
As discussed above, validation of both the SZ transport abstraction model and the SZ 1-D 
transport model involves comparison with the underlying process model (BSC 2004 
[DIRS 170036]). In making these comparisons, three cases for radionuclide transport are 
defined for implementation: median case, fast case, and slow case. The median case uses 
median values from uncertainty distributions for the relevant flow and transport parameters. The 
fast case uses parameter values set at the 90th percentile or the 10th percentile, depending on the 
parameter, that result in more rapid transport of radionuclides through the SZ. For example, the 
flowing interval spacing is set to its 90th percentile value, and the sorption coefficient is set to its 
10th percentile value for transport of neptunium in the fast case. The slow case uses parameter 
values set at the 90th percentile or 10th percentile that result in less rapid transport of 
radionuclides through the SZ. These three cases approximately span the range of uncertainty in 
results of the SZ transport abstraction model with regard to radionuclide transport in the SZ, as 
shown in Figures 6-28 and 6-32. The parameter values used in the median, fast, and slow cases 
are summarized in Table 7-1. 
The SZ site-scale transport model (BSC 2004 [DIRS 170036]) was run for each of the three 
model validation cases by varying the input parameters to conform to the values given in 
Table 7-1. The steady-state groundwater flow solution for each case was first established by 
running the flow model (BSC 2004 [DIRS 170037]) to equilibrium with the specified values of 
the parameters GWSPD and HAVO. The particle-tracking algorithm in the FEHM V2.20 
software code [DIRS 161725] was then used to obtain the simulated mass breakthrough curves 
with the SZ site-scale transport model at the regulatory boundary of the accessible environment. 

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MDL-NBS-HS-000021 REV 02 7-2 October 2004 
Table 7-1. Parameter Values in the Three Cases for SZ Transport Model Validation 
Parameter 
Name Parameter Description Median Case Fast Case Slow Case 
FISVO Flowing interval spacing in 
volcanic units 
1.29 
(19.5 m) 
1.82 
(66.1 m) 
0.67 
(4.68 m) 
HAVO Ratio of horizontal anisotropy in 
permeability 
4.2 16.25 1.0 
LDISP Longitudinal dispersivity 2.0 
(100 m) 
2.96 
(920 m) 
1.03 
(10.9 m) 
FPLAW Western boundary of the alluvial 
uncertainty zone 
0.5 0.1 0.9 
FPLAN Northern boundary of the alluvial 
uncertainty zone 
0.5 0.1 0.9 
NVF19 Effective porosity in shallow 
alluvium 
0.18 0.114 0.245 
NVF7 Effective porosity in 
undifferentiated valley fill 
0.18 0.114 0.245 
FPVO Fracture porosity in volcanic 
units 
-3.0 
(10-3) 
-3.89 
(1.29  10-4) 
-1.50 
(0.0316) 
DCVO Effective diffusion coefficient in 
volcanic units 
-10.3 
(5.0  10-11 m2/s) 
-10.68 
(2.08  10-11 m2/s) 
-9.65 
(2.22  10-10 m2/s) 
GWSPD Groundwater specific discharge 
multiplier 
0.0 
(1.0) 
0.477 
(3.0) 
-0.477 
(0.333) 
bulkdensity Bulk density of alluvium 1910 kg/m3 1810 kg/m3 2010 kg/m3 
KDNPVO Neptunium sorption coefficient in 
volcanic units 
1.3 mL/g 1.04 mL/g 1.6 mL/g 
KDNPAL Neptunium sorption coefficient in 
alluvium 
6.35 mL/g 4.26 mL/g 8.44 mL/g 
NOTE: Values in parentheses are the parameter values from log-transformed uncertainty distributions. 
7.1.1 SZ Transport Abstraction Model 
Validation of the SZ transport abstraction model is accomplished by running this model using the 
breakthrough curves for the three validation cases from the SZ site-scale transport model 
(BSC 2004 [DIRS 170036]). The SZ transport abstraction model uses the convolution integral 
method as implemented by the SZ_Convolute V3.0 software code (STN: 10207-3.0-00, SNL 
2003 [DIRS 164180]) to produce the radionuclide mass breakthrough to the accessible 
environment, given the time-varying input of mass at the water table below the repository for the 
TSPA-LA. Note that model validation tests were performed with the SZ_Convolute V2.2 
software code (STN: 10207-2.2-00, SNL 2003 [DIRS 163344]). 
For the first validation test, a constant input of 1 g/year from the UZ is applied at the water table 
beneath the repository in the SZ transport abstraction model. This is essentially the same 
transport boundary condition used in the SZ site-scale transport model (BSC 2004 
[DIRS 170036]) to derive the SZ breakthrough curves for input to the abstraction model. 
Consequently, the output of the SZ transport abstraction model should reproduce the 
breakthrough curve used as the input in the validation test. This validation test is conducted for 
both a nonsorbing species and for neptunium. The validation test is also run for the three 

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MDL-NBS-HS-000021 REV 02 7-3 October 2004 
validation cases described in the previous section. To facilitate comparison of the results, the 
transport simulations in both the SZ site-scale transport model and the SZ transport abstraction 
model are performed without radioactive decay. 
As a second validation test, the mass balance of radionuclides transported in the SZ transport 
abstraction model is checked. This check is performed by setting the upstream boundary 
condition equal to 1 g/year for time up to 1,000 years and reducing this to 0 g/year for the 
remainder of the simulation. Thus, the total radionuclide mass input to the SZ transport 
abstraction model is 1,000 grams. Since radioactive decay is not included in this validation test, 
the cumulative output of the model over a long simulation time should also be 1,000 grams. This 
second validation test is also run for the three validation cases described in the previous section 
(Table 7-1). 
It should be noted that several additional test cases for the SZ_Convolute V2.2 software code 
(SZ_Convolute V2.2, STN: 10207-2.2-00, [DIRS 163344]) have been conducted for the 
purposes of software verification (BSC 2003, [DIRS 163587]). These tests verify the ability of 
the convolution integral method, as implemented by the SZ_Convolute V2.2 software code 
(STN: 10207-2.2-00, SNL 2003 [DIRS 163344]), to simulate accurately radionuclide transport 
with variable input boundary conditions, radioactive decay, and variations in groundwater flux 
with climate change. Although not directly applied to the radionuclide transport results of the SZ 
transport abstraction model presented in this report, the numerical testing of the software code 
used in this model provides additional confidence in the validity of the model. 
7.1.2 SZ 1-D Transport Model 
Validation of the SZ 1-D transport model is conducted by running this model and comparing the 
results to the output of the SZ site-scale transport model (BSC 2004 [DIRS 170036] and 
DTN: LA0306SK831231.001 [DIRS 164362]). The SZ 1-D transport model is implemented 
using the GoldSim V7.50.100 software code. Ultimately, the SZ 1-D transport model is fully 
integrated into the TSPA-LA model; however, for the purposes of model development and 
validation, a stand-alone version of this model is used. 
For the validation test, a constant input of 1 g/year from the UZ is applied at the upstream 
boundary of the SZ 1-D transport model. This is the same radionuclide mass boundary condition 
used in the SZ site-scale transport model (BSC 2004 [DIRS 170036]). The breakthrough curves 
from the SZ 1-D model should approximately match the output of the site-scale transport model. 
This validation test is conducted for both a nonsorbing species and for neptunium, and is run for 
the three validation cases described in the previous section. To facilitate comparison of the 
results, the transport simulations in both the SZ site-scale transport model and the SZ 1-D 
transport model are performed without radioactive decay. 
It should be noted that several additional test cases for the GoldSim V7.50.100-00 software code 
have been conducted for the purposes of software verification (BSC 2002 (BSC 2002 
[DIRS 163962]). These tests verify the ability of the GoldSim V7.50.100-00 software code to 
accurately simulate radioactive decay and ingrowth. Although not directly applied to the 
radionuclide transport results of the SZ 1-D transport model presented in this report, the 
numerical testing of the software code used in this model provides additional confidence in the 

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MDL-NBS-HS-000021 REV 02 7-4 October 2004 
validity of the model. It should also be noted that a problem in the GoldSim V7.50.100-00 
software code with regard to parameter sampling was identified subsequent to the validation 
testing documented in this report and this problem is reported in CR 2222 (Evaluate Revised LH 
Sampling Algorithm on the Results of ANL-EBS-PA-000009). The parameter-sampling 
component of the GoldSim V7.50.100-00 software code was not used in the validation testing of 
the SZ 1-D transport model and the problem reported in CR 2222 is thus not relevant to the 
validation testing conducted for this report. 
Groundwater flow rates and flow-path lengths derived from the SZ site-scale transport model 
(BSC 2004 [DIRS 170036]) were used in the development of the SZ 1-D transport model. 
However, both the approximate nature of the equivalency between the two models and the 
reduction in dimensionality in the 1-D transport model limit the ability of the 1-D model to 
match the results of the site-scale transport model. Among the realizations of SZ transport in the 
TSPA-LA analyses, the source locations within each of the four source regions beneath the 
repository are varied in the SZ transport abstraction model. However, the impact of this 
variability on flow paths and flow-path lengths is not captured in the SZ 1-D transport model. 
This limitation of the SZ 1-D transport model results in some differences in simulation results 
between the SZ transport abstraction model and the SZ 1-D transport model for any given 
realization in the TSPA-LA analyses. These differences are evaluated for a sampling of 
realizations and the results are also documented in Section 7.3.2. The results of this evaluation 
indicate acceptable agreement between the SZ 1-D transport model and the SZ site-scale 
transport model, from which it was abstracted. 
7.2 VALIDATION CRITERIA 
The current Technical Work Plan For: Natural System  Saturated Zone Analysis and Model 
Report Integration (BSC 2004 [DIRS 171421], Section 2.2.1.1) states that model validation was 
completed following criteria in the previous version of the technical work plan (TWP). Model 
validation presented in Section 7 of this report follows the Technical Work Plan for: Saturated 
Zone Flow and Transport Modeling and Testing (BSC 2003 [DIRS 166034], Section 2.5). The 
previous TWP (BSC 2003 [DIRS 166034], Section 2.5) states that Level-II validation will be 
achieved through confidence building activities during model development and by implementing 
one post-development validation method. In the cases of the SZ transport abstraction model and 
the SZ 1-D transport model, the post-development method was chosen to be the corroboration of 
the abstraction model results to the results of the validated process model from which the 
abstraction was derived (BSC 2003 [DIRS 166034], Section 2.5). This is the most appropriate 
method of model validation because the underlying process model (the SZ site-scale transport 
model) has undergone validation independently, and the SZ transport abstraction model and the 
SZ 1-D transport model are derived directly from this process model. In addition, the TWP 
validation plan for the SZ Flow and transport abstraction model includes a check of output for 
mass balance. 
The acceptance criterion for validation of both the SZ transport abstraction model and the 
SZ 1-D transport model is a favorable qualitative comparison between the simulated 
SZ breakthrough curves from these two models and the breakthrough curve from the SZ 
site-scale transport model conducted by visual examination of graphs made of the breakthrough 
curves (BSC 2004 [DIRS 170036] and DTN: LA0306SK831231.001 [DIRS 164362]). The 

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MDL-NBS-HS-000021 REV 02 7-5 October 2004 
breakthrough curves are compared at 10 percent, 50 percent, and 90 percent mass breakthrough 
in the evaluation of this criterion. Breakthrough curves are compared for a nonsorbing species 
and for neptunium. Breakthrough curves for the median, fast, and slow cases outlined above are 
compared. 
An additional acceptance criterion for the validation of the SZ transport abstraction model is a 
check of the radionuclide mass balance in the model. The mass input to the model should equal 
the mass output from the model over long time periods. Discrepancies of a few percent are 
acceptable due to both less-than-complete discharge of radionuclide mass from the model and 
numerical (truncation) errors in the computer software implementing the numerical integration 
used in the convolution integral method. 
These acceptance criteria reflect the essential functions of the SZ system with regard to the 
transport time and radionuclide mass delivery to the accessible environment. 
7.2.1 Confidence Building During Model Development to Establish Scientific Basis and 
Accuracy for Intended Use 
For Level II validation, the development of the models should be documented in accordance with 
the requirements of Section 5.3.2(b) of AP-SIII.10Q. The development of the SZ transport 
abstraction model and the SZ 1-D transport model has been conducted in accordance with these 
criteria, as follows: 
1. Selection of input parameters and/or input data, and a discussion of how the selection 
process builds confidence in the model. [AP-SIII.10 Q 5.3.2(b) (1) and AP-2.27Q 
Attachment 3 Level I (a)] 
The inputs to the SZ transport abstraction model and the SZ 1-D transport model have 
all been obtained from controlled sources (see Tables 4-1, 4-2, and 4-3), including 
discussion about selection of input and design parameters (Section 4.1). The SZ 
transport abstraction model takes the SZ site-scale transport model, which has been 
independently validated (BSC 2004 [DIRS 170036]), as a direct input. Model 
assumptions have been described in Section 5. Detailed discussion about model 
concepts can be found in Section 6.3. Section 6.5.2 contains detailed discussion and 
analyses of data sources and parameter uncertainty, leading to increased confidence in 
the parameters that are used in the models presented in this report. Thus, this 
requirement is considered satisfied. 
2. Description of calibration activities, and/or initial boundary condition runs, and/or 
run convergences, simulation conditions set up to span the range of intended use and 
avoid inconsistent outputs, and a discussion of how the activity or activities build 
confidence in the model. Inclusion of a discussion of impacts of any non-convergence 
runs [(AP-SIII.10Q 5.3.2(b)(2) and AP-2.27Q Attachment 3 Level I (e)]. 
The SZ transport abstraction model and the SZ 1-D transport model use the SZ sitescale 
transport model (BSC 2004 [DIRS 170036]), which is itself based on the 
calibrated SZ site-scale flow model (BSC 2004 [DIRS 170037]), as a starting point. 
The SZ transport abstraction model generates breakthrough curves for a unit point 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-6 October 2004 
source, hence initial and boundary conditions for radionuclide mass transport are 
established through linkage to the UZ transport model in TSPA-LA model 
simulations. The SZ 1-D transport model obtains boundary conditions for 
radionuclide mass from the UZ in the TSPA-LA model. Section 6.3.3 discusses the 
source term for the models. Section 6.6 provides detailed discussion of model results. 
Discussion about nonconvergence runs is not relevant for this model report. Thus, this 
requirement is considered satisfied. 
3. Discussion of the impacts of uncertainties to the model results including how the 
model results represent the range of possible outcomes consistent with important 
uncertainties.[(AP-SIII.10 Q 5.3.2(b)(3) and AP-2.27Q Attachment 3 Level 1 (d) and 
(f)]. 
Results of 200 realizations of the SZ transport abstraction model are presented in 
Section 6.6. These results constitute an assessment of the impacts of uncertainty in 
model parameters and provide this information as a direct feed to the probabilistic 
analyses of the TSPA-LA model. 
4. Formulation of defensible assumptions and simplifications. [AP-2.27Q Attachment 3 
Level I (b)]. 
Discussion of assumptions and simplifications are provided in Section 5 and Section 
6.3. The conceptual model of transport in the SZ and the components of the model are 
discussed in Section 6.3. Justification of assumptions and discussion of their 
implications for the models are also provided. 
5. Consistency with physical principles, such as conservation of mass, energy, and 
momentum. [AP-2.27Q Attachment 3 Level I (c)] 
Consistency with physical principles is demonstrated by the conceptual and 
mathematical formulation of the SZ transport abstraction model and the SZ 1-D 
transport model in Sections 6.3 and 6.5.1, and the selection and use of the FEHM and 
GoldSim software codes in Section 3. Thus, this requirement is considered satisfied. 
7.2.2 Confidence Building After Model Development to Support the Scientific Basis of 
the Model 
Model validation requires mathematical models be validated by one or more of several methods 
given in Section 5.3.2(c and d) of AP-SIII.10Q. Validation of the SZ transport abstraction model 
and the SZ 1-D transport model is documented in Section 7 of this report and is related to the 
procedural requirements as follows: 
1. AP-SIII.10 Q 5.3.2(c), Method 6: Corroboration of abstraction model results to the 
results of the validated mathematical model from which the abstraction model is 
derived. 
The SZ transport abstraction model and the SZ 1-D transport model are validated by 
comparing results from these models with the SZ site-scale transport model, which is 

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MDL-NBS-HS-000021 REV 02 7-7 October 2004 
the underlying validated mathematical (process) model from which they are derived. 
The validation criteria, testing, and results are described in detail in Section 7 of this 
report. 
2. AP-SIII.10 Q 5.3.2(d): Technical review through publication in a refereed 
professional journal. 
The SZ transport abstraction model and its results are described in the refereed 
professional publication of Arnold et al. (2003 [DIRS 163857]). This publication 
demonstrates additional confidence in the model, when taken in conjunction with the 
model validation activity described in item 1 above. 
7.3 RESULTS OF VALIDATION ACTIVITIES 
The numerical results of the model validation activities described above are presented primarily 
as a series of plots of simulated breakthrough curves. A quantitative comparison of models with 
regard to radionuclide mass balance is also presented for the SZ transport abstraction model. 
7.3.1 SZ Transport Abstraction Model Validation Results 
Results of the SZ transport abstraction model and the SZ site-scale transport model (BSC 2004 
[DIRS 170036]) for a nonsorbing species are shown as simulated breakthrough curves in 
Figure 7-1. This figure shows results for the median, fast and slow cases of SZ transport. Note 
that all simulations were conducted without radioactive decay. The simulated breakthrough 
curves from the SZ site-scale transport model are shown with the solid and dashed lines for the 
three cases. The results from the SZ transport abstraction model are shown as the open symbols 
that are superimposed on the breakthrough curves from the site-scale model. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-8 October 2004 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case 
(solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ transport 
abstraction model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-1. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction 
Model and the SZ Site-Scale Transport Model for a Nonsorbing Radionuclide 
Visual comparison of the open symbols and the lines in Figure 7-1 indicates agreement within a 
few percent of relative mass in the results from the SZ transport abstraction model and the SZ 
site-scale transport model for all three cases of SZ transport. The one exception is the first point 
in the results of the SZ transport abstraction model for the fast case, which is lower than the 
corresponding breakthrough curve from the SZ site-scale transport model. It should be noted 
that the time step used in the abstraction model is 20 years, which differs from the 10-year time 
step used in the site-scale model for the fast case. This difference in time-step size accounts for 
the small discrepancy between the models at the first time step. 
Results of the SZ transport abstraction model and the SZ site-scale transport model (BSC 2004 
[DIRS 170036] and DTN: LA0306SK831231.001 [DIRS 164362]) for neptunium are shown as 
simulated breakthrough curves in Figure 7-2. This figure shows results for the median, fast, and 
slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. 
The simulated breakthrough curves from the SZ site-scale transport model are shown with the 
solid and dashed lines for the three cases. The results from the SZ transport abstraction model 
are shown as the open symbols that are superimposed on the breakthrough curves from the 
site-scale model. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-9 October 2004 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case 
(solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ transport 
abstraction model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-2. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction 
Model and the SZ Site-Scale Transport Model for Neptunium 
Visual comparison of the open symbols and the lines in Figure 7-2 indicates agreement within a 
few percent of relative mass in the results from the SZ transport abstraction model and the SZ 
site-scale transport model for all three cases of SZ transport of neptunium. 
Figure 7-3 shows the simulated breakthrough curve from the SZ transport abstraction model of a 
nonsorbing species for the median case. This simulation applies a radionuclide mass influx 
boundary condition of 1 g/year for the first 1,000 years of the simulation, which results in a total 
mass input of 1,000 grams. The mass balance in the SZ transport abstraction model is checked 
by summing the total mass output from the simulated breakthrough curve shown in Figure 7-3 
over the 100,000 years of the simulation. The output sum is 981 grams, which is 98.1 percent of 
the input mass. Examination of the simulated breakthrough curve from the SZ site-scale 
transport model for the median case indicates that 98 percent of the mass has reached the 
accessible environment within 100,000 years. Consequently, the discrepancy between total input 
mass and total output mass can be explained as the radionuclide mass retained in the SZ system 
after 100,000 years. The total output mass from the SZ transport abstraction model for the fast 
case and the slow case is 99.8 percent and 99.5 percent of the input mass, respectively. Mass 
breakthrough for the median case has a longer tail than the slow and fast cases due to matrix 
diffusion. Consequently, the total mass output is somewhat lower for the median case than the 
slow and fast cases in this validation test. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-10 October 2004 
10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ transport abstraction model are shown for the median case. The breakthrough curve 
does not include radioactive decay. 
Figure 7-3. Simulated Breakthrough Curve for a Nonsorbing Radionuclide from a 1000-Year-Duration 
Source 
7.3.2 SZ 1-D Transport Model Validation Results 
Results of the SZ 1-D transport model and the SZ site-scale transport model for a nonsorbing 
species are shown as simulated breakthrough curves in Figure 7-4. This figure shows results for 
the median, fast, and slow cases of SZ transport. Note that all simulations were conducted 
without radioactive decay. The simulated breakthrough curves from the SZ site-scale transport 
model are shown with the solid and dashed lines for the three cases. The results from the SZ 1-D 
transport model are shown as the open symbols superimposed on the breakthrough curves from 
the SZ site-scale transport model. 
Visual comparison of the open symbols and the lines in Figure 7-4 indicates close agreement in 
the results for a nonsorbing species from the SZ 1-D transport model and the SZ site-scale 
transport model for the median case of SZ transport. There is generally close comparison in the 
overall shapes of the breakthrough curves from the SZ 1-D transport model and the SZ site-scale 
transport model, as indicated by the times of 10 percent, 50 percent, and 90 percent of mass 
breakthrough, with somewhat greater deviation for the upper tails of the breakthrough curves. 
Results of the SZ 1-D transport model and the SZ site-scale transport model for neptunium are 
shown as simulated breakthrough curves in Figure 7-5. This figure shows results for the median, 
fast and slow cases of SZ transport. Note that all simulations were conducted without 
radioactive decay. The simulated breakthrough curves from the SZ site-scale transport model are 
shown with the solid and dashed lines for the three cases. The results from the SZ 1-D transport 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-11 October 2004 
model are shown as the open symbols superimposed on the breakthrough curves from the SZ 
site-scale transport model. 
Visual comparison of the open symbols and the lines in Figure 7-5 indicates close agreement in 
the results for neptunium from the SZ 1-D transport model and the SZ site-scale transport model 
for the median case of SZ transport. The comparison is slightly less close for the fast case and 
slow case. There is generally close comparison in the overall shapes of the breakthrough curves 
from the SZ 1-D transport model and the SZ site-scale transport model. 
Results of the SZ 1-D transport model and the SZ transport abstraction model for a nonsorbing 
species and neptunium are shown and compared in Figure 7-6. These results are for a single 
realization (above) and for the average of 15 realizations (below). Comparison between the 
simulated breakthrough curves for the SZ 1-D transport model and the SZ transport abstraction 
model for a single realization shows differences between the simulated results, particularly for 
neptunium transport in this realization. However, there are small differences between the 
simulated breakthrough curves when the results are averaged over 15 realizations of the models, 
as shown in the lower plot in Figure 7-6. For the case of nonsorbing species, the average of the 
SZ 1-D transport model simulations shows somewhat earlier breakthrough for the tail of the 
breakthrough curve, relative to the SZ transport abstraction model. 

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MDL-NBS-HS-000021 REV 02 7-12 October 2004 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
Output DTN: SN0306T0502103.005. 
NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case 
(solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D 
transport model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-4. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and 
the SZ Site-Scale Transport Model for a Nonsorbing Radionuclide 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-13 October 2004 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
Output DTN: SN0306T0502103.005. 
NOTE: Results from the SZ site-scale transport model (BSC 2004 [DIRS 170036]) are shown for the median case 
(solid line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D 
transport model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-5 Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and 
the SZ Site-Scale Transport Model for Neptunium 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 7-14 October 2004 
Figure 7-6. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport 
Model (1D) and the SZ Transport Abstraction Model (3D) for a Nonsorbing Radionuclide 
(I129) and Neptunium (Np237) for a Single Realization (Above) and for the Average of 
15 Realizations (Below) 

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MDL-NBS-HS-000021 REV 02 7-15 October 2004 
7.4 CONCLUSIONS 
7.4.1 SZ Transport Abstraction Model Validation 
Validation testing of the SZ transport abstraction model indicates good agreement with the 
SZ site-scale transport model (BSC 2004 [DIRS 170036]). Acceptance criteria established for 
the model validation regarding the qualitative comparison of simulated breakthrough curves and 
the quantitative evaluation of radionuclide mass balance are met. Results of the validation 
testing indicate that the SZ transport abstraction model is valid for the approximate range of 
uncertainty incorporated into the model through parameter uncertainty distributions. Results also 
indicate that the SZ transport abstraction model is valid for both nonsorbing and sorbing 
radionuclide species for its intended use. 
It should be noted that the SZ is more effective as a barrier for highly sorbing, short-lived 
radionuclides such as 90Sr and 137Cs, relative to neptunium, as used in this validation testing. 
The validation testing does not demonstrate the delay afforded by the SZ in the migration of 
these radionuclides; nor does it demonstrate the impact of radionuclide decay. However, the 
importance of the SZ as a barrier to 90Sr and 137Cs transport, with regard to both delay and decay, 
is discussed in Section 6.7. 
The small deviation from the SZ site-scale transport model results at early times for the fast case 
is a result of the time-step size used in the simulation. Such deviations in the abstraction model 
for realizations with very fast transport in the SZ would not be significant within the context of 
the TSPA-LA analyses using this model. The discrepancy in radionuclide mass balance 
identified in the validation testing is a small percentage and is readily understood with regard to 
long-term mass retention in the SZ due to the matrix diffusion process. No future activities are 
needed to complete this model validation for its intended use. 
7.4.2 SZ 1-D Transport Model Validation 
Validation testing of the SZ 1-D transport model indicates acceptable agreement with the 
SZ site-scale transport model (BSC 2004 [DIRS 170036]). Qualitative acceptance criteria 
regarding the comparison of the simulated breakthrough curves with the results of the SZ 
site-scale transport model are met. Results of the validation testing indicate that the SZ 1-D 
transport model is valid for the approximate range of uncertainty incorporated into the model 
through parameter uncertainty distributions. Results also indicate that the SZ 1-D transport 
model is valid for both nonsorbing and sorbing radionuclide species for its intended use. 
It is relevant to consider the purpose and use of the SZ 1-D transport model in the evaluation of 
validation testing results. This model is used for the purpose of simulating radioactive decay and 
ingrowth for four decay chains. This simplified model is required because the SZ transport 
abstraction model is not capable of simulating ingrowth by radioactive decay. It is not 
anticipated that the decay products in these decay chains would be significant contributors to 
total radiological dose; however, groundwater protection regulations require assessment of 
groundwater concentrations for some of these decay products. The results of the SZ 1-D 
transport model are used only for the decay products in these decay chains within the 
TSPA-LA analyses. 

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MDL-NBS-HS-000021 REV 02 7-16 October 2004 
It must also be considered that there are fundamental differences between the SZ 1-D transport 
model and the SZ site-scale transport model that limit the degree of consistency that can be 
expected between these two models. Groundwater flow and radionuclide transport simulation in 
the SZ site-scale transport model occur in three dimensions with a relatively complex 
representation of geological heterogeneity from the hydrogeologic framework model. 
Radionuclide transport in the SZ 1-D transport model is simulated in a significantly simplified 
representation of the SZ system consisting of three pipe segments. Each pipe segment has 
properties that represent the average characteristics in that area of the SZ site-scale transport 
model. There are also variations in the source location within the four source regions beneath 
the repository simulated by the SZ transport abstraction model that are not incorporated in the SZ 
1-D transport model on a realization-by-realization basis, as discussed in Section 7.1.2. 
Another difference between the SZ 1-D transport model and the SZ transport abstraction model 
is the way in which changes in groundwater flux related to climate change are handled. A 
fundamental limitation to the Laplace transform solution used by the GoldSim software code to 
simulate radionuclide transport in the pipe module is that radionuclide mass in transit through 
a particular pipe segment does not change in response to changes in specified groundwater flow 
rate. Consequently, radionuclide mass that has entered a pipe segment in the SZ 1-D transport 
model before increased flow rates are imposed at 600 and 2,000 years for the monsoonal and 
glacial-transition climate states in the TSPA-LA model, would not be instantaneously 
accelerated, as it is in the SZ transport abstraction model. Because peak releases of 
radionuclides to the SZ are not expected to occur within the first 2,000 years of the TSPA-LA 
simulations, this limitation to the SZ 1-D transport model is unlikely to have a significant impact 
on the simulation results. 
Comparison of simulation results from the SZ 1-D transport model and the SZ transport 
abstraction model shows that there are differences for individual realizations, as used in the 
TSPA-LA analyses. However, when results are averaged over several realizations the ensemble 
behavior of the SZ 1-D transport model is very similar to the SZ transport abstraction model. 
This indicates that there is no consistent bias in the simulation results from the SZ 1-D transport 
model relative to the SZ transport abstraction model. Given this finding and the intended use of 
the SZ 1-D transport model for the simulation of decay chain products only, differences in the 
results with the SZ transport abstraction model for individual realizations are acceptable. 
Considering these factors, the SZ 1-D transport model provides a good approximation of 
simulated radionuclide transport in the 3-D system of the SZ. No future activities are needed to 
complete this model validation for its intended use. 
7.4.3 Validation Summary 
The SZ transport abstraction model and the SZ 1-D transport model have been validated by 
applying acceptance criteria based on an evaluation of the models relative importance to the 
potential performance of the repository system. All relevant validation requirements have been 
fulfilled, including corroboration of model results with comparison to the model from which they 
were derived and publication in a refereed professional journal. Activities requirements for 
confidence building during model development have also been satisfied. The model 
development activities and post-development validation activities described establish the 

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MDL-NBS-HS-000021 REV 02 7-17 October 2004 
scientific bases for the SZ transport abstraction model and the SZ 1-D transport model. Based on 
this, the SZ transport abstraction model and the SZ 1-D transport model used in this report are 
considered to be sufficiently accurate and adequate for the intended purpose and to the level of 
confidence required by the models relative importance to the potential performance of the 
repository system. 
7.5 CORRECTION TO THE SZ 1-D TRANSPORT MODEL 
Reevaluation of the SZ 1-D transport model has indicated two corrections to the model relative 
to the model file contained in output DTN: SN0306T0502103.005. This section of the report 
describes those corrections and evaluates their impact with regard to radionuclide transport 
simulation results in the SZ 1-D transport model. The first correction is for the value of average 
matrix porosity of the volcanic units used to divide the free water diffusion coefficient. The 
value used in the original model file is 0.20, but it should be 0.21 to be consistent with the value 
used in the pipe segments to analyze matrix diffusion. The second correction is to the effective 
value of the flowing interval spacing used in the pipe segments to simulate matrix diffusion. In 
the original model file the value of flowing interval spacing (FISVO) was converted from the 
log-transformed value to the actual value and divided by 4. The corrected calculation is to divide 
the value by 2. 
The impact of these corrections is evaluated by comparing the original results with the corrected 
results for the average breakthrough curves of a nonsorbing species and of neptunium with the 
SZ 1-D transport model. The model results for this comparison are shown in Figure 7-7. 
Examination of these results indicates that the agreement between the average breakthrough 
curves for the SZ 1-D transport model and the SZ transport abstraction model is better for the 
corrected SZ 1-D transport model than for the original SZ 1-D transport model. This is 
particularly true for the transport of nonsorbing radionuclides; the differences between the 
original and corrected versions of the SZ 1-D transport model are minimal for the transport of 
neptunium. 
Based on these results it is concluded that the impacts of the corrections to the SZ 1-D transport 
model are small with regard to validation of the SZ 1-D transport model. Further more, for the 
15 realizations used in the impact analysis, the original SZ 1-D transport model overpredicts the 
rate of migration of nonsorbing species in the tail of the average breakthrough curve, relative to 
the SZ transport abstraction model. Overprediction of the rate of migration of radionuclides 
results in higher simulated dose in the TSPA-LA model. 

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MDL-NBS-HS-000021 REV 02 7-18 October 2004 
Figure 7-7. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D transport model (1D) 
and the SZ Transport Abstraction Model (3D) for a Nonsorbing Radionuclide (I129) and 
Neptunium (Np237) for the Average of 15 Realizations for the Original (Above) and 
Corrected SZ 1-D Transport Model (Below) 

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MDL-NBS-HS-000021 REV 02 8-1 October 2004 
8. CONCLUSIONS 
8.1 SUMMARY OF MODELING ACTIVITY 
The SZ transport abstraction model and the SZ 1-D transport model are developed for use in the 
TSPA-LA analyses. In addition, analyses of uncertainty in input parameters for these models are 
conducted, and the results are documented as uncertainty distributions. Values of uncertain 
parameters are sampled for 200 realizations of the SZ flow and transport system. Simulations 
using the SZ transport abstraction model are conducted for these 200 realizations, and the results 
are documented in this report. 
Analyses of parameter uncertainty and of multiple realizations of the SZ system, using the 
SZ transport abstraction model, constitute an assessment of uncertainty in the SZ system that is 
useful for direct implementation in the TSPA-LA model. The simulated radionuclide mass 
breakthrough curves from the SZ transport abstraction model are coupled to the TSPA-LA 
analyses using the convolution integral method (via the SZ_Convolute V3.0 software code 
(STN: 10207-3.0-00, SNL 2003 [DIRS 164180])). 
In addition, the SZ 1-D transport model is developed for direct implementation, in conjunction 
with the GoldSim V7.50.100 software code, in the TSPA-LA. The uncertain input parameters 
defined for the SZ transport abstraction model are used in the SZ 1-D transport model, to provide 
consistency between the two models when they are used in the probabilistic analyses of the 
TSPA-LA. 
The SZ transport abstraction model and the SZ 1-D transport model are validated, and the results 
of these validation activities are documented in this report. Validation of the SZ transport 
abstraction model indicates very close agreement with the underlying SZ site-scale transport 
model when the convolution integral method is used. Although the SZ 1-D transport model is 
much simpler than the 3-D SZ transport abstraction model, validation of the SZ 1-D transport 
model indicates there is close agreement, over a broad range of uncertainty, between the 1-D and 
3-D models with respect to each models assessment of transport behavior of representative 
radionuclides. 
The technical bases of FEPs included in the models are presented in this report, and are provided 
to clarify the parameters and components of the SZ transport abstraction model and the SZ 1-D 
transport model. The role of the SZ as a natural barrier to the transport of radionuclides is 
assessed in relation to the results of the SZ transport abstraction model. In addition, the model 
development and analyses presented in this report address those YMRP acceptance criteria (NRC 
2003 [DIRS 163274]) that are listed in Section 4.2 of this report. 
Information on the correlation between distribution coefficients (Kds) used in the sampling of 
uncertain parameters for the SZ transport abstraction model and for the SZ 1-D transport model 
is provided in Table 4-3 and Table 6-8. Positive correlation between the distribution coefficient 
for uranium in volcanic units and alluvium is specified, based on potentially similar 
hydrochemical conditions in the two aquifers. Positive correlation between the distribution 
coefficient for neptunium in volcanic units and alluvium is specified, based on potentially similar 
hydrochemical conditions in the two aquifers. Positive correlation between the distribution 

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MDL-NBS-HS-000021 REV 02 8-2 October 2004 
coefficient for plutonium in volcanic units and alluvium is specified, based on potentially similar 
hydrochemical conditions in the two aquifers. Positive correlation between the distribution 
coefficients for uranium and neptunium is specified, based on similarities in the chemical 
behavior of these radioelements. The technical bases for correlations between distribution 
coefficients (or the lack thereof) are documented in Site-Scale Saturated Zone Transport 
(BSC 2004 [DIRS 170036], Section C1.2.1). 
Evaluation of uncertainty in horizontal anisotropy in permeability is summarized in 
Section 6.5.2.10. Complete documentation of the technical basis for this evaluation of 
uncertainty is given in Saturated Zone In-Situ Testing (BSC 2004 [DIRS 170010]), Section 6.2.6. 
Results of this evaluation indicate that there is a greater probability of enhanced permeability in 
the north-south direction, but a small probability of greater permeability in the east-west 
direction. Implementation of uncertainty in horizontal anisotropy in the SZ transport abstraction 
model and in the SZ 1-D transport model is discussed in Section 6.5.3.1 and Section 6.5.1.2, 
respectively. 
The impacts of spatial variability of parameters affecting radionuclide transport in the alluvium 
are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, 
Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. Uncertainties in 
individual parameters affecting radionuclide transport, as influenced by spatial variability, are 
combined in the probabilistic analyses with the SZ transport abstraction model. The technical 
bases for uncertainty in distribution coefficients are documented in Site-Scale Saturated Zone 
Transport (BSC 2004 [DIRS 170036], Attachment A). 
Information on geological uncertainty in the location of the contact between tuff and alluvium, 
and the consequent uncertainty in flow-path lengths in the alluvium, is presented in 
Section 6.5.2.2. This evaluation of uncertainty includes information from the Nye County 
drilling program. Reevaluation of the uncertainty in the northern and western extent of the 
alluvium resulted in significant reduction in this uncertainty, in comparison to the previous 
evaluation (CRWMS M&O 2000 [DIRS 147972], Section 6.2). 
The sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in 
the assessment of ACMs in Section 6.4. The results of this sensitivity analysis indicate that a 
minimal matrix diffusion ACM is captured within the range of uncertainty used in the SZ 
transport abstraction model. 
8.2 MODEL OUTPUTS 
8.2.1 Developed Output 
The technical output from this report is given in seven DTNs; these DTNs are summarized in 
Table 8-1. 

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MDL-NBS-HS-000021 REV 02 8-3 October 2004 
Table 8-1. Summary of Developed Output 
Output DTN Description 
SN0310T0502103.009 Uncertainty distributions for parameters used in the SZ transport abstraction model. 
Sampling output of uncertain parameters for 200 realizations is also included (see 
Appendix I). This DTN also includes a description of each uncertain parameter. 
SN0310T0502103.010 Input and output files for the SZ transport abstraction model. This DTN also contains 
the output breakthrough curves for use in the TSPA-LA analyses. 
SN0306T0502103.005 Input and output files for the SZ 1-D transport model. 
SN0306T0502103.006 Data spreadsheets to support data uncertainty development. 
SN0310T0502103.012 Input and output files for the SZ transport abstraction model for the fast fraction of 
radionuclides irreversibly attached to colloids. This DTN also contains the output 
breakthrough curves for use in the TSPA-LA analyses. 
SN0407T0502103.013 Input and output files for the SZ transport abstraction model with re-sampling of input 
parameters to address CR 2222 (Evaluate Revised LH Sampling Algorithm on the 
Results of ANL-EBS-PA-000009). This DTN also contains the output breakthrough 
curves for use in the TSPA-LA analyses. 
MO0310SPANGRAC.000 Results of the background gross alpha concentration analysis. 
Results of the parameter uncertainty analyses from this report are given in 
DTN: SN0310T0502103.009. These results include the uncertainty distributions for parameters 
that were developed in this analysis or incorporated from other analyses and the input file for the 
GoldSim V7.50.100 software code for sampling 200 realizations from these uncertainty 
distributions. DTN:SN0310T0502103.009 also contains the output file from the GoldSim 
V7.50.100 software code, which includes the parameter vectors to be used in the SZ transport 
abstraction model. 
Results of the SZ transport abstraction model from this report are given in 
DTN: SN0310T0502103.010. These results consist of the input and output files from the 
FEHM V2.20 software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code 
(STN: 10914-2.0-00), and the SZ_Post V3.0 software code (STN: 10915-3.0-00) used in the 
analyses. The results that form a direct input to the TSPA-LA model are the files that contain the 
breakthrough curves (from the SZ transport abstraction model) from the 200 realizations of 
radionuclide transport. The breakthrough curves used in the TSPA-LA model (i.e., the 
breakthrough curves at the regulatory boundary of the accessible environment) are defined in the 
output files in the first column (time) and the third column (relative mass). 
The input and output files for the SZ 1-D transport model are given in 
DTN: SN0306T0502103.005. The input file of the SZ 1-D transport model for the GoldSim 
V7.50.100 software code is intended for incorporation into the TSPA-LA model. Output 
pertaining to parameter values for use in the SZ 1-D transport model is also found in Section 
6.5.1.2 of this report. Estimates of groundwater specific discharge for the three pipe segments 
(in the SZ 1-D transport model) taken from the SZ transport abstraction model are given in 
Table 6-6, as a function of horizontal anisotropy in permeability. Estimates of the minimum and 
maximum pipe lengths for the second and third pipe segments in the SZ 1-D transport model are 
given in Table 6-7 as a function of source region and horizontal anisotropy in permeability. 

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MDL-NBS-HS-000021 REV 02 8-4 October 2004 
The data spreadsheets in DTN: SN0306T0502103.006 have the data used in the analyses of 
parameter uncertainty summarized in this report and in DTN: SN0310T0502103.009. The 
spreadsheets mentioned by filename in this report are included in DTN: SN0306T0502103.006. 
Results of the SZ transport abstraction model that used re-sampling of the input parameters from 
Appendix B of this report are given in DTN: SN0407T0502103.013. These results were 
generated primarily to address CR 2222 (Evaluate Revised LH Sampling Algorithm on the 
Results of ANL-EBS-PA-000009) with respect to evaluation of the impact of the sampling 
difference in the GoldSim V7.50.100 software code. These radionuclide transport simulation 
results are also appropriate for use as input to the TSPA-LA for purposes of evaluating the 
impacts of the problem identified in CR 2222 at the total-system level, if necessary. These 
results consist of the input and output files from the following codes used in the analyses: the 
FEHM V2.20 software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code 
(STN: 10914-2.0-00), and the SZ_Post V3.0 software code (STN: 10915-3.0-00). The 
breakthrough curves accepted for use in the TSPA-LA model (i.e., the breakthrough curves at the 
regulatory boundary of the accessible environment) are defined in the output files, in the first 
column (time) and the third column (relative mass). 
This reports results of the SZ transport abstraction model for the fast fraction of radionuclides 
irreversibly attached to colloids are given in DTN: SN0310T0502103.012. These results consist 
of the input and output files from the following codes used in the analyses: the FEHM V2.20 
software code (STN: 10086-2.20-00), the SZ_Pre V2.0 software code (STN: 10914-2.0-00), 
and the SZ_Post V3.0 software code (STN: 10915-3.0-00). The results that form a direct input 
to the TSPA-LA model are the files that contain the breakthrough curves (from the SZ transport 
abstraction model) used for the 200 realizations of radionuclide transport. The breakthrough 
curves accepted for use in the TSPA-LA model (i.e., the breakthrough curves at the regulatory 
boundary of the accessible environment) are defined in the output files, in the first column 
(time) and the third column (relative mass). 
The results of the background gross alpha concentration analysis (as documented in Section 6.8) 
are given in DTN: MO0310SPANGRAC.000. 
8.2.2 Output Uncertainties and Limitations 
The assessment of uncertainty in model parameters and model outputs is an integral part of the 
performed analyses in this report. Uncertainty in model parameters is quantitatively represented 
by the statistical distributions developed and given in DTN: SN0310T0502103.009. Uncertainty 
in radionuclide transport in the SZ transport abstraction model is embodied in the breakthrough 
curves for the 200 realizations given in DTN: SN0310T0502103.010. The SZ 1-D transport 
model is intended for direct incorporation into the TSPA-LA model, with which uncertainty will 
be assessed using Monte Carlo probabilistic analyses. 
All relevant uncertainties in data and model parameters, with respect to their affect upon 
groundwater flow and radionuclide transport, have been included in both the SZ transport 
abstraction model and the SZ 1-D transport model. Uncertainties have been propagated through 
the results of the SZ transport abstraction model (i.e., the radionuclide breakthrough curves for 
multiple realizations) documented in this report. These output uncertainties address the 

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MDL-NBS-HS-000021 REV 02 8-5 October 2004 
requirements of acceptance criterion 3 of the YMRP (NRC 2003 [DIRS 163274]) for the 
propagation of data uncertainty through model abstraction for flow paths in the SZ and for 
radionuclide transport in the SZ. 
Use of the SZ transport abstraction model and the SZ 1-D transport model is subject to the 
limitations and restrictions imposed by the assumptions listed in Sections 5, 6.3, and 6.5 of this 
report. Limitations in knowledge of specific parameter values are addressed in this report in the 
analysis of parameter uncertainties. The radionuclide breakthrough curves generated for the SZ 
Transport Abstraction model are limited to 100,000 years duration for present climatic 
conditions; this limits the time period that can be simulated with the TSPA-LA model when 
using these breakthrough curves for the SZ. Because the SZ breakthrough curves are scaled for 
higher groundwater flow rates under future climatic conditions, the time period that can be 
simulated with the TSPA-LA model would be significantly less than 100,000 years. If the 
glacial-transition climate state is applied for most of the simulation period in the TSPA-LA 
model, the SZ breakthrough curves would be scaled by a factor of approximately four, thereby 
limiting the TSPA-LA model simulation time to about 25,000 years. 
8.3 YUCCA MOUNTAIN REVIEW PLAN ACCEPTANCE CRITERIA 
The following information describes how this analysis addresses the acceptance criteria in the 
Yucca Mountain Review Plan (NRC 2003 [DIRS 163274], Sections 2.2.1.3.8.3 and 2.2.1.3.9.3). 
Only those acceptance criteria that are applicable to this report (see Section 4.2) are discussed. 
In most cases, the applicable acceptance criteria are not addressed solely by this report; rather, 
the acceptance criteria are fully addressed when this report is considered in conjunction with 
other analysis and model reports that describe flow and transport in the saturated zone. Where a 
subcriterion includes several components, only some of those components may be addressed. 
How these components are addressed is summarized below. 
Acceptance Criteria from Section 2.2.1.3.8.3 Flow Paths in the Saturated Zone 
Acceptance Criterion 1: System Description and Model Integration Are Adequate 
Subcriterion (1): Total system performance assessment adequately incorporates 
important design features, physical phenomena, and couplings, and uses 
consistent and appropriate assumptions, throughout the flow paths in the saturated 
zone abstraction process; 
Important physical phenomena and couplings are incorporated into the SZ flow and transport 
model abstraction through application of the best relevant, qualified data from the Yucca 
Mountain site and region (Sections 4.1.1 and 4.1.2). Consistent and appropriate assumptions 
noted in Sections 5 and 6.3 are used throughout this abstraction report and other abstractions, 
model reports, and analysis reports related to flow paths in the SZ. Integration of the SZ 
abstraction models for the TSPA-LA is described in Sections 6.3.3 and 6.5.3. 
Subcriterion (2): The description of the aspects of hydrology, geology, 
geochemistry, design features, physical phenomena, and couplings that affect 
flow paths in the saturated zone, is adequate. Conditions and assumptions in the 

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MDL-NBS-HS-000021 REV 02 8-6 October 2004 
abstraction of flow paths in the saturated zone are readily identified, and 
consistent with the body of data presented in the description; 
This abstraction provides fully adequate descriptions of the aspects of hydrology, geology, 
geochemistry, physical phenomena, and couplings that may affect flow paths in the saturated 
zone through reference to supporting analysis and model reports in Table 4-1, discussion of 
incorporated features, events, and processes in Table 6-1, and detailed discussions of base-case 
conceptual model and inputs in Sections 6.3 and 6.5.2. Additional and more detailed 
descriptions of these aspects of the system are provided in supporting documents, particularly 
Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]) and BSC 2004 
[DIRS 170036]. Conditions and assumptions in the abstraction of flow paths in the saturated 
zone are readily identified in Sections 5 and 6.3, and they are consistent with the body of data 
presented in the descriptions (Sections 4.1, 6.2, 6.3, and 6.5). 
Subcriterion (3): The abstraction of flow paths in the saturated zone uses 
assumptions, technical bases, data, and models that are appropriate and consistent 
with other related U.S. Department of Energy abstractions. For example, the 
assumptions used for flow paths in the saturated zone are consistent with the total 
system performance assessment abstraction of representative volume (Section 
2.2.1.3.12 of the Yucca Mountain Review Plan). The descriptions and technical 
bases provide transparent and traceable support for the abstraction of flow paths 
in the saturated zone; 
Assumptions, described in Section 5, are consistent with those used in other model and analysis 
reports. For example, two of the six assumptions are carried forward directly from the Saturated 
Zone Colloid Transport scientific analysis report (BSC 2004 [DIRS 170006], Section 6.3). 
Technical bases, data, models, and local modeling assumptions are described in Section 6.3. 
Transparent and traceable support for the abstraction of flow paths in the SZ is provided for the 
SZ transport abstraction and the SZ 1-D transport model. For example, estimates of the variation 
in groundwater specific discharge and flow-path lengths in the SZ 1-D transport model are 
explained and illustrated in Section 6.5.1.2. 
Subcriterion (4): Boundary and initial conditions used in the total system 
performance assessment abstraction of flow paths in the saturated zone are 
propagated throughout its abstraction approaches. For example, abstractions are 
based on initial and boundary conditions consistent with site-scale modeling and 
regional models of the Death Valley ground water flow system; 
Boundary conditions used in the TSPA-LA abstraction of flow paths in the SZ are taken from the 
SZ site-scale flow model, as described in Section 6.5. These boundary conditions are based on 
analyses that use the regional model of the Death Valley groundwater flow system, as described 
in Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]). The effects of these 
boundary conditions are implicitly propagated to the SZ 1-D transport model through estimates 
of flow rates and pipe-segment lengths, as described in Section 6.5.1.2. Initial conditions are not 
used in the abstraction of flow paths because steady-state conditions are assumed. 

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MDL-NBS-HS-000021 REV 02 8-7 October 2004 
Subcriterion (5): Sufficient data and technical bases to assess the degree to which 
features, events, and processes have been included in this abstraction are 
provided; 
FEPs addressed in this model report are documented in Section 6.2. Table 6-1 summarizes those 
SZ FEPs for which the technical bases are provided in this report, and includes the location 
within this report of the information providing sufficient data and bases. 
Subcriterion (7): Long-term climate change, based on known patterns of climatic 
cycles during the Quaternary period, particularly the last 500,000 years, and other 
paleoclimate data, are adequately evaluated; 
The patterns of climatic cycles used for modeling were provided in the USGS Report Future 
Climate Analysis (USGS 2003 [DIRS 167961]), and were adequately evaluated for impacts on 
groundwater flow paths and flow rates in the SZ. The USGS analyzed known patterns of 
climatic cycles covering the last 500,000 years and correlated them with relevant paleoclimate 
data to produce the climate projections incorporated in this report. The application of climate 
information in modeling is described in Section 6.5. 
Subcriterion (9): The impact of the expected water table rise on potentiometric 
heads and flow directions, and consequently on repository performance, is 
adequately considered; 
The impact of expected water table rise has been adequately considered in Section 5 of this 
report by conservatively scaling transport rates in the SZ. Water table rise directly beneath the 
repository would place flow in hydrogeologic units with lower values of permeability (Section 5, 
item 6). This approximation of climate change with unaltered SZ flow paths is shown to 
underestimate radionuclide transport times in sensitivity studies documented in Site-Scale 
Saturated Zone Transport (BSC 2004 [DIRS 170036], Attachment E). 
Subcriterion (10): Guidance in NUREG1297 and NUREG1298 (Altman, et al., 
1988a, b), or other acceptable approaches for peer review and data qualification is 
followed. 
This report was developed in accordance with the Quality Assurance Requirements and 
Description (QARD) (DOE 2004 [DIRS 171539]), which commits to NUREGs 1297 and 1298. 
Moreover, compliance with the DOE procedures, which are designed to ensure compliance with 
the QARD, is verified by audits by QA and other oversight activities. Accordingly, the guidance 
in NUREGs 1297 and 1298 has been followed as appropriate. 
Acceptance Criterion 2: Data Are Sufficient for Model Justification 
Subcriterion (1): Geological, hydrological, and geochemical values used in the 
license application to evaluate flow paths in the saturated zone are adequately 
justified. Adequate descriptions of how the data were used, interpreted, and 
appropriately synthesized into the parameters are provided; 

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MDL-NBS-HS-000021 REV 02 8-8 October 2004 
Section 6.5.2 of this report provides thorough explanations that adequately justify the use of 
geological, hydrological, and geochemical values in the evaluation of flow paths. Section 6.5.2 
also adequately describes the interpretation of data and development of parameter values and 
distributions. Additional and more detailed descriptions of these aspects of the analysis are 
provided in supporting documents, particularly, Site-Scale Saturated Zone Flow Model (BSC 
2004 [DIRS 170037]) and BSC 2004 [DIRS 170036]. 
Subcriterion (3): Data on the geology, hydrology, and geochemistry of the 
saturated zone used in the total system performance assessment abstraction are 
based on appropriate techniques. These techniques may include laboratory 
experiments, site-specific field measurements, natural analog research, and 
process-level modeling studies. As appropriate, sensitivity or uncertainty 
analyses used to support the U.S. Department of Energy total system performance 
assessment abstraction are adequate to determine the possible need for additional 
data; 
Section 6.5.2 of this report describes the sources of data that were used in the development of 
modeling parameters in the TSPA-LA abstraction, the techniques used to evaluate these data, 
and the sufficiency of the data; the section also shows these techniques were appropriate. 
Table 6-8 includes the sources of input data, and associated uncertainty types. 
Acceptance Criterion 3: Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction 
Subcriterion (1): Models use parameter values, assumed ranges, probability 
distributions, and bounding assumptions that are technically defensible, 
reasonably account for uncertainties and variabilities, and do not result in an 
under-representation of the risk estimate; 
The development of parameter values, bounding values, and probability distributions is 
described in Section 6.5.2. The development was conducted in a technically defensible manner 
that reasonably accounts for uncertainty and variability. Two bounding assumptions are also 
described in Section 5, and model-specific assumptions are discussed in Section 6.3. Table 6-8 
shows probability distributions associated with the parameters, and Section 6.5.2 explains the 
sources of uncertainties in the parameters. The conservative simplifications and assumptions 
used for the abstraction models reasonably account for uncertainties and variabilities, and do not 
result in an under-representation of the risk estimate (Sections 5 and 6.3). 
Subcriterion (2): Uncertainty is appropriately incorporated in model abstractions 
of hydrologic effects of climate change, based on a reasonably complete search of 
paleoclimate data; 
The treatment of climate change and associated changes in infiltration are explained in 
Section 6.5 and Table 6-5. Applicable paleoclimate data was incorporated in the development of 
the climate phases adopted through the USGS Report Future Climate Analysis (USGS 2003 
[167961]). 

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MDL-NBS-HS-000021 REV 02 8-9 October 2004 
Subcriterion (3): Uncertainty is adequately represented in parameter development 
for conceptual models, process-level models, and alternative conceptual models 
considered in developing the abstraction of flow paths in the saturated zone. This 
may be done either through sensitivity analyses or use of conservative limits. For 
example, sensitivity analyses and/or similar analyses are sufficient to identify 
saturated zone flow parameters that are expected to significantly affect the 
abstraction model outcome; 
Section 6.5.2 includes detailed explanations of parameter representations and uncertainty sources 
of parameters that were used in the development of flow paths. Alternative conceptual models 
and associated sensitivity analyses used to address uncertainty are discussed in Section 6.4. 
Subcriterion (4): Where sufficient data do not exist, the definition of parameter 
values and conceptual models is based on appropriate use of expert elicitation, 
conducted in accordance with NUREG1563 (Kotra, et al., 1996). If other 
approaches are used, the U.S. Department of Energy adequately justifies their 
uses. 
Expert elicitation was used in the determination of groundwater specific discharge in the SZ. 
The expert elicitation process was conducted in accordance with DOE procedures that conform 
to NUREG-1563, and use of these results in quantifying uncertainty in specific discharge is 
described, with references, in Section 6.5.2.1. 
Acceptance Criterion 4: Model Uncertainty Is Characterized and Propagated Through the 
Model Abstraction 
Subcriterion (1): Alternative modeling approaches of features, events, and 
processes are considered and are consistent with available data and current 
scientific understanding, and the results and limitations are appropriately 
considered in the abstraction; 
The process of minimal matrix diffusion and the feature of horizontal anisotropy in permeability 
are considered in alternative conceptual models, as described in Section 6.4 and Table 6-4. The 
models are shown to be consistent with available data and current scientific knowledge and are 
considered appropriately in the abstraction through the ranges of parameter uncertainties in the 
base-case model. 
Subcriterion (2): Conceptual model uncertainties are adequately defined and 
documented, and effects on conclusions regarding performance are properly 
assessed. For example, uncertainty in data interpretations is considered by 
analyzing reasonable conceptual flow models that are supported by site data, or 
by demonstrating through sensitivity studies that the uncertainties have little 
impact on repository performance; 
Alternative conceptual models are discussed in Section 6.4. ACMs are also listed in Table 6-4, 
which includes key assumptions and bases for screening decisions. A sensitivity analysis was 
used to determine the impact of these alternatives on repository performance. Additional 

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MDL-NBS-HS-000021 REV 02 8-10 October 2004 
descriptions of ACMs of the SZ flow system are provided in the supporting document, Site-Scale 
Saturated Zone Flow Model (BSC 2004 [DIRS 170037]). 
Subcriterion (3): Consideration of conceptual model uncertainty is consistent with 
available site characterization data, laboratory experiments, field measurements, 
natural analog information and process-level modeling studies; and the treatment 
of conceptual model uncertainty does not result in an under-representation of the 
risk estimate. 
The parameters and parameter uncertainty related to groundwater flow from external sources 
used directly in the modeling documented in this report are shown in Table 4-3. Spatial 
variability in rock properties is encompassed within uncertainty distributions for key parameters 
(Tables 6-1 and 6-8). The uncertainty distributions incorporate uncertainties associated with 
Yucca Mountain field or laboratory data, knowledge of how the parameter will be used in the 
model, and theoretical considerations (Section 6.5.2). The probabilistic analysis of uncertainty in 
groundwater flow is implemented through Monte Carlo realizations of the SZ flow and transport 
system, in a manner consistent with the TSPA-LA simulations (Section 6.3). Variability in the 
results of multiple radionuclide breakthrough curves reflects the uncertainty in groundwater flow 
and radionuclide transport behavior in the SZ (Section 6.6). These results are intended for direct 
incorporation into the TSPA-LA model (Section 8.2.2), and as such, do not contribute to an 
under-representation of the risk estimate as determined in the TSPA-LA. 
Subcriterion (4): Appropriate alternative modeling approaches are consistent with 
available data and current scientific knowledge, and appropriately consider their 
results and limitations, using tests and analyses that are sensitive to the processes 
modeled. 
The process, bases, and results for alternative modeling approaches are discussed in Section 6.4. 
Results obtained by use of an ACM are also shown in Figure 6-3. Additional descriptions of 
ACMs of the SZ flow system are provided in the supporting document, Site-Scale Saturated 
Zone Flow Model (BSC 2004 [DIRS 170037]). An example is an alternative model based on 
different interpretations of pump test results in the fractured volcanic units. 
Acceptance Criterion 5: Model Abstraction Output Is Supported by Objective 
Comparisons 
Subcriterion (1): The models implemented in this total system performance 
assessment abstraction provide results consistent with output from detailed 
process-level models and/or empirical observations (laboratory and field testings 
and/or natural analogs); 
Results of TSPA-LA abstraction modeling are compared with results of detailed process-level 
models in Section 7. Graphical representations of these comparisons between the results of the 
SZ transport abstraction model and the SZ site-scale transport model, and between the results of 
the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 
7-4, and 7-5. These figures show consistent results between the abstraction models and detailed 
process-level models. 

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MDL-NBS-HS-000021 REV 02 8-11 October 2004 
Subcriterion (2): Outputs of flow paths in the saturated zone abstractions 
reasonably produce or bound the results of corresponding process-level models, 
empirical observations, or both; 
Model outputs, in the form of breakthrough curves, are presented in Section 6.6. In Section 7, 
results are compared with those of process models. The analysis abstracting the flow-path 
lengths from the SZ site-scale transport model, for use in the SZ 1-D transport model, is 
described in Section 6.5.1.2. 
Subcriterion (3): Well-documented procedures that have been accepted by the 
scientific community to construct and test the mathematical and numerical models 
are used to simulate flow paths in the saturated zone; and 
Section 7.2 documents the procedures that were followed in the testing and validation of the 
abstraction models developed in this model report. Approved QA procedures identified in the 
TWP (BSC 2004 [DIRS 171421], Section 4) have been used to conduct and document the 
activities described in this model report. Section 7.2 documents the procedures accepted by the 
scientific community that were followed in the testing and validation of the abstraction models 
developed in this model report. 
Subcriterion (4): Sensitivity analyses or bounding analyses are provided to 
support the abstraction of flow paths in the saturated zone, that cover ranges 
consistent with site data, field or laboratory experiments and tests, and natural 
analog research. 
Bounding analyses consistent with Yucca Mountain field and laboratory data were conducted to 
support the TSPA abstraction of flow paths in the saturated zone. These analyses considered 
uncertainties in the parameter that characterizes horizontal anisotropy. In addition, analyses 
were completed to bound the effects of uncertainty in the geometry of the alluvial uncertainty 
zone (Section 6.5.1.2) and the flow paths represented therein. 
Acceptance Criteria from Section 2.2.1.3.9, Radionuclide Transport in the Saturated 
Zone 
Acceptance Criterion 1: System Description and Model Integration Are Adequate 
Subcriterion (1): Total system performance assessment adequately incorporates 
important design features, physical phenomena, and couplings, and uses 
consistent and appropriate assumptions, throughout the radionuclide transport in 
the saturated zone abstraction process; 
Important physical phenomena and couplings are incorporated into the SZ flow and transport 
model abstraction through application of the best relevant, qualified data from the Yucca 
Mountain site and region (Sections 4.1.1 and 4.1.2). Consistent and appropriate assumptions 
noted in Sections 5 and 6.3 are used throughout this abstraction report and other abstractions, 
model reports, and analysis reports related to radionuclide transport in the SZ. 

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MDL-NBS-HS-000021 REV 02 8-12 October 2004 
Subcriterion (2): The description of the aspects of hydrology, geology, 
geochemistry, design features, physical phenomena, and couplings that may affect 
radionuclide transport in the saturated zone, is adequate. For example, the 
description includes changes into transport properties in the saturated zone, from 
water-rock interaction. Conditions and assumptions in the abstraction of 
radionuclide transport in the saturated zone are readily identified, and consistent 
with the body of data presented in the description; 
The abstraction in Section 6.3 of this report adequately describes the physical phenomena for the 
base-case conceptual model because it includes the aspects of hydrology, geology, geochemistry, 
physical phenomena, and couplings that may affect radionuclide transport in the saturated zone 
through reference to supporting analysis and model reports in Table 4-1, discussion of 
incorporated features, events, and processes in Table 6-1, and detailed discussions of important 
model considerations and inputs in Sections 6.3 and 6.5.2. Additional and more detailed 
descriptions of these aspects of the system are provided in supporting documents, particularly, 
Site-Scale Saturated Zone Flow Model (BSC 2004 [DIRS 170037]) and BSC 2004 
[DIRS 170036]. Conditions and assumptions in the abstraction of radionuclide transport in the 
saturated zone are readily identified in Sections 5, 6.3, and 6.5, and they are consistent with the 
body of data presented in the descriptions (Sections 4.1, 6.2, 6.3, and 6.5). 
Subcriterion (3): The abstraction of radionuclide transport in the saturated zone 
uses assumptions, technical bases, data, and models that are appropriate and 
consistent with other, related U.S. Department of Energy abstractions. For 
example, assumptions used for radionuclide transport in the saturated zone are 
consistent with the total system performance assessment abstractions of 
radionuclide release rates and solubility limits, and flow paths in the saturated 
zone (Sections 2.2.1.3.4 and 2.2.1.3.8 of the Yucca Mountain Review Plan, 
respectively). The descriptions and technical bases provide transparent and 
traceable support for the abstraction of radionuclide transport in the saturated 
zone; 
Assumptions, described in Section 5, are consistent with those used in other model and analysis 
reports. For example, two of the six assumptions are carried forward directly from the Saturated 
Zone Colloid Transport scientific analysis report (BSC 2003 [DIRS 170006], Section 6.3). 
Section 6.3.3 addresses the issue of consistency with interfacing UZ and biosphere models. 
Technical bases, data, models, and local modeling assumptions are described in Section 6.3. 
Transparent and traceable support for the abstraction of radionuclide transport in the SZ is 
provided for the SZ transport abstraction and the SZ 1-D transport model. For example, 
estimates of the variation in groundwater-specific discharge and flow-path lengths in the SZ 1-D 
transport model are explained and illustrated in Section 6.5.1.2. 
Subcriterion (4): Boundary and initial conditions used in the abstraction of 
radionuclide transport in the saturated zone are propagated throughout its 
abstraction approaches. For example, the conditions and assumptions used to 
generate transport parameter values are consistent with other geological, 
hydrological, and geochemical conditions in the total system performance 
assessment abstraction of the saturated zone; 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-13 October 2004 
Section 6.5 discusses boundary and initial conditions used in transport modeling. The 
groundwater flow boundary conditions for the SZ site-scale flow model, the SZ site-scale 
transport model, and the SZ transport abstraction model are specified head at the lateral 
boundaries and specified groundwater flux for recharge at the upper boundary. These boundary 
conditions are described in detail in Site-Scale Saturated Zone Flow Model (BSC 2004 
[DIRS 170037], Section 6.3.2). 
Subcriterion (5): Sufficient data and technical bases for the inclusion of features, 
events, and processes related to radionuclide transport in the saturated zone in the 
total system performance assessment abstraction are provided; and 
FEPs addressed in this model report are documented in Section 6.2. Table 6-1 summarizes those 
SZ FEPs for which the technical bases are provided in this report, and includes the location 
within this report of the technical information. 
Subcriterion (6): Guidance in NUREG1297 and NUREG1298 (Altman, et al., 
1988a, b), or other acceptable approaches for peer review and data qualification is 
followed. 
This report was developed in accordance with the QARD (DOE 2004 [DIRS 171539]), which 
commits to NUREGs 1297 and 1298. Moreover, compliance with the DOE procedures, which 
are designed to ensure compliance with the QARD, is verified by audits by QA and other 
oversight activities. Accordingly, the guidance in NUREGs 1297 and 1298 has been followed as 
appropriate. 
Acceptance Criterion 2: Data Are Sufficient for Model Justification 
Subcriterion (1): Geological, hydrological, and geochemical values used in the 
license application are adequately justified (e.g., flow path lengths, sorption 
coefficients, retardation factors, colloid concentrations, etc.). Adequate 
descriptions of how the data were used, interpreted, and appropriately synthesized 
into the parameters are provided; 
Section 6.5.2 of this report provides adequate and thorough explanations of the use of geological, 
hydrological, and geochemical values in evaluating flow, sorption, and colloid retardation. 
Section 6.5.2 also documents the interpretation of data, and the development of parameter values 
and uncertainty distributions. 
Subcriterion (2): Sufficient data have been collected on the characteristics of the natural 
system to establish initial and boundary conditions for the total system performance 
assessment abstraction of radionuclide transport in the saturated zone; 
The boundary conditions and interfaces between radionuclide transport in the SZ and the UZ and 
the biosphere are described in Section 6.3.3. An analysis of background gross alpha 
concentrations in groundwater, which represent the initial conditions of the system with regard to 
groundwater protection standards, is presented in Section 6.8. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-14 October 2004 
Acceptance Criterion 3: Data Uncertainty Is Characterized and Propagated Through the 
Model Abstraction 
Subcriterion (1): Models use parameter values, assumed ranges, probability 
distributions, and bounding assumptions that are technically defensible, 
reasonably account for uncertainties and variabilities, and do not result in an 
under-representation of the risk estimate; 
The development of parameter values, bounding values, and probability distributions is 
described in Section 6.5.2. The development was conducted in a technically defensible manner 
that reasonably accounts for uncertainty and variability. Two bounding assumptions are also 
described in Section 5. Table 6-8 shows probability distributions associated with the parameters, 
and Section 6.5.2 explains the sources of uncertainties in the parameters. The probabilistic 
analysis of uncertainty is implemented through Monte Carlo realizations of the SZ flow and 
transport system, in a manner consistent with the TSPA-LA simulations (Section 6.3). 
Subcriterion (4): Parameter values for processes, such as matrix diffusion, 
dispersion, and ground water mixing, are based on reasonable assumptions about 
climate, aquifer properties, and ground water volumetric fluxes (Section 2.2.1.3.8 
of the Yucca Mountain Review Plan); 
The conceptual model descriptions of processes such as advection, dispersion, and matrix 
diffusion are found in Section 6.3. Section 6.5.2 includes detailed explanations of the 
development of parameters used in these SZ flow processes, including discussions on the 
assumptions (e.g., climate changes, aquifer properties, and colloid transport properties) and bases 
upon which the parameter values are developed. 
Subcriterion (5): Uncertainty is adequately represented in parameter development 
for conceptual models, process-level models, and alternative conceptual models 
considered in developing the abstraction of radionuclide transport in the saturated 
zone. This may be done either through sensitivity analyses or use of conservative 
limits; 
Uncertainty in parameter values is adequately represented in Sections 6.3 and 6.4 of this report, 
in the context of conceptual models and alternative conceptual models. Parameter uncertainty at 
the process and abstraction level is discussed in detail in Sections 6.5.1 and 6.5.2. A 
probabilistic analysis of uncertainty in key model parameters is implemented through Monte 
Carlo realizations of the SZ flow and transport system, in a manner consistent with the TSPA-LA 
simulations. 
Subcriterion (6): Where sufficient data do not exist, the definition of parameter 
values and conceptual models is based on appropriate use of other sources, such 
as expert elicitation conducted in accordance with NUREG1563 (Kotra, et al., 
1996). If other approaches are used, the U.S. Department of Energy adequately 
justifies their use. 
Expert elicitation was used in the determination of dispersivity in the SZ. The expert elicitation 
process was conducted in accordance with DOE procedures that conform to NUREG-1563, and 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-15 October 2004 
use of these results in quantifying uncertainty in dispersivity is described, with references, in 
Section 6.5.2.9. 
Acceptance Criterion 4: Model Uncertainty Is Characterized and Propagated Through the 
Model Abstraction 
Subcriterion (1): Alternative modeling approaches of features, events, and 
processes are considered, and are consistent with available data and current 
scientific understanding, and the results and limitations are appropriately 
considered in the abstraction; 
The process of minimal matrix diffusion and the feature of horizontal anisotropy in permeability 
are considered in alternative conceptual models, as described in Section 6.4 and Table 6-4. The 
models are shown to be consistent with available Data and current scientific knowledge and are 
considered appropriately in the abstraction through the ranges of parameter uncertainties in the 
base-case model. 
Subcriterion (2): Conceptual model uncertainties are adequately defined and 
documented, and effects on conclusions regarding performance are properly 
assessed; 
Conceptual model uncertainties are adequately defined and documented in Sections 6.3 and 6.5 
of this report. The effects of the uncertainties on conclusions regarding performance of the 
conceptual model are discussed and shown in curves presented in Section 6.6 figures. 
Subcriterion (3): Consideration of conceptual model uncertainty is consistent 
with available site characterization data, laboratory experiments, field 
measurements, natural analog information and process-level modeling studies; 
and the treatment of conceptual model uncertainty does not result in an 
under-representation of the risk estimate; and 
The parameters and parameter uncertainty from external sources used directly in the modeling 
documented in this report are shown in Table 4-3. Spatial variability in rock properties is 
encompassed within uncertainty distributions for key parameters (Tables 6-1 and 6-8). The 
uncertainty distributions incorporate uncertainties associated with Yucca Mountain field or 
laboratory data, knowledge of how the parameter will be used in the model, and theoretical 
considerations (Section 6.5.2). The probabilistic analysis of uncertainty is implemented through 
Monte Carlo realizations of the SZ flow and transport system, in a manner consistent with the 
TSPA-LA simulations (Section 6.3). Variability in the results of multiple radionuclide 
breakthrough curves reflects the uncertainty in groundwater flow and radionuclide transport 
behavior in the SZ (Section 6.6). These results are intended for direct incorporation into the 
TSPA-LA model (Section 8.2.2), and as such, do not contribute to an under-representation of the 
risk estimate as determined in the TSPA-LA. 
Subcriterion (4): Appropriate alternative modeling approaches are consistent with 
available data and current scientific knowledge, and appropriately consider their 
results and limitations, using tests and analyses that are sensitive to the processes 
modeled. For example, for radionuclide transport through fractures, the U.S. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-16 October 2004 
Department of Energy adequately considers alternative modeling approaches to 
develop its understanding of fracture distributions and ranges of fracture flow and 
transport properties in the saturated zone. 
Alternative model approaches discussed in Section 6.4 are consistent with alternative 
interpretations of available data. Alternative conceptual models are also listed in Table 6-4, 
which includes key assumptions and bases for screening decisions. Alternative modeling 
approaches of fracture distributions and ranges of fracture flow and transport properties in the SZ 
are incorporated in upstream model reports. The conclusion of sensitivity analyses with regard 
to matrix diffusion in fractured media is that the alternative model of essentially no matrix 
diffusion is incorporated in the range of parameter uncertainties in the SZ transport abstraction 
model, as described in Section 6.4. 
Acceptance Criterion 5: Model Abstraction Output Is Supported by Objective 
Comparisons 
Subcriterion (1): The models implemented in this total system performance 
assessment abstraction provide results consistent with output from detailed 
process-level models and/or empirical observations (laboratory and field testings 
and/or natural analogs); 
Results of TSPA-LA abstraction modeling are compared with results of detailed process-level 
models in Section 7. Graphical representations of these comparisons between the results of the 
SZ transport abstraction model and the SZ site-scale transport model, and between the results of 
the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 
7-4, and 7-5. These figures show consistent results between the abstraction models and detailed 
process-level models. 
Subcriterion (2): Outputs of radionuclide transport in the saturated zone 
abstractions reasonably produce or bound the results of corresponding 
process-level models, empirical observations, or both. The U.S. Department of 
Energy-abstracted models for radionuclide transport in the saturated zone are 
based on the same hydrological, geological, and geochemical assumptions and 
approximations shown to be appropriate for closely analogous natural systems or 
laboratory experimental systems; 
Results of TSPA abstraction modeling are compared with results of detailed process-level 
models in Section 7. Graphical representations of these comparisons between the results of the 
SZ transport abstraction model and the SZ site-scale transport model, and between the results of 
the SZ 1-D transport model and the SZ site-scale transport model, are shown in Figures 7-1, 7-2, 
7-4, and 7-5. These figures show consistent results between the abstraction models and detailed 
process-level models. 
Subcriterion (3): Well-documented procedures that have been accepted by the 
scientific community to construct and test the mathematical and numerical models 
are used to simulate radionuclide transport through the saturated zone; and 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-17 October 2004 
Section 7.2 documents the procedures accepted by the scientific community that were followed 
in the testing and validation of the abstraction models developed in this model report. Approved 
QA procedures identified in the TWP (BSC 2004 [DIRS 171421], Section 4) have been used to 
conduct and document the activities described in this model report. Section 7.2 documents the 
procedures that were followed in the testing and validation of the abstraction models developed 
in this report. 
Subcriterion (4): Sensitivity analyses or bounding analyses are provided to 
support the total system performance assessment abstraction of radionuclide 
transport in the saturated zone, that cover ranges consistent with site data, field or 
laboratory experiments and tests, and natural analog research). 
Sensitivity analyses consistent with Yucca Mountain field and laboratory data were conducted to 
support the TSPA abstraction of radionuclide transport in the saturated zone. In particular, a 
sensitivity analysis of matrix diffusion in the SZ transport abstraction model is presented in the 
assessment of alternative conceptual models in Section 6.4. This analysis used the SZ transport 
abstraction model to show that the minimal matrix diffusion alternate model is included within 
the range of parameter uncertainties considered. Sensitivity analyses have also been performed 
on previous SZ transport modeling results (Arnold et al. 2003 [DIRS 163857]) (Section 6.7). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 8-18 October 2004 
INTENTIONALLY LEFT BLANK 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-1 October 2004 
9. INPUTS AND REFERENCES 
The following is a list of the references cited in this document. Column 2 represents the unique 
six digit numerical identifier (the Document Input Reference System number), which is placed in 
the text following the reference callout (e.g., BSC 2004 [DIRS 170014]). The purpose of these 
numbers is to assist in locating a specific reference. Within the reference list, multiple sources 
by the same author (e.g., BSC 2004) are sorted alphabetically by title. 
9.1 DOCUMENTS CITED 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Qualification of Existing 
Data for High-Level Nuclear Waste Repositories: Generic Technical Position. 
NUREG-1298. Washington, D.C.: U.S. Nuclear Regulatory Commission. 
TIC: 200652. 
103750 
Altman, W.D.; Donnelly, J.P.; and Kennedy, J.E. 1988. Peer Review for 
High-Level Nuclear Waste Repositories: Generic Technical Position. 
NUREG-1297. Washington, D.C.: U.S. Nuclear Regulatory Commission. 
TIC: 200651. 
103597 
Arnold, B.W.; Kuzio, S.P.; and Robinson, B.A. 2003. Radionuclide Transport 
Simulation and Uncertainty Analyses with the Saturated-Zone Site-Scale Model at 
Yucca Mountain, Nevada. Journal of Contaminant Hydrology, 62-63, 401-419. 
New York, New York: Elsevier. TIC: 254205. 
163857 
Bear, J. 1972. Dynamics of Fluids in Porous Media. Environmental Science 
Series. Biswas, A.K., ed. New York, New York: Elsevier. TIC: 217356. 
156269 
Bedinger, M.S.; Sargent, K.A.; Langer, W.H.; Sherman, F.B.; Reed, J.E.; and 
Brady, B.T. 1989. Studies of Geology and Hydrology in the Basin and Range 
Province, Southwestern United States, for Isolation of High-Level Radioactive 
WasteBasis of Characterization and Evaluation. U.S. Geological Survey 
Professional Paper 1370-A. Washington, D.C.: U.S. Government Printing Office. 
ACC: NNA.19910524.0125. 
129676 
Bower, K.M.; Gable, C.W.; and Zyvoloski, G.A. 2000. Effect of Grid Resolution on 
Control Volume Finite Element Groundwater Modeling of Realistic Geology. 
LA-UR-001870. Los Alamos, New Mexico: Los Alamos National Laboratory. 
TIC: 248256. 
149161 
BSC (Bechtel SAIC Company) 2001. Data Qualification Report: Calculated 
Porosity and Porosity-Derived Values for Lithostratigraphic Units for Use on the 
Yucca Mountain Project. TDR-NBS-GS-000020 REV 00. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: MOL.20010531.0193. 
163479

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-2 October 2004 
BSC 2001. Data Qualification Report: Matrix Hydrologic Properties and Alcove 1 
Infiltration Rate Data for Use on the Yucca Mountain Project. TDR-NBS-HS- 
000014 REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: MOL.20010924.0268. 
163566 
BSC 2002. Guidelines for Developing and Documenting Alternative Conceptual 
Models, Model Abstractions, and Parameter Uncertainty in the Total System 
Performance Assessment for the License Application. TDR-WIS-PA-000008 REV 
00, ICN 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
MOL.20020904.0002. 
158794 
BSC 2002. Validation Test Report, GoldSim Version 7.50.100. SDN: 10344-VTR- 
7.50.100-00. Las Vegas, Nevada: BSC (Bechtel SAIC Company). 
ACC: MOL.20030312.0227. 
163962 
BSC 2003. Saturated Zone Flow and Transport Model Abstraction. MDL-NBSHS-
000021 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20040128.0001. 
167651 
BSC 2003. SZ Flow and Transport Model Abstraction. MDL-NBS-HS-000021 
REV 00. Las Vegas, Nevada: Bechtel SAIC Company. 
ACC: DOC.20030818.0007. 
164870 
BSC 2003. Technical Work Plan for: Saturated Zone Flow and Transport 
Modeling and Testing. TWP-NBS-MD-000002 REV 01 ICN 01. Las Vegas, 
Nevada: Bechtel SAIC Company. ACC: DOC.20031203.0002. 
166034 
BSC 2003. Validation Test Report, SZ_Convolute Version 2.2. SDN: 10207-VTR- 
2.2-00. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
MOL.20021202.0341. 
163587 
BSC 2004. Analysis of Hydrologic Properties Data. ANL-NBS-HS-000042, 
Rev. 00. Las Vegas, Nevada: Bechtel SAIC Company. 
170038 
BSC 2004. D&E / PA/C IED Subsurface Facilities. 800-IED-WIS0-00101-000- 
00A. Las Vegas, Nevada: Bechtel SAIC Company. ACC: ENG.20040309.0026. 
164519 
BSC 2004. Features, Events, and Processes in SZ Flow and Transport. ANL-NBSMD-
000002, Rev. 03. Las Vegas, Nevada: Bechtel SAIC Company. 
170013 
BSC (Bechtel SAIC Company) 2004. Future Climate Analysis. ANL-NBS-GS- 
000008 REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
DOC.20040908.0005. 
170002 
BSC 2004. Hydrogeologic Framework Model for the Saturated Zone Site Scale 
Flow and Transport Model. MDL-NBS-HS-000024, Rev. 00. Las Vegas, Nevada: 
Bechtel SAIC Company. 
170008

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-3 October 2004 
BSC 2004. Probability Distribution for Flowing Interval Spacing. ANL-NBS-MD- 
000003, Rev. 01. Las Vegas, Nevada: Bechtel SAIC Company. 
170014 
BSC 2004. Q-List. 000-30R-MGR0-00500-000-000 REV 00. Las Vegas, Nevada: 
Bechtel SAIC Company. ACC: ENG.20040721.0007. 
168361 
BSC 2004. Recharge and Lateral Groundwater Flow Boundary Conditions for the 
Saturated Zone Site-Scale Flow and Transport Model. ANL-NBS-MD-000010 
REV 01. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
DOC.20041008.0004. 
170015 
BSC 2004. Rock Properties Model. MDL-NBS-GS-000004, Rev. 01. Las Vegas, 
Nevada: Bechtel SAIC Company. 
170032 
BSC 2004. Saturated Zone Colloid Transport. ANL-NBS-HS-000031, Rev. 02. 
Las Vegas, Nevada: Bechtel SAIC Company. 
170006 
BSC 2004. Saturated Zone In-Situ Testing. ANL-NBS-HS-000039, Rev. 01. Las 
Vegas, Nevada: Bechtel SAIC Company. 
170010 
BSC 2004. Saturated Zone Site-Scale Flow Model. MDL-NBS-HS-000011, Rev. 
02. Las Vegas, Nevada: Bechtel SAIC Company. 
170037 
BSC 2004. Site-Scale Saturated Zone Transport. MDL-NBS-HS-000010, Rev. 02. 
Las Vegas, Nevada: Bechtel SAIC Company. 
170036 
BSC 2004. Technical Work Plan for: Natural System - Saturated Zone Analysis 
and Model Report Integration. TWP-NBS-MD-000002 REV 02 ICN 01. Las 
Vegas, Nevada: Bechtel SAIC Company. ACC: DOC.20040818.0004. 
171421 
BSC 2004. Total System Performance Assessment (TSPA) Model/Analysis for the 
License Application. MDL-WIS-PA-000004, Rev. 00. Las Vegas, Nevada: Bechtel 
SAIC Company. 
168504 
BSC 2004. UZ Flow Models and Submodels. MDL-NBS-HS-000006, Rev. 02. Las 
Vegas, Nevada: Bechtel SAIC Company. 
169861 
BSC 2004. Waste Form and In-Drift Colloids-Associated Radionuclide 
Concentrations: Abstraction and Summary. MDL-EBS-PA-000004, Rev. 01. Las 
Vegas, Nevada: Bechtel SAIC Company. 
170025 
BSC 2004. Water-Level Data Analysis for the Saturated Zone Site-Scale Flow and 
Transport Model. ANL-NBS-HS-000034, Rev. 02. Las Vegas, Nevada: Bechtel 
SAIC Company. 
170009

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MDL-NBS-HS-000021 REV 02 9-4 October 2004 
Buchholtz ten Brink, M.; Phinney, D.L.; and Smith, D.K. 1991. Actinide 
Transport in Topopah Spring Tuff: Pore Size, Particle Size and Diffusion. 
Scientific Basis for Nuclear Waste Management XIV, Symposium held November 
26-29, 1990, Boston, Massachusetts. Abrajano, T.A., Jr. and Johnson, L.H., eds. 
212, 641-648. Pittsburgh, Pennsylvania: Materials Research Society. 
TIC: 203656. 
162954 
Buesch, D.C.; Spengler, R.W.; Moyer, T.C.; and Geslin, J.K. 1996. Proposed 
Stratigraphic Nomenclature and Macroscopic Identification of Lithostratigraphic 
Units of the Paintbrush Group Exposed at Yucca Mountain, Nevada. Open-File 
Report 94-469. Denver, Colorado: U.S. Geological Survey. ACC: 
MOL.19970205.0061. 
100106 
Burbey, T.J. and Wheatcraft, S.W. 1986. Tritium and Chlorine-36 Migration from 
a Nuclear Explosion Cavity. DOE/NV/10384-09. Reno, Nevada: University of 
Nevada, Desert Research Institute, Water Resources Center. TIC: 201927. 
129679 
Callahan, T.J.; Reimus, P.W.; Bowman, R.S.; and Haga, M.J. 2000. Using 
Multiple Experimental Methods to Determine Fracture/Matrix Interactions and 
Dispersion of Nonreactive Solutes in Saturated Volcanic Tuff. Water Resources 
Research, 36, (12), 3547-3558. Washington, D.C.: American Geophysical Union. 
TIC: 250760. 
156648 
Canori, G.F. and Leitner, M.M. 2003. Project Requirements Document. TERMGR-
MD-000001 REV 02. Las Vegas, Nevada: Bechtel SAIC Company. ACC: 
DOC.20031222.0006. 
166275 
Cooper, H.H., Jr. and Jacob, C.E. 1946. A Generalized Graphical Method for 
Evaluating Formation Constants and Summarizing Well-Field History. 
Transactions, American Geophysical Union, 27, (IV), 526-534. Washington, D.C.: 
American Geophysical Union. TIC: 225279. 
150245 
CRWMS (Civilian Radioactive Waste Management System) M&O (Management 
& Operating Contractor) 1997. Report of Results of Hydraulic and Tracer Tests at 
the C-Holes Complex. Deliverable SP23APM3. Las Vegas, Nevada: CRWMS 
M&O. ACC: MOL.19971024.0074. 
100328 
CRWMS M&O 1997. The Site-Scale Unsaturated Zone Transport Model of Yucca 
Mountain. Milestone SP25BM3, Rev. 1. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19980224.0314. 
124052 
CRWMS M&O 1997. Yucca Mountain Site Characterization Project Radiological 
Programs White Paper: Radioactivity in Groundwater in the Vicinity of Yucca 
Mountain. Las Vegas, Nevada: CRWMS M&O. ACC: MOL.19971215.0904. 
147759

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MDL-NBS-HS-000021 REV 02 9-5 October 2004 
CRWMS M&O 1998. Saturated Zone Flow and Transport. Chapter 8 of Total 
System Performance Assessment-Viability Assessment (TSPA-VA) Analyses 
Technical Basis Document. B00000000-01717-4301-00008 REV 01. Las Vegas, 
Nevada: CRWMS M&O. ACC: MOL.19981008.0008. 
100365 
CRWMS M&O 1998. Saturated Zone Flow and Transport Expert Elicitation 
Project. Deliverable SL5X4AM3. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19980825.0008. 
100353 
CRWMS M&O 1998. Yucca Mountain Site Characterization Project Radiological 
Programs, Radioactivity in FY 1997 Groundwater Samples from Wells and Springs 
Near Yucca Mountain. Rev. 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.19990218.0213. 
104963 
CRWMS M&O 1999. Radioactivity in FY 1998 Groundwater Samples from Wells 
and Springs Near Yucca Mountain. BA0000000-01717-5705-00029 REV 00. Las 
Vegas, Nevada: CRWMS M&O. ACC: MOL.19990622.0219. 
150420 
CRWMS M&O 2000. Modeling Sub Gridblock Scale Dispersion in Three- 
Dimensional Heterogeneous Fractured Media (S0015). ANL-NBS-HS-000022 
REV 00 ICN 01. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20001107.0376. 
152259 
CRWMS M&O 2000. Total System Performance Assessment for the Site 
Recommendation. TDR-WIS-PA-000001 REV 00 ICN 01. Las Vegas, Nevada: 
CRWMS M&O. ACC: MOL.20001220.0045. 
153246 
CRWMS M&O 2000. Uncertainty Distribution for Stochastic Parameters. 
ANL-NBS-MD-000011 REV 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000526.0328. 
147972 
CRWMS M&O 2000. Unsaturated Zone and Saturated Zone Transport Properties 
(U0100). ANL-NBS-HS-000019 REV 00. Las Vegas, Nevada: CRWMS M&O. 
ACC: MOL.20000829.0006. 
152773 
D'Agnese, F.A.; O'Brien, G.M.; Faunt, C.C.; and San Juan, C.A. 1999. Simulated 
Effects of Climate Change on the Death Valley Regional Ground-Water Flow 
System, Nevada and California. Water-Resources Investigations Report 98-4041. 
Denver, Colorado: U.S. Geological Survey. TIC: 243555. 
120425 
DOE (U.S. Department of Energy) 1997. Regional Groundwater Flow and Tritium 
Transport Modeling and Risk Assessment of the Underground Test Area, Nevada 
Test Site, Nevada. DOE/NV-477. Las Vegas, Nevada: U.S. Department of Energy. 
ACC: MOL.20010731.0303. 
103021

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MDL-NBS-HS-000021 REV 02 9-6 October 2004 
DOE 2003. Design Document for: SZ_CONVOLUTE Version 3.0. 10207-DD-3.0- 
00. Las Vegas, Nevada: U.S. Department of Energy, Office of Repository 
Development. ACC: MOL.20030717.0479. 
167588 
DOE 2004. Quality Assurance Requirements and Description. DOE/RW-0333P, 
Rev. 16. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: DOC.20040907.0002. Replacement for 
171386 
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Domenico, P.A. and Schwartz, F.W. 1990. Physical and Chemical Hydrogeology. 
New York, New York: John Wiley & Sons. TIC: 234782. 
100569 
EDCON. 2000. Report for the Borehole Gravity Survey in the NC-EWDP-19D Well 
in Nye County, Nevada on Behalf of TRW Corp. EDCON Job# 00011. Denver, 
Colorado: EDCON. TIC: 249823. 
154704 
Eddebbarh, A.A.; Zyvoloski, G.A.; Robinson, B.A.; Kwicklis, E.M.; Reimus, P.W.; 
Arnold, B.W.; Corbet, T.; Kuzio, S.P.; and Faunt, C. 2003. The Saturated Zone at 
Yucca Mountain: An Overview of the Characterization and Assessment of the 
Saturated Zone as a Barrier to Potential Radionuclide Migration. Journal of 
Contaminant Hydrology, 62-63, 477-493. New York, New York: Elsevier. 
TIC: 254205. 
163577 
Ferrill, D.A.; Winterle, J.; Wittmeyer, G.; Sims, D.; Colton, S.; Armstrong, A.; and 
Morris, A.P. 1999. Stressed Rock Strains Groundwater at Yucca Mountain, 
Nevada. GSA Today, 9, (5), 1-8. Boulder, Colorado: Geological Society of 
America. TIC: 246229. 
118941 
Flint, L.E. 1998. Characterization of Hydrogeologic Units Using Matrix 
Properties, Yucca Mountain, Nevada. Water-Resources Investigations Report 
97-4243. Denver, Colorado: U.S. Geological Survey. ACC: MOL.19980429.0512. 
100033 
Freeze, R.A. and Cherry, J.A. 1979. Groundwater. Englewood Cliffs, New Jersey: 
Prentice-Hall. TIC: 217571. 
101173 
Gelhar, L.W. 1986. Stochastic Subsurface Hydrology from Theory to 
Applications. Water Resources Research, 22, (9), 135S-145S. Washington, D.C.: 
American Geophysical Union. TIC: 240749. 
101131 
Hillel, D. 1980. Fundamentals of Soil Physics. New York, New York: Academic 
Press. TIC: 215655. 
101134 
Howard, N.W. 1985. Variation in Properties of Nuclear Test Areas and Media at 
the Nevada Test Site. UCRL-53721. Livermore, California: Lawrence Livermore 
National Laboratory. TIC: 229690. 
153266

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-7 October 2004 
Jury, W.A.; Sposito, G.; and White, R.E. 1986. A Transfer Function Model of 
Solute Transport Through Soil. 1. Fundamental Concepts. Water Resources 
Research, 22, (2), 243-247. Washington, D.C.: American Geophysical Union. 
TIC: 254552. 
164314 
Knoll, G.F. 1989. Radiation Detection and Measurement. 2nd Edition. New York, 
New York: John Wiley & Sons. TIC: 233703. 
161052 
Kreft, A. and Zuber, A. 1978. On the Physical Meaning of the Dispersion 
Equation and Its Solutions for Different Initial and Boundary Conditions. 
Chemical Engineering Science, 33, (11), 1471-1480. New York, New York: 
Pergamon Press. TIC: 245365. 
107306 
Li, Y-H. and Gregory, S. 1974. Diffusion of Ions in Sea Water and Deep-Sea 
Sediments. Geochimica et Cosmochimica Acta, 38, (5), 703-714. New York, New 
York: Pergamon Press. TIC: 246823. 
129827 
Luckey, R.R.; Tucci, P.; Faunt, C.C.; Ervin, E.M.; Steinkampf, W.C.; D'Agnese, 
F.A.; and Patterson, G.L. 1996. Status of Understanding of the Saturated-Zone 
Ground-Water Flow System at Yucca Mountain, Nevada, as of 1995. Water- 
Resources Investigations Report 96-4077. Denver, Colorado: U.S. Geological 
Survey. ACC: MOL.19970513.0209. 
100465 
Manger, G.E. 1963. Porosity and Bulk Density of Sedimentary Rocks. Geological 
Survey Bulletin 1144-E. Washington, D.C.: U.S. Government Printing Office. 
TIC: 249699. 
154474 
McKenna, S.A.; Walker, D.D.; and Arnold, B. 2003. Modeling Dispersion in 
Three-Dimensional Heterogeneous Fractured Media at Yucca Mountain. Journal 
of Contaminant Hydrology, 62-63, 577-594. New York, New York: Elsevier. 
TIC: 254205. 
163578 
Miller, I. and Kossik, R. 1998. Repository Integration Program RIP Integrated 
Probabilistic Simulator for Environmental Systems Theory Manual and Users 
Guide. Redmond, Washington: Golder Associates. ACC: MOL.19980526.0374. 
100449 
Moyer, T.C. and Geslin, J.K. 1995. Lithostratigraphy of the Calico Hills Formation 
and Prow Pass Tuff (Crater Flat Group) at Yucca Mountain, Nevada. Open-File 
Report 94-460. Denver, Colorado: U.S. Geological Survey. 
ACC: MOL.19941208.0003. 
101269 
Newman, J. 1973. Electrochemical Systems. Englewood Cliffs, New Jersey: 
Prentice-Hall. TIC: 210201. 
148719 
NRC (U.S. Nuclear Regulatory Commission) 2003. Yucca Mountain Review Plan, 
Final Report. NUREG-1804, Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory 
Commission, Office of Nuclear Material Safety and Safeguards. TIC: 254568. 
163274

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-8 October 2004 
Reimus, P.W.; Haga, M.J.; Adams, A.I.; Callahan, T.J.; Turin, H.J.; and Counce, 
D.A. 2003. Testing and Parameterizing a Conceptual Solute Transport Model in 
Saturated Fractured Tuff Using Sorbing and Nonsorbing Tracers in Cross-Hole 
Tracer Tests. Journal of Contaminant Hydrology, 62-63, 613-636. New York, 
New York: Elsevier. TIC: 254205. 
162950 
Reimus, P.W.; Haga, M.J.; Humphrey, A.R.; Counce, D.A.; Callahan, T.J.; and 
Ware, S.D. 2002. Diffusion Cell and Fracture Transport Experiments to Support 
Interpretations of the BULLION Forced-Gradient Experiment. LA-UR-02-6884. 
Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 253859. 
162956 
Reimus, P.W.; Ware, S.D.; Benedict, F.C.; Warren, R.G.; Humphrey, A.; Adams, 
A.; Wilson, B.; and Gonzales, D. 2002. Diffusive and Advective Transport of 3H, 
14C, and 99Tc in Saturated, Fractured Volcanic Rocks from Pahute Mesa, Nevada. 
LA-13891-MS. Los Alamos, New Mexico: Los Alamos National Laboratory. 
TIC: 253905. 
163008 
Rundberg, R.S.; Partom, I.; Ott, M.A.; Mitchell, A.J.; and Birdsell, K. 1987. 
Diffusion of Nonsorbing Tracers in Yucca Mountain Tuff. Milestone R524. 
Los Alamos, New Mexico: Los Alamos National Laboratory. 
ACC: NNA.19930405.0074. 
106481 
Simpson, J.H and Carr, H.Y. 1958. Diffusion and Nuclear Spin Relaxation in 
Water. The Physical Review, Second Series, 111, (5), 1201-1202. New York, 
New York: American Physical Society. TIC: 246907. 
139449 
Skagius, K. and Neretnieks, I. 1986. Porosities and Diffusivities of Some 
Nonsorbing Species in Crystalline Rocks. Water Resources Research, 22, (3), 
389-398. Washington, D.C.: American Geophysical Union. TIC: 225291. 
156862 
Sudicky, E.A. and Frind, E.O. 1982. Contaminant Transport in Fractured Porous 
Media: Analytical Solutions for a System of Parallel Fractures. Water Resources 
Research, 18, (6), 1634-1642. Washington, D.C.: American Geophysical Union. 
TIC: 217475. 
105043 
Townsend, Y.E. and Grossman, R.F., eds. 2001. Nevada Test Site Annual Site 
Environmental Report for Calendar Year 2000. DOE/NV/11718-605. Las Vegas, 
Nevada: U.S. Department of Energy, Nevada Operations Office. TIC: 251545. 
156604 
Triay, I.R.; Birdsell, K.H.; Mitchell, A.J.; and Ott, M.A. 1993. Diffusion of 
Sorbing and Non-Sorbing Radionuclides. High Level Radioactive Waste 
Management, Proceedings of the Fourth Annual International Conference, 
Las Vegas, Nevada, April 26-30, 1993. 2, 1527-1532. La Grange Park, Illinois: 
American Nuclear Society. TIC: 208542. 
145123

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-9 October 2004 
USGS (U.S. Geological Survey) 2003. Future Climate Analysis. ANL-NBS-GS- 
000008 REV 00 ICN 01 Errata 001. Denver, Colorado: U.S. Geological Survey. 
ACC: MOL.20011107.0004; DOC.20031015.0003. 
167961 
USGS 2001. Water-Level Data Analysis for the Saturated Zone Site-Scale Flow 
and Transport Model. ANL-NBS-HS-000034 REV 01. Denver, Colorado: U.S. 
Geological Survey. ACC: MOL.20020209.0058. 
157611 
USGS n.d. Bulk Density. Denver, Colorado: U.S. Geological Survey. 
ACC: NNA.19940406.0076. 
154495 
Viswanath, D.S. and Natarajan, G. 1989. Data Book on the Viscosity of Liquids. 
714-715. New York, New York: Hemisphere Publishing Corporation. 
TIC: 247513. 
129867 
Wilson, M.L.; Gauthier, J.H.; Barnard, R.W.; Barr, G.E.; Dockery, H.A.; Dunn, E.; 
Eaton, R.R.; Guerin, D.C.; Lu, N.; Martinez, M.J.; Nilson, R.; Rautman, C.A.; 
Robey, T.H.; Ross, B.; Ryder, E.E.; Schenker, A.R.; Shannon, S.A.; Skinner, L.H.; 
Halsey, W.G.; Gansemer, J.D.; Lewis, L.C.; Lamont, A.D.; Triay, I.R.; Meijer, A.; 
and Morris, D.E. 1994. Total-System Performance Assessment for Yucca Mountain 
 SNL Second Iteration (TSPA-1993). SAND93-2675. Executive Summary and 
two volumes. Albuquerque, New Mexico: Sandia National Laboratories. ACC: 
NNA.19940112.0123. 
100191 
Zyvoloski, G.; Kwicklis, E.; Eddebbarh, A.A.; Arnold, B.; Faunt, C.; and 
Robinson, B.A. 2003. The Site-Scale Saturated Zone Flow Model for Yucca 
Mountain: Calibration of Different Conceptual Models and their Impact on Flow 
Paths. Journal of Contaminant Hydrology, 62-63, 731-750. New York, New 
York: Elsevier. TIC: 254340. 
163341 
Zyvoloski, G.A.; Robinson, B.A.; Dash, Z.V.; and Trease, L.L. 1997. Summary of 
the Models and Methods for the FEHM ApplicationA Finite-Element Heat-and 
Mass-Transfer Code. LA-13307-MS. Los Alamos, New Mexico: Los Alamos 
National Laboratory. TIC: 235587. 
110491 
9.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
10 CFR 63. Energy: Disposal of High-Level Radioactive Wastes in a Geologic 
Repository at Yucca Mountain, Nevada. 
156605 
AP-2.22Q, Rev. 1, ICN 1. Classification Analyses and Maintenance of the Q-List. 
Washington, D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste 
Management. ACC: DOC.20040714.0002. 
AP-AC.1Q, Rev. 0, ICN 2. Expert Elicitation. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20020416.0050. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-10 October 2004 
AP-SIII.10Q, Rev. 2, ICN 7. Models. Washington, D.C.: U.S. Department of Energy, Office 
of Civilian Radioactive Waste Management. ACC: DOC.20040920.0002. 
LP-SI.11Q-BSC, Rev. 0, ICN 1. Software Management. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20041005.0008. 
9.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS010908312332.002. Borehole Data from Water-Level Data Analysis for the 
Saturated Zone Site-Scale Flow and Transport Model. Submittal date: 10/02/2001. 
163555 
GS030108314211.001. Interpretation of the Lithostratigraphy in Deep Boreholes 
NC-EWDP-18P, NC-EWDP-22SA, NC-EWDP-10SA, NC-EWDP-23P, NCEWDP-
19IM1A, and NC-EWDP-19IM2A, Nye County Early Warning Drilling 
Program, Phase III. Submittal date: 02/11/2003. 
163483 
GS031008312315.002. Transport Parameters from Analysis of Conservative (Non- 
Sorbing) Tracer Tests Conducted in the Fractured Tuff at the C-Hole Complex 
from 1996 to 1999. Submittal date: 10/09/2003. 
166261 
LA0002JC831341.001. Depth Intervals and Bulk Densities of Alluviums. 
Submittal date: 03/08/2000. 
147081 
LA0302RP831228.001. Type Curve Data for FEHM Macro SPTR Based on 
Sudicky and Frind Solution. Submittal date: 02/11/2003. 
163557 
LA0303HV831352.002. Colloid Retardation Factors for the Saturated Zone 
Fractured Volcanics. Submittal date: 03/31/2003. 
163558 
LA0303HV831352.004. Colloid Retardation Factors for the Saturated Zone 
Alluvium. Submittal date: 03/31/2003. 
163559 
LA0303PR831231.002. Estimation of Groundwater Drift Velocity from Tracer 
Responses in Single-Well Tracer Tests at Alluvium Testing Complex. 
Submittal date: 03/18/2003. 
163561 
LA0303PR831231.005. Simple Calculations for SZ In-Situ Testing AMR. 
Submittal date: 03/19/2003. 
166259 
LA0306SK831231.001. SZ Site-Scale Transport Model, FEHM Files for Base 
Case. Submittal date: 06/25/2003. 
164362 
LA0310AM831341.002. Saturated Zone Distribution Coefficients (Kds) for U, 
Np, Pu, Cs, Am, Pa, SR, Th, Ra, C, Tc, and I. Submittal date: 10/21/2003. 
165891 
LB0205REVUZPRP.001. Fracture Properties for UZ Model Layers Developed 
from Field Data. Submittal date: 05/14/2002. 
159525

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-11 October 2004 
LB03023DSSCP9I.001. 3-D Site Scale UZ Flow Field Simulations for 9 
Infiltration Scenarios. Submittal date: 02/28/2003. 
163044 
MO0003SZFWTEEP.000. Data Resulting from the Saturated Zone Flow and 
Transport Expert Elicitation Project. Submittal date: 03/06/2000. 
148744 
MO0010CPORGLOG.002. Calculated Porosity from Geophysical Logs Data from 
Old 40 Boreholes. Submittal date: 10/16/2000. 
155229 
MO0105GPLOG19D.000. Geophysical Log Data from Borehole NC EWDP 19D. 
Submittal date: 05/31/2001. 
163480 
MO0105HCONEPOR.000. Hydraulic Conductivity and Effective Porosity for the 
Basin and Range Province, Southwestern United States. Submittal date: 
05/02/2001. 
155044 
MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. 
Submittal date: 09/17/2001. 
155989 
MO0407SEPFEPLA.000. LA FEP List. Submittal date: 07/20/2004. 170760 
MO9904RWSJJS98.000. Radioanalytical Water Data for Samples Collected in 
June, July, and September 1998. Submittal date: 04/08/1999. 
165866 
SN0004T0501399.002. Correlation of RH (Relative Humidity) Porosity and Bulk 
Density. Submittal date: 04/13/2000. 
155046 
SN0004T0501399.003. Statistical Summary of Porosity Data. 
Submittal date: 04/13/2000. 
155045 
SN0302T0502203.001. Saturated Zone Anisotropy Distribution Near the C-Wells. 
Submittal date: 02/26/2003. 
163563 
SN0306T0504103.005. Revised Groundwater Colloid Mass Concentration 
Parameters for TSPA (Total System Performance Assessment). 
Submittal date: 06/30/2003. 
164132 
SN0306T0504103.006. Revised Sorption Partition Coefficients (Kd Values) for 
Selected Radionuclides Modeled in the TSPA (Total System Performance 
Assessment). Submittal date: 06/30/2003. 
164131 
SN9907T0571599.001. Probability Distribution of Flowing Interval Spacing. 
Submittal date: 07/15/1999. 
122261 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 9-12 October 2004 
9.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
MO0310SPANGRAC.000. Natural Gross Alpha Concentration In Amargosa Valley 
Groundwater. Submittal date: 10/23/2003. 
SN0306T0502103.005. SZ (SZ) 1-D Transport Model. Submittal date: 06/05/2003. 
SN0306T0502103.006. Data Spreadsheets To Support Parameter Uncertainty Development. 
Submittal date: 06/05/2003. 
SN0310T0502103.009. Revised Sz Transport Abstraction Model Uncertain Inputs. Submittal 
date: 10/09/2003. 
SN0310T0502103.010. Revised Sz Flow And Transport Model Abstraction Inputs And Results. 
Submittal date: 10/09/2003. 
SN0310T0502103.012. SZ Flow And Transport Model Abstraction Inputs And Results For Fast 
Fraction Of Irreversible Colloids. Submittal date: 10/24/2003. 
SN0407T0502103.013. Re-Sampled Sz Flow And Transport Model Abstraction Inputs And 
Results. Submittal date: 7/13/2004. 
9.5 SOFTWARE CODES 
BSC (Bechtel SAIC Company) 2003. Software Code: GoldSim. V7.50.100. PC. 
10344-7.50.100-00. 
161572 
BSC 2004. Software Code: GoldSim. V8.01 Service Pack 4. PC, Windows 2000. 
10344-8.01SP4-00. 
169695 
LANL (Los Alamos National Laboratory) 2001. Software Code: CORPSCON. 
V5.11.08. 10547-5.11.08-00. 
155082 
LANL 2003. Software Code: FEHM. V2.20. SUN, PC. 10086-2.20-00. 161725 
SNL (Sandia National Laboratories) 2003. Software Code: SZ_Convolute. V2.2. 
PC, Windows 2000. 10207-2.2-00. 
163344 
SNL 2003. Software Code: SZ_Convolute. V3.0. PC, Windows 2000. 10207-3.0- 
00. 
164180 
SNL 2003. Software Code: SZ_Post. V3.0. Sun, SunO.S. 5.7. 10915-3.0-00. 163571 
SNL 2003. Software Code: SZ_Pre. V2.0. Sun, Solaris 7. 10914-2.0-00. 163281 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 October 2004 
APPENDIX A 
STOCHASTIC PARAMETER VALUES 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 October 2004 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 A-1 October 2004 
This appendix contains a table listing the stochastic parameter values sampled for the SZ 
transport abstraction model and the SZ 1-D transport model. These parameter vectors for 200 
realizations were sampled using the uncertainty distributions described in Section 6.5.2. The 
base-case model results described in Section 6.6 correspond to the input parameter values 
tabulated in Table A-1. 

MDL-NBS-HS-000021 REV 02 A-2 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
1 0.70451 0.028309 0.15851 0.11373 1.3862 -3.7026 -10.092 1.7762 6.3364 268.07 259.27 
2 0.61702 0.70184 0.11408 0.081329 0.84234 -3.0161 -10.116 1.2311 4.8505 258.99 113.51 
3 0.35217 0.61633 0.083152 0.20585 1.0234 -3.3666 -10.146 1.09 4.2112 113.11 290.67 
4 0.43734 0.35304 0.20587 0.19441 0.83422 -3.8921 -10.539 1.3057 7.6552 290.9 159.82 
5 0.3726 0.4368 0.19441 0.16058 0.92304 -4.461 -10.042 1.5285 6.1118 160.14 199.68 
6 0.38137 0.37493 0.16033 0.17169 1.4084 -2.3306 -10.426 1.1931 6.4302 200.28 240.98 
7 0.96095 0.38323 0.17133 0.16309 0.81193 -2.6095 -10.325 1.556 5.7365 240.86 85.61 
8 0.96721 0.96199 0.1631 0.16459 1.1285 -3.3333 -10.197 1.2925 7.73 86.233 122.88 
9 0.063508 0.96547 0.16442 0.26596 1.3996 -3.1397 -10.612 1.1273 4.6382 122.69 82.931 
10 0.39763 0.063782 0.26525 0.26907 1.2126 -3.2812 -10.518 1.2363 7.7179 83.165 99.983 
11 0.12641 0.39708 0.26845 0.1011 0.63908 -3.2658 -10.619 1.2345 6.2902 100.11 249.1 
12 0.83363 0.12855 0.10207 0.16643 1.5206 -1.199 -10.572 1.8288 7.5701 248.31 79.438 
13 0.82638 0.83084 0.16658 0.12153 1.3272 -1.15 -10.174 1.2777 6.451 79.842 156.96 
14 0.46725 0.82571 0.12117 0.22766 0.62506 -3.976 -10.626 1.22 4.9316 156.83 245.64 
15 0.11482 0.46679 0.2272 0.22709 1.6764 -3.2319 -10.431 1.4189 6.8839 244.94 185.29 
16 0.24233 0.11166 0.22688 0.17505 1.0682 -3.8285 -10.185 1.5742 7.3231 183.88 46.974 
17 0.8055 0.24472 0.17513 0.11746 1.2021 -1.8383 -10.366 1.6247 7.8869 47.598 285.48 
18 0.1329 0.80984 0.11813 0.14376 1.0712 -1.8602 -10.758 1.2913 5.1106 284.54 222.27 
19 0.73058 0.13299 0.14387 0.22266 1.4018 -3.0689 -10.059 1.7072 5.8951 223.16 46.513 
20 0.34072 0.73141 0.22261 0.12312 1.3451 -3.856 -10.26 1.7658 8.6697 45.328 329.38 
21 0.048591 0.34315 0.12247 0.21023 1.0043 -3.5674 -10.801 1.5571 7.4175 327.85 136.96 
22 0.74837 0.048613 0.21035 0.15875 1.4574 -1.9719 -9.921 1.6685 7.7301 137.24 181.17 
23 0.93881 0.74785 0.15923 0.093691 1.2402 -3.8166 -10.485 1.5587 6.4626 180.92 138.35 
24 0.55458 0.93563 0.09379 0.21283 1.1247 -2.2296 -10.372 1.0925 1.9633 139.62 247.14 
25 0.79283 0.55378 0.21273 0.25453 1.668 -3.3458 -10.476 1.7332 6.3834 246.15 228.25 
26 0.37734 0.79098 0.25543 0.18598 1.816 -4.0395 -10.185 5.906 7.6101 227.35 115.13 

MDL-NBS-HS-000021 REV 02 A-3 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
27 0.67108 0.37594 0.18625 0.2203 0.94555 -2.1743 -10.24 1.5551 7.8466 116.36 264.39 
28 0.65266 0.67222 0.22046 0.16351 1.6175 -1.3137 -10.538 0.83687 6.7485 264.74 194.12 
29 0.62918 0.65188 0.1638 0.20193 1.5918 -2.8203 -10.13 1.6876 10.779 194.18 155.64 
30 0.24883 0.62618 0.20225 0.199 1.3545 -2.032 -10.341 1.135 2.4415 156.36 325.19 
31 0.71164 0.2459 0.19922 0.19577 0.76344 -3.2677 -10.437 1.3511 6.4552 325.42 362 
32 0.36584 0.7122 0.1961 0.14524 2.4058 -2.4327 -9.9314 1.5141 6.5489 361.97 105.28 
33 0.47113 0.36787 0.14464 0.20748 1.2638 -2.4921 -9.6565 1.5069 6.2446 103.82 313.97 
34 0.58157 0.47388 0.20749 0.16199 1.8275 -2.5698 -10.565 1.0319 5.3839 313.5 308.63 
35 0.17154 0.58391 0.16242 0.17587 1.381 -3.5586 -9.9702 1.1229 4.5499 307.59 232.62 
36 0.27276 0.17077 0.17593 0.19016 1.7866 -2.2884 -9.9878 1.2241 6.5466 230.98 72.64 
37 0.16841 0.2727 0.18985 0.13151 1.3153 -3.2946 -10.231 1.4754 5.7734 71.65 395.34 
38 0.21269 0.16757 0.13141 0.14914 1.5424 -3.0598 -10.645 1.0729 4.3751 395.81 200.88 
39 0.60151 0.21358 0.14881 0.13017 1.6877 -2.7243 -9.3455 1.1663 4.6523 201.21 362.94 
40 0.15729 0.60256 0.13036 0.13857 1.4451 -3.7297 -10.322 1.2935 5.863 363.36 239.29 
41 0.3647 0.15605 0.13923 0.19281 1.2456 -3.5069 -9.6366 1.402 7.3494 238.67 353.32 
42 0.59284 0.36398 0.19225 0.12862 1.5022 -3.7412 -10.208 1.1224 6.6715 353.63 219.29 
43 0.43429 0.59413 0.1289 0.16172 1.0933 -3.6399 -9.7391 1.7931 4.4304 218.86 293.52 
44 0.074964 0.43453 0.1616 0.1909 1.3933 -2.6663 -10.274 1.2546 6.7603 293.54 329.87 
45 0.69768 0.072714 0.19154 0.17113 1.7338 -3.7591 -10.037 1.0482 4.24 329.95 260.63 
46 0.53002 0.69555 0.17083 0.10469 0.60159 -3.3102 -9.9122 5.9484 12.998 260.58 195.92 
47 0.066897 0.53497 0.10634 0.20539 1.5563 -2.6836 -10.14 1.3471 6.3144 195.81 278.81 
48 0.81253 0.067039 0.20548 0.18333 1.629 -3.1487 -10.338 1.7807 8.2368 279.26 147.09 
49 0.307 0.81175 0.18364 0.10332 1.1917 -3.954 -10.079 1.1421 5.1387 146.39 242.3 
50 0.42421 0.30885 0.10441 0.2239 1.6554 -2.3446 -10.461 5.8964 12.116 242.61 342.55 
51 0.31471 0.42162 0.22428 0.15377 1.015 -2.8939 -10.193 1.7596 7.6537 342.37 42.645 
52 0.59783 0.31468 0.15362 0.16942 1.0887 -3.9623 -9.8347 1.3367 6.3723 41.049 296.42 
53 0.54881 0.59673 0.16958 0.15458 0.92816 -1.937 -10.881 1.826 5.3289 296.98 317.67 
54 0.25186 0.54916 0.15499 0.19171 1.3722 -3.4313 -10.022 2.9922 10.605 316.68 177.7 
55 0.64107 0.25325 0.19159 0.18521 0.58809 -3.1758 -9.9578 1.4494 6.9642 177.84 322.55 
56 0.45988 0.64197 0.18541 0.14594 0.70644 -3.4213 -10.38 1.3908 5.5995 322.77 120.09 
57 0.35868 0.45653 0.14567 0.19779 1.1816 -2.6824 -9.9416 1.8202 8.3781 119.49 144.75 

MDL-NBS-HS-000021 REV 02 A-4 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
58 0.80213 0.35725 0.19771 0.17377 1.8448 -2.8405 -10.526 1.4432 8.2585 144.07 102.59 
59 0.89925 0.80492 0.17397 0.16094 1.8056 -3.5446 -10.465 1.7504 8.3775 102.46 238.09 
60 0.22248 0.89986 0.16077 0.22181 0.8828 -2.5185 -10.569 2.0366 7.6319 238.24 40.481 
61 0.77121 0.22433 0.22181 0.24279 1.776 -3.0919 -10.209 4.6391 8.5555 39.125 60.504 
62 0.75746 0.77304 0.24181 0.14055 1.4833 -3.3141 -10.914 1.3779 5.6484 61.745 174.98 
63 0.55579 0.75953 0.14106 0.21688 0.29449 -1.9893 -10.676 1.5845 6.0788 175.27 368.07 
64 0.13508 0.5581 0.2173 0.2146 0.97023 -1.5186 -10.388 1.6112 7.9421 368.85 358.4 
65 0.9875 0.13511 0.21415 0.18662 0.67711 -3.6141 -9.5831 1.4423 7.3588 358.6 93.383 
66 0.47965 0.98618 0.18644 0.12437 1.0221 -2.0912 -9.6872 1.6498 6.3947 93.089 351.55 
67 0.90123 0.47822 0.12407 0.28381 1.3397 -2.146 -10.594 1.4092 4.8544 350.82 273.61 
68 0.57866 0.90303 0.28224 0.17637 1.1865 -2.81 -9.7422 1.5295 7.097 272.91 29.222 
69 0.87669 0.57844 0.17686 0.24362 1.3222 -3.8028 -10.099 1.7656 8.2015 29.194 109.73 
70 0.52246 0.87687 0.24338 0.18948 1.4151 -1.0566 -11.127 1.689 7.9085 110.4 55.672 
71 0.71788 0.52221 0.18946 0.23674 1.8942 -3.0485 -10.55 1.5342 7.2882 54.464 122.53 
72 0.81847 0.71882 0.23781 0.182 1.7624 -1.4862 -10.686 1.0478 4.0931 122.07 225.24 
73 0.63474 0.81922 0.18229 0.20867 0.738 -2.7404 -10.522 1.3844 5.8392 225.84 177.4 
74 0.46117 0.63266 0.20818 0.22519 1.7318 -1.6079 -10.25 1.1146 5.563 177.5 220.21 
75 0.68208 0.46283 0.22459 0.19667 1.533 -2.9264 -10.382 1.4729 4.6409 220.36 251.38 
76 0.33346 0.68422 0.19617 0.1746 1.7237 -2.2736 -10.267 3.8397 5.4484 250.42 379.89 
77 0.58661 0.33143 0.17454 0.2033 2.5288 -1.9123 -10.169 1.108 5.8758 379.91 348.05 
78 0.84781 0.58957 0.20353 0.15752 0.18779 -2.5558 -9.4799 3.6575 8.1698 347.72 65.785 
79 0.055061 0.84838 0.15727 0.1908 1.4319 -3.0857 -9.7859 1.7059 8.3184 65.77 340.28 
80 0.72545 0.059548 0.19074 0.23065 0.65772 -2.3987 -10.66 1.0474 6.9709 340.32 288.61 
81 0.78233 0.72652 0.23023 0.09896 1.0081 -3.3729 -9.8592 4.7524 7.3093 288.29 337.65 
82 0.41537 0.78383 0.10033 0.21009 1.5687 -2.7055 -10.051 1.3448 4.2383 338.42 396.46 
83 0.79615 0.4153 0.21009 0.21848 0.1867 -1.7701 -9.868 1.116 4.5096 396.97 24.361 
84 0.26279 0.79769 0.21877 0.169 1.8692 -3.9839 -9.3285 1.3663 6.2532 24.087 256.82 
85 0.32585 0.26149 0.16913 0.22126 1.0848 -2.2475 -11.197 3.2666 8.0548 257.05 51.292 
86 0.21935 0.32771 0.22133 0.14731 0.43697 -2.0638 -10.149 1.2834 6.8038 50.403 118.69 
87 0.57287 0.21868 0.14692 0.15714 1.0417 -3.1822 -10.698 1.1281 5.642 117.57 303.07 
88 0.05408 0.5743 0.15668 0.14015 0.69929 -2.0111 -10.532 1.5478 6.9799 302.88 23.539 

MDL-NBS-HS-000021 REV 02 A-5 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
89 0.10576 0.054487 0.13962 0.18832 1.2717 -3.5333 -10.005 1.6866 5.067 22.372 375.01 
90 0.40754 0.10529 0.18845 0.096424 1.6977 -3.3872 -11.258 2.6858 8.1054 374.3 142.05 
91 0.91603 0.40782 0.098203 0.11647 0.90599 -3.6232 -9.5364 1.2958 7.3349 143.11 32.802 
92 0.89135 0.91567 0.11686 0.16758 1.7454 -2.7577 -10.47 1.7117 6.3243 33.088 128.36 
93 0.19019 0.89023 0.16751 0.24842 0.46766 -3.9928 -11.072 1.5973 5.532 129.99 59.201 
94 0.87315 0.19372 0.24868 0.24104 1.2729 -3.8725 -10.503 1.4454 8.2211 58.595 204.12 
95 0.66517 0.87134 0.24128 0.13522 1.7668 -3.2063 -10.678 1.3136 6.3196 203.25 333.28 
96 0.024123 0.66764 0.13509 0.2357 0.79926 -1.415 -10.318 1.3962 5.1403 333.2 96.423 
97 0.23899 0.022985 0.23591 0.20122 0.78641 -1.5294 -9.9071 1.6784 10.47 96.617 343.73 
98 0.093079 0.23563 0.20126 0.079449 0.50753 -3.6823 -10.585 1.5156 6.2799 344.24 33.838 
99 0.26953 0.090888 0.078007 0.14284 1.6105 -1.6374 -9.8223 2.0086 12.343 33.832 205.03 
100 0.54079 0.26698 0.14297 0.1121 0.7266 -2.4384 -11.023 1.3193 4.8847 205.87 348.78 
101 0.41165 0.54048 0.11173 0.14771 1.2905 -4.5523 -10.31 1.114 5.4429 349.62 77.497 
102 0.52854 0.41152 0.14803 0.18493 1.053 -3.5782 -9.7593 5.3252 7.4087 77.534 76.842 
103 0.60808 0.52661 0.18474 0.16809 1.8672 -3.9083 -10.633 1.6194 5.0404 76.359 36.081 
104 0.94548 0.60856 0.1683 0.18302 1.8887 -3.5167 -10.633 1.0013 4.9632 36.121 311.98 
105 0.86326 0.94988 0.18294 0.19313 1.9802 -2.8632 -10.973 1.2785 5.8423 312.49 63.968 
106 0.12173 0.86184 0.19307 0.25889 2.2252 -3.196 -9.9776 1.5042 8.3694 64.993 210.78 
107 0.84161 0.12403 0.259 0.23369 0.81543 -2.9144 -10.666 1.0022 4.0211 210.19 132.5 
108 0.70681 0.84374 0.23391 0.12085 1.0518 -2.6365 -10.296 1.6652 8.0432 133.56 371.99 
109 0.83677 0.70737 0.12071 0.22943 1.0756 -1.2562 -10.492 1.404 7.1784 372.31 378.64 
110 0.99128 0.83905 0.22953 0.20708 1.0619 -1.6871 -9.5526 1.8088 6.2277 377.8 384.4 
111 0.010519 0.99171 0.20724 0.2288 1.1152 -3.8399 -9.5112 1.5117 8.0958 383.78 389.32 
112 0.62269 0.011542 0.22836 0.28924 1.5627 -1.7758 -9.4549 0.46893 2.0554 388.62 81.669 
113 0.084204 0.62223 0.29036 0.067107 1.1593 -2.3046 -9.3949 1.3874 5.0674 81.049 131.2 
114 0.25597 0.083179 0.063538 0.19537 1.7925 -1.8199 -10.623 1.0262 4.8538 131.47 141.54 
115 0.74132 0.25944 0.19539 0.10837 1.8399 -1.0372 -10.499 1.4555 4.3711 140.73 134.5 
116 0.007434 0.74115 0.10822 0.14618 1.3104 -4.793 -10.473 1.4463 4.6318 135.74 152.57 
117 0.93236 0.008269 0.14655 0.21192 1.0318 -2.5914 -10.486 1.2589 4.8102 151.56 300.09 
118 0.32035 0.93043 0.21235 0.049913 0.25923 -3.925 -10.447 1.6972 8.4928 299.64 166.3 
119 0.030233 0.32271 0.054478 0.25292 1.8314 -3.5417 -10.015 1.3911 6.5942 167.99 355.78 

MDL-NBS-HS-000021 REV 02 A-6 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
120 0.28508 0.034057 0.25215 0.15635 1.6384 -2.197 -10.408 1.0517 4.3142 355.96 366.8 
121 0.10144 0.28681 0.15579 0.084439 1.4232 -4.8885 -9.7061 4.1216 8.6042 365.99 216.81 
122 0.48434 0.10353 0.087276 0.15092 1.2272 -1.3375 -9.6162 1.7822 10.632 216.07 125.11 
123 0.82334 0.4826 0.15078 0.11532 1.2217 -3.394 -10.28 1.1916 6.8495 126.33 25.85 
124 0.20394 0.82124 0.1155 0.17726 1.8577 -4.3628 -10.513 0.55633 5.2954 25.77 364.38 
125 0.8532 0.20325 0.1773 0.2256 0.64581 -3.4685 -11.163 0.60824 5.5611 364.43 319.08 
126 0.037624 0.85435 0.22552 0.13752 2.2805 -3.8812 -9.6208 1.6654 8.6597 318.59 252.72 
127 0.48593 0.038573 0.1374 0.23209 1.8027 -3.0395 -9.9522 1.1375 4.852 253.06 189.7 
128 0.86876 0.48711 0.2322 0.090398 1.4724 -1.8783 -10.167 1.5864 7.4125 189.11 188.25 
129 0.1544 0.86639 0.087853 0.17752 0.8727 -3.6625 -10.349 1.2554 6.6315 189 371.09 
130 0.14816 0.15141 0.17766 0.23528 1.4626 -1.7361 -10.354 1.7691 6.1952 371.34 48.507 
131 0.043598 0.14898 0.2347 0.12704 0.8525 -4.2851 -9.5649 0.57225 6.1647 49.552 391 
132 0.76846 0.043645 0.12788 0.12639 1.9175 -3.0322 -10.707 1.5393 8.5753 392.36 358.05 
133 0.11602 0.76916 0.12658 0.091042 0.77682 -1.663 -9.3758 1.5539 6.1291 357.09 270.33 
134 0.50019 0.11576 0.091188 0.21608 1.5858 -3.7717 -9.697 1.4248 5.1128 268.94 91.21 
135 0.29848 0.50385 0.21619 0.11938 0.66707 -3.782 -10.108 1.7533 7.8604 91.012 266.13 
136 0.92706 0.29908 0.11876 0.1795 0.9665 -4.1659 -10.598 1.3229 6.3067 266.24 87.774 
137 0.94102 0.92914 0.17972 0.15236 1.6015 -2.1023 -10.123 1.4054 4.568 87.49 381.85 
138 0.95563 0.94338 0.1525 0.25203 1.0371 -3.8468 -10.607 1.3532 6.9416 382.11 73.304 
139 0.97152 0.95988 0.25117 0.25751 1.4984 -2.9884 -9.4764 1.4846 7.5599 75.05 305.76 
140 0.16243 0.97467 0.25758 0.26263 1.3352 -3.4489 -10.64 1.4352 6.1782 306.58 52.742 
141 0.29141 0.16433 0.26227 0.27269 1.3693 -1.3574 -9.9925 1.0025 4.2885 52.555 108.71 
142 0.31613 0.29468 0.27054 0.12983 0.90791 -1.2856 -10.691 1.304 5.0186 107.51 310.21 
143 0.30444 0.31977 0.12929 0.1517 1.1741 -1.2235 -10.553 1.2773 6.5328 309.31 127.74 
144 0.34719 0.30198 0.15141 0.15513 2.5485 -1.1431 -9.9839 1.6238 4.665 126.78 278.2 
145 0.73918 0.34993 0.15548 0.15306 1.2035 -3.7544 -10.508 1.5304 6.9865 278.09 224.01 
146 0.38633 0.73982 0.15327 0.15945 0.94859 -3.4626 -10.086 1.7279 6.2592 223.97 234.71 
147 0.88281 0.38841 0.15936 0.21123 1.7483 -3.4067 -10.258 1.4001 7.0045 235.6 98.655 
148 0.91034 0.88286 0.21103 0.16498 1.5123 -3.4429 -10.217 0.9905 2.7287 98.884 173.85 
149 0.51841 0.91188 0.16505 0.2382 0.12866 -3.3353 -10.578 0.96945 3.0842 172.58 398.45 
150 0.27749 0.51972 0.23803 0.24697 1.4763 -2.2129 -10.391 1.8137 7.36 399.04 182.7 

MDL-NBS-HS-000021 REV 02 A-7 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
151 0.018691 0.27629 0.2464 0.18134 1.6242 -3.245 -9.3007 1.6874 6.8565 182.75 106.24 
152 0.90977 0.017058 0.18162 0.14925 0.88989 -1.5786 -10.367 1.6278 7.3442 106.39 346.76 
153 0.78691 0.90918 0.14972 0.071036 1.1644 -1.444 -10.56 1.7089 8.5463 345.34 282.36 
154 0.61273 0.78833 0.073847 0.24478 1.5462 -2.9437 -9.806 1.532 4.5883 283.74 20.174 
155 0.44835 0.61154 0.24491 0.21959 1.509 -3.4983 -10.066 1.644 6.1311 20.054 272.36 
156 0.44417 0.44562 0.21926 0.19385 2.3672 -4.6266 -11.292 1.578 7.6511 270.96 316.33 
157 0.92465 0.44049 0.19402 0.17247 1.2376 -1.4517 -10.102 1.5821 7.0916 315.47 94.793 
158 0.076609 0.92395 0.17275 0.17226 1.297 -2.0342 -9.9661 1.036 4.1036 95.841 169.24 
159 0.97647 0.077995 0.17184 0.25011 1.2888 -2.622 -10.589 1.8158 6.7876 169.73 294.38 
160 0.88672 0.97946 0.24939 0.10731 1.3071 -3.1179 -10.4 1.4875 6.203 294.14 280.49 
161 0.65647 0.88508 0.10708 0.27559 1.3647 -3.1224 -10.027 1.4853 7.3059 281.47 392.49 
162 0.18665 0.65755 0.2747 0.2403 1.4503 -1.3913 -10.072 1.3696 4.7212 392.92 192.19 
163 0.64606 0.18543 0.23956 0.19953 0.86176 -3.9385 -9.369 5.6796 11.544 192.4 212.7 
164 0.17568 0.6463 0.19972 0.13401 1.2833 -1.1169 -10.347 1.0218 5.7699 212.65 209.44 
165 0.95061 0.17555 0.13472 0.19829 1.1026 -1.5522 -10.29 3.2702 12.928 209.18 215.42 
166 0.14335 0.95267 0.19855 0.13239 0.68419 -2.4821 -10.302 1.1476 4.9715 215.41 233.45 
167 0.75389 0.14211 0.13248 0.26065 0.35455 -3.6937 -10.285 1.4987 6.0234 233.3 262.83 
168 0.088815 0.75375 0.26063 0.12567 1.5235 -2.5044 -10.222 1.7817 7.7213 262.21 88.429 
169 0.23232 0.08869 0.12491 0.21379 1.4276 -3.7156 -10.133 1.1922 5.8916 89.341 207.49 
170 0.76434 0.23274 0.21353 0.11061 1.1196 -1.2367 -10.602 1.0342 6.3693 207.28 148.16 
171 0.28202 0.7616 0.11071 0.14232 1.2168 -3.7935 -10.308 1.3828 7.5455 147.76 56.742 
172 0.67838 0.28377 0.1421 0.21493 1.1411 -2.1576 -10.453 1.0248 4.8431 56.111 30.192 
173 0.53511 0.67815 0.2155 0.15048 1.1566 -3.9196 -10.686 1.3506 7.8087 30.992 286.7 
174 0.56885 0.53997 0.15046 0.20288 2.0937 -3.5938 -11.111 5.5651 10.593 286.98 254.82 
175 0.20533 0.5681 0.20264 0.18426 2.1634 -2.1331 -10.054 5.0921 12.993 254.19 153.59 
176 0.40471 0.20916 0.18434 0.18769 0.61684 -3.4847 -10.156 1.0081 2.0458 153.92 185.52 
177 0.9995 0.40055 0.18774 0.13838 1.1696 -2.4075 -10.442 1.5078 6.559 186.74 162.09 
178 0.42544 0.99674 0.13813 0.1669 0.74682 -2.8729 -10.359 1.76 6.093 160.92 166.26 
179 0.22637 0.42607 0.16701 0.29202 1.7114 -2.7766 -10.421 1.8183 8.4675 165.99 386.06 
180 0.85993 0.22959 0.29861 0.17001 1.7077 -3.649 -10.414 0.37838 4.25 385.73 387.44 
181 0.69081 0.85616 0.17039 0.14118 1.2552 -3.218 -9.4402 1.5396 6.3219 388.13 42.922 

MDL-NBS-HS-000021 REV 02 A-8 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
182 0.000316 0.69391 0.14143 0.23223 0.71843 -1.0082 -9.4219 1.6811 7.6176 44.051 170.83 
183 0.66425 0.000898 0.23224 0.20456 0.98249 -3.165 -10.84 0.82101 1.8184 170.21 68.282 
184 0.77963 0.6644 0.20481 0.02251 1.6687 -3.6051 -10.4 1.2373 4.7156 67.757 336.51 
185 0.19856 0.77701 0.026558 0.20066 0.75819 -1.714 -10.656 1.4965 5.9137 336.43 333.76 
186 0.39325 0.19937 0.2007 0.21764 1.5619 -2.3599 -9.8929 1.3319 6.6568 334.86 197.72 
187 0.72376 0.39066 0.21781 0.13599 1.1067 -4.9164 -9.9021 4.4429 10.666 197.9 62.435 
188 0.68892 0.7222 0.13594 0.16567 0.55484 -2.4516 -10.331 1.063 4.4061 61.878 112.56 
189 0.98274 0.6877 0.1656 0.2091 1.5759 -2.0718 -10.67 4.0276 8.2587 112.62 326.39 
190 0.45275 0.98273 0.20896 0.20396 1.8807 -3.6752 -10.546 1.699 8.1244 326.54 71.187 
191 0.50526 0.45272 0.20412 0.28052 1.3502 -3.2414 -9.9247 1.3218 7.4539 70.071 298.21 
192 0.49598 0.50781 0.27675 0.17357 1.6501 -2.2593 -10.652 1.4167 6.163 298.79 151.05 
193 0.51183 0.49782 0.17314 0.18015 1.1476 -2.3726 -10.017 1.5236 4.1231 150.2 38.786 
194 0.56134 0.51179 0.18047 0.17902 1.4929 -1.0761 -10.45 0.036671 6.0078 38.545 304.18 
195 0.63937 0.56322 0.17911 0.18073 1.469 -3.1087 -10.948 1.5217 5.8151 303.54 376.34 
196 0.18288 0.63794 0.18074 0.18708 1.4386 -2.9756 -9.9997 1.0782 4.5618 376.21 230.27 
197 0.49279 0.18439 0.18748 0.19706 0.99788 -3.0038 -9.5125 1.2419 5.6844 229.91 321.71 
198 0.33957 0.49261 0.19742 0.13392 1.5377 -2.9649 -10.239 1.2661 7.7128 321.32 162.65 
199 0.097933 0.33587 0.13394 0.17855 1.1373 -2.7936 -9.9428 1.1672 5.5324 163.61 275.46 
200 0.02951 0.098121 0.17837 0.15841 1.2559 -2.5445 -10.415 0.37655 1.9883 274.65 268.56 

MDL-NBS-HS-000021 REV 02 A-9 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
1 6.3929 4.0476 0.8181 1791.7 1.0875 1.0042 0.39801 0.12912 0.82832 0.11435 0.46636 
2 5.4235 4.3547 -0.85495 1889.7 3.5582 1.6714 0.12714 0.83286 0.46792 0.2438 0.11184 
3 6.091 4.121 -0.1215 1820.9 3.5695 1.1986 0.83439 0.82826 0.11009 0.80568 0.24456 
4 6.0964 4.1487 -0.44224 1984.5 0.90319 1.3675 0.82819 0.4672 0.24114 0.13093 0.80542 
5 7.4704 6.9729 0.39432 1983.7 1.1434 1.5138 0.46584 0.11053 0.80879 0.73468 0.13052 
6 7.5767 7.1394 0.3885 1904.1 0.90338 0.83369 0.11165 0.24447 0.13119 0.34017 0.73259 
7 6.7357 2.9464 -0.03684 1815.2 2.9725 1.0459 0.24061 0.80742 0.73112 0.046301 0.34463 
8 6.9733 4.2057 -0.46085 1855.7 2.9604 0.81838 0.80897 0.13118 0.34463 0.7483 0.04631 
9 5.4813 3.1882 -0.30786 1978.3 1.4071 0.91882 0.13468 0.73388 0.04603 0.93663 0.74671 
10 6.1144 5.8512 0.36448 1823.5 0.90334 1.5367 0.73421 0.34146 0.74618 0.55383 0.93928 
11 8.0149 5.8404 -0.43612 1957.8 0.90373 0.79926 0.34235 0.045831 0.93877 0.79495 0.55274 
12 7.3052 4.4718 0.27522 1878.4 2.8768 1.1894 0.049235 0.74967 0.55011 0.37712 0.79438 
13 5.7365 3.13 -0.19072 1777.8 0.9034 1.5267 0.74852 0.93563 0.79164 0.67425 0.37882 
14 6.3898 3.6295 -0.97733 1961.7 2.5538 1.3075 0.93625 0.55419 0.37553 0.65406 0.67351 
15 8.0955 5.7631 0.29233 2028.3 0.94105 0.77849 0.55335 0.79368 0.67241 0.62614 0.65251 
16 5.418 3.2064 0.66404 1920 0.90314 1.6522 0.79004 0.37616 0.65068 0.24578 0.62768 
17 7.2363 5.4719 0.059967 1973.9 2.6065 1.4544 0.37912 0.67379 0.62866 0.7112 0.24627 
18 6.297 3.9963 0.3514 1885.7 3.4344 0.77844 0.67485 0.65038 0.24892 0.3687 0.71087 
19 6.1532 2.8633 -0.14488 1944.9 1.7505 1.8446 0.65415 0.62701 0.711 0.47078 0.36665 
20 6.3443 5.5418 0.20717 1940.3 2.8112 1.0993 0.62895 0.24539 0.36569 0.58084 0.47477 
21 7.247 6.249 0.18479 1935.4 1.0695 1.288 0.24752 0.71071 0.47397 0.17007 0.5826 
22 6.6527 4.799 0.15118 1856.8 2.2828 1.1135 0.71398 0.36774 0.58472 0.27474 0.1718 
23 7.1839 5.711 -0.30353 1953.7 2.2025 1.5333 0.36813 0.47456 0.17021 0.1663 0.27316 
24 6.3895 4.1293 0.25181 1883.7 2.0793 1.4721 0.47446 0.58489 0.27248 0.21154 0.16614 
25 6.9776 5.251 -0.15875 1904.5 0.90375 1.0179 0.58135 0.17051 0.16512 0.60233 0.21337 
26 14.466 5.1801 -0.03341 1925.9 2.4697 1.5852 0.17104 0.27259 0.21288 0.15556 0.60328 
27 5.7245 5.0737 0.099475 1836.3 1.04 1.3493 0.27161 0.1696 0.60274 0.36263 0.15521 
28 5.4412 3.6421 -0.38882 1862.7 1.4328 1.1809 0.16813 0.2111 0.15655 0.59017 0.36338 

MDL-NBS-HS-000021 REV 02 A-10 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
29 7.345 5.3989 -0.27169 1834.9 1.8884 1.7837 0.21312 0.60029 0.36028 0.43416 0.59491 
30 6.6146 4.1024 -0.39819 1847.3 0.90353 2.3132 0.60039 0.15621 0.59053 0.070562 0.43237 
31 6.4572 4.4969 -0.34483 1930.7 0.90382 0.94597 0.15578 0.36256 0.43289 0.69568 0.072704 
32 6.7446 4.9141 0.11944 1831.2 0.90351 1.7452 0.36078 0.59297 0.074871 0.53396 0.69861 
33 6.5102 3.3664 -0.41112 1882.9 0.90364 1.7258 0.59401 0.43237 0.69566 0.066305 0.53255 
34 6.3393 3.7497 -0.16609 1928.7 1.9686 1.4833 0.43426 0.073074 0.53246 0.81035 0.069985 
35 5.9997 3.344 0.10967 1896.5 0.90348 0.77891 0.073323 0.6975 0.067696 0.30531 0.81321 
36 5.9559 3.508 -0.07847 1796.8 1.0186 2.8271 0.6963 0.53488 0.81113 0.42313 0.30702 
37 7.7597 4.9963 -0.76296 1950.8 1.9415 1.3809 0.53406 0.06581 0.30994 0.3125 0.42397 
38 5.4215 3.3073 0.23755 1916.7 1.2853 2.3632 0.065321 0.81078 0.4221 0.59713 0.31337 
39 7.5782 4.0865 0.037959 1792.3 0.90322 1.5062 0.81429 0.30812 0.31475 0.54755 0.59695 
40 6.8481 4.9427 -0.81314 1978.7 2.3987 2.2149 0.30883 0.42455 0.59518 0.25434 0.54791 
41 6.4336 4.348 0.37313 1870.6 1.6641 1.4434 0.42078 0.31241 0.54998 0.64335 0.25415 
42 5.9679 2.9858 -0.23107 1894.9 0.9032 1.6805 0.31042 0.59809 0.25497 0.45955 0.64074 
43 7.6914 5.3518 -0.08994 1872.4 2.8904 1.8892 0.59966 0.549 0.64079 0.35531 0.45927 
44 6.5365 4.7282 -0.2259 1929.2 0.90393 1.5782 0.54701 0.25493 0.45549 0.80303 0.35881 
45 3.8988 2.9717 0.11488 1919 1.2471 1.3553 0.25287 0.64012 0.35869 0.89767 0.8011 
46 7.76 5.7864 0.054703 1857.7 0.90394 1.634 0.64341 0.45504 0.80265 0.22022 0.89575 
47 6.9593 3.8645 -0.29576 1938.4 1.9461 1.1435 0.45681 0.35554 0.89736 0.77279 0.22201 
48 6.3023 4.2993 0.16765 1902 1.729 1.5204 0.35767 0.8033 0.22106 0.75653 0.7745 
49 7.1005 3.8948 -0.05232 1881.8 0.90376 2.0395 0.80219 0.8976 0.77391 0.55844 0.75595 
50 7.2944 4.9688 -0.17085 1976.9 2.1536 0.77839 0.89527 0.22021 0.75624 0.13669 0.55693 
51 6.9967 4.7739 0.35802 2009.1 1.3766 1.6906 0.22262 0.77394 0.55501 0.98761 0.13778 
52 6.1107 3.6678 0.4722 1850.2 1.0029 1.7566 0.77311 0.75559 0.136 0.47673 0.98982 
53 5.5058 5.1336 -0.32842 1968.2 2.8598 1.2814 0.75897 0.55733 0.98911 0.90165 0.47795 
54 8.0283 4.4488 0.3249 1965 3.2589 1.7758 0.55928 0.13643 0.47798 0.57992 0.9017 
55 7.1634 4.0579 0.30516 1921.4 0.90367 1.0305 0.13924 0.9852 0.90361 0.87597 0.57623 
56 7.7182 5.7363 0.069194 1824.4 2.7248 1.1388 0.98859 0.47716 0.57516 0.52119 0.8799 
57 16.934 6.1005 -0.43183 2082 2.6468 0.93337 0.47781 0.9021 0.87838 0.71927 0.52202 
58 6.3677 3.5446 0.92526 1905.5 1.7898 1.5033 0.90019 0.57664 0.52429 0.81645 0.71732 

MDL-NBS-HS-000021 REV 02 A-11 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
59 8.0137 5.6306 -0.02427 2011 0.90342 0.77833 0.57734 0.87993 0.7155 0.63189 0.8157 
60 7.5803 5.5676 0.47755 1925.5 3.6555 0.77871 0.87726 0.52225 0.81696 0.46085 0.63455 
61 7.8045 4.8121 0.093825 2000.3 1.4533 1.2651 0.52405 0.71818 0.63403 0.6836 0.4645 
62 6.8065 3.2399 0.44786 1914.8 3.2957 2.4448 0.71743 0.81913 0.46208 0.33488 0.68352 
63 7.8024 8.2148 0.027231 1955.4 1.8794 2.2914 0.81684 0.63478 0.68113 0.58819 0.33071 
64 6.3658 4.5135 0.26113 1979.9 3.1858 0.87284 0.63336 0.46033 0.33102 0.84547 0.58869 
65 6.6401 6.1286 0.38063 1936 1.6237 2.1973 0.46483 0.68187 0.58955 0.056247 0.84656 
66 8.0802 4.8948 0.15618 1902.7 2.4911 1.6189 0.68036 0.33279 0.84721 0.72827 0.058062 
67 7.5176 6.0288 -0.04535 1947.4 2.9073 0.77816 0.33359 0.58683 0.055556 0.78499 0.72763 
68 6.292 4.6899 0.21756 1876.5 2.1063 0.98331 0.5888 0.84941 0.72882 0.41564 0.78044 
69 7.9056 5.4261 -0.19898 1927.3 1.3901 0.77861 0.84696 0.057968 0.78458 0.79874 0.41834 
70 7.6321 5.7935 0.10325 1990.4 2.3218 1.0352 0.059202 0.72741 0.41612 0.26343 0.79713 
71 7.3797 5.1016 0.41512 1786.2 0.91759 1.4684 0.72908 0.783 0.79694 0.32595 0.26112 
72 6.5261 4.4622 -0.90291 1957.5 1.9062 1.2751 0.78309 0.41711 0.26183 0.21814 0.32885 
73 7.6682 5.2846 0.2696 1971.2 3.0586 1.4506 0.41849 0.79753 0.3285 0.57109 0.21954 
74 5.9958 3.9643 0.33449 1893.6 0.90317 1.5424 0.79539 0.26215 0.21556 0.051789 0.57407 
75 6.3393 4.9391 -0.0988 1974.5 2.5336 2.6217 0.26288 0.32672 0.57298 0.10611 0.052027 
76 7.6319 5.9195 0.3558 1860.1 2.769 2.1371 0.32568 0.21746 0.053163 0.40591 0.10719 
77 5.7279 2.9262 -0.2854 1874.8 1.2181 0.7788 0.21624 0.57483 0.10741 0.91972 0.40777 
78 7.3452 5.4588 -0.20391 1849.7 2.8383 2.0286 0.57311 0.052277 0.40829 0.8908 0.91655 
79 7.8172 5.6723 -0.33597 1924.3 0.90379 1.6683 0.05449 0.10898 0.91926 0.19459 0.89262 
80 7.2748 4.293 0.088795 1785.3 0.90398 1.9847 0.10825 0.4085 0.89123 0.87371 0.19373 
81 13.835 5.7162 -0.95629 1813.8 0.90365 2.8559 0.40932 0.91507 0.19271 0.66865 0.87036 
82 6.9084 3.6944 -0.46886 1891.7 1.847 0.77807 0.91592 0.89045 0.87402 0.022481 0.66851 
83 6.2653 3.9482 -0.11054 2018.2 0.90316 1.5616 0.89293 0.19045 0.66901 0.23693 0.024774 
84 5.4962 3.5414 0.57263 2006.8 0.90333 0.77854 0.19004 0.87062 0.023309 0.091047 0.2352 
85 7.7176 4.87 0.47059 1842.7 1.1819 1.0206 0.87302 0.66938 0.2368 0.26906 0.091802 
86 5.916 2.9113 -0.3659 1998.4 3.3469 1.7082 0.6656 0.024152 0.090667 0.54398 0.26823 
87 5.885 3.1148 0.44164 1944.2 3.2399 0.77803 0.023333 0.23528 0.26661 0.41455 0.54303 
88 6.5153 4.2502 0.19729 1751.8 0.90358 2.5253 0.23803 0.090919 0.54429 0.52672 0.41381 

MDL-NBS-HS-000021 REV 02 A-12 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
89 18.883 6.1699 -1.2709 1853.8 3.1498 1.1287 0.093541 0.26709 0.4112 0.6066 0.52874 
90 7.4636 6.0913 -0.31499 1806.3 2.2535 0.77822 0.26696 0.54419 0.52817 0.94606 0.60614 
91 5.5562 3.4321 -0.57236 1861.2 0.90307 1.0671 0.54172 0.41108 0.60997 0.86265 0.94816 
92 15.126 6.0081 -0.27432 1917.9 0.90372 0.77868 0.41491 0.52686 0.94891 0.12263 0.86301 
93 7.5253 5.2247 0.050354 1892.7 0.90328 1.3907 0.52942 0.60533 0.86005 0.84008 0.12295 
94 6.0635 2.2972 -0.10337 1915.2 0.9038 1.9143 0.60947 0.9471 0.12418 0.70779 0.84136 
95 6.1259 3.6118 0.032758 1931.1 1.7069 0.90439 0.94625 0.86346 0.84482 0.83642 0.70974 
96 6.019 3.0688 0.13087 2035.9 1.2067 2.0823 0.86403 0.12324 0.70673 0.9929 0.83838 
97 6.7596 3.7298 0.73013 1995.7 1.6498 0.77824 0.12021 0.84037 0.83719 0.014448 0.9937 
98 6.65 4.7642 0.43066 1819 1.9956 1.3968 0.84499 0.70858 0.99258 0.62177 0.010011 
99 7.1823 4.2707 -0.45167 1988.1 3.4882 2.1656 0.70993 0.83907 0.011816 0.080484 0.62177 
100 6.451 4.6949 0.40649 1952.6 3.1045 0.7812 0.83656 0.99291 0.62029 0.25668 0.084052 
101 7.4039 4.9982 0.24501 1986.7 0.90337 0.77897 0.99369 0.011109 0.084139 0.74363 0.25783 
102 7.4767 6.296 0.40263 2096.8 3.03 0.77829 0.012139 0.6206 0.25558 0.008536 0.74421 
103 7.0457 5.9683 0.9646 1736.1 2.4303 1.7389 0.62312 0.083331 0.74082 0.93232 0.008844 
104 5.7161 3.1765 -1.3741 1934.3 2.9977 0.77877 0.082851 0.25726 0.005755 0.32377 0.93333 
105 5.9557 5.8845 0.14663 1800.5 3.6849 1.4182 0.25651 0.74433 0.93264 0.031595 0.32274 
106 6.9747 5.3933 -0.65556 1859.7 0.90304 1.0833 0.74383 0.008921 0.32254 0.28928 0.032629 
107 8.938 5.8838 -0.29014 1960.3 2.0719 2.503 0.007082 0.93162 0.032139 0.10235 0.28732 
108 11.561 8.4623 0.28677 1711.5 0.90325 2.5914 0.9343 0.32226 0.28774 0.48315 0.10135 
109 6.12 1.9755 -1.4049 2027.8 0.90377 2.6724 0.32398 0.033875 0.10227 0.82137 0.48128 
110 6.9574 5.0698 0.65206 1874.1 2.5889 2.7358 0.034804 0.28617 0.48419 0.20142 0.82385 
111 5.7228 3.0312 -0.2145 1765.8 0.90302 0.8074 0.28713 0.10452 0.82206 0.85408 0.20133 
112 5.5625 3.6783 -1.1351 1866.8 3.4201 1.0809 0.10321 0.48255 0.20087 0.03713 0.85191 
113 7.3147 5.5068 -0.25443 1811.7 0.90397 1.1169 0.48009 0.82013 0.85325 0.48798 0.038156 
114 6.3164 1.9046 -0.47282 1906.2 0.9031 1.0955 0.82478 0.20143 0.036873 0.86745 0.48608 
115 7.5921 6.2268 -0.02221 1981.5 0.90386 1.1662 0.20399 0.85208 0.48667 0.15011 0.86707 
116 5.6012 3.9339 0.38733 1845.1 0.90331 1.7033 0.85464 0.036304 0.86896 0.14649 0.15383 
117 1.2364 2.4753 -0.35313 1991.5 1.4715 1.2305 0.038431 0.48549 0.15269 0.041893 0.14705 
118 6.6036 3.7894 0.42255 1773.4 2.934 2.2435 0.4888 0.86597 0.1496 0.76799 0.042585 

MDL-NBS-HS-000021 REV 02 A-13 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
119 5.6675 3.1009 -1.0969 1907.4 0.90361 2.4104 0.86947 0.1505 0.041331 0.11687 0.76983 
120 8.0168 4.5391 -0.01547 1997.7 3.0755 1.434 0.15471 0.14696 0.76917 0.50225 0.11804 
121 7.805 5.8264 0.4368 1830.6 0.90311 1.0568 0.1482 0.041927 0.11919 0.29972 0.50172 
122 7.3702 3.4667 -0.41438 1827.8 1.4778 0.77813 0.043749 0.76965 0.50249 0.92993 0.29938 
123 6.7213 5.929 -0.41778 1776.7 3.1256 2.3797 0.76795 0.11768 0.29931 0.94398 0.92995 
124 4.3306 2.6339 -1.0303 1966.5 0.90346 1.7621 0.11763 0.50186 0.92988 0.9591 0.94279 
125 6.2064 4.5436 0.31744 1818.1 0.90345 1.5484 0.50125 0.29969 0.9417 0.9723 0.95904 
126 7.6523 5.9877 -0.45746 1910.2 0.90312 1.3264 0.29829 0.92712 0.95959 0.16336 0.9735 
127 5.563 3.2852 0.001514 1868.8 2.6949 1.3193 0.92626 0.94495 0.97011 0.29355 0.16075 
128 6.1336 3.2702 -0.24028 2024.4 0.90336 2.4598 0.94317 0.95688 0.16089 0.31924 0.29198 
129 6.3297 2.6876 0.63084 2032.1 1.5522 0.77853 0.95718 0.97024 0.29356 0.30068 0.31688 
130 8.0247 5.6069 0.70954 2044.3 0.9039 2.7802 0.97338 0.16089 0.31924 0.34894 0.30226 
131 5.8546 3.1558 0.77432 2060.7 3.4028 2.2586 0.16471 0.29112 0.30169 0.73742 0.34723 
132 6.8369 4.6179 0.8669 1834 3.4585 1.6053 0.2919 0.31659 0.34685 0.38542 0.73879 
133 7.0371 3.8323 -0.40523 1867.7 3.5324 0.86487 0.31639 0.30034 0.7382 0.8844 0.38707 
134 8.0813 6.22 -0.24736 1873.1 3.5873 1.5948 0.30114 0.34737 0.38911 0.91417 0.88103 
135 7.7775 6.2657 -0.21795 1869.7 0.9035 0.84208 0.34709 0.7389 0.8827 0.51527 0.91491 
136 8.0432 6.5706 -0.23599 1879.7 0.90388 2.6439 0.73959 0.38723 0.91191 0.27739 0.51637 
137 7.1933 7.4878 -0.18222 1959.9 0.90395 0.77896 0.3856 0.88123 0.51821 0.01555 0.27512 
138 5.4294 3.3293 0.28472 1888.1 0.90392 1.721 0.8846 0.91276 0.27884 0.90859 0.015142 
139 7.4959 3.8249 -0.13344 2003.3 0.96295 0.77857 0.91058 0.51807 0.019829 0.78559 0.9075 
140 7.0592 3.9127 0.45875 2015.8 2.5618 0.96496 0.51863 0.27877 0.90669 0.61248 0.78753 
141 5.8007 3.847 0.55231 1913.2 1.1215 1.7325 0.27928 0.018004 0.78506 0.44553 0.6123 
142 6.8881 4.0184 0.022971 1864.3 3.212 1.0603 0.017035 0.90513 0.61484 0.44206 0.44827 
143 7.4777 5.5041 -0.26788 1747.7 3.339 1.6273 0.90617 0.7874 0.44935 0.92037 0.44137 
144 7.7513 4.1826 -1.319 2012.9 1.6067 1.4599 0.78778 0.61244 0.44289 0.077399 0.92211 
145 7.312 6.0396 0.51974 1971.7 0.90383 1.4942 0.61002 0.44738 0.92177 0.9795 0.075209 
146 14.261 6.1585 0.34072 1931.8 0.90305 0.9128 0.44868 0.44026 0.078919 0.88632 0.9771 
147 6.8555 4.6736 0.13291 1900.1 3.3213 1.2546 0.44447 0.92422 0.97874 0.65608 0.88741 
148 6.0243 3.7619 -0.06401 1898.7 2.7905 2.8905 0.92373 0.077673 0.88803 0.18793 0.65881 

MDL-NBS-HS-000021 REV 02 A-14 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
149 5.5135 2.0896 -0.07036 2019.6 2.0286 1.2974 0.076063 0.97623 0.65712 0.646 0.1872 
150 10.004 6.1315 0.60144 1800.4 1.3319 0.95621 0.977 0.88897 0.18621 0.17963 0.6468 
151 7.2786 5.6864 -0.70644 2065.3 1.3096 2.1114 0.88659 0.65894 0.64638 0.9533 0.17576 
152 7.0625 5.0306 0.88838 2004.3 3.3771 1.6455 0.65842 0.18734 0.17977 0.14185 0.9527 
153 7.3807 4.394 0.46244 1941.7 0.90323 0.77801 0.18664 0.64891 0.95287 0.75049 0.14379 
154 5.5048 4.3793 0.1871 1840.8 3.6119 1.6096 0.64507 0.17691 0.14233 0.086316 0.75248 
155 7.5409 6.1992 -0.37093 1939.2 3.2128 1.7536 0.17711 0.95118 0.75482 0.23203 0.087912 
156 6.3404 2.9992 0.17419 1838.4 2.2216 0.88998 0.95059 0.14242 0.086579 0.7641 0.23087 
157 6.1266 7.8565 -0.38192 2039.2 0.90356 1.2436 0.14252 0.75409 0.23232 0.28118 0.76162 
158 6.9607 6.0621 0.75051 1826.1 2.1818 1.6866 0.75153 0.088803 0.76344 0.67984 0.28492 
159 8.1312 5.1999 -0.42699 1963.6 0.90353 1.6433 0.08683 0.2337 0.28051 0.53945 0.67884 
160 5.6327 3.4208 0.29815 1803.9 3.5015 2.797 0.23407 0.76141 0.67786 0.56739 0.53767 
161 7.5186 5.1585 -0.61352 1852.5 0.90344 1.3361 0.76128 0.2824 0.53504 0.20679 0.5676 
162 7.238 3.3742 -0.3168 1966.2 2.6324 1.4226 0.28348 0.67679 0.56754 0.4036 0.20555 
163 8.0541 6.3283 0.31264 1864.5 0.90326 1.4115 0.6774 0.5359 0.20907 0.99995 0.40382 
164 1.2445 3.2461 -0.26077 1945.8 0.9037 1.4326 0.53853 0.56976 0.40303 0.42927 0.99514 
165 7.6782 5.5608 0.21202 1917.8 2.6793 1.4902 0.56716 0.20581 0.99747 0.22505 0.42972 
166 4.29 3.0393 0.042953 1923.5 0.90386 1.5815 0.20914 0.40267 0.42578 0.85881 0.22675 
167 7.0772 3.5934 0.082558 1846.9 2.304 0.85035 0.40148 0.99633 0.22882 0.69465 0.85692 
168 8.1091 5.5989 -0.3463 1890.8 1.6854 1.4043 0.99946 0.429 0.85968 0.002816 0.69442 
169 6.5584 3.7778 -0.11436 2150 1.8197 1.1554 0.42931 0.22809 0.69398 0.66467 0.004499 
170 7.6312 5.2625 0.9848 1896.2 0.90363 0.77864 0.22617 0.85547 0.000323 0.77513 0.66304 
171 6.7437 4.737 -0.08534 1851.6 1.1755 0.77818 0.85851 0.69354 0.66257 0.19757 0.77725 
172 5.6544 4.8472 -0.32558 1992.9 3.6966 1.6616 0.69111 0.003257 0.77945 0.39292 0.19571 
173 6.0848 3.487 0.42615 1949.6 1.2557 1.5596 0.003656 0.66345 0.19765 0.72304 0.3905 
174 10.67 4.2364 0.23043 1675.6 0.90369 1.1742 0.66204 0.77506 0.39062 0.68608 0.72139 
175 19.991 8.772 -1.4274 1942.6 3.1009 1.3104 0.77547 0.19838 0.72232 0.98368 0.68895 
176 5.7069 4.3221 0.1918 1969.8 2.3748 1.2113 0.19977 0.39453 0.68752 0.45485 0.98231 
177 5.8428 3.5686 0.32826 1844.1 0.903 1.2221 0.39164 0.72283 0.98031 0.50929 0.45473 
178 14.033 5.9529 -0.36243 1888.8 2.2491 2.6986 0.72173 0.68745 0.45427 0.49792 0.50512 

MDL-NBS-HS-000021 REV 02 A-15 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD BULKDE 
NSITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
179 6.969 5.3194 -0.1308 1955.7 2.7377 2.7263 0.68811 0.98268 0.5089 0.51067 0.49559 
180 4.8706 1.7248 0.26453 1948.5 0.90359 0.77843 0.98291 0.45113 0.49716 0.56127 0.51465 
181 7.2743 5.2177 0.22384 2076 1.14 1.249 0.45143 0.50761 0.51411 0.63635 0.56495 
182 14.003 5.6477 0.90461 1900.3 2.4991 0.77886 0.50641 0.4978 0.56414 0.18298 0.63987 
183 5.5135 3.4549 -0.05683 1911.2 2.3608 1.9716 0.49998 0.51184 0.63908 0.49347 0.18035 
184 7.4711 4.1951 0.010673 1909.7 3.6328 1.9303 0.51124 0.56314 0.18468 0.33757 0.49318 
185 6.7534 5.4358 -0.00257 1912.2 1.3576 1.3653 0.56096 0.63868 0.49378 0.095147 0.339 
186 7.6828 5.3098 0.015309 1922.2 1.5741 0.77876 0.63832 0.18425 0.33664 0.02893 0.098947 
187 8.1434 7.9127 0.072474 1937 1.5171 0.98742 0.18035 0.4943 0.0968 0.70491 0.029299 
188 6.7702 4.4289 0.16452 1839.5 1.5859 1.8086 0.49056 0.33741 0.026781 0.61604 0.70419 
189 7.4674 4.637 -0.37947 1909 1.7945 0.77888 0.33874 0.096534 0.70431 0.35289 0.61966 
190 6.9612 4.5943 -0.00717 1877.3 2.1272 1.6963 0.096831 0.029759 0.61591 0.43939 0.35146 
191 6.5706 4.6492 -0.19088 1809 0.90355 1.1569 0.028917 0.70069 0.35311 0.37338 0.43794 
192 6.4819 4.8274 -0.50508 1763.2 1.5065 0.77832 0.70456 0.6185 0.43943 0.38091 0.37255 
193 6.2727 5.1259 -1.2166 1951.2 0.921 1.7169 0.61513 0.35035 0.37237 0.96251 0.38203 
194 2.3318 3.4099 0.23869 1933.3 0.9033 2.5605 0.35362 0.43951 0.38267 0.96816 0.96337 
195 6.6827 4.5729 0.13794 1880 0.90309 1.4774 0.43658 0.37213 0.96475 0.063027 0.96716 
196 6.4829 3.9869 -0.176 1897.5 2.4068 1.766 0.37128 0.38098 0.96775 0.39953 0.061097 
197 5.7686 3.0866 -0.07449 1884.9 2.0457 1.2188 0.38369 0.964 0.061914 0.1285 0.3971 
198 6.1081 2.3548 -0.15273 1887.1 0.98501 1.6249 0.96476 0.96823 0.39947 0.83442 0.12711 
199 6.5657 5.3679 -0.14182 2047.7 1.3082 1.601 0.96697 0.061409 0.12965 0.82773 0.83158 
200 6.7453 5.0355 0.79534 2055 1.0649 1.5667 0.061482 0.39772 0.83314 0.46639 0.82855 

MDL-NBS-HS-000021 REV 02 A-16 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
1 0.83233 0.24005 0.80624 14.221 1.9903 812.85 440.3 109.47 108.87 4.8775 
2 0.82718 0.80526 0.13308 4.609 1.6863 438.05 704.33 129.6 92.939 5.0531 
3 0.46566 0.13442 0.73247 9.336 1.0289 707.27 688.4 38.71 77.02 4.2620 
4 0.11361 0.73275 0.34383 3.211 0.54985 688.19 663.39 79.503 109.71 4.5371 
5 0.24003 0.34009 0.049709 6.490 2.4022 663.62 323.7 93.181 124.51 4.2375 
6 0.80576 0.046205 0.7459 6.106 2.2194 321.01 742.97 102.03 100.9 4.3941 
7 0.13452 0.74864 0.93901 5.590 1.7185 741.48 430.16 101.08 112.08 5.1399 
8 0.73186 0.93694 0.55457 2.180 1.8825 429.34 525.79 96.651 94.367 4.2041 
9 0.34145 0.55106 0.79371 7.319 1.7536 526.19 626.36 116.43 106.1 4.6918 
10 0.047266 0.79274 0.37606 3.153 1.7716 626.1 256.08 94.687 105.03 5.1004 
11 0.74875 0.37598 0.67186 3.965 3.3158 255.36 346.45 94.86 104.08 4.8134 
12 0.9384 0.67431 0.65349 4.865 3.4105 344.48 252.75 107.78 89.193 3.8495 
13 0.55426 0.65427 0.62915 1.599 0.85794 250.6 293.32 122.12 107.76 5.3892 
14 0.79285 0.62833 0.24857 2.380 1.8079 289.57 644.32 104.11 93.974 4.9578 
15 0.37977 0.24591 0.71151 1.533 1.1538 644.32 240.83 58.263 97.825 3.8205 
16 0.67304 0.71226 0.36864 1.911 2.7247 241.27 425.57 112.1 102.21 5.5740 
17 0.65016 0.36852 0.47149 5.094 2.7109 426.26 632.99 96.424 85.471 4.6028 
18 0.62547 0.47303 0.58007 1.476 1.9399 631.8 489.65 114.56 90.109 4.8036 
19 0.24894 0.58477 0.17326 3.117 1.099 489.47 166.43 98.307 85.408 4.6142 
20 0.71268 0.17148 0.2719 4.941 1.4758 166.72 727.65 109.97 87.421 5.1106 
21 0.36671 0.27358 0.16723 3.642 2.6485 726.02 580.16 67.302 102.9 4.9749 
22 0.47389 0.16561 0.2131 0.834 1.1613 578.39 161.12 123.13 84.683 4.4990 
23 0.58452 0.21367 0.60303 7.035 2.4699 159.62 829.77 91.467 93.664 5.2601 
24 0.17185 0.60264 0.15762 4.458 1.6923 830.57 376.18 96.067 102.68 4.8586 
25 0.27162 0.15986 0.36181 0.809 0.73272 375.4 481.98 91.381 96.375 4.6846 
26 0.16981 0.36202 0.59096 9.867 2.4972 479.18 381.72 96.797 79.051 5.5658 
27 0.21102 0.59494 0.43437 2.680 3.1595 381.7 638.55 129.53 107.22 5.6739 
28 0.60015 0.43132 0.070798 3.579 2.1024 638.67 590.61 90.95 100.17 4.4166 
29 0.15677 0.070876 0.69583 2.681 2.615 593.85 328.84 112.58 78.996 5.5237 

MDL-NBS-HS-000021 REV 02 A-17 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
30 0.36158 0.69708 0.53266 5.000 1.7618 326.95 678.7 108.37 113.21 5.4983 
31 0.59138 0.53117 0.065333 4.581 2.3314 677.42 509.58 94.841 91.582 4.9849 
32 0.43049 0.068262 0.81193 2.210 2.2912 511.98 422.18 90.197 96.013 4.1083 
33 0.074454 0.81122 0.30876 5.930 2.2459 422.1 820.66 58.974 91.679 5.9685 
34 0.6978 0.3088 0.42281 3.841 1.4862 822.12 909.44 110.04 102.71 4.8878 
35 0.53021 0.42103 0.3129 3.077 2.4162 909.46 300.12 126.65 100.7 5.6821 
36 0.068291 0.31034 0.59624 9.575 1.7497 298.61 796.55 93.625 89.246 5.0253 
37 0.81435 0.59788 0.5451 12.473 1.9504 794.22 779.79 103.89 104.64 5.6522 
38 0.30796 0.54611 0.25403 1.983 2.1609 779.57 599.93 120.88 97.323 4.9442 
39 0.42208 0.25262 0.64219 8.726 1.2938 599.68 224.14 73.613 93.554 5.4314 
40 0.31087 0.64499 0.45689 8.364 1.5451 222.51 987.6 191.27 112.55 5.5843 
41 0.59771 0.45948 0.35958 4.645 1.2728 987.07 529.6 124.49 119.63 5.2355 
42 0.54692 0.35889 0.80226 1.284 1.4037 530.28 914.05 93.929 87.977 4.8650 
43 0.2541 0.80481 0.89657 17.394 2.1923 910.33 620.16 179.01 110.89 5.3636 
44 0.64387 0.89955 0.2211 4.001 1.2504 620.04 891.15 124.42 110 4.6416 
45 0.45648 0.22056 0.77458 12.785 1.7351 891.41 571.89 54.883 101.28 5.0719 
46 0.35594 0.77106 0.75751 4.813 2.1801 571.12 746.07 106.71 83.562 5.6180 
47 0.8044 0.75705 0.55876 11.844 1.8744 747.9 837.75 111.76 135.96 3.7922 
48 0.89716 0.55861 0.13615 4.372 0.91376 835.64 667.68 91.97 98.093 5.4487 
49 0.22083 0.1361 0.98634 7.493 2.3907 670.09 514.51 98.776 120.19 5.5328 
50 0.7728 0.98683 0.4783 9.902 2.0576 514.64 715.01 126.99 102.03 4.7887 
51 0.75745 0.47635 0.90182 5.705 0.88603 712.87 399.44 83.962 118.01 5.5539 
52 0.5575 0.90124 0.57823 3.901 2.6678 399.58 628.62 112.43 99.752 4.5138 
53 0.13948 0.57826 0.87579 6.717 1.6269 627.55 864.64 126.74 107.99 4.6338 
54 0.9886 0.87902 0.52465 2.859 1.849 864.15 150.75 258.23 113.65 4.4139 
55 0.47636 0.52426 0.71777 4.903 1.6384 151.12 756.56 118.39 104.29 5.0128 
56 0.90226 0.71853 0.81891 10.737 2.1894 754.26 803.41 127.89 97.509 3.7624 
57 0.57565 0.81586 0.63343 0.739 2.0898 806.44 474.02 128.39 106.51 3.9613 
58 0.87726 0.63481 0.46333 7.676 1.5057 476.79 818.8 83.831 92.659 4.7692 
59 0.52271 0.46349 0.68074 9.049 2.2752 818.62 336.85 88.254 102.42 5.6955 
60 0.71539 0.68244 0.33489 3.526 1.9216 336.49 394.56 122.77 115.57 5.6712 

MDL-NBS-HS-000021 REV 02 A-18 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
61 0.81858 0.33278 0.58895 9.446 1.7264 394.68 294.57 81.37 78.053 4.3374 
62 0.63424 0.58517 0.84543 2.290 2.6399 296.99 615.74 100.52 108.66 5.6464 
63 0.46136 0.84982 0.056311 2.831 2.956 613.08 148.46 121.59 111.49 5.3243 
64 0.68066 0.057841 0.72978 1.928 1.426 145.92 195.85 75.673 95.797 3.5267 
65 0.33153 0.72969 0.78261 4.799 2.5599 198.3 467.99 108.21 112.44 4.4555 
66 0.58726 0.78325 0.4167 0.690 2.5179 465.66 924.72 96.256 89.718 3.9177 
67 0.84941 0.41653 0.79797 1.040 2.1075 926.22 903.86 105.75 92.376 4.5297 
68 0.058578 0.79803 0.26066 3.457 1.1735 903.5 273.95 102.44 87.717 4.9694 
69 0.728 0.26347 0.32972 13.311 3.6979 272.15 883.85 45.587 101.83 4.7835 
70 0.78038 0.32548 0.21687 12.414 1.9618 885.32 702.03 43.519 77.264 4.9502 
71 0.41596 0.21798 0.57346 1.751 2.9809 700.89 121.54 105.41 81.802 5.1614 
72 0.79808 0.57228 0.054074 11.625 2.1481 119.34 314.87 94.86 95.495 5.8209 
73 0.26002 0.052024 0.10657 6.408 2.8736 311.66 183.97 108.3 121.95 5.6385 
74 0.32626 0.10795 0.40776 0.436 2.039 183.08 339.8 114.71 119.24 4.0269 
75 0.21674 0.40841 0.91631 2.097 2.4268 339.18 589.62 63.997 86.459 5.6138 
76 0.57425 0.91592 0.89188 0.955 2.6786 588.04 473.21 128.28 117.71 5.4099 
77 0.053163 0.89356 0.19002 2.324 2.2583 471.84 575.22 84.112 105.81 5.6053 
78 0.10825 0.19055 0.87486 4.521 1.933 572.68 648.88 112.64 73.738 5.9754 
79 0.40749 0.87385 0.66564 3.502 2.361 646.51 950.64 76.018 88.667 3.3825 
80 0.91533 0.66936 0.024592 4.407 1.6742 952.86 877.79 15.936 80.824 5.1987 
81 0.89182 0.024802 0.238 5.160 2.1683 877.91 212.04 90.958 89.887 3.8823 
82 0.19247 0.23768 0.092733 14.707 2.7659 208.9 860.23 125.16 100.63 4.5064 
83 0.8716 0.093798 0.2697 11.234 0.82441 860.11 736.5 93.682 95.705 5.4698 
84 0.66663 0.26782 0.54484 1.175 2.4578 738.68 855.93 123.3 100.03 3.2578 
85 0.022039 0.54487 0.41286 10.610 2.5864 854.64 993.11 113.89 103.17 5.7672 
86 0.23834 0.41297 0.5255 7.247 1.8464 994.47 110.54 118.18 126.14 4.6235 
87 0.09303 0.52693 0.60617 10.538 2.6304 110.62 659.13 299.8 116.81 3.6374 
88 0.26994 0.6098 0.94768 18.734 1.5209 658.39 174.16 120.3 82.794 4.5614 
89 0.54397 0.94692 0.8623 0.348 1.6666 172.55 331.74 120.44 115.37 3.9564 
90 0.41441 0.86116 0.12201 5.461 1.4188 329.82 767.45 106.38 107.69 4.8941 
91 0.52656 0.12189 0.84487 0.899 2.1415 766.83 108.83 104.64 115.02 5.5922 

MDL-NBS-HS-000021 REV 02 A-19 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
92 0.60929 0.84095 0.70556 2.267 0.76916 108.02 939.97 177.71 139.22 4.3696 
93 0.94947 0.70568 0.83988 7.963 1.062 937.88 389.58 100.55 71.507 5.6284 
94 0.8607 0.83864 0.99131 0.244 1.8277 388.79 129.98 92.897 103.93 3.6732 
95 0.12496 0.99254 0.012151 13.874 3.0474 127.83 358.17 113.61 80.093 4.8986 
96 0.84424 0.014322 0.6206 2.779 2.9291 359.12 191.36 125.2 89.546 5.6454 
97 0.70863 0.62212 0.081579 0.537 1.3502 192.1 534.33 123.97 109.3 4.1823 
98 0.83814 0.081611 0.25537 2.518 2.8488 534.89 840.2 69.572 68.715 4.1468 
99 0.99153 0.25963 0.74219 1.040 2.3268 841.52 281.38 118.18 124.07 3.7073 
100 0.01084 0.74266 0.00638 4.070 0.4986 282.1 868.25 94.204 92.211 5.5092 
101 0.6226 0.008537 0.9333 10.121 1.4611 866.27 135.17 33.92 74.655 3.9941 
102 0.082755 0.93024 0.32214 1.816 1.0042 131.91 540.77 81.289 90.751 4.9205 
103 0.25772 0.32134 0.031583 10.910 1.5392 539 882.9 17.356 81.538 4.5873 
104 0.74379 0.031874 0.28828 0.588 2.0766 880.48 236.85 95.217 98.315 5.7497 
105 0.0066 0.28693 0.10244 4.092 1.833 238.35 232.4 121.57 113.88 5.8007 
106 0.9304 0.10181 0.48385 11.375 2.0524 232.95 136.31 34.896 86.943 5.8716 
107 0.32214 0.48365 0.82219 1.424 2.2089 139.73 790.5 109.12 116.02 5.9238 
108 0.034931 0.82127 0.20133 1.361 3.2142 789.56 205.25 16.508 75.807 4.2303 
109 0.28848 0.20343 0.85064 0.647 2.8115 204.97 554.05 83.719 98.454 4.5744 
110 0.10153 0.85494 0.037852 8.580 1.131 552.51 367.97 106.86 117.35 4.6150 
111 0.48488 0.039425 0.48927 1.134 2.7541 369.82 936.25 54.043 84.514 4.5945 
112 0.82181 0.48703 0.86816 4.212 2.4064 935.32 947.4 101.16 84.306 4.6692 
113 0.20309 0.86964 0.15423 2.581 2.735 949.48 963.04 98.817 76.071 5.4624 
114 0.85318 0.15153 0.14775 13.639 3.9162 960.13 975.53 126.69 110.59 4.7348 
115 0.037029 0.14723 0.043615 14.307 0.28545 973.13 244.95 80.878 82.558 5.6580 
116 0.48919 0.044629 0.76977 15.467 2.2311 247.87 362.6 120.8 98.991 5.6920 
117 0.86816 0.76877 0.11639 16.361 0.96482 361.16 385.18 93.073 91.229 4.9390 
118 0.15324 0.11722 0.50208 1.506 1.5153 386.4 373.33 121.41 123.17 4.5446 
119 0.14901 0.50107 0.29533 2.556 2.4838 370.58 412.47 115.09 124.87 3.4129 
120 0.042737 0.29727 0.92996 2.757 0.24038 414.2 765.76 96.594 127.87 5.6875 
121 0.76893 0.92623 0.94325 2.617 3.1079 763.07 449.47 204.67 130.96 5.5441 
122 0.11682 0.94167 0.9558 2.972 1.6573 450.84 893.8 98.19 85.118 5.1761 

MDL-NBS-HS-000021 REV 02 A-20 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
123 0.50185 0.95667 0.97337 7.856 0.63252 896.39 919.94 90.724 90.898 4.8374 
124 0.29877 0.97469 0.16451 3.297 1.5766 920.24 564.89 81.361 92.057 4.8294 
125 0.9262 0.16335 0.29046 12.053 1.0562 566.15 347.78 105.17 91.285 5.7118 
126 0.94249 0.29347 0.31994 13.073 1.963 349.81 116.51 94.688 93.119 3.8728 
127 0.95651 0.31629 0.30057 4.359 2.6953 115.03 915.08 98.763 109.14 5.9370 
128 0.97227 0.30062 0.34665 2.407 1.3783 917.36 808.56 120.32 94.609 5.6665 
129 0.16375 0.34816 0.73806 0.396 2.7931 807.17 653.26 56.345 118.5 5.3010 
130 0.2908 0.73514 0.38982 12.887 0.64424 650.78 504.69 122.96 121.56 4.3202 
131 0.31825 0.38902 0.88375 9.230 1.9739 502.29 497.53 96.43 99.609 5.2718 
132 0.30346 0.8811 0.91445 5.287 2.8316 497.26 928.08 109.77 90.397 4.2901 
133 0.34536 0.91351 0.51775 3.793 1.2279 932.09 167.74 96.177 71.682 5.8432 
134 0.73979 0.51891 0.27618 3.753 1.2149 170.49 978.15 63.713 120.69 4.1248 
135 0.38918 0.27944 0.017364 13.549 0.71527 981.81 900.52 33.543 111.8 5.4871 
136 0.88142 0.018064 0.90692 0.871 2.5438 899.31 692.85 106.49 103.46 3.9044 
137 0.91369 0.90812 0.78832 16.548 1.1016 691.49 268.16 89.996 96.932 4.4487 
138 0.51854 0.78574 0.61055 12.129 2.0081 266.74 684.08 122.92 96.697 5.5024 
139 0.27967 0.61066 0.44885 6.175 1.6021 682.82 261.21 108.67 122.43 4.5558 
140 0.018437 0.44944 0.44473 1.681 3.1047 259.8 957.8 62.316 79.558 5.3464 
141 0.90992 0.44492 0.92486 6.018 3.1925 959.02 228.62 117.29 132.79 4.9658 
142 0.78977 0.92496 0.077725 1.626 3.2736 228.36 778.38 115.04 118.79 4.9995 
143 0.61162 0.077621 0.97922 14.966 3.4137 776.75 180.78 105.11 105.23 4.3784 
144 0.44672 0.97709 0.88689 1.355 1.2599 177.45 308.05 97.168 86.269 4.7661 
145 0.44483 0.88694 0.65537 8.294 1.5851 307.83 787.18 29.899 104.91 5.9886 
146 0.92381 0.65965 0.18644 0.932 1.6389 788.47 355.4 94.639 85.829 4.8111 
147 0.077437 0.18566 0.64725 2.079 1.6102 354.67 709.36 126.18 127.33 4.4372 
148 0.97688 0.64518 0.17796 8.446 1.7018 710.03 584.97 112.95 83.89 5.6345 
149 0.88764 0.17513 0.95462 2.479 2.4779 585.05 611.31 110.25 109.74 5.3747 
150 0.65902 0.95013 0.14251 6.661 1.7862 610.1 285.37 52.359 80.593 3.1110 
151 0.18671 0.14065 0.75367 4.480 2.8909 285.78 461.67 21.46 88.309 5.3096 
152 0.64903 0.75082 0.085452 4.723 3.0224 462.78 999.51 114.38 110.43 5.5276 
153 0.17695 0.087076 0.23365 1.871 2.0351 999.67 483.77 93.823 90.563 4.3465 

MDL-NBS-HS-000021 REV 02 A-21 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
154 0.9512 0.23467 0.76487 3.420 1.5586 484.97 306.89 113.63 106.18 4.7466 
155 0.14091 0.76127 0.2801 19.238 0.38107 306.1 872.4 127.4 100.45 5.4393 
156 0.75336 0.28179 0.67652 3.611 3.0035 871.12 725.39 116.87 101.58 5.3692 
157 0.08953 0.67582 0.53817 2.021 2.5998 721.14 103.99 72.216 87.341 5.9484 
158 0.23059 0.53548 0.56945 11.103 2.2116 101.08 695.4 40.23 95.224 4.8526 
159 0.7646 0.56552 0.20822 6.888 1.8999 698.34 798.89 108.46 148.17 4.9279 
160 0.28497 0.20529 0.40255 0.176 1.8931 798.55 277.25 197.34 96.195 4.9132 
161 0.67504 0.40101 0.99992 6.311 3.0661 275.58 455.23 102.95 88.301 4.9346 
162 0.53552 0.99938 0.42575 8.932 0.9365 455.05 748.2 111.1 116.45 4.9929 
163 0.56653 0.42685 0.22858 1.774 3.5397 751.7 720.14 63.445 106.92 5.2455 
164 0.20863 0.22935 0.85861 3.334 2.9012 718.67 983.76 123.47 63.959 4.3054 
165 0.40195 0.85843 0.69288 7.557 2.3059 984.15 509.34 118.65 105.54 4.9098 
166 0.99884 0.69375 0.001538 6.803 1.3307 505.59 556.96 116.61 111.26 4.6501 
167 0.4295 0.00151 0.66146 16.959 2.2877 556.95 548.66 68.395 86.894 3.9386 
168 0.22599 0.66498 0.77751 3.825 1.3026 547.43 562.63 110.89 94.915 3.5547 
169 0.8586 0.77867 0.19755 4.276 3.2398 561.48 608.45 100.01 108.24 5.4048 
170 0.69437 0.1954 0.39244 4.192 1.1982 608.46 671.99 99.386 106.64 5.1931 
171 0.001231 0.39299 0.72459 4.305 2.514 671.82 265.99 231.89 134.49 4.6748 
172 0.6606 0.72016 0.68846 4.690 0.97624 262.5 541.5 120.61 97.076 4.8286 
173 0.77628 0.68789 0.98023 5.795 1.4467 545.05 402.29 113.14 99.164 4.7081 
174 0.19637 0.98146 0.45478 1.678 2.5403 403.25 185.89 54.005 98.867 4.7295 
175 0.39311 0.45483 0.50829 4.127 1.5639 189.74 125.45 122.69 99.409 5.8882 
176 0.72453 0.50536 0.49776 2.894 2.3457 124.24 734.44 100.24 101.46 5.9004 
177 0.68917 0.49845 0.51009 0.990 2.0682 731.22 654.92 95.999 104.55 3.8036 
178 0.98396 0.51107 0.56335 0.488 2.1292 653.57 416.24 116.28 86.075 4.7517 
179 0.45418 0.56394 0.63905 7.186 1.394 416.08 492.31 103.99 98.647 4.0583 
180 0.50686 0.6384 0.18176 5.367 1.8196 493.18 435.53 118.77 92.833 5.6042 
181 0.49959 0.18351 0.49236 3.002 4.0513 437.08 445.56 34.207 81.084 5.5955 
182 0.51036 0.49117 0.33981 3.713 1.862 446.28 964.34 104.91 74.407 4.8724 
183 0.56418 0.33823 0.098419 3.186 1.4389 965.64 970.23 124.85 107.46 3.9848 
184 0.63522 0.098359 0.029148 3.280 2.8066 970.12 157.45 94.654 103.63 4.4748 

MDL-NBS-HS-000021 REV 02 A-22 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
185 0.18001 0.028657 0.7049 15.790 2.3825 155.45 458.25 63.226 93.339 5.5682 
186 0.49328 0.70242 0.61821 15.872 -0.00165 458.27 216.04 106.68 96.562 4.0889 
187 0.33932 0.6174 0.35471 0.779 2.3105 213.33 848.03 116.92 94.132 5.4564 
188 0.095855 0.35206 0.43994 3.371 2.5777 848.42 845.9 129.27 94.576 4.6564 
189 0.025006 0.43563 0.37403 1.236 1.3627 843.72 521.17 120.76 129.18 3.7290 
190 0.70291 0.37478 0.38384 10.428 1.7917 519.67 200.06 120.91 130.24 5.4786 
191 0.61896 0.38398 0.96484 10.269 2.4475 199.43 316.94 103.58 78.41 5.7810 
192 0.35329 0.96202 0.96738 3.958 2.3695 320.09 827.3 114.03 95.042 4.9796 
193 0.43628 0.9654 0.062055 1.092 3.5458 826.09 219 85.037 83.247 5.5478 
194 0.37169 0.061335 0.39868 2.121 1.9109 218.91 760.81 93.183 114.66 4.7098 
195 0.38195 0.39667 0.12538 9.702 2.0123 761.17 408.2 93.174 114.11 5.3385 
196 0.96264 0.12797 0.83326 1.247 1.9917 406.69 142.25 106.22 97.678 5.2878 
197 0.96574 0.8321 0.82688 7.725 2.0208 144.67 773.83 28.908 82.048 5.2122 
198 0.063634 0.82798 0.46962 2.930 2.1217 772.31 943.72 93.594 88.773 4.4856 
199 0.39766 0.46669 0.11218 0.664 2.2674 943.38 595.47 114.98 113.09 5.4216 
200 0.12612 0.1129 0.24114 8.080 1.3256 596.34 813.08 109.78 83.544 4.6979 

MDL-NBS-HS-000021 REV 02 A-23 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
1 6488.6 5700.9 5.6503 4168 178.08 3.4892 -4.4407 
2 7769.2 6721 5.8331 2766.9 799.65 2.9211 -4.4107 
3 5702.4 5037 5.9814 5772.4 945 3.0682 -8.7573 
4 6712.4 6161.5 5.0086 6542.1 653.54 3.3114 -7.4077 
5 5039.6 6078.9 5.4456 5006.4 833.8 2.6497 -8.4926 
6 6166.2 5984.6 4.9920 5951.3 521.65 2.8072 -5.4465 
7 6096 4478.6 5.2380 4312.3 744.24 2.6360 -5.476 
8 5984.4 6343.7 6.0000 5475.1 729.51 2.7197 -7.1382 
9 4483.4 4998.1 4.9762 5389.5 710.35 3.3486 -8.5426 
10 6347.6 5398.5 5.6375 5296.6 405.6 2.6160 -8.0268 
11 5003.5 5816.1 5.9903 3786 773.96 2.9143 -5.6308 
12 5395.8 4080.1 5.7619 5640.9 512.41 3.3299 -8.4685 
13 5804 4586.6 4.7149 4258.3 596.07 2.9856 -6.0663 
14 4084.8 4056 6.3464 4687.9 676.07 2.3959 -7.6293 
15 4591.2 4298.1 5.9175 5127.8 330.43 3.4717 -8.8063 
16 4071.1 5882.9 4.6899 3493.9 431.82 3.2197 -6.018 
17 4312.5 3986.6 6.5623 3882.3 328.73 2.3635 -4.6686 
18 5887.7 4981.3 5.5315 3471 371.58 3.5901 -6.7922 
19 3997.5 5842.8 5.7451 3656.9 692.74 2.8522 -5.715 
20 4964.8 5254.5 5.5465 5206.8 318.51 2.9747 -7.4927 
21 5841.3 3352.8 5.9978 3424.7 509.22 2.8589 -6.3092 
22 5249.8 6267.7 5.9360 4246.1 684.76 3.3399 -6.3854 
23 3350.7 5629.4 5.3838 5164.9 563.37 3.2550 -6.4937 
24 6266.9 3265 6.1931 4532.5 211.99 2.7812 -8.015 
25 5614 6838 5.8089 3093.9 761.1 3.4056 -6.1406 
26 3268.8 4754.3 5.6274 5569 639.2 3.0266 -7.5392 
27 6830 5203.4 6.5441 4917.6 203.9 2.9089 -7.1142 
28 4752.1 4769.3 6.6739 3067.4 847.86 3.5824 -6.6703 
29 5208.6 5863.3 5.2765 6042 461.44 3.6609 -8.3015 
30 4760.6 5676.8 6.5011 4035.3 556.39 2.7344 -7.9093 
31 5868 4504.5 6.4728 4490.8 466.35 3.5520 -8.3327 

MDL-NBS-HS-000021 REV 02 A-24 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
32 5686.4 6049.8 5.9494 4039.5 688.99 3.5412 -8.1408 
33 4496.5 5340.1 4.9233 5173.5 651.93 3.2668 -6.5819 
34 6054.1 4946 6.9605 4978.7 411.96 2.5760 -8.3777 
35 5335.9 6784.5 5.8382 3800 720.52 3.9447 -7.556 
36 4954.1 7395.9 6.6776 5350.2 582.95 3.0918 -6.6373 
37 6768.2 4367.7 5.9759 4628 502.03 3.6629 -7.2777 
38 7399.6 6606.1 6.6522 4233 839.43 3.3045 -8.7023 
39 4349 6544.1 5.9085 5999.7 916.61 3.6457 -6.2199 
40 6613.4 5717.4 6.3962 6377.4 383.48 3.2028 -6.8793 
41 6556 3873.3 6.5717 3691.6 818.98 3.4953 -8.7381 
42 5719.5 8732.1 6.1461 5871.8 808.27 3.5966 -5.5862 
43 3858.1 5413.4 5.8195 5824.7 660.06 3.3930 -7.7721 
44 8721.8 7419.7 6.3075 5026.1 294.01 3.0345 -7.3063 
45 5413.9 5800.7 5.5809 3349.8 991.22 3.4557 -7.745 
46 7437.8 7226.2 5.9859 6739.4 598.1 2.8849 -6.6174 
47 5796.5 5589.3 6.6128 4704.9 919.06 3.3241 -6.8126 
48 7243.6 6357.7 4.6388 6398.1 672.8 3.6195 -7.9985 
49 5589.2 6861.8 6.4183 5104.8 899.64 2.3345 -6.4285 
50 6364.8 6003.9 6.5159 6302.1 634.71 3.5066 -7.1708 
51 6866 5353.2 5.7348 4883.7 777.9 3.5638 -7.5752 
52 6008.3 6205.2 6.5366 5656.5 852.87 2.9709 -5.6643 
53 5358 4858.7 5.4150 6057.5 712.71 3.5795 -5.0276 
54 6218.9 5834.7 5.5775 5310.3 586.49 2.7970 -8.1064 
55 4843 7046.9 5.2695 4642.6 750.31 2.8776 -5.8657 
56 5831.9 3132.8 5.9717 5519.3 484.63 2.7310 -5.9515 
57 7035.9 6410 4.6104 4131 681.99 3.2964 -6.7658 
58 3173.9 6675 4.8343 5133.9 873.87 2.3122 -8.4411 
59 6397.3 5193.9 5.7110 6175.2 194.82 2.4968 -4.1002 
60 6670.5 6733.1 6.6972 3036.4 784.86 2.9609 -7.0941 
61 5191.2 4558.9 6.6712 5688.1 825.8 3.6766 -4.9691 
62 6755 4836.8 5.1367 5911.1 550.47 3.6582 -6.6998 

MDL-NBS-HS-000021 REV 02 A-25 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
63 4559.2 4322.6 6.6454 4468.5 836.11 2.6876 -5.161 
64 4826 5767.5 6.2577 5976.8 421.28 3.6429 -6.9188 
65 4342.6 3093.2 4.3501 3837.3 477.44 3.4355 -6.1259 
66 5774 3650.4 5.3404 4101.5 378.03 2.1519 -5.5367 
67 3112.8 5143.1 4.7901 3677.3 668.9 2.7602 -6.4733 
68 3652.9 7554.3 5.4249 5088.1 186.91 2.4561 -7.1524 
69 5141.2 7336 5.9355 3018.3 260.88 2.8035 -6.2729 
70 7565.7 4199.1 5.7202 3230.6 545.33 3.2382 -7.6777 
71 7361.4 7210.9 5.9101 4422.1 931.75 2.9685 -6.6509 
72 4211.5 6137.8 6.0374 6460.7 911.36 3.2124 -5.3511 
73 7212.3 2536.1 6.8306 6348.8 351.33 3.3517 -8.7724 
74 6144.2 4428.3 6.6335 3560.8 896.71 3.6989 -6.0952 
75 2583 3502.6 4.8833 6283.9 739.45 3.6343 -5.7992 
76 4435.6 4576.3 6.6053 5466.5 142.3 2.5393 -7.3313 
77 3519.2 5666.3 6.3674 1332.8 399.64 3.6162 -5.6828 
78 4580.1 5162 6.5966 3743.7 241.47 3.4880 -7.9519 
79 5656.1 5596.2 6.9741 3163.1 426.23 3.6116 -7.6875 
80 5172.4 5914 4.2386 3858.5 647.46 3.9614 -8.1309 
81 5609.8 7944.5 6.1038 4957.3 550.07 2.0951 -6.7135 
82 5912.4 7132.6 4.7531 4448.8 634.96 3.3796 -8.7844 
83 7914.7 3773.6 5.4065 4893.1 697.02 2.4256 -8.5657 
84 7132.3 7012.5 6.4456 5219 955.7 2.7860 -7.3649 
85 3753.5 6324.4 4.1847 6566.3 885.57 3.5229 -4.8334 
86 6986.5 6980.9 6.7505 6234.4 276.95 2.0594 -5.0489 
87 6306.8 8979.8 5.5658 3296 872.71 3.6879 -8.2303 
88 6979.8 2198.1 4.4545 6153.4 769.22 2.8735 -5.1937 
89 9020.7 5962.9 5.4814 5609.9 868.01 2.2234 -6.3262 
90 2223.7 3419.5 4.8231 6129.4 995.38 2.8308 -8.9159 
91 5959.5 4534.1 5.8457 6760.5 122.28 2.4814 -8.049 
92 3435.1 6465.6 6.5752 698.84 707.86 3.1066 -8.6293 
93 4518.4 1938.8 5.1959 5287.2 226.24 3.6012 -7.9308 

MDL-NBS-HS-000021 REV 02 A-26 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
94 6479.5 7749.4 6.6201 3126.2 418.09 2.7010 -6.8351 
95 1944.9 4815.2 4.4834 3829.2 794.98 3.6242 -7.3558 
96 7738.3 2757.9 5.8567 5762.7 116.33 2.2479 -6.8801 
97 4813.7 4650.8 6.6405 669.12 943.93 3.1094 -6.5674 
98 2752.3 3626 4.9596 6518.4 474.28 3.6371 -4.579 
99 4668.5 5430.8 4.9532 4078.5 156.07 2.6025 -5.2514 
100 3590.2 6886.2 4.5261 2047.5 445.26 2.5987 -8.5003 
101 5437.2 4246.3 6.4871 3955.1 253.85 2.2623 -5.3798 
102 6878.3 7050 4.8636 3207.5 602.23 3.5479 -6.1694 
103 4242.2 2836.9 5.8808 4724.6 855.89 2.5293 -5.4229 
104 7071.8 5458.1 5.5038 6071.5 365.43 3.1555 -3.9017 
105 2849 7165.5 6.7372 3615.2 879.29 2.8449 -8.9485 
106 5452 3968.1 6.8082 6203.8 161.11 3.6822 -6.5045 
107 7180.6 3947.5 6.8733 2313.5 607.45 3.6947 -8.6754 
108 3975.9 2963 6.9243 4750.4 889.84 3.7506 -7.9714 
109 3949.9 6585 4.9802 6255.2 310.82 3.8465 -6.0296 
110 2961.6 3722.4 5.4942 3405.5 306.56 2.6266 -8.9706 
111 6583.9 5508.2 5.5563 3396.5 167.18 2.8365 -4.7113 
112 3744.8 4713.2 5.5211 2566.2 815.33 2.8642 -7.7037 
113 5502.7 7651.4 5.6117 5859.1 271.76 2.8499 -8.8791 
114 4707.5 7827.8 6.4298 3276 619.25 2.9020 -7.8504 
115 7668.2 8061.2 5.6812 4801.1 451.04 3.5209 -8.5921 
116 7875.1 8371.1 6.6551 3985.2 937.03 2.9405 -7.0702 
117 8054.6 4033.3 6.6920 6498.8 952.66 3.6481 -5.5235 
118 8382.8 4674.7 5.9025 6550.2 965.4 3.6725 -8.1812 
119 4032.2 4794.8 5.4548 6613.1 975.16 3.1876 -5.3301 
120 4682.7 4727.1 4.3159 6665.6 320.43 2.8162 -8.8483 
121 4789.7 4923.1 6.6857 3448.6 446.62 2.1361 -7.0482 
122 4733.6 6446.1 6.5263 3960.9 470.86 3.6683 -5.226 
123 4918.3 5066.3 6.0719 4064.5 456.71 3.5702 -8.3913 
124 6457.4 7265.2 5.7917 4014.1 493.65 3.3600 -8.4006 

MDL-NBS-HS-000021 REV 02 A-27 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
125 5073.8 7501.7 5.7853 4190.3 792.72 2.9976 -8.8265 
126 7269 5566.2 6.7024 5728.5 527.66 2.9937 -5.8902 
127 7503.6 4620.7 4.7329 4350.1 902.78 3.6804 -8.5362 
128 5573.1 2382.2 6.9325 6325 928.67 2.4095 -6.9813 
129 4622.1 7497.1 6.6599 6426.1 629.98 3.8979 -7.8073 
130 2420.4 6694.9 6.2405 4867.7 435.71 3.6530 -4.7451 
131 7457.5 5934.5 5.1173 3908.3 127.29 3.4250 -4.6212 
132 6679.9 5310 6.1987 995.09 924.13 2.6807 -4.4973 
133 5936.4 5289 5.0374 6414.2 830.59 3.4087 -4.3664 
134 5304.7 7600.3 6.8506 5940.5 698.01 2.6538 -8.3547 
135 5285.5 3394.1 4.9341 5233.1 575.88 3.7269 -7.8364 
136 7609.5 8528.2 6.4669 4588 572.62 2.5810 -7.7319 
137 3398.2 7310.8 4.7676 4566.4 934.01 3.5342 -7.7884 
138 8495.8 6104.3 5.3160 6480.9 220.56 2.4374 -7.6139 
139 7329.9 4160.2 6.4786 3100.4 981.25 2.7538 -6.0479 
140 6102.7 6062.9 5.4698 6693 907.73 3.5430 -7.4548 
141 4166.5 4117.4 6.2900 6337.7 733.62 2.8222 -5.1313 
142 6062 7991.4 5.9253 5422.8 349.23 3.4512 -4.9116 
143 4131.1 3906.2 5.9633 3546.9 726.94 3.2263 -6.9204 
144 8021.9 6524.3 5.2175 5384.1 336.27 3.2910 -7.891 
145 3903.4 3468.8 5.7076 3509.5 960.78 2.7132 -8.9265 
146 6511.8 4418.7 6.9969 6586.2 300.53 2.9582 -4.9539 
147 3457.3 6579.8 5.7505 3359.8 803.03 3.9972 -5.7348 
148 4404.6 4630.4 5.2945 5803.8 232.94 2.9797 -6.5489 
149 6571.7 6183.3 6.6243 3147.6 394.75 2.7420 -7.2133 
150 4650.1 5637.9 6.3304 3734.3 809.21 3.6309 -7.225 
151 6185.5 5757.9 4.0403 5840.2 439.43 3.4709 -4.7824 
152 5645.3 4276.8 6.2553 3929.5 747.16 2.0382 -8.6861 
153 5748.4 5137.6 6.5065 5492.1 644.24 3.4298 -4.3303 
154 4277.4 9300.6 5.1614 4944.8 668.14 3.5591 -5.0869 
155 5131 5222.6 5.6857 5055.9 369.36 2.6922 -6.3617 

MDL-NBS-HS-000021 REV 02 A-28 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
156 9534.9 4376.2 6.3997 3628.1 540.59 2.9465 -8.2544 
157 5223.8 7111.8 6.3160 4397.9 998.61 3.5045 -6.4036 
158 4371.9 6245.4 6.9528 6778.5 559.62 3.4647 -8.2975 
159 7107.4 1511.6 5.8035 4506.4 387.34 3.9291 -4.5372 
160 6262.1 6123.3 5.8876 3710.1 884.11 3.0123 -8.4216 
161 1345 6652.3 5.8745 6222 759.54 3.1609 -5.9679 
162 6117.2 4216 5.8954 5553.8 106.16 3.1339 -8.6561 
163 6648.8 5090.8 5.9552 133.63 737.64 3.1759 -8.0717 
164 4235.5 6390.9 6.1584 5437.7 821.88 3.2811 -5.909 
165 5089.3 6227.3 5.0969 5895.3 357.82 3.3966 -7.878 
166 6385.7 8608 5.8603 3585.5 532.58 2.6703 -6.2949 
167 6223.2 5321.4 5.5933 4356.9 781.14 3.1305 -6.8452 
168 8546.8 5534.4 4.8125 5669.7 755.11 2.8881 -6.7339 
169 5319.2 5483.1 4.4143 5538.5 983.03 2.4729 -8.1665 
170 5521.6 5542.5 6.3617 6717.7 580.56 2.1921 -7.3829 
171 5495.8 5731.1 6.0755 4608.6 622.03 3.4794 -3.6765 
172 5549.6 6033.4 5.6232 4816.2 613.79 3.3727 -7.2856 
173 5727.9 4140 5.7782 4782.9 623.75 2.9066 -8.0952 
174 6023.7 5477.9 5.6590 4843.3 664.5 2.9908 -5.2724 
175 4148.4 4872.6 5.6693 5042 719.54 2.9265 -6.2288 
176 5479.6 3549.9 6.8814 5344 343.37 2.9380 -8.9859 
177 4879.1 2624.6 6.9058 3534 608.71 3.8063 -6.3475 
178 3562.2 6292.3 4.6491 4764.2 488.67 3.8289 -5.8284 
179 2691.1 5944.7 5.6981 4144.2 248.32 2.3548 -8.2179 
180 6293.7 4927.5 4.8968 3190.7 150.62 2.9539 -7.4396 
181 5941.6 5265.2 6.5944 1697.7 766.1 2.5494 -6.1073 
182 4940.1 5004.8 6.5843 5606.2 701.74 3.6094 -6.2584 
183 5261.6 5043.6 5.8215 5251.5 497.44 3.6051 -4.1654 
184 5020.3 8191.8 4.8495 4209.5 568.89 3.0603 -7.1812 
185 5060.4 8242.6 5.3579 4551.7 517.51 2.5082 -6.9617 
186 8136.4 3206.1 6.5563 4293.2 522.73 2.7668 -7.0139 

MDL-NBS-HS-000021 REV 02 A-29 October 2004 
Saturated Zone Flow and Transport Model Abstraction 
Table A-1. Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
187 8289.8 5112.5 4.9119 4326.7 967.88 3.5857 -6.9487 
188 3212.5 3783.9 6.4232 6625 972.79 2.5597 -6.7548 
189 5101.7 6943.9 5.6010 6654.5 199 3.5129 -6.4514 
190 3797.2 6920.3 4.5707 3041.1 535.96 2.8922 -8.267 
191 6929.3 5377.6 6.4533 4377.2 283.4 2.2913 -7.0285 
192 6916.6 3672.1 6.7846 3319.1 863.42 3.5281 -7.651 
193 5384 4451.3 5.9450 6111.5 861.69 3.6906 -8.615 
194 3694.1 6790.8 6.5366 6096.6 590.15 3.2638 -8.8951 
195 4459 3827.5 5.6646 4668.2 262.72 3.5723 -6.1974 
196 6789.6 6419 6.2765 3248.5 403.04 2.9325 -6.5318 
197 3839.3 4891.3 6.2175 3762.3 844.46 3.4436 -7.5985 
198 6419.4 3017.7 6.1335 6014.8 285.99 3.4185 -7.2599 
199 4889 6501.1 5.3766 3329.5 788.24 3.3858 -7.5095 
200 3037 7780.9 6.3784 5721.1 489.71 2.7745 -7.4663 
Source: DTN: SN0310T0502103.009 [DIRS 168763]. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 A-30 October 2004 
INTENTIONALLY LEFT BLANK

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 October 2004 
APPENDIX B 
RE-SAMPLED STOCHASTIC PARAMETER VALUES 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 October 2004 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-1 October 2004 
This appendix documents the results of the SZ transport abstraction model using a re-sampling of 
the uncertain input parameters. The re-sampling uses the same uncertainty distributions 
described in Section 6.5 of this model report, but utilizes a different sampling algorithm 
implemented in an updated version of the GoldSim software code. 
The version of the GoldSim software code ([DIRS 161572]) used to sample the uncertain 
parameter vectors for the SZ transport abstraction model for the simulations presented in Section 
6.6 contained a dfference in the sampling routine relative to Latin Hypercube Sampling. This 
difference was reported in CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results of 
ANL-EBS-PA-000009), and the problem was corrected in subsequent versions of the GoldSim 
software. Appendix B documents the impact analysis of this sampling difference on the SZ 
transport simulation results, as indicated by the plan in CR 2222. The inputs and outputs from 
the SZ transport abstraction model for the analysis documented in this appendix are contained in 
DTN: SN0407T0502103.013. 
The impact analysis for SZ radionuclide transport results consists of the following steps. The 
uncertain parameter inputs to the SZ transport abstraction model are re-sampled using GoldSim 
V8.01 SP4 (STN: 10344-8.01SP4-00, BSC 2004 [DIRS 169695]), in which the sampling 
difference has been corrected. The re-sampled values of the stochastic parameters are given in 
Table B-1. The full suite of radionuclide transport simulations is conducted using the re-sampled 
parameter vectors. Among the 200 realizations for the 10 groups of radionuclides, the median 
transport times are extracted and ranked to determine the fifth percentile, median, and 95 
percentile values out of the 200 realizations. The values of median transport time for these three 
levels of cumulative probability are then compared to the comparable values from the base-case 
results (as presented in Section 6.6). The comparison of median simulated transport times at 
these three levels of cumulative probability is presented in Table B-2. 
The impact analysis plan in CR 2222 (Evaluate Revised LH Sampling Algorithm on the Results 
of ANL-EBS-PA-000009) gives a criterion of 10 percent difference between the base case SZ 
transport simulation results and the re-sampled parameter case for the impacts of the sampling 
difference in GoldSim to be considered significant. The results shown in Table B-2 indicate that 
this criterion for significant impact is exceeded for several of the radionuclide groups and for 
each of the levels of cumulative probability. In contrast, a graphical comparison of the CDFs for 
the median simulated transport times of nonsorbing species for the base case and the re-sampled 
parameters suggests little difference in the overall uncertainty distributions for the modeling 
results (see Figure B-1). 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-2 October 2004 
Table B-1. Resampled Stochastic Parameter Values 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
1 0.15451 0.61331 0.17939 0.24512 0.82056 -3.8248 -11.253 1.7437 6.1641 102.77 160.47 
2 0.47702 0.13684 0.11408 0.11487 1.2012 -2.1908 -10.542 1.1902 4.6904 127.89 398.51 
3 0.56717 0.97133 0.18689 0.20301 1.1162 -1.0748 -10.369 1.2517 4.7706 230.91 100.67 
4 0.10734 0.95304 0.15792 0.21281 2.1091 -4.0288 -10.449 1.4754 8.214 89.503 239.62 
5 0.4026 0.3768 0.21127 0.083927 0.99514 -3.2734 -9.9334 1.1209 4.4149 329.24 382.08 
6 0.84137 0.72993 0.14731 0.21163 1.1126 -3.0427 -10.626 0.75688 5.2304 261.08 41.482 
7 0.31095 0.11323 0.10118 0.16575 1.1435 -3.1508 -9.5171 1.8229 7.0925 368.16 85.61 
8 0.61721 0.30199 0.26624 0.10631 1.1633 -3.9555 -10.391 1.514 8.4012 86.233 246.38 
9 0.64351 0.54047 0.22131 0.21951 1.33 -3.8841 -10.355 1.2195 5.0232 295.59 348.93 
10 0.017634 0.69878 0.24485 0.09997 1.3982 -2.0052 -10.148 1.2513 7.772 366.26 232.98 
11 0.36141 0.69208 0.16297 0.16612 1.7877 -3.4103 -9.8462 1.2362 6.2984 79.21 300.4 
12 0.66863 0.51855 0.16177 0.17671 1.6181 -2.7493 -9.6179 1.8261 7.555 50.712 237.14 
13 0.93638 0.86084 0.17432 0.18663 1.4548 -2.8833 -9.9251 1.7219 8.2876 39.942 221.56 
14 0.54225 0.74071 0.12117 0.20404 1.0209 -2.114 -10.469 1.3192 5.3529 97.935 25.237 
15 0.079818 0.14179 0.21335 0.19217 0.92842 -1.2718 -10.2 1.3252 6.4525 121.44 187.19 
16 0.22733 0.53666 0.23757 0.22169 1.0914 -3.7174 -10.51 1.815 8.3339 153.48 35.574 
17 0.9105 0.78472 0.1764 0.15444 1.4341 -2.8256 -10.457 1.7151 8.2226 87.498 154.38 
18 0.7729 0.084835 0.14338 0.087999 1.1292 -3.9712 -10.267 1.5264 6.1475 339.64 53.169 
19 0.22058 0.092993 0.16874 0.12009 1.8222 -1.1551 -9.3046 5.3108 7.0649 293.46 293.51 
20 0.63572 0.22141 0.19893 0.18049 1.2755 -3.6338 -10.606 1.7728 8.6851 355.03 61.475 
21 0.46859 0.15315 0.23131 0.07532 1.7139 -2.7178 -10.28 1.405 6.7432 248.05 306.06 
22 0.55837 0.73861 0.14775 0.17517 1.8189 -2.5646 -10.364 1.6164 7.5053 188.54 285.67 
23 0.93381 0.16285 0.20725 0.1593 1.4084 -1.4373 -11.221 1.1998 4.8646 393.72 71.854 
24 0.27958 0.19563 0.18585 0.16883 1.5481 -2.2463 -10.472 1.0035 1.8242 71.215 171.14 
25 0.67783 0.82878 0.19173 0.26284 1.2494 -4.7125 -10.179 1.8117 6.8152 213.85 129.45 
26 0.14234 0.90098 0.15347 0.17201 2.1518 -3.2488 -10.428 5.9266 7.6134 331.85 113.23 
27 0.63108 0.32094 0.11105 0.1861 1.8577 -4.1457 -10.082 1.5185 7.7077 370.96 182.69 
28 0.97766 0.98722 0.23521 0.053929 1.2998 -3.9616 -10.998 1.0002 6.8603 133.64 281.52 
29 0.094175 0.76688 0.12078 0.1676 1.6638 -1.4805 -9.8115 1.6107 9.075 66.879 77.741 
30 0.57883 0.21118 0.17048 0.10311 1.5749 -1.3229 -10.564 1.0831 2.1409 135.46 95.29 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-3 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
31 0.94664 0.2609 0.10912 0.17843 2.4064 -3.3455 -10.769 1.653 7.7886 334.92 156.8 
32 0.59584 0.3372 0.11284 0.19882 1.4641 -3.8551 -10.131 1.5419 6.679 132.07 207.88 
33 0.32113 0.037874 0.2104 0.16284 0.91225 -1.2881 -10.259 1.7135 7.2404 286.22 108.77 
34 0.29157 0.36888 0.18025 0.18707 1.0402 -4.319 -9.9468 0.99292 5.1509 110.2 394.13 
35 0.74654 0.033906 0.15763 0.13045 1.8976 -2.3712 -10.312 1.1913 4.8234 163.19 90.119 
36 0.27276 0.49577 0.13898 0.19081 1.1846 -3.1034 -10.459 1.4026 7.3466 386.78 224.64 
37 0.37341 0.7327 0.064858 0.1695 1.2109 -1.7128 -10.317 1.4201 5.5295 301.55 313.64 
38 0.81269 0.71257 0.17073 0.15785 2.2255 -3.9375 -10.273 1.3814 5.664 285.61 164.78 
39 0.20651 0.81858 0.17469 0.1795 0.72671 -2.9076 -10.422 1.0858 4.3503 288.61 340.14 
40 0.41729 0.39756 0.27779 0.11298 1.3697 -3.5408 -10.244 1.3096 5.9389 399.46 269.69 
41 0.5347 0.10605 0.19533 0.17748 1.3558 -1.2155 -10.058 1.4409 7.5078 267.17 243.12 
42 0.68784 0.35898 0.17567 0.15113 1.3862 -3.119 -10.399 1.5773 8.3875 61.025 304.79 
43 0.20429 0.98413 0.18889 0.19525 1.0585 -3.9954 -9.6862 1.6986 4.2141 361.36 179.52 
44 0.17996 0.079534 0.21288 0.19748 0.83332 -2.9663 -10.08 1.2322 6.6549 160.54 369.77 
45 0.23268 0.70271 0.13104 0.095923 0.61091 -3.7591 -9.5589 1.2574 5.0532 111.45 135.23 
46 0.94002 0.68555 0.17212 0.14843 2.499 -4.2914 -9.9183 5.4986 12.997 201.68 205.42 
47 0.9219 0.62997 0.048637 0.21442 1.2257 -3.4446 -10.122 1.5445 7.2167 117.91 311.11 
48 0.11753 0.38704 0.13991 0.20593 1.4879 -2.9231 -10.638 1.6764 7.8139 338.16 50.193 
49 0.827 0.80175 0.25328 0.17901 1.4701 -3.0873 -9.9755 1.1679 5.2619 300.29 137.8 
50 0.26421 0.52885 0.25032 0.19922 1.6234 -2.0279 -10.068 5.9955 12.169 311.01 319.75 
51 0.064713 0.27162 0.15502 0.14136 1.1368 -1.8908 -10.284 1.726 7.4901 49.767 245.94 
52 0.30783 0.76468 0.14528 0.22367 1.0829 -2.6102 -10.349 1.3565 6.4651 204.45 378.12 
53 0.38381 0.55173 0.15182 0.14712 0.23855 -2.858 -10.671 1.7973 5.1993 36.678 97.266 
54 0.72186 0.96916 0.18828 0.17131 1.6293 -1.9453 -9.8153 1.8224 9.4862 44.982 145.4 
55 0.40607 0.83325 0.25785 0.096324 1.2842 -1.5205 -10.66 1.2942 6.2467 341.24 166.75 
56 0.90988 0.84697 0.21523 0.2761 1.5133 -3.288 -10.051 1.1281 4.5134 90.968 395.59 
57 0.19368 0.66653 0.28314 0.20833 1.025 -3.3438 -9.9961 1.6278 7.5936 320.89 283.45 
58 0.75213 0.15725 0.20111 0.23127 1.4182 -4.4429 -10.254 1.3372 7.9413 202.97 321.09 
59 0.51425 0.75492 0.1873 0.072509 1.8376 -3.1668 -10.11 1.5346 7.5754 379.86 105.09 
60 0.33748 0.30986 0.1379 0.20891 2.3767 -2.6185 -10.321 3.5 7.8272 145.14 262.78 
61 0.33121 0.47933 0.19631 0.18439 0.76825 -3.4808 -9.979 4.244 8.518 105.62 199.2 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-4 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
62 0.17246 0.77804 0.14847 0.19701 0.45371 -3.5141 -9.9163 1.6616 6.9774 23.745 273.78 
63 0.11079 0.34953 0.17999 0.18161 1.459 -3.6508 -10.614 1.1611 4.379 194.27 37.474 
64 0.77508 0.018099 0.22246 0.22977 1.1456 -3.6972 -9.5041 1.9761 8.666 298.55 126.6 
65 0.9675 0.14511 0.15072 0.20751 1.2068 -2.2546 -9.9972 1.1835 6.1704 269.3 144.68 
66 0.65465 0.78618 0.17502 0.18945 0.94653 -3.3942 -10.481 1.3794 5.1835 254.59 374.35 
67 0.31623 0.058215 0.19715 0.19132 0.9235 -1.644 -10.129 1.1442 4.0732 174.12 362.92 
68 0.053659 0.46803 0.2408 0.15517 0.73387 -2.0934 -10.4 1.7598 8.0943 377.41 397.82 
69 0.49169 0.87844 0.22613 0.21365 1.5542 -3.0917 -10.733 1.4624 6.9132 31.094 257.93 
70 0.48746 0.80687 0.18213 0.27987 0.68653 -2.2711 -10.492 1.689 7.9085 279.5 219.07 
71 0.25288 0.062208 0.23415 0.26998 1.6942 -2.6728 -10.417 1.4776 7.0384 229.26 149.13 
72 0.50847 0.60382 0.15427 0.17439 1.544 -2.3075 -10.155 0.68438 3.1663 72.667 141.64 
73 0.29974 0.64922 0.24811 0.11975 0.41584 -2.4904 -10.536 1.3651 5.7509 108.04 369.3 
74 0.001166 0.19266 0.21429 0.20577 1.8758 -3.0257 -10.341 1.2398 6.1983 377 279.11 
75 0.042079 0.79283 0.21926 0.20281 1.4286 -1.3395 -10.616 1.3141 4.2133 64.565 29.08 
76 0.45846 0.64422 0.18071 0.12158 1.4986 -3.6824 -10.693 1.7602 4.9213 43.315 271.59 
77 0.95161 0.41143 0.20249 0.19316 1.5263 -3.8388 -11.053 1.5576 7.8909 186.11 348.05 
78 0.26781 0.91957 0.19013 0.25676 1.6361 -1.5587 -10.004 2.3748 8.0176 262.22 335.59 
79 0.41006 0.75838 0.11607 0.18122 0.90185 -2.9452 -10.574 1.4521 7.3697 345.07 47.677 
80 0.51545 0.57455 0.22788 0.19986 1.0973 -2.6487 -9.7701 0.99093 6.6515 150.32 263.91 
81 0.95733 0.066521 0.10282 0.22548 1.5359 -2.526 -10.375 1.7889 6.6458 81.188 250.25 
82 0.88537 0.41883 0.22329 0.13661 0.77396 -2.1389 -11.108 1.3361 4.2183 290.92 231.16 
83 0.36615 0.5453 0.13476 0.24087 1.1623 -3.7423 -10.506 1.301 5.2676 275.37 189.66 
84 0.16779 0.45269 0.15697 0.11679 0.7852 -3.9283 -9.9037 1.6366 7.4887 227.39 112.42 
85 0.16085 0.096493 0.17871 0.22874 1.777 -3.6095 -11.122 1.7966 7.708 323.55 64.592 
86 0.72935 0.34271 0.12544 0.22486 1.2609 -3.7092 -9.4071 1.482 7.6459 211.9 342.89 
87 0.83287 0.32868 0.13686 0.20156 0.80618 -2.5733 -10.297 1.4215 7.0502 168.87 303.07 
88 0.76408 0.6793 0.17136 0.29058 1.0047 -3.0518 -9.4712 1.6056 7.2449 76.778 118.54 
89 0.095763 0.40949 0.20964 0.16791 1.5617 -2.4667 -9.3754 1.6457 4.9158 41.372 196.41 
90 0.48254 0.42029 0.24328 0.23031 1.6577 -3.8094 -10.49 3.1973 8.1647 250.8 105.95 
91 0.19603 0.52282 0.17748 0.13717 1.2429 -1.5273 -10.554 1.2838 7.2846 21.507 287.4 
92 0.18135 0.68067 0.21231 0.10727 1.1721 -1.0366 -10.499 1.7196 6.3647 384.59 265.16 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-5 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
93 0.24519 0.085228 0.22374 0.16178 1.2181 -2.7725 -10.142 1.2655 4.349 147.09 120 
94 0.00815 0.88372 0.16053 0.21214 1.1511 -2.7587 -10.651 1.7821 11.569 157.39 295.32 
95 0.88017 0.97634 0.13176 0.15667 0.75645 -4.8566 -10.544 1.4468 6.9344 58.853 346.58 
96 0.65912 0.22764 0.070533 0.15584 1.7601 -1.59 -9.9109 1.4401 5.3184 314.2 43.223 
97 0.61399 0.31798 0.23951 0.12847 0.85851 -3.1242 -10.582 1.5445 8.596 343.62 288.63 
98 0.038079 0.28563 0.089285 0.21639 1.1241 -3.7934 -10.917 1.2656 5.1581 317.64 66.138 
99 0.55453 0.63089 0.19061 0.22716 1.0105 -2.2082 -10.679 1.6838 9.6272 195.33 70.128 
100 0.86079 0.48698 0.12253 0.20049 0.56076 -2.2218 -9.5403 1.4352 5.3442 190.67 259.48 
101 0.78665 0.82048 0.052355 0.14924 0.19142 -2.4254 -10.035 1.1362 5.5581 207.12 372 
102 0.01354 0.92652 0.20619 0.1519 1.2618 -2.7006 -10.672 2.7514 7.029 256.13 141.44 
103 0.58308 0.70661 0.16817 0.1885 1.8112 -3.0639 -9.7574 1.4899 4.6051 220.76 75.981 
104 0.13048 0.91356 0.1939 0.20205 1.7447 -1.7877 -9.4766 1.0647 5.3233 247.02 387.98 
105 0.28326 0.59488 0.092197 0.16021 0.62008 -2.2965 -9.9623 1.1416 5.1875 211.79 240.67 
106 0.74173 0.006837 0.18534 0.13162 1.438 -1.0161 -10.409 1.3379 7.8773 304.39 26.481 
107 0.81661 0.94903 0.16504 0.15313 1.0701 -3.3763 -10.594 0.51139 3.3166 263.39 267.4 
108 0.49681 0.84374 0.27156 0.23532 1.6115 -2.0365 -10.29 1.359 6.766 129.76 124.99 
109 0.70677 0.50237 0.27545 0.23256 0.66038 -2.7875 -10.938 1.6052 7.9792 385.61 253.24 
110 0.71628 0.20405 0.15244 0.2108 0.67724 -3.8943 -10.787 1.6233 5.338 140.3 323.6 
111 0.020519 0.11671 0.13676 0.21789 1.8909 -1.3647 -10.447 1.466 7.9455 94.978 214.52 
112 0.42269 0.86654 0.23582 0.18235 1.3075 -1.7508 -10.413 0.99845 2.3406 325.92 227.97 
113 0.9942 0.25223 0.21716 0.17794 1.1071 -3.9809 -9.8537 1.4078 5.1478 96.249 366.8 
114 0.89097 0.74818 0.25081 0.22697 0.69674 -2.0799 -10.604 1.3234 6.3414 104.87 59.842 
115 0.62132 0.46444 0.18441 0.15 1.6799 -3.4277 -9.4566 1.1019 2.294 26.732 109.8 
116 0.86743 0.63615 0.15577 0.12705 0.3135 -1.6733 -10.301 1.4408 4.6148 38.838 74.671 
117 0.25736 0.88827 0.16637 0.15376 0.79901 -1.9871 -10.377 1.3022 4.9784 364.36 51.185 
118 0.79535 0.53043 0.16581 0.28089 1.4781 -3.3028 -10.504 4.3222 11.776 356.64 210 
119 0.82023 0.89271 0.17265 0.13346 1.7514 -2.6625 -10.885 1.7887 8.295 245.89 386.18 
120 0.78008 0.029057 0.24583 0.22147 1.1758 -1.3955 -9.6455 1.0774 4.4117 63.359 34.305 
121 0.99644 0.001809 0.25403 0.24598 1.7237 -3.2987 -10.619 1.7513 8.0951 348.89 254.81 
122 0.43434 0.56853 0.21893 0.13887 0.70301 -1.8625 -10.015 3.8152 12.36 362.37 225.81 
123 0.66334 0.9426 0.12918 0.15897 1.0999 -2.541 -10.646 1.0579 6.1532 284.03 20.15 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-6 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
124 0.34894 0.61624 0.1638 0.20696 1.4508 -1.6157 -9.7203 1.1641 6.4144 225.27 330.18 
125 0.6482 0.55825 0.19996 0.14063 1.4038 -2.8694 -10.306 1.0934 6.2914 172.53 87.277 
126 0.52262 0.47435 0.15944 0.15274 1.6703 -2.6884 -9.8678 1.3137 7.6635 52.594 353.42 
127 0.12093 0.99857 0.14089 0.17042 1.521 -3.0728 -9.699 1.3607 5.8605 397.46 102.3 
128 0.50376 0.40211 0.12462 0.24028 1.3506 -3.7681 -10.233 1.8162 8.3619 240.41 30.549 
129 0.4494 0.58139 0.08441 0.15786 1.3227 -3.7514 -9.7281 1.4336 7.4172 219.4 277.99 
130 0.87816 0.65641 0.20889 0.17611 1.834 -1.6861 -9.3586 1.7359 6.0229 48.342 160.61 
131 0.8586 0.42898 0.11757 0.24908 1.2823 -3.265 -10.173 1.2161 7.4377 68.552 180.1 
132 0.42846 0.043645 0.14276 0.19387 1.5002 -1.2474 -9.9678 1.6985 10.784 116.86 80.647 
133 0.68102 0.87416 0.1497 0.14457 1.2919 -3.8169 -11.011 1.7445 7.0723 353.29 359.63 
134 0.79019 0.44076 0.16073 0.16496 1.2304 -3.1606 -9.5735 1.0969 4.0565 270.84 248.91 
135 0.24348 0.44885 0.11533 0.25325 0.37138 -1.7344 -10.023 1.5748 7.043 138.51 344.03 
136 0.54706 0.014079 0.26015 0.17058 1.3755 -1.8165 -10.17 1.1307 5.3682 235.84 256.87 
137 0.23602 0.39414 0.21771 0.26047 0.95554 -2.5023 -10.689 1.1687 3.9222 184.39 334.35 
138 0.59063 0.43338 0.2567 0.19021 1.0313 -3.3801 -10.383 1.4407 7.3211 209.21 375.4 
139 0.96152 0.33488 0.11912 0.23777 0.63887 -2.1551 -10.643 1.4238 7.3109 149.15 328.56 
140 0.057431 0.90967 0.18381 0.14781 1.486 -2.39 -9.783 1.6775 7.3174 374.98 356.74 
141 0.67141 0.24933 0.20516 0.24424 1.0503 -3.2255 -10.041 1.0837 4.6347 100.06 177.11 
142 0.28613 0.99468 0.20035 0.12554 1.2671 -3.1936 -11.151 1.2299 4.7301 92.315 68.913 
143 0.30444 0.35477 0.13232 0.25113 1.7961 -2.0657 -9.9496 1.0069 5.1081 265.61 310.14 
144 0.18719 0.12198 0.075385 0.21826 1.6441 -1.4681 -9.9415 1.7274 5.0211 77.379 93.901 
145 0.58918 0.45993 0.099761 0.2382 0.49254 -2.3316 -10.432 1.3627 6.2112 192.59 163.21 
146 0.34133 0.04982 0.22967 0.10123 1.4409 -3.3182 -10.684 1.5502 5.4328 136.57 382.91 
147 0.047805 0.29341 0.093901 0.1227 1.5628 -3.5622 -10.533 1.2252 6.1875 252.7 174.65 
148 0.84534 0.58786 0.18263 0.14408 0.60164 -1.9215 -10.654 1.1387 4.179 155.88 132.05 
149 0.87341 0.66188 0.12757 0.14625 1.7067 -4.6177 -10.15 1.0285 3.8389 125.08 314.85 
150 0.73249 0.93472 0.16928 0.18818 1.597 -1.1944 -10.052 1.7162 6.8352 34.243 351.8 
151 0.75869 0.56129 0.14396 0.26452 1.4149 -3.7228 -10.329 1.7684 7.2748 336.65 379.84 
152 0.60477 0.10206 0.19316 0.13411 1.5702 -2.3524 -10.548 1.5811 7.1311 216.59 308.76 
153 0.35691 0.37418 0.23304 0.20966 1.3384 -1.419 -11.288 1.9484 10.538 324.44 80.964 
154 0.072725 0.27833 0.22884 0.14222 1.7334 -3.5069 -10.517 1.4743 4.4277 55.745 388.77 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-7 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
155 0.39335 0.71654 0.14475 0.16243 1.0566 -2.4475 -10.388 1.1995 4.3703 318.35 188.76 
156 0.15917 0.96062 0.2046 0.19583 0.59304 -3.4141 -10.666 1.763 8.3527 170.26 173.83 
157 0.39965 0.23549 0.17357 0.13773 1.7958 -3.9008 -10.217 1.3955 6.2267 114.07 115.69 
158 0.56161 0.17895 0.22476 0.18496 1.529 -2.8009 -10.075 0.25242 2.953 234.54 290.84 
159 0.47147 0.858 0.13501 0.13566 0.64763 -2.4053 -10.699 2.0714 6.9061 259.03 191.78 
160 0.13672 0.85446 0.19772 0.22029 1.5876 -2.3436 -10.088 1.4322 5.9479 166.84 31.595 
161 0.70147 0.62008 0.22654 0.14342 1.3647 -3.6558 -9.3177 1.5789 7.6938 239.67 324.09 
162 0.066647 0.24255 0.19121 0.12682 0.85199 -3.4406 -10.359 1.3309 4.5934 280.82 213.09 
163 0.89606 0.070428 0.096858 0.17308 1.0672 -2.1244 -10.328 2.7149 8.9685 152.5 229.8 
164 0.02568 0.3813 0.10695 0.1826 1.3181 -3.4742 -10.485 1.0952 6.1953 182.25 298.74 
165 0.35061 0.26555 0.21632 0.18526 1.1954 -3.3565 -10.435 1.6407 11.12 199.68 63.421 
166 0.92835 0.49267 0.12642 0.21678 0.65329 -3.877 -10.588 1.4321 6.2817 143.21 39.647 
167 0.71389 0.92211 0.24224 0.17395 1.9965 -3.5493 -10.097 1.4841 5.9563 176.3 194.43 
168 0.62881 0.60875 0.19841 0.1838 1.878 -1.0817 -9.8839 1.4514 6.1409 307.81 97.929 
169 0.69732 0.28369 0.18911 0.1926 1.2536 -3.0156 -10.187 1.1429 5.641 237.54 91.586 
170 0.084344 0.89774 0.1668 0.16429 2.5922 -3.8607 -9.6075 1.1017 6.7401 123.68 216.56 
171 0.85202 0.1316 0.19256 0.16686 1.1878 -3.0046 -10.56 1.3442 7.3912 389.06 22.542 
172 0.38838 0.18377 0.15513 0.21493 1.3441 -3.1384 -10.015 1.0801 5.1351 118.81 184.09 
173 0.085109 0.21815 0.13377 0.17292 1.868 -3.6307 -10.338 1.6482 8.6312 74.692 168.9 
174 0.97385 0.16997 0.18179 0.16388 0.96591 -3.216 -10.581 5.5253 10.554 395.28 338.42 
175 0.98033 0.5781 0.15892 0.12967 1.7293 -3.3332 -10.63 4.2776 12.983 31.891 316.99 
176 0.69471 0.20916 0.12876 0.26707 1.3352 -3.6736 -10.162 1.1452 3.1774 180.52 219.72 
177 0.2195 0.95555 0.20163 0.045592 0.74502 -3.4606 -10.226 1.6675 7.3099 348.24 152.59 
178 0.44044 0.29674 0.14158 0.24225 1.507 -3.9153 -10.521 1.4003 4.6243 390.82 198.56 
179 0.53637 0.18607 0.082572 0.10823 0.71592 -1.1148 -10.597 2.0903 8.5282 224.89 365.16 
180 0.21493 0.024592 0.15055 0.091297 0.97907 -4.5409 -10.033 1.2357 5.5589 372.43 45.443 
181 0.83581 0.12616 0.20355 0.19617 0.98965 -3.2402 -10.251 1.4982 6.1282 57.534 136.02 
182 0.14532 0.81391 0.16419 0.13944 1.8493 -3.5703 -9.5983 1.3632 6.1587 25.051 326.63 
183 0.73925 0.8359 0.20368 0.14546 1.0133 -1.8463 -10.84 0.80881 1.8179 305.11 123.38 
184 0.91963 0.7744 0.23864 0.25804 2.2662 -3.5828 -9.3523 1.4038 5.3787 314.76 157.91 
185 0.52856 0.59701 0.18463 0.086432 0.84059 -3.2062 -9.4032 1.6226 6.5072 330.73 54.46 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-8 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
186 0.32825 0.17437 0.23089 0.12394 1.691 -3.4955 -10.57 1.1034 5.5235 351.96 296.52 
187 0.80375 0.67066 0.26343 0.1607 1.7672 -2.5861 -9.6591 3.1931 9.5432 161.8 360.73 
188 0.76892 0.7972 0.20806 0.23394 0.86958 -3.6122 -10.103 1.145 4.7396 293.68 201.86 
189 0.45274 0.052696 0.28832 0.22293 1.9214 -1.1328 -10.347 5.3608 8.4137 359.62 354.89 
190 0.12775 0.25773 0.16217 0.11778 1.3804 -2.4795 -9.4334 1.7721 8.3851 28.238 150.99 
191 0.030259 0.51272 0.19591 0.19479 0.15589 -3.5969 -10.21 1.2344 7.0844 381.67 275.41 
192 0.43598 0.48281 0.14608 0.20493 1.2364 -3.5284 -10.442 1.3869 6.0249 222.79 392.35 
193 0.80683 0.31282 0.29252 0.24753 0.8914 -3.7818 -10.525 1.4914 4.0691 197.7 122.39 
194 0.98634 0.65179 0.10579 0.23597 1.0463 -4.9046 -10.115 0.029211 6.0052 274.14 209.18 
195 0.37937 0.93822 0.19449 0.13212 1.0804 -2.1797 -10.465 1.2632 4.7519 242.74 235.74 
196 0.46288 0.50794 0.16731 0.29215 1.593 -3.1837 -9.9573 1.2085 5.1291 178.61 203.67 
197 0.57279 0.72439 0.26898 0.11042 0.1268 -2.9724 -10.203 1.4679 6.7437 309.71 84.214 
198 0.60957 0.43761 0.17809 0.25562 1.3057 -2.9982 -10.196 1.4713 8.3448 83.824 132.25 
199 0.90293 0.36087 0.20795 0.11238 1.3925 -1.9654 -10.234 1.1741 5.5667 277.61 332.46 
200 0.10451 0.23312 0.22015 0.068105 0.87763 -2.8445 -9.9863 0.13075 1.9303 164.45 57.659 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-9 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
1 6.1493 3.7076 -0.25613 1875.6 0.90315 1.249 0.14801 0.37912 0.95332 0.49935 0.55136 
2 0.13979 2.9947 -0.90495 2066.2 1.1938 0.77885 0.092137 0.47786 0.91792 0.8188 0.97184 
3 7.0802 5.5188 -0.04399 1936.2 0.90379 0.77851 0.60439 0.68826 0.66009 0.53068 0.82956 
4 6.9144 5.3198 0.89094 1914 3.1598 1.4824 0.41319 0.8772 0.87114 0.76593 0.015416 
5 5.4386 3.2889 -1.1703 1846.5 0.90303 1.5138 0.42084 0.42053 0.66879 0.14968 0.65052 
6 5.707 3.7543 0.35869 1871.3 0.90329 1.1456 0.016647 0.81447 0.35119 0.19017 0.45259 
7 15.582 5.9308 -0.22168 1957.1 3.4966 0.83018 0.54561 0.74242 0.22112 0.6963 0.84463 
8 8.0173 5.9057 -1.3916 1895.9 0.90319 1.8458 0.48397 0.53618 0.81963 0.2233 0.06631 
9 5.9674 4.076 0.12144 1972.7 0.90359 0.77867 0.20968 0.66388 0.56603 0.72163 0.16671 
10 6.1912 5.9646 0.20946 1848.1 3.3813 0.77817 0.35921 0.91146 0.086184 0.26383 0.61428 
11 8.0239 5.8593 0.57785 1955.5 3.0428 1.0566 0.25235 0.28583 0.14377 0.33995 0.37274 
12 7.2804 4.434 0.978 1908.5 0.96748 2.6259 0.96923 0.38967 0.53011 0.37712 0.87938 
13 7.9246 6.2089 -0.44711 1824 1.3524 1.436 0.91852 0.74563 0.60164 0.51425 0.28382 
14 6.9083 4.3284 -0.01196 1860.2 0.90381 2.8391 0.061248 0.59919 0.035534 0.42406 0.12351 
15 7.6659 4.8564 -0.46491 1901.3 1.0338 1.2741 0.18335 0.93868 0.44241 0.83114 0.66251 
16 6.9608 5.7375 0.15593 1789.4 1.5556 2.8528 0.24504 0.23616 0.41568 0.56078 0.24768 
17 7.723 6.1141 0.071892 1904.9 0.90311 2.1018 0.56412 0.71879 0.45866 0.6612 0.88127 
18 7.4356 5.583 0.089054 1899.8 2.2769 1.4215 0.46985 0.17038 0.36892 0.4337 0.41587 
19 15.261 6.4804 -0.2701 2008.9 3.3885 2.2946 0.15415 0.29201 0.926 0.13578 0.10665 
20 6.398 5.6174 0.37412 1897.5 1.6537 0.90638 0.93395 0.38039 0.88069 0.83584 0.78477 
21 6.5091 5.3612 0.14902 1967 2.8222 1.5622 0.70752 0.19571 0.96397 0.40507 0.072601 
22 6.361 4.3835 0.26446 1941.6 2.4794 1.1297 0.89898 0.51774 0.51472 0.44474 0.076803 
23 5.4631 3.0854 0.10788 1871.8 2.7048 0.77872 0.11813 0.97456 0.31021 0.6663 0.22816 
24 5.6171 3.0148 -1.2654 1913.5 2.9966 0.8072 0.59446 0.50489 0.98748 0.23154 0.36614 
25 7.5432 5.9876 -0.20048 1786.8 1.5056 1.554 0.95635 0.59051 0.050116 0.64233 0.45837 
26 19.454 5.9545 0.27664 1876.9 0.90357 2.6816 0.74104 0.20259 0.33288 0.00056 0.94328 
27 5.5521 4.6393 -0.30598 1905.6 3.2025 1.1549 0.48661 0.5346 0.40274 0.22763 0.38021 
28 5.6577 4.1899 -0.34112 1986.6 1.743 2.5966 0.32813 0.3461 0.52155 0.30517 0.35838 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-10 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
29 6.9259 4.8134 -0.1107 1949.3 0.90353 1.2222 0.72812 0.35529 0.48028 0.18916 0.43491 
30 6.2501 3.6112 0.61346 1917 0.90384 2.0319 0.57539 0.27621 0.90553 0.61556 0.49737 
31 7.9127 8.0006 0.000996 1997.8 3.5195 2.0158 0.67078 0.43256 0.86789 0.37068 0.3227 
32 6.8819 5.103 -0.13694 1826.2 2.9475 0.82037 0.63578 0.087969 0.059871 0.013958 0.61861 
33 7.5956 4.9153 0.43555 1928.6 3.0686 1.0455 0.32401 0.28237 0.62066 0.27631 0.64255 
34 5.8952 3.1641 -0.2913 1938 0.90391 2.405 0.57426 0.17807 0.63746 0.13035 0.049985 
35 6.4071 3.8918 -0.05131 1857.7 0.90374 1.7737 0.38832 0.5125 0.7477 0.040306 0.80321 
36 6.8402 4.7547 0.76045 1884.8 1.9106 0.77881 0.021301 0.00988 0.32113 0.24313 0.62202 
37 7.5056 4.5429 -0.33819 1879.9 0.9031 1.6376 0.85906 0.67081 0.77494 0.5175 0.87397 
38 7.0917 6.0084 -0.3587 1821.8 2.5739 1.3567 0.49032 0.78578 0.8421 0.92213 0.69837 
39 7.0048 3.2365 -0.40327 1946.6 3.2872 1.7059 0.34929 0.10812 0.86475 0.26755 0.44695 
40 6.9305 5.0561 -1.0631 1928.9 3.4907 0.77805 0.23383 0.96955 0.55518 0.21934 0.14791 
41 6.6206 4.6125 -0.31852 1977.6 0.90347 0.78696 0.78578 0.67741 0.85998 0.44835 0.56415 
42 14.413 8.5213 -0.81469 1867.6 0.90364 1.887 0.79542 0.48809 0.30997 0.68955 0.27574 
43 7.0801 4.4074 0.23203 1829.1 2.3007 1.3741 0.054658 0.409 0.65079 0.16031 0.03927 
44 6.4178 4.5582 0.42998 1896.6 2.8908 1.5358 0.44201 0.36493 0.58549 0.10303 0.34881 
45 6.5805 5.1817 0.025447 1964 1.6772 2.5271 0.90287 0.84512 0.23369 0.88767 0.7561 
46 6.7732 4.3508 0.17992 1906.4 0.9037 1.4949 0.76341 0.65504 0.38765 0.92522 0.81075 
47 7.8863 5.3757 -0.6572 1839.2 2.7542 1.3217 0.55681 0.080545 0.68236 0.78279 0.68201 
48 5.5915 3.1849 0.38826 1849.6 0.90382 1.4538 0.47267 0.5233 0.42106 0.49153 0.4295 
49 7.2685 4.1403 0.33525 1887 1.5231 1.4289 0.30719 0.9826 0.97391 0.34844 0.30095 
50 8.1591 7.477 0.46714 1907.9 1.9352 1.4188 0.75527 0.79521 0.79124 0.59169 0.94693 
51 6.7672 4.4528 0.18511 1919.4 2.3538 1.6967 0.11262 0.78394 0.065009 0.96761 0.93778 
52 6.2051 3.8 -0.0048 1843.4 0.90378 2.1284 0.21311 0.45059 0.101 0.87173 0.85482 
53 0.001592 2.0902 -0.53103 2040 1.7023 1.7024 0.63397 0.75733 0.63411 0.59665 0.73295 
54 7.7203 3.6933 0.48981 1940 2.5819 0.77875 0.74928 0.001434 0.017975 0.15992 0.5667 
55 6.4049 3.0945 -0.12414 2075.6 0.90336 1.6481 0.59924 0.8652 0.39361 0.17097 0.78623 
56 6.2952 3.7152 -0.19316 1881.2 2.2225 1.0983 0.46359 0.90716 0.64016 0.016186 0.5749 
57 7.154 3.5316 -0.02042 1862.5 0.90385 2.182 0.98781 0.7921 0.91338 0.19927 0.20202 
58 5.8708 2.9401 -0.26747 2097.2 0.90303 1.6425 0.10519 0.22164 0.62929 0.081447 0.65732 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-11 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
59 6.8836 3.7417 -0.13756 1890.7 3.4252 1.9758 0.16734 0.57493 0.6155 0.97189 0.060699 
60 7.927 6.0964 -1.3759 1794.2 2.1267 1.3454 0.75226 0.55725 0.82696 0.85085 0.68955 
61 7.6493 4.5099 -0.25796 1816.9 1.789 0.77828 0.20405 0.61318 0.76903 0.7736 0.5395 
62 8.144 5.6387 -0.44055 1865.6 0.90313 1.6613 0.26243 0.87413 0.71708 0.71988 0.053525 
63 5.7201 3.568 0.22399 1974.2 1.7265 0.86279 0.94684 0.43978 0.19613 0.63319 0.52571 
64 7.8152 7.7093 -0.98719 2025.1 0.90356 2.794 0.088359 0.48033 0.84602 0.86047 0.96369 
65 5.4064 3.8242 0.40448 1662.6 1.995 0.88188 0.19983 0.046866 0.94455 0.35625 0.19656 
66 6.8026 1.7728 -0.45796 1930.3 1.967 0.77896 0.69036 0.15279 0.70221 0.95827 0.098062 
67 6.1203 4.121 0.02024 1931.6 0.90386 0.77816 0.72359 0.12183 0.58056 0.039986 0.54263 
68 7.5772 6.7573 -0.10442 1940.9 2.2592 2.2193 0.073801 0.96441 0.44882 0.88064 0.59544 
69 6.2977 3.065 -0.23475 1963.3 2.7847 1.2303 0.97696 0.20797 0.084584 0.57374 0.70334 
70 7.6321 5.7935 -0.03985 1780.6 3.5667 0.79181 0.7142 0.26741 0.78112 0.79843 0.88713 
71 7.1083 4.7049 -0.35404 1952.3 0.91759 0.98496 0.99908 0.803 0.59694 0.31095 0.11612 
72 5.6574 3.1777 0.04461 1852.1 0.90392 1.7219 0.45309 0.23211 0.34683 0.29814 0.033845 
73 7.5767 5.1335 0.09073 1990.3 1.1033 1.4748 0.61349 0.70253 0.6485 0.95109 0.83954 
74 6.7295 5.041 0.036364 1869.4 1.3657 1.2939 0.40039 0.22715 0.12556 0.84679 0.92907 
75 5.6064 3.6735 0.32454 1947.8 2.1186 1.2692 0.13788 0.64172 0.39798 0.84111 0.76703 
76 6.5068 4.3706 0.42735 1850.1 3.5552 1.1377 0.93568 0.052459 0.43316 0.27091 0.95719 
77 8.0066 6.1562 0.39433 1883.3 2.1891 2.4279 0.036244 0.31983 0.85241 0.099715 0.98777 
78 6.9771 4.9488 0.446 1977 0.90318 0.77863 0.52811 0.32228 0.69329 0.5458 0.17655 
79 6.5367 3.7835 -0.84437 2036.5 3.0898 2.3931 0.23949 0.58398 0.51926 0.15459 0.62762 
80 6.5752 3.3485 -0.29877 1968.9 2.9533 1.5442 0.79325 0.8985 0.93623 0.053707 0.48373 
81 7.0924 3.2418 -0.70629 1962.3 0.9032 1.288 0.49932 0.12507 0.89771 0.82865 0.54536 
82 6.8652 3.6377 -0.02764 1969.6 1.2058 1.7129 0.33092 0.65045 0.69902 0.23748 0.72851 
83 7.3348 5.4404 -0.20594 1760 3.6174 1.5253 0.92293 0.72545 0.89401 0.91693 0.47477 
84 6.8026 5.7136 -0.07956 2004.7 0.90395 1.1809 0.36004 0.035625 0.67331 0.77605 0.8152 
85 7.085 3.85 -0.73072 1903 2.5396 2.4615 0.10302 0.13938 0.2868 0.79406 0.9918 
86 6.8698 4.1013 -0.59536 1922.1 3.4561 1.4602 0.4156 0.099152 0.46067 0.50898 0.35323 
87 7.4268 5.2303 0.4476 1909.9 2.9123 2.566 0.88833 0.71028 0.55161 0.029548 0.60303 
88 6.8131 4.6657 0.92386 1840.5 1.3934 1.7451 0.33803 0.99092 0.099285 0.11672 0.40881 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-12 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
89 8.1135 5.1499 -0.37491 1900.3 0.90326 1.2421 0.31854 0.46209 0.3012 0.5016 0.12874 
90 7.596 6.2424 0.35281 1916.2 0.90397 0.77889 0.68696 0.76919 0.80317 0.94606 0.006143 
91 5.503 3.3187 0.12577 1959.2 0.90339 1.0995 0.12672 0.92108 0.75997 0.99265 0.79816 
92 18.034 6.2536 0.035734 1882.1 1.6093 0.77841 0.89491 0.92686 0.50891 0.30263 0.52301 
93 5.9194 3.0336 0.062279 1942.7 0.90349 1.7296 0.029419 0.54533 0.97505 0.76008 0.082954 
94 7.8762 5.3551 -0.08548 1993.1 0.90389 1.7347 0.004466 0.7771 0.81418 0.60279 0.77636 
95 6.7676 4.4996 0.33088 1934.2 0.90367 0.779 0.27625 0.75346 0.94982 0.73642 0.92474 
96 6.2249 3.3144 -0.46538 1815.1 3.5953 2.3636 0.50903 0.54324 0.52673 0.1679 0.64838 
97 6.0388 2.7715 0.11734 1845.5 2.6544 1.0609 0.86021 0.61537 0.43719 0.29445 0.4137 
98 5.4833 2.9698 0.84905 1994.9 1.2393 1.5103 0.53499 0.73858 0.54758 0.28177 0.71001 
99 6.0469 2.608 -0.07007 1925.1 0.90337 1.4681 0.31493 0.44407 0.026816 0.41548 0.26677 
100 7.0153 5.4693 0.7169 2131.4 1.3278 0.77801 0.37156 0.39791 0.34029 0.046676 0.71905 
101 7.562 5.2438 0.53172 1863.9 1.8433 1.2537 0.52369 0.89111 0.72414 0.94363 0.97783 
102 6.3275 4.8416 0.056803 1958.2 2.6805 1.3798 0.92714 0.1456 0.15558 0.32354 0.57921 
103 6.3913 5.1183 0.9123 1809.1 3.6533 1.0224 0.61812 0.30333 0.26082 0.39232 0.38884 
104 6.3176 4.0453 -0.16064 1765.8 0.9403 2.5396 0.66785 0.29726 0.31575 0.71377 0.40333 
105 1.8792 3.8256 -0.43173 2012.3 2.3309 1.5695 0.88151 0.50933 0.15264 0.36659 0.76274 
106 6.1733 4.26 -0.22998 2019.2 2.8064 1.0266 0.22383 0.85892 0.002543 0.12428 0.23763 
107 7.4244 4.316 0.41343 1981.6 0.98874 1.5407 0.30208 0.62662 0.74214 0.43735 0.50232 
108 6.7656 4.1715 0.14963 1917.9 3.6802 1.5234 0.8293 0.57726 0.96774 0.078148 0.29635 
109 7.1081 3.9256 0.104 1812 2.9781 1.0732 0.22898 0.49888 0.36227 0.80137 0.026276 
110 5.716 3.2754 0.30823 1873 3.3533 0.7781 0.5898 0.88117 0.18919 0.96142 0.73885 
111 5.5159 1.9335 0.047852 1991.6 3.2485 1.0785 0.55213 0.70952 0.48706 0.97908 0.25633 
112 6.1179 4.7172 0.070586 1904.1 1.4289 1.6676 0.033208 0.42755 0.76087 0.81213 0.74691 
113 7.4123 5.639 0.29412 1923.5 1.018 1.7611 0.12009 0.49013 0.49325 0.067976 0.15316 
114 16.09 6.1433 0.40963 2000 0.90369 0.77822 0.069784 0.93143 0.33687 0.70245 0.63608 
115 5.7307 3.6202 0.82416 1923.8 0.90344 1.4409 0.013986 0.63208 0.57667 0.39511 0.51207 
116 5.5766 3.8772 -0.05986 1892.8 1.4837 0.85576 0.87464 0.021304 0.83896 0.45149 0.21883 
117 5.4557 3.4754 -0.055 1944.8 1.0634 0.77891 0.16343 0.15549 0.32769 0.80689 0.95205 
118 10.416 6.8428 0.52583 1935.9 0.90322 2.7216 0.8338 0.60597 0.1746 0.60799 0.53258 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-13 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
119 7.7888 6.0854 0.59735 1803.9 0.90352 1.6841 0.25947 0.3505 0.13133 0.69187 0.46983 
120 14.987 5.5024 -0.28378 1889.1 0.90351 2.1477 0.17971 0.01696 0.12417 0.65725 0.21304 
121 6.5408 3.9942 0.25196 1933.7 0.90341 1.5891 0.3682 0.32693 0.14919 0.82472 0.49172 
122 10.671 5.3934 0.80396 2022.8 0.90395 2.5036 0.26875 0.30965 0.53749 0.75493 0.63438 
123 5.8361 4.5879 0.017479 2045.4 3.0164 2.7454 0.60795 0.21768 0.77931 0.20398 0.16495 
124 7.1499 5.6726 0.34544 2019.8 2.4344 1.9289 0.18763 0.16686 0.20988 0.5691 0.58279 
125 7.6797 8.1239 0.096832 1842.8 2.5249 1.5968 0.98125 0.76469 0.2517 0.3173 0.85904 
126 5.932 3.5889 0.28785 1832.8 2.4076 1.5787 0.39829 0.95212 0.034587 0.52336 0.1135 
127 6.7048 5.0797 0.17443 1981 1.2767 1.6157 0.056255 0.90495 0.98011 0.48855 0.91575 
128 7.5849 5.2913 -0.12699 1835.2 1.5866 1.3035 0.87817 0.94688 0.25589 0.33424 0.20698 
129 7.212 3.9432 0.1424 1798.4 1.7706 1.7714 0.47718 0.47024 0.19356 0.55568 0.55688 
130 7.831 5.1913 -0.31069 1720.1 3.1815 2.2739 0.95338 0.39089 0.73424 0.72894 0.50726 
131 8.0972 7.2211 0.64357 1965.9 0.90343 1.116 0.69971 0.58612 0.92169 0.67742 0.27223 
132 7.6639 5.7891 -0.2927 1985.9 0.90305 1.5025 0.1319 0.56659 0.26685 0.90542 0.13879 
133 8.0294 5.5701 0.36393 1938.8 1.3017 1.6536 0.90639 0.66534 0.7532 0.2594 0.31207 
134 6.2922 3.5566 -0.18177 1961 3.4344 1.1616 0.24114 0.94237 0.65911 0.34417 0.28603 
135 6.7919 4.9812 -0.11658 1859.2 0.90309 1.0038 0.042086 0.3139 0.012702 0.70527 0.89991 
136 6.9603 4.733 0.67106 2061.5 0.90365 0.93824 0.43459 0.98723 0.17691 0.36239 0.39637 
137 5.9763 4.7807 -0.0749 1892.1 1.4591 1.6802 0.8406 0.24623 0.24321 0.74055 0.34012 
138 5.8133 4.1604 0.20124 1927.6 0.90399 2.8913 0.4496 0.73276 0.79884 0.86859 0.29014 
139 7.209 3.3904 0.34952 1756 1.1114 2.2309 0.85058 0.013066 0.70983 0.98059 0.4625 
140 10.967 6.066 -0.23887 2084.8 2.1687 1.4077 0.19363 0.91877 0.57169 0.062484 0.59253 
141 6.5514 5.0181 0.28548 1915.2 2.1627 1.96 0.81428 0.213 0.23506 0.62553 0.8923 
142 6.4987 3.5084 -0.21553 2033.8 1.5521 2.7681 0.28203 0.030125 0.99984 0.93706 0.43827 
143 5.6205 2.9164 -1.4733 2007.2 0.90372 1.0108 0.78117 0.1124 0.90435 0.68037 0.00137 
144 15.631 5.7692 0.13213 1920.1 0.90361 1.478 0.45778 0.62244 0.20289 0.1124 0.67711 
145 6.5031 5.0007 -0.37782 1782.1 3.6308 1.3834 0.54002 0.83238 0.54177 0.059496 0.055209 
146 7.3723 4.2696 -0.17206 1856.2 1.4484 1.7392 0.58368 0.82026 0.49892 0.93132 0.8671 
147 5.9872 3.4647 0.46085 1874.5 2.7317 1.1979 0.28947 0.064219 0.008741 0.086082 0.042408 
148 7.4014 5.6886 -0.32636 2010.9 2.048 1.5757 0.83873 0.18767 0.45303 0.24793 0.17381 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-14 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
149 5.9334 3.358 0.16814 1861 3.7102 1.4905 0.71606 0.45623 0.60712 0.106 0.8472 
150 7.5823 4.8848 -0.36515 1955.4 0.90362 1.5925 0.772 0.25397 0.046208 0.35463 0.7418 
151 7.765 6.2909 0.24095 1887.6 0.9033 1.0412 0.99159 0.37394 0.16138 0.8983 0.33576 
152 6.8184 4.6906 -0.16259 1876 0.92863 1.8934 0.078416 0.26234 0.47477 0.41185 0.8627 
153 10.24 6.0373 0.080839 1950.4 0.90306 0.95402 0.37664 0.16391 0.072875 0.20549 0.98379 
154 0.55423 3.1138 -0.1468 1801.7 0.90376 1.3353 0.67507 0.85191 0.56233 0.91132 0.77248 
155 5.3984 2.9881 -0.18609 1852.6 2.0553 1.7596 0.64711 0.24118 0.78982 0.14203 0.022912 
156 7.4192 4.4159 0.23382 1946.4 0.90324 1.3632 0.29059 0.11742 0.16658 0.5841 0.33087 
157 1.2752 3.9764 -0.34614 1932 3.2184 0.77879 0.21752 0.56409 0.37232 0.071179 0.086622 
158 5.5865 3.9088 0.38434 1818.8 1.876 0.92785 0.40653 0.028803 0.093443 0.45984 0.90492 
159 16.91 5.8988 -1.1077 1823.5 2.4529 1.8267 0.09683 0.8887 0.99051 0.28945 0.44384 
160 5.3907 2.9297 0.29815 1921.2 3.3049 1.6886 0.77907 0.84141 0.82286 0.40239 0.14267 
161 7.9461 5.8762 -0.39788 1805.6 1.0831 0.77834 0.94128 0.067398 0.59004 0.87679 0.1026 
162 7.0477 3.1286 -0.47182 1748.7 1.8898 1.085 0.73848 0.27179 0.11254 0.033604 0.25055 
163 6.6373 4.2243 -0.42075 1943.2 2.0836 0.77865 0.5124 0.090902 0.29907 0.78995 0.93382 
164 5.7946 4.965 -0.27865 1979 2.3667 0.77856 0.65853 0.044761 0.71303 0.009268 0.13014 
165 6.0033 3.2186 -0.21132 1975.6 3.1379 0.94558 0.42716 0.99581 0.93247 0.63505 0.79472 
166 6.7439 5.457 -0.38635 1954 0.90328 1.5573 0.80914 0.14267 0.18078 0.46381 0.36175 
167 7.0064 3.4989 -0.03073 1830.6 1.1302 1.6278 0.97148 0.19133 0.83382 0.54465 0.22192 
168 6.3715 2.5263 -0.48095 1831.6 0.903 1.2828 0.86946 0.419 0.13968 0.55282 0.99942 
169 6.2635 3.4 0.21954 1999.3 0.99714 0.8477 0.34431 0.073091 0.68898 0.89467 0.4245 
170 14.659 8.659 0.45565 1814.2 2.6418 1.1898 0.68117 0.33547 0.40532 0.90013 0.91304 
171 6.5549 4.4726 0.16509 1893.7 2.401 1.1109 0.70351 0.69854 0.72757 0.98757 0.75225 
172 6.1013 5.7161 -0.15267 1983.3 1.2186 1.4499 0.81611 0.25826 0.61445 0.46792 0.90571 
173 7.5434 5.527 0.20554 2050.5 2.6047 2.3379 0.76866 0.058454 0.21765 0.58804 0.3155 
174 8.2794 4.0664 0.96462 1911.2 2.7415 0.89771 0.082041 0.40006 0.060625 0.38108 0.96639 
175 7.9979 4.2885 0.31596 1894.7 0.90325 1.6091 0.91047 0.82838 0.88732 0.99868 0.18895 
176 6.8041 6.0221 -1.2186 1776.4 3.2702 0.7785 0.66477 0.46953 0.042516 0.62485 0.48731 
177 6.6767 4.7963 -0.09508 1855.9 2.0157 0.88506 0.96164 0.33283 0.29031 0.47929 0.60973 
178 6.4386 2.255 -0.45186 1988.5 2.8606 0.77832 0.006732 0.52745 0.28427 0.74792 0.23012 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-15 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KDUVO KDUAL GWSPD 
BULKDEN 
SITY CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
179 7.141 5.5461 0.006338 1837.4 0.90374 0.77859 0.15811 0.55268 0.023901 0.18067 0.47559 
180 7.8443 6.2661 0.37781 1899.1 2.8672 1.3971 0.62791 0.36613 0.37716 0.25127 0.19465 
181 7.0736 4.9344 0.27154 1926.4 1.6385 0.77808 0.84643 0.60261 0.079115 0.17635 0.72495 
182 6.7374 1.996 -0.39143 1880.1 1.822 2.081 0.53641 0.4478 0.35914 0.38798 0.014873 
183 5.5053 3.436 0.47384 2052.7 2.5136 1.3331 0.43998 0.95684 0.41408 0.21347 0.83035 
184 16.604 6.1784 0.70686 2016.2 0.90358 1.3131 0.82124 0.41314 0.95968 0.61257 0.39318 
185 7.3825 6.1914 -0.94859 2028.7 0.90389 1.2114 0.14096 0.86368 0.87878 0.73015 0.824 
186 6.3639 3.4209 0.3194 1970.8 1.8143 1.6253 0.17332 0.83925 0.42664 0.75893 0.18395 
187 7.7803 5.8127 -0.42838 1853.7 1.1646 2.6512 0.29535 0.6393 0.2468 0.32991 0.2443 
188 7.3968 5.3167 -0.40788 1889.8 1.2623 1.2132 0.62056 0.077406 0.27678 0.12604 0.51919 
189 8.0923 5.8459 -0.0098 1878.8 0.90314 1.1667 0.27374 0.81653 0.73931 0.52789 0.26466 
190 7.4329 5.2743 0.42213 1912.5 0.90346 0.77845 0.80183 0.10476 0.10591 0.85939 0.80646 
191 6.1279 4.0069 -0.09548 1868.6 1.4057 1.3999 0.50392 0.80569 0.22811 0.023383 0.32794 
192 6.3392 4.6196 -0.41476 2003.6 3.3367 1.791 0.64456 0.1335 0.21443 0.53591 0.66755 
193 6.1161 4.8803 -1.3166 1866 0.90332 0.7784 0.73013 0.97535 0.38237 0.67251 0.69203 
194 0.30637 2.8997 0.24466 1735.4 1.9855 1.6741 0.38362 0.34451 0.67767 0.42816 0.70837 
195 5.4753 2.3675 -0.24962 1768.8 0.90341 1.6045 0.51658 0.77213 0.27475 0.48303 0.58716 
196 7.3568 5.2147 -0.176 1795.8 1.3102 0.9639 0.35128 0.64598 0.11775 0.64953 0.3061 
197 6.8571 4.5789 -0.33088 1836.8 0.90334 1.7525 0.56869 0.694 0.50191 0.4735 0.6721 
198 7.1083 4.0231 0.77472 1951.9 1.152 0.99489 0.39476 0.72323 0.46947 0.57942 0.092109 
199 6.6074 5.4246 0.25766 1885.4 2.2515 1.178 0.65197 0.18141 0.47965 0.65273 0.37658 
200 6.1683 4.2044 0.19183 1910.7 3.1226 0.77824 0.046482 0.68272 0.80814 0.091389 0.15855 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-16 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
1 0.92233 0.25505 0.74124 15.158 1.313 191.85 170.3 90.304 87.115 4.2804 
2 0.95718 0.43026 0.82308 5.231 1.996 438.05 321.83 296.2 128.74 4.5635 
3 0.39566 0.78442 0.12747 7.789 1.8919 315.77 508.4 96.723 102.66 4.6501 
4 0.83861 0.26775 0.71883 8.064 1.8993 823.19 978.39 33.548 93.633 4.8718 
5 0.52003 0.57509 0.094709 6.281 2.5643 875.12 769.2 55.826 102.81 3.7980 
6 0.40076 0.96621 0.9459 9.449 2.1515 789.01 900.47 58.053 74.556 5.1715 
7 0.094518 0.093636 0.46901 4.946 2.6278 786.48 844.16 100.7 111.5 4.5060 
8 0.32186 0.17194 0.84957 5.365 1.8634 865.84 827.29 63.628 76.41 5.8273 
9 0.30145 0.85606 0.16371 15.893 2.2814 364.19 527.36 120.34 112.2 5.5088 
10 0.57727 0.11274 0.96106 7.689 1.4344 797.1 251.58 98.732 110.55 4.1104 
11 0.74875 0.15598 0.086856 1.125 2.1713 322.86 935.95 108.93 141.46 3.9581 
12 0.6884 0.20431 0.40849 9.047 1.3276 366.98 176.25 115.46 97.821 4.6365 
13 0.11426 0.97927 0.80415 0.968 3.3988 237.1 459.82 125.54 115.14 5.0327 
14 0.077847 0.038325 0.39857 4.660 1.8369 892.57 306.82 99.777 89.356 4.7745 
15 0.47977 0.67091 0.53651 2.573 2.1315 342.82 722.33 47.92 94.597 4.9787 
16 0.56804 0.91726 0.52864 5.602 2.5869 947.77 592.07 124.29 126.95 5.8763 
17 0.97516 0.75352 0.96649 4.996 1.738 277.76 398.99 108.06 98.209 5.0810 
18 0.22547 0.098027 0.27507 1.676 2.8558 181.8 804.65 109.59 83.384 3.7712 
19 0.11894 0.90477 0.51826 1.077 1.7207 169.97 229.43 106.12 94.169 3.9250 
20 0.44268 0.65648 0.4869 3.141 2.2336 382.72 520.65 109.97 87.421 3.6536 
21 0.86671 0.87858 0.86223 3.002 1.8704 915.02 368.66 96.453 125.67 4.1820 
22 0.37889 0.51061 0.8531 4.304 1.4624 483.89 143.12 169.19 103.75 5.6731 
23 0.18952 0.45367 0.61803 4.741 0.83082 357.62 604.77 109.04 115.5 5.3456 
24 0.77685 0.032638 0.93762 3.898 1.5078 839.57 137.68 95.04 101.48 5.6393 
25 0.48162 0.79486 0.64681 3.671 1.8783 901.9 765.48 96.029 101.76 4.9227 
26 0.67481 0.28202 0.28096 2.710 2.2218 749.18 638.22 124.09 116.2 4.1439 
27 0.016023 0.91494 0.79437 15.809 0.67777 386.2 670.05 268.23 156.79 3.9292 
28 0.48515 0.29132 0.2558 5.676 1.7298 728.67 595.11 48.879 87.909 4.7882 
29 0.31677 0.86088 0.87083 1.401 3.1006 710.85 801.34 223.13 124.07 5.5724 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-17 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
30 0.47158 0.95708 0.22766 9.231 1.3287 578.95 287.2 103.57 106.62 4.5271 
31 0.87638 0.25117 0.35533 13.125 2.1624 600.92 550.08 95.733 92.572 4.4803 
32 0.84049 0.75826 0.066926 4.410 1.385 205.98 336.68 44.124 82.144 4.3017 
33 0.79945 0.36122 0.71376 4.877 2.6009 269.1 816.16 26.919 75.323 4.2503 
34 0.087804 0.8988 0.88781 2.241 2.7057 525.12 994.94 89.955 77.693 3.8711 
35 0.73521 0.77603 0.2629 1.957 2.0292 927.46 543.12 121.2 91.276 4.8427 
36 0.28329 0.060343 0.24624 17.711 3.0503 172.61 355.55 70.693 76.655 4.9358 
37 0.82935 0.82288 0.070104 2.402 1.9786 920.22 181.29 52.094 74.015 4.6561 
38 0.042963 0.33111 0.15903 1.183 1.4821 829.07 374.93 117.73 93.13 4.5549 
39 0.85708 0.73262 0.89719 3.329 1.9402 293.68 894.64 98.184 107.62 4.0871 
40 0.60087 0.72999 0.42689 10.239 2.6368 906.51 560.1 129.16 105.03 3.2589 
41 0.49271 0.10448 0.77958 2.445 2.3116 231.07 691.6 99.503 85.243 3.8497 
42 0.64192 0.96389 0.50726 2.844 2.2754 944.28 158.05 100.71 95.463 5.5640 
43 0.2041 0.71481 0.94157 7.315 2.1155 968.83 620.16 127.49 100.21 4.9771 
44 0.18387 0.27955 0.6511 3.041 2.3907 152.04 292.65 104.9 84.399 5.5546 
45 0.98648 0.43556 0.40458 0.417 2.7365 900.41 774.39 93.399 121.6 5.6584 
46 0.23594 0.70606 0.097513 4.133 2.3716 724.12 192.57 123.5 105.44 4.6247 
47 0.9144 0.46205 0.26876 1.828 2.0254 257.4 617.25 101.5 108.69 5.0652 
48 0.63216 0.56861 0.30615 4.532 1.1684 696.14 654.18 108.09 121.87 5.4658 
49 0.51583 0.8261 0.74634 1.277 2.1974 850.09 213.01 68.76 99.02 4.5905 
50 0.8528 0.83683 0.2883 6.354 2.0765 249.14 868.01 120.19 90.383 4.4906 
51 0.53245 0.42635 0.90682 18.841 2.7894 636.37 916.94 31.245 96.036 4.3295 
52 0.3125 0.12124 0.18823 3.581 1.7479 228.58 660.12 119.08 108.23 5.5882 
53 0.79448 0.99326 0.38079 0.862 2.1889 308.05 927.64 127.89 111.08 5.7803 
54 0.2736 0.41402 0.75965 0.664 0.46339 756.15 726.75 121.96 80.495 4.9715 
55 0.82136 0.94926 0.57277 3.463 0.97016 506.62 873.56 111.78 96.438 5.6818 
56 0.24226 0.47853 0.65891 9.264 2.3606 799.26 884.41 123.18 87.709 4.9327 
57 0.30565 0.31586 0.63843 13.715 1.6016 999.94 681.02 118.62 89.156 4.4186 
58 0.87226 0.30481 0.23333 4.827 0.25367 431.79 571.3 92.604 97.251 4.3427 
59 0.34771 0.81349 0.55574 2.905 2.5133 652.12 480.85 52.708 92.983 5.9321 
60 0.53539 0.18244 0.43489 0.078 0.93803 966.49 813.06 108.88 96.181 4.9131 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-18 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
61 0.69358 0.072783 0.20895 6.208 2.2049 327.18 326.07 113.29 109.16 4.9928 
62 0.37424 0.005167 0.43543 3.770 2.1004 773.99 539.24 61.532 88.724 5.1110 
63 0.80636 0.65482 0.62131 4.271 1.5823 802.08 319.46 93.79 70.915 5.6913 
64 0.95066 0.54284 0.91978 12.312 2.4195 348.42 276.85 82.819 97.502 5.6667 
65 0.94153 0.97469 0.057611 14.551 1.4013 765.3 746.99 64.415 83.784 5.6949 
66 0.38226 0.048251 0.4617 13.256 3.199 105.66 821.22 96.256 89.718 5.4470 
67 0.62941 0.61653 0.38797 8.296 1.7649 512.22 908.36 126.18 127.89 5.4320 
68 0.56358 0.98803 0.62566 4.697 1.6497 597.5 255.95 113.55 99.808 5.3808 
69 0.753 0.13847 0.19972 2.381 1.0524 411.65 757.85 47.151 102.43 4.5852 
70 0.41038 0.61048 0.47687 3.750 4.5701 628.82 652.53 107.02 114.16 3.9909 
71 0.50596 0.76298 0.75346 4.791 2.553 777.39 630.04 128.15 117.51 5.3169 
72 0.35308 0.58728 0.83407 11.250 1.49 501.84 854.87 100.54 101.63 4.7010 
73 0.72002 0.84202 0.17657 10.774 1.6344 806.66 134.47 101.57 109.6 4.7159 
74 0.14626 0.68295 0.07776 4.085 1.619 813.08 740.3 105.18 104.64 4.2315 
75 0.066744 0.38841 0.026305 12.916 1.7716 145.68 396.12 111.4 124.17 5.4556 
76 0.40925 0.42092 0.041884 1.901 2.9928 912.04 342.71 126.98 113.06 4.6658 
77 0.75816 0.63356 0.19002 0.972 2.0748 683.34 714.72 16.105 69.555 4.9426 
78 0.17325 0.53555 0.79986 11.716 0.036259 271.18 756.88 127.94 103.52 4.6721 
79 0.17749 0.08885 0.50064 0.735 1.2689 759.01 860.64 110.31 118.45 4.5498 
80 0.65533 0.31436 0.13959 0.533 2.8701 372.36 364.79 16.123 81.2 4.3902 
81 0.13682 0.5298 0.543 1.222 0.793 355.91 752.04 107.09 108.04 5.8997 
82 0.34247 0.32268 0.29273 14.707 2.135 420.4 302.23 169.79 117.2 5.3603 
83 0.8816 0.1638 0.004696 3.298 2.5754 477.61 687 115.38 138.11 4.8906 
84 0.021631 0.93282 0.034844 0.496 1.6476 576.68 738.93 120.33 95.649 4.5763 
85 0.36704 0.28987 0.33286 2.052 1.8058 215.64 664.61 111.45 100.39 5.5779 
86 0.49834 0.98297 0.2155 2.143 2.2666 962.97 313.04 110.97 110.15 5.4691 
87 0.26303 0.59693 0.14617 2.230 3.1643 137.62 695.13 299.14 109.9 5.3922 
88 0.77494 0.5598 0.64268 13.897 3.326 343.39 381.16 117.26 73.277 5.6234 
89 0.29397 0.38192 0.4223 3.828 3.2587 982.55 430.74 112.79 103.68 5.3744 
90 0.89941 0.35616 0.44701 0.593 1.22 568.32 573.95 116.53 130.47 5.6770 
91 0.76656 0.80189 0.45487 4.908 1.962 118.83 126.83 110.22 131.81 5.6881 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-19 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
92 0.63929 0.74595 0.53056 2.347 1.3698 333.02 989.47 120.59 99.181 4.2700 
93 0.86447 0.92068 0.66988 2.098 2.24 559.88 344.58 128.29 119.99 5.6460 
94 0.9357 0.50364 0.31131 1.976 3.4595 424.79 512.48 81.96 98.194 4.9060 
95 0.35996 0.37754 0.98715 12.749 1.7585 199.83 416.67 214.97 120.86 3.7339 
96 0.99924 0.64932 0.6606 0.800 0.41495 134.12 114.86 237.13 110.95 3.5904 
97 0.28863 0.35212 0.36658 2.730 1.6868 102.1 795.33 102.76 81.501 5.1375 
98 0.99314 0.34661 0.10037 0.647 3.0595 318.89 309.2 99.114 93.699 4.4413 
99 0.42653 0.23963 0.037187 7.917 1.417 873.02 402.88 90.315 85.688 5.8433 
100 0.33084 0.79766 0.17138 7.995 1.2469 583.6 247.25 108.06 107.42 5.6115 
101 0.42259 0.22354 0.7233 3.626 1.7033 713.27 211.67 53.206 85.996 4.8792 
102 0.84776 0.62524 0.73714 4.336 2.6104 284.91 941.27 93.82 97.341 4.7655 
103 0.057725 0.36634 0.76158 12.561 1.2976 633.5 464.4 69.486 105.78 4.8590 
104 0.96879 0.47187 0.13328 1.373 0.89703 691.48 731.85 46.285 77.453 4.4407 
105 0.7066 0.37193 0.57744 4.452 1.4986 679.35 502.4 103.07 90.736 3.9455 
106 0.2104 0.71681 0.99385 9.661 1.93 718.95 370.31 92.207 106.78 5.9834 
107 0.032139 0.30865 0.35219 0.770 2.4818 958.73 102 92.673 95.276 5.5449 
108 0.78493 0.55127 0.23633 3.241 1.91 465.56 857.75 96.317 123.31 5.4404 
109 0.54848 0.08343 0.68564 2.518 2.4269 618.97 536.05 99.752 113.53 4.9968 
110 0.96153 0.89494 0.54785 6.785 0.337 854.01 921.47 100.86 107.96 5.7257 
111 0.62488 0.044425 0.91427 3.854 1.6652 981.82 472.75 91.209 95.83 4.7466 
112 0.69681 0.85203 0.92816 6.698 1.5314 165.82 830.4 124.37 114.99 4.8282 
113 0.52809 0.86964 0.70423 1.461 2.0875 647.98 162.04 127.06 120.16 4.5992 
114 0.61818 0.58153 0.80775 2.611 1.6168 519.13 930.53 108.83 84.747 5.6487 
115 0.46203 0.41723 0.31862 3.167 1.123 937.13 195.45 99.599 96.639 3.8759 
116 0.20919 0.33963 0.49977 10.959 1.8505 292.87 785.6 106.33 79.1 4.9638 
117 0.39316 0.84877 0.86639 1.510 2.3377 221.66 466.18 96.406 94.934 4.7551 
118 0.51324 0.69222 0.84208 10.391 2.0452 845.4 791.83 80.688 72.275 4.9250 
119 0.50401 0.18607 0.37533 9.622 2.6881 730.58 236.97 58.767 79.498 5.8599 
120 0.97274 0.72227 0.32996 8.551 2.0178 702.2 441.76 23.371 85.839 3.6388 
121 0.90393 0.76623 0.69825 1.537 2.2099 124.07 120.97 129.61 115.89 5.9687 
122 0.16682 0.90667 0.3208 2.812 1.1146 887.34 601.3 101.88 89.549 4.9881 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-20 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
123 0.88685 0.78667 0.33837 3.377 1.8277 594.89 487.94 99.719 100.93 4.6396 
124 0.93377 0.88469 0.049508 14.072 0.54525 389.24 983.39 96.849 102.08 5.2270 
125 0.8012 0.49335 0.59546 3.433 2.979 480.65 433.28 97.548 81.699 4.8332 
126 0.27749 0.078469 0.90494 8.195 1.963 547.81 265.01 111.24 112.29 3.7221 
127 0.15151 0.11629 0.56557 5.101 2.4552 178.03 424.58 108.54 135.4 4.8871 
128 0.23227 0.66062 0.60165 4.047 2.6825 264.86 331.56 127.96 108.46 5.4989 
129 0.55875 0.88816 0.47306 16.849 2.1129 528.17 486.76 23.377 98.536 5.5355 
130 0.2558 0.46514 0.20482 4.371 1.9442 862.28 297.69 119.44 112.74 5.5138 
131 0.98325 0.44402 0.78375 1.879 2.0021 196.29 493.03 104.65 109.29 4.8069 
132 0.70346 0.6861 0.51445 2.790 2.6619 933.76 608.58 106.59 86.628 5.2099 
133 0.43036 0.74351 0.67275 2.993 2.3754 113.09 563.74 108.84 92.665 4.8474 
134 0.59479 0.24391 0.18118 2.673 2.8191 611.49 703.65 17.447 92.329 3.4887 
135 0.029181 0.54944 0.44236 7.478 3.5157 554.31 284.02 19.775 100.62 5.6529 
136 0.29642 0.40806 0.16692 4.512 2.9033 660.81 166.35 91.784 87.352 3.8309 
137 0.71369 0.59312 0.59332 3.694 3.0078 515.99 578.66 50.496 86.272 3.4490 
138 0.91854 0.19074 0.63055 3.529 3.307 140.74 648.08 123.04 96.886 4.9556 
139 0.45967 0.51566 0.95385 7.008 1.676 664.82 585.21 85.754 94.293 4.8637 
140 0.25344 0.93944 0.52473 10.442 1.5508 336.3 476.3 112.83 116.62 4.9499 
141 0.099923 0.80992 0.89486 3.231 1.1519 995.02 449.12 93.917 93.336 4.8208 
142 0.24977 0.13496 0.98272 10.658 2.4377 394.86 674.88 118.52 132.7 5.7715 
143 0.036624 0.20762 0.24422 4.612 3.5447 304.25 234.78 116.07 124.91 4.1553 
144 0.051719 0.26209 0.006894 8.680 1.5218 879.45 947.05 119.99 113.85 5.3273 
145 0.57483 0.63694 0.58037 9.901 2.1419 442.83 152.68 12.842 88.442 5.5179 
146 0.41881 0.15465 0.36144 2.311 1.8391 410.47 719.9 101.76 93.923 5.9539 
147 0.22244 0.14066 0.14225 7.603 2.0595 827.17 889.36 116.49 104.14 5.2782 
148 0.68188 0.19518 0.10796 3.925 2.6459 300.53 634.47 118.02 91.116 3.9851 
149 0.72764 0.10513 0.88462 1.599 2.5012 891.05 390.81 66.221 78.156 5.4854 
150 0.43902 0.44513 0.11251 5.203 1.2316 241.1 546.37 105.69 110.49 4.8009 
151 0.83171 0.60065 0.25367 4.160 2.3044 186.78 223.17 26.465 91.677 5.7046 
152 0.21903 0.05082 0.99545 1.323 1.7878 624.78 842.01 104.69 98.913 5.4203 
153 0.73195 0.12708 0.83865 1.791 2.8058 783.67 956.27 104.7 102.2 4.4565 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-21 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
154 0.6762 0.029674 0.77487 6.511 1.1833 988.97 531.89 112.04 104.21 5.4115 
155 0.15591 0.40127 0.2951 3.088 0.99647 454.6 912.9 118.23 84.029 5.5970 
156 0.65336 0.16679 0.45652 16.213 1.0783 488.62 243.89 100.77 82.78 4.4704 
157 0.78953 0.64082 0.81817 2.941 2.4897 815.64 679.99 100.08 103.24 4.6806 
158 0.92559 0.17548 0.58945 16.672 2.3218 456.58 186.9 47.529 97.876 4.0638 
159 0.6146 0.60552 0.56322 1.685 0.70349 212.34 996.89 40.481 84.26 5.8121 
160 0.16497 0.000294 0.68255 12.220 1.5591 461.05 178.25 177.41 94.482 5.4813 
161 0.59504 0.87101 0.019925 10.114 2.5235 563.58 882.73 122.08 111.91 4.5191 
162 0.19052 0.39438 0.72575 5.808 1.697 738.55 847.2 99.741 101.24 4.3831 
163 0.74153 0.34185 0.87858 15.300 2.0564 495.2 499.64 61.494 106.25 3.7808 
164 0.083627 0.52435 0.34361 1.094 1.4214 534.17 808.26 127.98 88.797 3.9056 
165 0.45195 0.81843 0.81288 0.701 2.3472 471.15 977.34 105.15 90.127 4.7870 
166 0.81384 0.22875 0.97654 0.445 2.251 613.59 205.96 112.9 106.05 5.5267 
167 0.2695 0.73651 0.30146 11.463 2.9584 858.45 589.16 96.349 99.705 4.6130 
168 0.66599 0.29998 0.92251 2.185 1.2731 115.43 148.63 102.27 85.113 4.0060 
169 0.1286 0.21367 0.73255 3.996 1.448 952.98 968.45 43.687 82.369 4.6983 
170 0.90937 0.2454 0.34744 1.752 1.09 689.46 442.49 93.817 100.01 5.2650 
171 0.001231 0.77299 0.11959 8.781 3.8606 554.82 261.49 127.63 106.41 3.1175 
172 0.4656 0.83016 0.93346 13.446 3.1732 244.5 699 105.07 61.47 4.7295 
173 0.19628 0.022893 0.76523 11.081 3.6345 500.05 780.29 105.03 90.458 5.6042 
174 0.54137 0.23146 0.60978 0.367 1.8184 416.75 968.89 95.594 122.48 5.6344 
175 0.36311 0.99983 0.053292 4.567 3.1094 707.24 953.45 119.63 95.041 5.1588 
176 0.60953 0.70036 0.27276 2.534 2.7539 155.74 945.94 99.692 100.87 4.5358 
177 0.064173 0.21845 0.15009 12.027 1.9175 654.72 623.42 104.98 118.15 4.3634 
178 0.76396 0.92607 0.21335 6.586 2.4006 433.07 555.74 126.82 102.99 5.9885 
179 0.10918 0.39894 0.41905 1.639 1.3675 740.08 105.31 109.7 104.85 5.2525 
180 0.89186 0.018397 0.12176 4.221 1.9905 403.18 777.53 122.92 98.747 4.9020 
181 0.13459 0.45851 0.67736 6.880 0.97985 131.08 877.56 31.075 78.69 5.5495 
182 0.94536 0.066174 0.22481 1.313 2.8343 450.78 266.84 107.18 80.179 4.4101 
183 0.074184 0.27323 0.063419 9.988 2.8894 259.14 358.23 105.52 80.941 4.6913 
184 0.33522 0.56336 0.69415 6.146 1.5716 538.12 202.45 64.375 91.579 5.9230 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-22 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
185 0.38501 0.57366 0.4949 3.517 0.89307 767.45 408.75 102.49 118.82 4.6171 
186 0.64828 0.67742 0.78821 7.207 0.75759 543.77 423.04 120.39 114.51 4.2114 
187 0.55432 0.3274 0.82971 2.035 1.3431 672.33 834.53 124.19 104.48 4.7366 
188 0.58086 0.49706 0.48494 19.322 1.0364 641.42 130.4 275.32 113.4 5.3329 
189 0.010006 0.95063 0.41403 0.843 1.591 929.22 413.17 90.251 83.199 3.3167 
190 0.81791 0.48478 0.97384 4.037 2.9223 974.17 384.56 109.61 105.37 5.5808 
191 0.10396 0.14898 0.95984 11.665 2.4702 743.93 640.94 117.27 96.809 5.0963 
192 0.008292 0.48702 0.022384 0.289 2.7737 284.09 219.8 108.01 88.152 5.6072 
193 0.66128 0.010403 0.85706 0.887 2.5306 587.59 453 109.69 107.23 5.2849 
194 0.44669 0.056335 0.013682 8.833 1.7959 668.91 963.31 34.465 91.033 5.2949 
195 0.58695 0.50667 0.080381 0.924 0.60612 162.67 903.2 37.662 92.086 5.6213 
196 0.14264 0.66797 0.39326 5.436 2.2902 604.69 272.75 100.65 91.916 5.2178 
197 0.71574 0.5321 0.55188 1.006 0.84056 837.67 112.33 45.028 89.853 5.0028 
198 0.048634 0.62298 0.37462 5.964 2.7289 218.81 349.72 103.43 99.369 5.1921 
199 0.12266 0.69669 0.61218 7.132 1.2041 398.88 514.47 118.09 119.54 5.4031 
200 0.32612 0.9429 0.70614 5.875 2.4135 375.84 709.58 112.16 86.921 4.3237 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-23 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
1 6309.1 4730.4 6.5351 4824.9 617.72 3.8786 -4.572 
2 5007.6 5342.1 5.4447 3283.2 560.12 3.4041 -5.7843 
3 5589.4 8261.8 4.8395 5971.4 534.18 3.6749 -8.8173 
4 7302.6 6245.2 6.6296 6323.1 827.68 3.9087 -8.0077 
5 5992.9 6287 4.8973 3155 674.44 2.2705 -5.7211 
6 5262.8 4788 6.7566 4040.3 690.22 2.8873 -6.7879 
7 2893 8144.2 5.2392 4133.2 606.63 3.5717 -7.6456 
8 3603.4 6889.1 4.5868 4957.6 306 2.5735 -8.5382 
9 5643.8 7741.2 5.6826 4672.8 867.06 2.6883 -8.3826 
10 3583.3 5909.9 5.7904 5535.5 750.13 3.5812 -7.8268 
11 8540.9 5513.8 4.8169 3188.8 740.75 2.7641 -5.4308 
12 5508.4 2825.5 6.6948 5720.5 770.37 3.4680 -7.4885 
13 8724.2 7377.1 6.8118 3442.1 266.83 2.1051 -7.9463 
14 5089.3 7061.1 6.3204 6041.6 657.5 2.3401 -5.3155 
15 5808.5 5920.6 5.3310 3614.8 668.57 3.6235 -6.3063 
16 4777.5 5522.6 5.8099 6539.7 965.15 3.5680 -6.038 
17 4977.8 3305.5 5.5915 4220.7 389.36 2.6242 -8.9285 
18 6542.9 2272 6.3937 3590.5 314.42 3.3368 -5.1203 
19 4993 5558.6 6.3339 4950.8 931.04 2.7255 -5.015 
20 6706.8 5120.3 5.7864 6480.9 748.94 2.5836 -8.6327 
21 5726.8 5387.4 5.2634 6331.2 876.74 3.6523 -7.7092 
22 6860.1 3553.6 5.0370 5142 910.33 2.8175 -6.4254 
23 7545.6 2579 5.3519 6001 773.03 3.6354 -3.895 
24 7054.6 3372.9 5.8597 5089.8 882.09 2.7515 -6.355 
25 3854.7 6983.9 6.5554 3213.3 211.23 3.5346 -6.8006 
26 6472.6 3036.3 5.8147 3001 396.27 3.2209 -7.9992 
27 4620.5 5009.2 6.4296 5355.6 757.18 3.2262 -5.2569 
28 5306.4 7479 5.1151 4520.6 677.06 3.6131 -8.3503 
29 5660.7 7023 6.2314 6300.8 393.27 2.7444 -8.4815 
30 4297.1 5867.5 6.0915 5966.3 887.33 3.5988 -8.7293 
31 5051.6 4283 6.8673 4550.5 474.94 3.5616 -8.1127 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-24 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
32 6115.2 4876.6 4.1311 4318.2 714.81 2.6805 -5.0346 
33 8317 5640.6 5.8788 5113.8 602.9 3.0525 -5.9699 
34 2275.6 5746.9 5.3663 6611.1 803.33 2.5272 -8.3377 
35 4908.8 4073.5 6.4875 4277.7 779.54 2.5392 -8.296 
36 6693 5035 6.9595 4693.2 411.36 3.6880 -5.8621 
37 4723.8 7013.3 4.8852 6499.2 705.79 2.1769 -7.9177 
38 6277.4 5160.7 6.9065 6124.2 709.48 3.3973 -4.4364 
39 5181.5 4893.3 5.5222 5800.6 720.07 2.8232 -7.2399 
40 7778.2 4527.7 5.9593 3033 343.37 3.2912 -6.1793 
41 5349.7 7316.6 4.9502 5821.6 777.99 2.9877 -8.9181 
42 6431.5 6816.2 4.8666 4617.6 549.49 3.1674 -6.3317 
43 2724.4 3759.5 4.9395 1221 796.79 2.9675 -7.5121 
44 6243.5 5785.8 5.8712 6359.9 590.83 2.8696 -7.3863 
45 5925.8 4714.3 6.1445 4464.6 243.19 2.7023 -8.425 
46 1965 6376.5 6.6558 6440.8 894.15 2.9331 -7.8574 
47 5037.4 6725.3 4.7309 2887.8 903.14 3.6463 -8.4126 
48 7443 4304 5.7277 4745.8 538.95 2.8814 -6.7385 
49 4462 5212.8 5.9290 6080.2 422.12 3.5294 -8.0285 
50 4035.1 5657.4 5.7352 6162.7 509.71 2.8766 -6.7708 
51 5554.9 6420.5 5.2172 5620.3 453.26 2.3533 -8.2752 
52 8071.4 4949.3 6.4202 3665.8 228.18 2.8028 -8.5786 
53 7348.9 5477.7 6.9912 4604.2 653.48 3.0161 -5.961 
54 5461.1 5625.9 5.7499 4374.7 331.77 3.4751 -7.1264 
55 7018.4 7145.9 4.9984 3269 110.95 3.6719 -5.6324 
56 3837.1 4805 5.6154 5041.6 936.66 2.6705 -5.6515 
57 6594.9 6131.6 6.7445 3732.9 524.79 2.6578 -8.6058 
58 5954.2 3231.6 6.4616 5512.2 987.52 3.4315 -6.5611 
59 5596.7 5326.9 4.7420 4582.7 763.5 3.6969 -4.6876 
60 5418.1 4607.3 6.4741 6579.8 807.2 3.6680 -7.1741 
61 5133.5 4100.7 6.5664 4294.6 520.07 2.4733 -6.8259 
62 5157.4 4938.7 5.8312 6408.7 256.39 3.8385 -6.0998 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-25 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
63 4670.8 4844 6.5497 6558.7 292.95 3.3557 -5.5944 
64 4867.2 5144 4.9779 6514.3 993.65 3.5556 -5.5647 
65 3446.8 7923 6.3795 4354.9 382.29 2.8582 -4.9253 
66 5491.3 8625.9 4.8559 5495 906.26 3.4896 -4.7857 
67 6156.1 4018.3 5.9815 6404.6 790.76 3.2972 -6.6733 
68 6385.1 4135.9 6.6414 3833.9 641.08 3.9440 -4.0582 
69 7549.7 4323.1 5.9031 6780.7 857.31 3.4630 -7.6129 
70 5771 3145.7 4.9035 5579.7 471.12 2.7098 -7.2777 
71 7105.6 6195.3 5.2926 3406.9 834.26 2.2552 -4.6302 
72 6982 4346.1 5.4560 5564.9 408.06 3.1792 -5.6844 
73 4534.3 6800.1 4.6366 1895.6 489.25 3.1359 -5.2873 
74 1379.9 6227.9 6.0219 141.19 756.85 3.0487 -7.0552 
75 2698.3 5880.5 5.6957 3098.8 367.47 2.8960 -8.7995 
76 5210.5 6572.4 6.7109 3475.8 134.04 2.1340 -5.8189 
77 4280 1694.7 4.2831 4996.3 360.62 2.5599 -7.2497 
78 3914.1 5389.7 5.6608 5933.4 853.07 3.5461 -6.2719 
79 9002.5 4631.3 6.3418 4915 403.1 3.5942 -8.0875 
80 6572.1 5364.9 5.1451 4057.6 477.94 3.7520 -8.6709 
81 6921.6 2799.2 5.7018 4897.6 445.81 3.4561 -6.4535 
82 4152.2 7436.8 4.9250 4190 683.38 2.2281 -6.5244 
83 7164.9 4389.7 5.6492 3320.4 693.33 2.8429 -6.4857 
84 2388.7 6013.4 5.7170 5696.7 163.8 2.6344 -4.3981 
85 6874.5 3492.4 5.5117 5013.6 983.28 3.9624 -4.5272 
86 3782.3 6217 5.9032 6214.5 461.19 2.6480 -7.4294 
87 3630.1 7190.7 4.5803 6282 952.5 3.4821 -8.0503 
88 4365.5 5547 6.8266 3923.8 925.98 3.6803 -4.5105 
89 3683.3 4475 5.0791 5231.6 430.68 3.6910 -6.8462 
90 6008.9 5068.9 6.4046 4138.7 249.24 3.3073 -7.9359 
91 3750 9774.6 6.0279 3655.1 918.62 3.0975 -7.889 
92 6233.9 6352.9 6.9300 5828.7 568.55 2.3213 -6.2493 
93 3459.8 4572.1 6.3086 4889 825.23 2.6000 -7.4708 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-26 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
94 7865.3 5818.5 5.6892 3166 202.33 2.5084 -3.7317 
95 4228.9 6409.7 6.2134 5202.8 836.23 3.4954 -5.393 
96 5531.3 5697.5 6.1669 3971.1 872.68 3.6501 -5.5001 
97 3939.6 8295.4 4.6709 3557.2 767.05 2.7793 -6.6074 
98 5965.7 5955.8 5.3185 4487.9 651.73 2.5491 -8.3675 
99 3738.6 3419.1 5.6059 5870.2 947.46 2.7711 -7.0308 
100 4802.2 6453.6 6.5686 6737.4 615.38 2.8674 -7.7203 
101 3334.5 6512.4 4.4403 3795.9 849.13 2.8082 -6.1279 
102 8595.9 3630.2 5.4799 4640.8 784.32 2.7580 -8.0694 
103 7182.9 6042.8 5.8660 3052.4 971.84 2.7981 -8.8338 
104 4958.2 6673.9 6.5135 6648.8 496.73 3.2720 -7.0745 
105 3082.9 6544.4 6.5400 6601.3 532.24 3.1580 -6.6485 
106 3965.4 3727.4 4.3639 5069.1 582.39 2.9045 -5.4409 
107 9913.3 5460.2 6.6081 5103.4 697.14 3.5093 -7.6354 
108 4795.8 4668.7 5.5864 6681.4 153.12 2.9743 -7.6714 
109 6304.8 4165.6 5.9615 3428.4 456.57 2.4158 -6.9696 
110 4754.5 7780.4 4.7672 4500.4 374.42 3.2487 -4.9795 
111 7603.7 8058.4 5.9161 3516 319.59 3.8641 -8.708 
112 4583.3 6781.7 4.5036 6016.5 923.56 3.6818 -7.1837 
113 4824.3 6329.4 6.3703 6695.2 648.33 3.1176 -7.1191 
114 5680.8 6059.6 6.6830 3694.1 730.7 2.9181 -8.9704 
115 5790.5 5772.9 6.4466 3566.9 858.66 2.4464 -7.5521 
116 6135.5 5134.4 5.8476 6374.1 816.55 3.4484 -7.0902 
117 6639.2 4002.7 4.6930 5443.8 611.58 2.3651 -7.7541 
118 7935.2 6464.4 6.6406 4340.5 999.65 2.6193 -6.1412 
119 6028.1 2417.6 5.9375 5657.6 624.34 3.5238 -8.158 
120 5565.1 5717 6.2693 5849.5 119.59 2.4063 -8.9883 
121 5245.4 5254.6 5.8866 5220.3 514.58 2.8493 -7.2082 
122 4859.2 8446.5 4.5456 3622.5 722.78 2.9518 -6.9556 
123 4938.5 4907.2 5.9711 5776.5 594.79 3.6188 -8.4713 
124 4263.1 6587 5.6385 3357.1 742.58 3.5120 -5.9011 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-27 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
125 6522 4395.8 5.5446 5683.3 289.63 3.5772 -6.5865 
126 6063.9 4229.3 6.8772 4852.6 347.87 2.7207 -7.7741 
127 6655.9 5738.2 6.2526 2360.3 220.63 2.9231 -8.1362 
128 5176.9 5850.1 6.5980 3398.7 279.91 3.5034 -6.0613 
129 7281.7 6652.4 6.2753 3858.1 504.53 3.4137 -6.0073 
130 5363.8 3970 5.9472 3952 545.05 2.9417 -8.2235 
131 6036.8 5837.6 5.9920 5341.6 570.11 3.3768 -8.1668 
132 5744.8 3624.1 5.4277 4555 812.12 2.9728 -7.3502 
133 4693.1 4979.4 6.6769 3229.1 208.85 2.7330 -7.0104 
134 5832.9 3820.4 6.6750 3531.8 957.43 2.8329 -6.6947 
135 6088.4 6504 6.6494 4237.7 700.06 2.9378 -4.3359 
136 4699.9 6627.1 6.7938 6200.4 822.84 2.1494 -5.7531 
137 6505.9 4594.3 5.9507 3809.9 498.66 2.9847 -7.5684 
138 4337.4 4680.7 6.3561 6640.2 192.87 2.4825 -5.3565 
139 3542.1 4758.5 5.8380 3697.6 663.39 3.4455 -7.4479 
140 5904.2 5223.5 5.6201 3766.7 254.42 3.3204 -6.7548 
141 6444.3 5584.3 5.6273 4406.8 939.57 3.5486 -6.9388 
142 4544.6 7527.3 5.7533 3312.6 733.53 2.6092 -6.1196 
143 4605.5 7679.4 6.5916 6234.3 916.07 2.9248 -6.7004 
144 5897.9 5606.4 5.8254 4030.4 620.29 3.6389 -7.371 
145 3214.5 7092.3 5.1766 5281.3 944.22 3.4867 -6.5065 
146 7462.2 7369.8 5.3910 4257.1 435.09 3.3861 -6.4789 
147 5103.6 6925.5 4.3864 3061.2 840.62 3.0916 -7.2809 
148 6768.2 5482.9 6.5755 6759.3 814.05 3.0240 -7.8089 
149 4003.2 7607.4 5.0107 5456.8 440.8 3.6597 -5.0888 
150 8022.6 6688.6 6.1236 5386.6 280.49 3.1915 -5.1417 
151 7385 5990.2 6.5229 4207.8 528.33 2.8321 -8.2405 
152 5476.4 6935.5 6.6920 5163.7 232.73 3.7372 -7.6861 
153 7657.2 3914.4 5.5505 4656 482.77 3.6637 -4.374 
154 6613.2 4824.2 5.4669 3989.2 188.78 2.0249 -8.8522 
155 4174.4 5260.6 6.0568 4797.1 637.17 3.6560 -6.1817 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-28 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
156 4384.3 4742 5.5270 541.24 681.73 3.5181 -7.5344 
157 6401.8 3705 6.4784 4716.4 737.32 3.3493 -8.6836 
158 4075.5 4987.3 6.8507 6061.8 447.66 3.5606 -6.3775 
159 4126.3 9063.8 6.6274 5601.3 954.54 3.5888 -7.4084 
160 3047.5 4545.2 5.9215 2606.8 553.13 2.9480 -8.8816 
161 5317.5 5310.4 5.2054 4788.7 800.32 3.6927 -8.2007 
162 4044.6 4444.7 6.4576 4100.6 981.31 3.3876 -4.2662 
163 5855.3 3867.3 6.9439 3898.7 899.82 3.3137 -7.3117 
164 6833.2 4440.7 4.7797 4979.9 644.04 2.9990 -6.9054 
165 5281.1 7158.9 5.4064 3128.2 628.51 2.4957 -7.598 
166 2947.2 1920 5.2725 4441.5 879.62 3.2435 -5.2248 
167 6202.2 3271 5.9978 5412 579.7 3.1305 -4.7488 
168 4188.8 3107.8 5.7779 6704.9 353.62 3.7884 -4.8991 
169 5070.1 6842.6 5.7652 5478.8 297.66 2.9944 -6.2265 
170 4399.1 5674.1 5.5660 5742.2 891.97 2.4558 -6.8629 
171 5627.1 6268.8 6.6095 3374.3 426.2 3.2084 -6.4087 
172 6748.7 7287.1 6.6205 4159.3 703.3 2.9821 -6.3856 
173 6787.9 7970.3 6.1174 5260.7 268.5 3.5398 -5.1919 
174 6186.4 7869.5 6.6647 3748.4 340.47 3.4275 -6.0434 
175 5228.2 5434.1 5.6690 1418.7 180.84 3.6291 -7.3288 
176 7144.7 5181.5 4.9585 6180 327.57 3.0748 -8.9459 
177 3394.1 7560.4 5.9763 5305.7 843.16 2.9581 -5.8791 
178 7724.3 6023.7 6.5819 3251.3 313.53 3.6042 -7.157 
179 4440.5 6145.1 4.7188 6453.4 977.55 2.6958 -8.7779 
180 6999.5 5277.7 6.1857 5320.7 418.41 3.5930 -6.5596 
181 5711 6168.9 5.9346 4842.2 511.78 3.4179 -8.5473 
182 5402.8 4243.5 5.5720 5188.1 167.1 3.3708 -5.4973 
183 5866.1 2595.4 5.4095 700.81 861.91 3.6422 -8.1846 
184 7249 2974.5 5.4930 3851.2 141.38 3.4392 -6.2812 
185 4647.9 4503.3 6.5013 4093.8 365.62 2.9097 -8.5817 
186 3142.8 6104.4 6.2958 5925.6 562.62 3.2596 -8.6539 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-29 October 2004 
Table B-1. Resampled Stochastic Parameter Values (Continued) 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
187 6954.6 6746.3 6.5090 4764.7 788.4 2.2855 -7.8687 
188 8147.1 8715.9 5.9861 5888.5 667.15 3.3601 -6.6348 
189 5368.6 3526.3 6.9769 4424.9 967.31 3.3299 -6.9914 
190 6359 3945.3 4.8049 6246.1 555.85 2.0420 -7.787 
191 6330 4117 4.9715 5631.4 587.59 3.6088 -8.7485 
192 4483.9 6078.1 6.6680 3896.4 378.1 3.2772 -4.8491 
193 3289.1 5088.1 4.0572 4001.4 600.52 3.9912 -6.895 
194 2548.5 3789.7 6.2105 3110.5 102.37 2.8567 -7.9751 
195 8255.2 5962.6 5.6564 5763.1 631.46 2.7879 -4.7318 
196 6161.5 7222.2 6.9137 6135 576.05 3.1997 -8.4518 
197 4506.1 5051 5.7987 3483.6 486.68 3.6209 -8.5185 
198 5427.5 4202.9 6.4161 1670.4 463.56 2.9615 -8.3199 
199 4889 5419 5.8950 6096.5 147.01 2.9019 -8.8695 
200 5703.4 6314.5 4.2159 5402.6 724.4 2.3891 -6.2063 
Output DTN: SN0407T0502103.013. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-30 October 2004 
Table B-2. Comparison of Simulated Median Transport Times for the Re-Sampled Parameters and the 
Base Case at Three Levels of Cumulative Probability 
5th Percentile 
Transport Time 
(years) 
Median Transport 
Time (years) 
95th Percentile 
Transport Time 
(years) 
Carbon, Technetium, Iodine (Re- 
Sampling) 70 620 15570 
Carbon, Technetium, Iodine (Base-Case) 90 640 13100 
% Difference 22.2 3.1 18.9 
Americium, Thorium, Protactinium (Re- 
Sampling) >100000 >100000 >100000 
Americium, Thorium, Protactinium (Base 
Case) >100000 >100000 >100000 
% Difference 0.0 0.0 0.0 
Cesium (Re-Sampling) >100000 >100000 >100000 
Cesium (Base Case) >100000 >100000 >100000 
% Difference 0.0 0.0 0.0 
Plutonium (Re-Sampling) 16000 >100000 >100000 
Plutonium (Base Case) 25000 >100000 >100000 
% Difference 36.0 0.0 0.0 
Neptunium (Re-Sampling) 2090 16450 >100000 
Neptunium (Base Case) 2300 18200 >100000 
% Difference 9.1 9.6 0.0 
Plutonium and Americium  Irreversible 
Colloids (Re-Sampling) 820 22130 >100000 
Plutonium and Americium  Irreversible 
Colloids (Base Case) 900 18500 >100000 
% Difference 8.9 20. 0.0 
Radium (Re-Sampling) >100000 >100000 >100000 
Radium (Base Case) >100000 >100000 >100000 
% Difference 0.0 0.0 0.0 
Strontium (Re-Sampling) 42100 >100000 >100000 
Strontium (Base Case) 86700 >100000 >100000 
% Difference 51.4 0.0 0.0 
Uranium (Re-Sampling) 1850 23360 >100000 
Uranium (Base Case) 2400 24300 >100000 
% Difference 22.9 3.9 0.0 
Plutonium and Americium  Irreversible 
Colloids  Fast Fraction (Re-Sampling) 50 330 3570 
Plutonium and Americium  Irreversible 
Colloids  Fast Fraction (Base Case) 70 310 2340 
% Difference 29. 6.5 53. 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-31 October 2004 
10 100 1000 10000 100000 
Median Transport Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Cumulative Probability 
Figure B-1. CDF of Median Simulated Transport Time of Nonsorbing Species (Carbon, Technetium, and 
Iodine) for the Base Case (Solid Blue Line) and the Re-Sampled Parameters (Dashed Red 
Line) 

Saturated Zone Flow and Transport Model Abstraction 
MDL-NBS-HS-000021 REV 02 B-32 October 2004 
INTENTIONALLY LEFT BLANK