SZ Flow and Transport Model Abstraction	Rev 00,	ICN 00

MDL-NBS-HS-000021

July 2003

1. PURPOSE 
The purpose of the saturated zone (SZ) flow and transport model abstraction task is to provide 
radionuclide transport simulation results for use in the Total System Performance Assessment 
(TSPA) calculations. This task also includes assessment of uncertainty in parameters related to 
both groundwater flow and radionuclide transport in the models used for this purpose. This 
model report documents the following: 
 The SZ Transport Abstraction Model, which consists of a set of radionuclide 
breakthrough curves at the accessible environment for use in the TSPA simulations of 
radionuclide releases to the biosphere. These radionuclide breakthrough curves contain 
information on the radionuclide transport times through the SZ. 
 The SZ One-Dimensional (1-D) Transport Model, which is incorporated in the TSPA 
model to simulate the transport, decay, and ingrowth of radionuclide decay chains in the 
SZ. 
 The analysis of uncertainty in groundwater flow and radionuclide transport input 
parameters for the SZ Transport Abstraction Model and for the SZ 1-D Transport Model. 
The scope of this model report includes of the technical basis for Features Events and Processes 
(FEPS) and contributes to the characterization of the SZ as a natural barrier, which provides 
evidence related to the capability of the SZ to delay movement of radionuclides through the SZ 
to the accessible environment. The scope of this report also contributes to the technical basis for 
the SZ transport system description used in the License Application (LA), and provides evidence 
for the acceptance criteria as specified in the Yucca Mountain Review Plan (YMRP) (NRC 2003 
[163274]). The scope of the model report is limited to adaptation of an existing model, the SZ 
Site-Scale Transport Model, for the uncertainty analysis as reflected in the SZ radionuclide 
breakthrough curves developed in this model report. 
Use of the SZ Transport Abstraction Model and the SZ 1-D Transport Model is subject to the 
limitations imposed by the assumptions listed in Section 5 of this model report. Limitations in 
knowledge of specific parameter values are addressed in the analysis of parameter uncertainties 
in this report. The radionuclide breakthrough curves generated for the SZ Transport Abstraction 
model are limited to 100,000 years, for present climatic conditions. This limits the time period 
that can be simulated with the TSPA model using these breakthrough curves for the SZ. Because 
the SZ breakthrough curves are scaled for higher groundwater flow rates under future climatic 
conditions, the time period that can be simulated with the TSPA model would be significantly 
less than 100,000 years. If the glacial-transition climate state is applied for most of simulation 
period in the TSPA model, the SZ breakthrough curves would be scaled by a factor of 
approximately 4, limiting the TSPA model simulation time to about 25,000 years. 
Information on the correlation between distribution coefficients (Kds) used in the sampling of 
uncertain parameters for the SZ Transport Abstraction Model and the SZ 1-D Transport Model is 
given in Table 4-3 and Table 6-8. The technical bases for correlations between distribution 
coefficients (or the lack thereof) are documented in BSC 2003 [162419], Section I.10.

MDL-NBS-HS-000021, REV 00 11 July, 2003 
Evaluation of uncertainty in horizontal anisotropy of permeability is summarized in Section 
6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is 
given in BSC 2003 [162415],Section 6.2.6. Implementation of uncertainty in horizontal 
anisotropy in the SZ Transport Abstraction Model and the SZ 1-D Transport Model is discussed 
in Section 6.5.3.1 and Section 6.5.1.2, respectively. 
The impacts of spatial variability of parameters affecting radionuclide transport in the alluvium 
are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, 
Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. The technical bases for 
uncertainty in distribution coefficients are documented in BSC 2003 [162419], Section I. 
Information on the geological uncertainty in the location of the contact between tuff and 
alluvium and the consequent uncertainty in the flow path lengths in the alluvium is presented in 
Section 6.5.2.2. This evaluation of uncertainty includes currently available information from the 
Nye County drilling program. 
The sensitivity analysis of matrix diffusion in the SZ Transport Abstraction Model is presented 
in the assessment of alternative conceptual models in Section 6.4. 
This model report is governed by the Office of Civilian Radioactive Waste Management 
(OCRWM) Technical Work Plan For: Saturated Zone Flow and Transport Modeling and 
Testing, TWP-NBS-MD-000002 (BSC 2003 [163965]), Work Package ASZM04. The work 
documented in this model report was conducted in accordance with the quality assurance 
procedure AP-SIII.10Q, Models [164074]. 
In this report, a unique six-digit numerical identifier (the Document Input Reference System 
[DIRS] number) is placed in the text following the reference callout (e.g., BSC 2001 [155950]). 
The purpose of the DIRS numbers is to assist the reader in locating a specific reference in the 
DIRS database.

MDL-NBS-HS-000021, REV 00 12 July, 2003 
2. QUALITY ASSURANCE 
Development of this model report and the supporting modeling activities is subject to the Yucca 
Mountain Project (YMP) quality assurance (QA) program (BSC 2003 [163965], Section 8, Work 
Package ASZM04). Approved QA procedures identified in the technical work plan (BSC 2003 
[163965], Section 4) have been used to conduct and document the activities described in this 
model report. The technical work plan also identifies the methods used to control the electronic 
management of data (BSC 2003 [163965], Section 8). 
This model report provides values for hydrologic properties of a natural barrier that is important 
to the demonstration of compliance with the post-closure performance objectives prescribed in 
10 CFR 63.113. Therefore, it is classified as a Quality Level  1 with regard to importance to 
waste isolation, as defined in AP-2.22Q Rev 0, ICN 1, Classification Criteria and Maintenance 
of the Monitored Geologic Repository Q-List [163021]. The report contributes to the analysis 
and modeling data used to support performance assessment; the conclusions do not directly 
impact engineered features important to safety, as defined in AP-2.22Q.

MDL-NBS-HS-000021, REV 00 13 July, 2003 
3. USE OF SOFTWARE 
3.1 SOFTWARE TRACKED BY CONFIGURATION MANAGEMENT 
The computer software codes used directly in this model report are listed in Table 3-1. The 
qualification status of the software is indicated in the Software Configuration Management 
(SCM) database. All software was obtained from SCM and is appropriate for the application. 
Qualified codes were used only within the range of validation as required by AP-SI.1Q, Rev. 5, 
ICN 0, Software Management [163085]. 
Table 3-1. Computer Software Used in this Model Report 
Software 
Name and 
Version (V) 
Software 
Tracking 
Number 
(STN) 
Description Computer Type, Platform, 
and Location 
Date 
Baselined 
FEHM V 2.20 
(LANL 2003 
[161725]) 
10086- 
2.20-00 
This code is a finite-element heatand 
mass-transport code that 
simulates nonisothermal, multiphase, 
multicomponent flow and solute 
transport in porous media. 
Sun UltraSPARC - SunOS 
5.7 
Sandia National 
Laboratories 
01/28/2003 
GoldSim 
V 7.50.100 
(BSC 2003 
[161572]) 
10344- 
7.50.100- 
00 
This code is the modeling software 
used in the TSPA. Probabilistic 
simulations are represented 
graphically in GoldSim. 
Dell OptiPlex GX260 - 
Windows 2000 Professional 
5.0.2195 
Sandia National 
Laboratories 
01/07/2003 
SZ_Pre V 2.0 
(SNL 2003 
[163281]) 
10914- 
2.0-00 
This software is an automated 
method for preparing the FEHM input 
files for the SZ site-scale flow and 
transport model for use in TSPA 
analyses. 
Sun UltraSPARC - SunOS 
5.7 
Sandia National 
Laboratories 
04/28/2003 
SZ_Post V 3.0 
(SNL 2003 
[163571]) 
10915- 
3.0-00 
This software is used to translate the 
output files from the SZ site-scale 
model into the format used by the 
SZ_Convolute software code. 
SZ_Post reads the output files from 
the FEHM software code and writes 
the breakthrough curve data for 
radionuclide transport in the SZ. 
Sun UltraSPARC - SunOS 
5.7, Solaris 2.7 
Sandia National 
Laboratories 
05/22/2003 
CORPSCON 
V 5.11.08 
(LANL 2001 
[155082]) 
10547- 
5.11.08- 
00 
This software is used to convert 
coordinate data to the Universal 
Transverse Mercator (UTM) 
coordinate system. 
IBM Thinkpad 770Z - 
Windows NT 4.0 
Sandia National 
Laboratories 
08/27/2001 
SZ_Convolute 
V.2.2 
(SNL 2003 
[163344]) 
10207- 
2.2-00 
This software is used to calculate 
saturated-zone response curves 
based on unsaturated-zone 
radionuclide source terms, generic 
saturated-zone responses, and 
climate scenarios for the YMP. 
Dell OptiPlex GX260 - 
Windows 2000 Professional 
5.0.2195 
Sandia National 
Laboratories 
01/13/2003 
Note: The SZ_Convolute v. 2.2 software code (STN: 10207-2.2-00, SNL 2003 [163344]) was used in the 
modeling and analyses in this report. SZ_Convolute v. 3.0 (STN: 10207-3.0-00, SNL 2003 [164180]) (or 
later version) will be used for implementation of the SZ Transport Abstraction Model in TSPA-LA.

MDL-NBS-HS-000021, REV 00 14 July, 2003 
3.2 EXEMPT SOFTWARE 
The commercially available software cited below is appropriate for use in this application. The 
results were spot-checked by hand to ensure the results were correct. The computer used was a 
Dell OptiPlex GX1 with Pentium II processor, running Microsoft Windows 2000 5.0.2195. The 
range of validation for Excel, Surfer, and Grapher is the set of real numbers. 
Commercially available software: 
 Excel 2000: Used for simple spreadsheet calculations in support of plotting and 
visualization. The formulas, listing of inputs, listing of outputs and other required 
information can be found in the following spreadsheets: Eff_MtrxDif_11.xls, 
bulkd_matr_eff_La.xls, and geonames.xls. These spreadsheets can be found in DTN: 
SN0306T0502103.006. 
 Surfer 8.0: Used for plotting and visualization. 
 Grapher 4.0: Used for plotting graphs. 
 Igor 4.07: Used for plotting graphs.

MDL-NBS-HS-000021, REV 00 15 July, 2003 
4. INPUTS 
4.1 DATA, PARAMETERS, AND OTHER MODEL INPUTS 
All data, parameters, and other model inputs documented in Section 4.1 are used as direct inputs 
to the analyses of parameter uncertainty and/or the SZ Transport Abstraction Model and SZ 1-D 
Transport Model. 
4.1.1 Data and Other Model Inputs 
The data providing input for the development of parameters used in the models documented in 
this report are identified in Table 4-1. 
These input data are considered appropriate for the development of uncertain parameters for the 
SZ Transport Abstraction Model and the SZ 1-D Transport Model. The data that are used as 
direct input to the models developed in this report are the best relevant qualified data because 
they are taken from the Yucca Mountain site and region. Where available and appropriate, nonqualified 
data are used to corroborate those data that are used as direct input (see Section 6.5.2). 
Uncertainty associated with the model, including development of parameter values and their 
implementation in the SZ Transport Abstraction Model and the SZ 1-D Transport Model, is 
discussed in Section 6.5.1 and 6.5.2. Parameter uncertainties are addressed by providing ranges, 
probability distributions and bounding assumptions as appropriate for each parameter. 
Table 4-1. Input Data 
Data Name Originating Report DTN 
Matrix Porosity in the Volcanic Units 
(HFM Units 15-8) 
MDL-NBS-GS-000004 (HFM Units 
15-13, 10-8) (BSC 2002 [159530]) 
OFR 94-469 (Buesch et al. 1996 
[100106]); Flint 1998 [100033]; OFR 
94-460 (Moyer and Geslin 1995 
[101269]); (HFM Units 12 and 11) 
TDR-NBS-GS-000020, BSC 2001 
[163479] (HFM Units 12 and 11) 
SN0004T0501399.003 [155045] 
(HFM Units 15-13, 10-8) 
MO0109HYMXPROP.001 [155989] 
(HFM Units 12 and 11) 
MO0010CPORGLOG.002 [155229] 
(HFM Units 12 and 11 ) 
Effective Porosity Alluvium Bedinger, et al. 1989 [129676] (HFM 
Units 19 and 7) 
EDCON 2000 [154704] (HFM Units 
19 and 7) 
Burbey and Wheatcraft [129679] 
1986 (HFM Units 19 and 7) 
DOE 1997 [103021], Table 8-2, p. 8- 
6, Table 8-1 p. 8-5 (HFM Units 19 
and 7) 
MO0105HCONEPOR.000 [155044] 
(HFM Units 19 and 7) 
MO0105GPLOG19D.000 [163480] 
(HFM Units 19 and 7) 
Burbey and Wheatcraft is considered 
Technical Information, no DTN. 
(HFM Units 19 and 7) 
DOE 1997 is considered Technical 
Information, no DTN. (HFM Units 19 
and 7)

MDL-NBS-HS-000021, REV 00 16 July, 2003 
Data Name Originating Report DTN 
Effective Porosity in the Other Units Bedinger, et al. 1989 [129676] 
(HFM Units, 18, 17, 16, 6-2, 1) 
MO0105HCONEPOR.000 [155044] 
(HFM Units, 18, 17, 16, 6-2, 1) 
Bulk Density in the Volcanic Units MDL-NBS-GS-000004 (HFM Units 
15-13, 10-8) (BSC 2002 [159530]) 
OFR 94-469 (Buesch et al. 1996 
[100106]); Flint 1998 [100033]; OFR 
94-460 (Moyer and Geslin 1995 
[101269]), (HFM Units 12 ,11 and 9) 
TDR-NBS-GS-000020, BSC 2001 
[163479] (HFM Units 17, 12, 11, 6-2) 
SN0004T0501399.002 [155046] 
(HFM Units 15-13, 10, 8) 
SN0004T0501399.003 [155045] 
(HFM Units 15-13, 10-8) 
MO0109HYMXPROP.001 [155989] 
(HFM Units 12 11, and 9) 
MO0010CPORGLOG.002 [155229] 
(HFM Units 17, 12 and 11, 6-2) 
Effective Diffusion Coefficient BSC 2001 [163566] (HFM Units 8- 
15) 
MO0109HYMXPROP.001 [155989] 
(HFM Units 8-15) 
Bulk Density - Alluvium EDCON 2000 [154704] (HFM Units 
19 and 7) 
MO0105GPLOG19D.000 [163480] 
(HFM Units 19 and 7) 
Flowing Interval Porosity in the 
Volcanic Units 
BSC 2003 [161773], p. 41 and 64 
(HFM Units 8-15) 
CRWMS M&O 1997 [100328], p. 28 
(HFM Units 8-15) 
DOE 1997 [103021], p. 5-14 (HFM 
Units 8-15) 
Wilson et al. 1994 [100191], Volume 
1, Chapter 7, Table 7-19, p. 7-30 
(HFM Units 8-15) 
Product Output, information not in 
DTN (HFM Units 8-15) 
Technical Information no DTN (HFM 
Units 8-15) 
Technical Information no DTN (HFM 
Units 8-15) 
Technical Information no DTN (HFM 
Units 8-15) 
Lithostratigraphy in Wells EWDP- 
10SA and EWDP-22SA 
N/A GS030108314211.001 [163483] 
Coordinates of Well Locations USGS 2001 [157611] GS010908312332.002 [163555] 
Uncertainty in Groundwater Specific 
Discharge 
CRWMS M&O 1998 [100353] MO0003SZFWTEEP.000 [148744] 
Uncertainty in Groundwater Specific 
Discharge at the Alluvial Tracer 
Complex 
BSC 2003 [162415] LA0303PR831231.002 [163561] 
UZ Site-Scale Model Flow Field  
Present Climate 
CRWMS M&O 2000 [122797] LB990801233129.004 [117129] 
UZ Site-Scale Model Flow Field  
Glacial-Transition Climate 
CRWMS M&O 2000 [122797] LB990801233129.009 [118717] 
UZ Site-Scale Model Flow Field  
Monsoonal Climate 
CRWMS M&O 2000 [122797] LB990801233129.015 [118730] 
Note: The column containing the originating report is provided for reference only. The direct source of 
the data used in this AMR is listed in the DTN column. The HFM Unit numbers given refer to the unit 
definitions in Table 6-9.

MDL-NBS-HS-000021, REV 00 17 July, 2003 
Other model input information is listed in Table 4-2. 
Table 4-2. Other Model/Analysis Inputs 
Input Name Input Description DTN / IED 
Site-Scale 
Saturated Zone 
Transport Model 
The SZ site-scale model that forms the basis of the SZ 
Transport Abstraction Model. 
LA0306SK831231.001 [164362] 
Matrix Diffusion 
Type Curves 
The analytical solution type curves for matrix diffusion in 
fractured media. These type curves are used in the particle 
tracking algorithm of the FEHM software to simulate 
radionuclide transport in fractured porous media. 
LA0302RP831228.001 [163557] 
Repository 
Design 
The coordinates of the outline of the repository design are 
used in defining the SZ source regions at the water table 
below the repository. 
800-IED-EBS0-00401-000-00C, 
BSC 2003 [162289] 
800-IED-EBS0-00402-000-00B, 
BSC 2003 [161727] 
Boundary of 
Accessible 
Environment 
Latitude of the accessible environment, as defined by 
regulation 
10 CFR 63.302 [156605], 
regulatory input, technical 
information, no DTN 
4.1.2 Parameters and Parameter Uncertainty 
The parameters and parameter uncertainty from external sources used directly in the modeling 
documented in this report are shown in Table 4-3. 
The input parameters are considered appropriate as direct input to the SZ Transport Abstraction 
Model and the SZ 1-D Transport Model. The data used in this report are appropriate for this 
study because they represent various parameter properties of the SZ at Yucca Mountain.

MDL-NBS-HS-000021, REV 00 18 July, 2003 
Table 4-3. Input Parameters 
Parameter 
Name 
Parameter 
Source 
DTN Value(s) Units Distribution 
KDNPVO 
(neptunium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 0.0 
0.05 1.0 
0.90 1.6 
1.0 6.0 
ml/g Distribution 
KDNPAL 
(neptunium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 1.8 
0.05 4.0 
0.95 8.7 
1.0 13.0 
ml/g Distribution 
KDSRVO 
(strontium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 20. 
Maximum 400. 
ml/g Distribution 
KDSRAL 
(strontium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 20. 
Maximum 400. 
ml/g Distribution 
KDUVO 
(uranium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 0.0 
0.05 5.4 
0.95 6.9 
1.0 20.0 
ml/g Distribution 
KDUAL 
(uranium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 1.7 
0.05 2.9 
0.95 6.3 
1.0 8.9 
ml/g Distribution 
KDRAVO 
(radium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 100. 
Maximum 1000. 
ml/g Distribution 
KDRAAL 
(radium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 100. 
Maximum 1000. 
ml/g Distribution

MDL-NBS-HS-000021, REV 00 19 July, 2003 
Parameter 
Name 
Parameter 
Source 
DTN Value(s) Units Distribution 
KD_Pu_Vo 
(plutonium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 10. 
0.25 75. 
0.95 100. 
1.0 300. 
ml/g Distribution 
KD_Pu_Al 
(plutonium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Beta: 
Mean 100. 
Standard Deviation 15. 
Minimum 50. 
Maximum 300. 
ml/g Distribution 
KD_Am_Vo 
(americium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
ml/g Distribution 
KD_Am_Al 
(americium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 1500. 
Minimum 1000. 
Maximum 10000. 
ml/g Distribution 
KD_Cs_Vo 
(cesium 
sorption 
coefficient in 
volcanic units) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 100. 
0.05 3700. 
1.0 7500. 
ml/g Distribution 
KD_Cs_Al 
(cesium 
sorption 
coefficient in 
alluvium) 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 728. 
Standard Deviation 464. 
Minimum 100. 
Maximum 1000. 
ml/g Distribution 
FISVO 
(flowing 
interval 
spacing in the 
volcanic units) 
BSC 2001 
[156965] 
SN9907T0571599.001 
[122261] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.087 
0.05 0.588 
0.25 1.00 
0.50 1.29 
0.75 1.58 
0.95 1.90 
1.0 2.62 
m Distribution

MDL-NBS-HS-000021, REV 00 20 July, 2003 
Parameter 
Name 
Parameter 
Source 
DTN Value(s) Units Distribution 
CORAL 
(colloid 
retardation 
factor in the 
alluvium) 
BSC 2003 
[163932] 
LA0303HV831352.004 
[163559] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.903 
0.331 0.904 
0.50 1.531 
1.0 3.715 
NA Distribution 
CORVO 
(colloid 
retardation 
factor in the 
volcanic units) 
BSC 2003 
[163932] 
LA0303HV831352.002 
[163558] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.778 
0.15 0.779 
0.25 1.010 
0.50 1.415 
0.80 1.778 
1.0 2.903 
NA Distribution 
HAVO 
(ratio of 
horizontal 
anisotropy in 
permeability) 
BSC 2003 
[162415] 
SN0302T0502203.001 
[163563] 
CDF: 
Probability Value 
0.0 0.05 
0.10 1.0 
0.60 5. 
1.0 20. 
NA Distribution 
LDISP 
(longitudinal 
dispersivity) 
CRWMS 
M&O 1998 
[100353] 
MO0003SZFWTEEP.000 
* [148744] 
Truncated Normal: (Logtransformed) 
Mean 2.0 
Standard Deviation 0.75 
m Distribution 
Kd_Pu_Col 
(plutonium 
sorption 
coefficient 
onto colloids) 
BSC 2003 
[161620] 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e3 
0.04 5.e3 
0.12 1.e4 
0.37 5.e4 
0.57 1.e5 
0.92 5.e5 
1.0 1.e6 
ml/g Distribution 
Kd_Am_Col 
(americium 
sorption 
coefficient 
onto colloids) 
BSC 2003 
[161620] 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e4 
0.07 5.e4 
0.17 1.e5 
0.40 5.e5 
0.60 1.e6 
0.92 5.e6 
1.0 1.e7 
ml/g Distribution

MDL-NBS-HS-000021, REV 00 21 July, 2003 
Parameter 
Name 
Parameter 
Source 
DTN Value(s) Units Distribution 
Kd_Cs_Col 
(cesium 
sorption 
coefficient 
onto colloids) 
BSC 2003 
[161620] 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e2 
0.2 5.e2 
0.45 1.e3 
0.95 5.e3 
1.0 1.e4 
ml/g Distribution 
Conc_Col 
(groundwater 
concentration 
of colloids) 
BSC 2003 
[161620] 
SN0306T0504103.005 
[164132] 
CDF: (Log-transformed) 
Probability Value 
0.0 -9.0 
0.50 -7.0 
0.75 -6.0 
0.90 -5.0 
0.98 -4.3 
1.0 -3.6 
g/ml Distribution 
Correlation 
coefficient for 
U Kd in 
volcanic units 
and alluvium 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
0.75 ml/g Single Value 
Correlation 
coefficient for 
Np Kd in 
volcanic units 
and alluvium 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
0.75 ml/g Single Value 
Correlation 
coefficient for 
Pu Kd in 
volcanic units 
and alluvium 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
0.50 ml/g Single Value 
Correlation 
coefficient for 
U Kd and Np 
Kd 
BSC 2003 
[162419] 
LA0302AM831341.001 
[163556] 
0.50 ml/g Single Value 
NOTE: * MO0003SZFWTEEP.000 [148744] contains qualified data from an Expert Elicitation that was 
determined to comply with Expert Elicitation Procedure AP-AC.1Q [138711], which is consistent with the 
Branch Technical Position on Expert Elicitation NUREG-1563 (Kotra et al. 1996 [100909]).

MDL-NBS-HS-000021, REV 00 22 July, 2003 
4.2 CRITERIA 
The general requirements to be satisfied by the TSPA are stated in 10 CFR 63.114 (10 CFR 63 
[156605]). Technical requirements to be satisfied by the TSPA are identified in the Yucca 
Mountain Project Requirements Document (Canori and Leitner 2003 [161770], Table B-9). The 
acceptance criteria that will be used by the Nuclear Regulatory Commission (NRC) to determine 
whether the technical requirements have been met are identified in the Yucca Mountain Review 
Plan NUREG-1804, Draft Final Revision 2 (YMRP; NRC 2003 [163274]). The pertinent 
requirements and criteria for this report are summarized in Table 4-2. 
Table 4-4. Project Requirements for This Model Report 
Requirement Numbera Requirement Titlea 10 CFR 63 Link 
[156605] 
YMRP Acceptance 
Criteriab 
PRD-002/T-014 Performance Objectives for the Geologic 
Repository After Permanent Closure 
10 CFR 63.113 2.2.1.1.3, criteria 1 
to 3 
PRD -002/T-015 Requirements for Performance Assessment 10 CFR 63.114 2.2.1.3.8.3, criteria 1 
to 4; 
2.2.1.3.9.3, criteria 1 
to 5 
PRD -002/T-016 Requirements for Multiple Barriers 10 CFR 63.115 2.2.1.1.3, criteria 1 
to 3 
NOTE: a from Canori and Leitner 2003 [161770]. 
b from NRC 2003 [163274] 
The acceptance criteria identified in Sections 2.2.1.1.3, 2.2.1.3.8.3, and 2.2.1.3.9.3 of the YMRP 
(NRC 2003 [163274]) are given below, followed by a short description of their applicability to 
this model report. Criteria item numbers not shown are considered to not apply to this model. 
Section 2.2.1.1.3 Acceptance Criteria [for 2.2.1.1 System Description and Demonstration of 
Multiple Barriers], which are based on meeting the requirements at 10 CFR 63.113(a) and 
63.115(a)(c): 
 Acceptance Criterion 1, Identification of Barriers is Adequate 
Barriers relied on to achieve compliance with 10 CFR 63.113(b), as demonstrated in the 
total system performance assessment, are adequately identified, and are clearly linked to 
their capability. The barriers identified include at least one from the engineered system 
and one from the natural system. 
This model report describes the SZ radionuclide transport simulation results for use in the 
TSPA calculation. This includes the 1-D model description, which is incorporated in the 
TSPA calculations to simulate transport, decay, and ingrowth of radionuclide decay 
chains in the SZ. Also discussed in Section 6.5.2 is the analysis of uncertainty in input 
parameters for the SZ Transport Abstraction Model and for the SZ 1-D Transport Model.

MDL-NBS-HS-000021, REV 00 23 July, 2003 
 Acceptance Criterion 2, Description of Barrier Capability to Isolate Waste is Acceptable 
The capability of the identified barriers to prevent or substantially reduce the rate of 
movement of water or radionuclides from the Yucca Mountain Repository is adequately 
identified and described: 
1. The information on the time period over which the SZ barrier performs its intended 
function, including any changes during the compliance period, is provided in Section 
6.7. 
2. The uncertainty associated with barrier capabilities is adequately described in Section 
6.7. 
 Acceptance Criterion 3, Technical Basis for Barrier Capability is Adequately Presented 
The technical bases are consistent with the technical basis for the performance 
assessment, although not explicitly addressed in this report it is addressed in the TSPA. 
The technical basis for assertions of barrier capability is commensurate with the 
importance of each barriers capability and the associated uncertainties. 
Section 2.2.1.3.8.3 Acceptance Criteria (for 2.2.1.3.8 Flow Paths in the Saturated Zone), which 
are based on meeting the requirements of 10 CFR 63.114(a)(c) and (e)(g), relating to flow 
paths in the saturated zone model abstraction: 
 Acceptance Criterion 1, System Description and Model Integration are Adequate: 
2. The description of the aspects of hydrology, geology, geochemistry, design features, 
physical phenomena, and couplings that may affect flow paths in the saturated zone is 
adequate. Conditions and assumptions in the abstraction of flow paths in the saturated 
zone are readily identified and consistent with the body of data presented in the 
description (see Section 6.3). 
3. The abstraction of flow paths in the saturated zone uses assumptions, technical bases, 
data, and models that are appropriate and consistent with other related DOE 
abstractions. For example, the assumptions used for flow paths in the saturated zone 
are consistent with the total system performance assessment abstraction of 
representative volume (Section 2.2.1.3.12 of NRC 2003 [163274]). The descriptions 
and technical bases provide transparent and traceable support for the abstraction of 
flow paths in the saturated zone (see Section 6.3). 
5. Sufficient data and technical bases to assess the degree to which features, events, and 
processes have been included in this abstraction are provided (see Section 6.2). 
7. Long-term climate change, based on known patterns of climatic cycles during the 
Quaternary period, particularly the last 500,000 years, and other paleoclimate data, 
are adequately evaluated (see the introductory text in Section 6.5). 
10. Guidance in NUREG-1297 (Altman et al. 1988 [103597]) and NUREG-1298 (Altman 
et al. 1988 [103750]) or other acceptable approaches for peer review and data 
qualification is followed (see Section 6.5.2.1).

MDL-NBS-HS-000021, REV 00 24 July, 2003 
 Acceptance Criterion 2, Data are Sufficient for Model Justification: 
1. Geological, hydrological, and geochemical values used in the safety case to evaluate 
flow paths in the saturated zone are adequately justified. Adequate descriptions of 
how the data were used, interpreted, and appropriately synthesized into the 
parameters are provided, as described in Section 6.5.2. 
3. Data on the geology, hydrology, and geochemistry of the saturated zone used in the 
total system performance assessment abstraction are based on appropriate techniques. 
These techniques may include laboratory experiments, site-specific field 
measurements, natural analog research, and process-level modeling studies (see 
Section 6.5.2). 
 Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
1. Models use parameter values, assumed ranges, probability distributions, and/or 
bounding assumptions that are technically defensible, and reasonably account for 
uncertainties and variabilities (see Section 6.5.2). 
2. Uncertainty is appropriately incorporated in model abstractions of hydrologic effects 
of climate change, based on a reasonably complete search of paleoclimate data (see 
the introduction to Section 6.5). 
3. Uncertainty is adequately represented in parameter development for conceptual 
models, process-level models, and alternative conceptual models considered in 
developing the abstraction of flow paths in the saturated zone (see Section 6.5.2). 
4. Where sufficient data do not exist, the definition of parameter values and conceptual 
models is based on appropriate use of expert elicitation, conducted in accordance with 
NUREG-1563 (Kotra et al. 1996 [100909]) (see Section 6.5.2.1). 
 Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
1. Alternative modeling approaches of features, events, and processes are considered 
and are consistent with available data and current scientific understanding, and the 
results and limitations are appropriately considered in the abstraction (see Section 
6.2). 
2. Conceptual model uncertainties are adequately defined and documented, and effects 
on conclusions regarding performance are properly assessed (see Section 6.4). 
4. Appropriate alternative modeling approaches are consistent with available data and 
current scientific knowledge and appropriately consider their results and limitations, 
using tests and analyses that are sensitive to the processes modeled, as described in 
Section 6.4. 
 Acceptance Criterion 5, Model Abstraction Output Is Supported by Objective 
Comparisons:

MDL-NBS-HS-000021, REV 00 25 July, 2003 
1. The models implemented in this total system performance assessment abstraction 
provide results consistent with output from detailed process-level models and/or 
empirical observations (laboratory and field testing and/or natural analogs) (see 
Section 7). 
2. Outputs of flow paths in the saturated zone abstractions reasonably produce or bound 
the results of corresponding process-level models, empirical observations, or both 
(see Sections 6.6 and 7). 
3. Well-documented procedures that have been accepted by the scientific community to 
construct and test the mathematical and numerical models are used to simulate flow 
paths in the saturated zone (Section 7). 
Section 2.2.1.3.9.3 Acceptance Criteria [for 2.2.1.3.9 Radionuclide Transport in the Saturated 
Zone], which are based on meeting the requirements of 10 CFR 63.114(a)(c) and (e)(g), 
relating to the radionuclide transport in the saturated zone model abstraction: 
 Acceptance Criterion 1, System Description and Model Integration are Adequate: 
2. The description of the aspects of hydrology, geology, geochemistry, design features, 
physical phenomena, and couplings that may affect radionuclide transport in the 
saturated zone is adequate, as described in Section 6.3. 
3. The abstraction of radionuclide transport in the saturated zone uses assumptions, 
technical bases, data, and models that are appropriate and consistent with other 
related DOE abstractions (see Section 6.5). 
4. Boundary and initial conditions used in the abstraction of radionuclide transport in the 
saturated zone are propagated throughout its abstraction approaches (see Section 6.3). 
5. Sufficient data and technical bases for the inclusion of features, events, and processes 
related to radionuclide transport in the saturated zone in the total system performance 
assessment abstraction are provided, as described in Section 6.2. 
6. Guidance in NUREG-1297 (Altman et al. 1988 [103597]) and NUREG-1298 (Altman 
et al. 1988 [103750]) or other acceptable approaches for peer review and data 
qualification is followed (see Section 6.5.2.9). 
 Acceptance Criterion 2, Data are Sufficient for Model Justification: 
1. Geological, hydrological, and geochemical values used in the safety case are 
adequately justified (e.g., flow path lengths, sorption coefficients, retardation factors, 
colloid concentrations, etc.). Adequate descriptions of how the data were used, 
interpreted, and appropriately synthesized into the parameters are provided (see 
Section 6.5.2). 
 Acceptance Criterion 3, Data Uncertainty is Characterized and Propagated Through the 
Model Abstraction:

MDL-NBS-HS-000021, REV 00 26 July, 2003 
1. Models use parameter values, assumed ranges, probability distributions, and/or 
bounding assumptions that are technically defensible, and reasonably account for 
uncertainties and variabilities (see Section 6.5.2). 
4. Parameter values for processes, such as matrix diffusion, dispersion, and groundwater 
mixing, are based on reasonable assumptions about climate, aquifer properties, and 
groundwater volumetric fluxes (Section 2.2.1.3.8 of NRC 2003 [163274]) (see Section 
6.5.2). 
5. Uncertainty is adequately represented in parameter development for conceptual 
models, process-level models, and alternative conceptual models considered in 
developing the abstraction of radionuclide transport in the saturated zone (see 
Sections 6.3 and 6.5.2). 
6. Where sufficient data do not exist, the definition of parameter values and conceptual 
models is based on appropriate use of expert elicitation, conducted in accordance with 
NUREG-1563 (Kotra et al. 1996 [100909]) (see Section 6.5.2.9). 
 Acceptance Criterion 4, Model Uncertainty is Characterized and Propagated Through the 
Model Abstraction: 
1. Alternative modeling approaches of features, events, and processes are considered 
and are consistent with available data and current scientific understanding, and the 
results and limitations are appropriately considered in the abstraction (see Section 
6.2). 
2. Conceptual model uncertainties are adequately defined and documented, and effects 
on conclusions regarding performance are properly assessed (see Section 6.4). 
4. Appropriate alternative modeling approaches are consistent with available data and 
current scientific knowledge and appropriately consider their results and limitations, 
using tests and analyses that are sensitive to the processes modeled (see Section 6.4). 
 Acceptance Criterion 5, Model Abstraction Output is Supported by Objective 
Comparisons: 
2. Outputs of radionuclide transport in the saturated zone abstractions reasonably 
produce or bound the results of corresponding process-level models, empirical 
observations, or both (see Section 7). 
3. Well-documented procedures that have been accepted by the scientific community to 
construct and test the mathematical and numerical models are used to simulate 
radionuclide transport through the saturated zone (see Sections 6.5 and 7). 
4. Sensitivity analyses or bounding analyses are provided, to support the total system 
performance assessment abstraction of radionuclide transport in the saturated zone, 
that cover ranges consistent with site data, field or laboratory experiments and tests, 
and natural analog research (see Section 7).

MDL-NBS-HS-000021, REV 00 27 July, 2003 
4.3 CODES AND STANDARDS 
No specific formally established codes or standards have been identified as applying to this 
modeling activity. This activity does not directly support License Application (LA) design.

MDL-NBS-HS-000021, REV 00 28 July, 2003 
5. ASSUMPTIONS 
There are several types of assumptions related to model development. The assumptions listed in 
this section of the AMR are restricted to those that meet the definition given in the quality 
assurance procedure AP-SIII.10Q, Models [164074], Section 3.2. This definition states that an 
assumption is a statement or proposition that is taken to be true or representative in the absence 
of direct confirming data or evidence. There are additional technical modeling bases 
(assumptions) related to the modeling framework that are documented in Section 6 of this AMR 
(primarily in Section 6.3). 
Underlying assumptions are embodied in the transport parameters used in the SZ Transport 
Abstraction Model and in the SZ 1-D Transport Model for decay chains. Complete descriptions 
of these underlying assumptions and associated justification are presented in the revision to the 
Site-Scale Saturated Zone Transport model report (BSC 2003 [162419], Section 5), the 
Saturated Zone In-Situ Testing scientific analysis report (BSC 2003 [162415], Section 5), and in 
the Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [163932], Section 5). 
1. It is assumed that the equilibrium, linear sorption model applies to sorption of radionuclides 
in the matrix of the volcanic units and in the alluvium of the valley-fill units. This 
assumption is carried forward from the Site-Scale Saturated Zone Transport model report 
(BSC 2003 [162419], Section 6.3). The Kd model of equilibrium, linear sorption is an 
applicable approximation of sorptive behavior in both laboratory experiments and at the field 
scale. In addition, the ranges in uncertainty distributions for sorption coefficients of 
radionuclides encompass the transport results that would be obtained using other non-linear 
models of sorption behavior. The contrasts in slope of the isotherm for moderately nonlinear 
sorptive behavior fall within the range of linear isotherms considered in the uncertainty 
distributions for sorption coefficients used in the modeling. This assumption is used in 
Sections 6.3.1, 6.5.1, and 6.5.2.8. This assumption needs no further confirmation, given that 
a wide range of non-linear sorptive behavior is encompassed by the uncertainty distributions 
in sorption coefficients used in the SZ Transport Abstraction Model and in the SZ 1-D 
Transport Model. 
2. For the transport of radionuclides irreversibly attached to colloids in the SZ, it is assumed 
that radionuclides will not desorb from colloids. This assumption is carried forward from the 
Saturated Zone Colloid Transport scientific analysis report (BSC 2003 [163932], Section 
6.3) and is consistent with the mineralogic characteristics of colloids from the degradation of 
the glass waste form. This assumption is also conservative with regard to repository 
performance due to the comparatively high mobility of colloids in the SZ relative to the 
sorptive characteristics of the radionuclides (Pu and Am) that are subject to colloid-facilitated 
transport. This assumption is used in Sections 6.3.1, 6.3.2, 6.5.1, and 6.5.2.11. This 
assumption needs no further confirmation, given that it is a bounding assumption that 
maximizes the rate of radionuclide migration in the SZ. 
3. Colloids with irreversibly attached radionuclides are assumed to be subject to attachment and 
detachment to mineral grains in the aquifer, but not to be subject to permanent filtration from 
the groundwater of the SZ. This assumption is carried forward from the Saturated Zone 
Colloid Transport scientific analysis report (BSC 2003 [163932], Section 6.3). The

MDL-NBS-HS-000021, REV 00 29 July, 2003 
kinetically controlled attachment and detachment of colloids in the aquifer is consistent with 
tracer testing in the SZ using microspheres. The permanent filtration of colloids in the SZ 
has not been demonstrated by field testing, although this process may occur. The alternative 
to this assumption, in which permanent filtration were simulated to occur, would lead to 
significant attenuation of the migration of radionuclides irreversibly attached to colloids. 
This assumption is used in Sections 6.3.1, 6.3.2, 6.5.1, and 6.5.2.11. This assumption needs 
no further confirmation, given that it is a bounding assumption that maximizes the migration 
of radionuclides in the SZ. 
4. The assumption is made that the average concentration of radionuclides in the groundwater 
supply of the hypothetical community is an appropriate estimate of radionuclide 
concentration for the calculation of radiological dose. Realistically, the concentrations of 
radionuclides encountered by wells in the hypothetical community would vary from location 
to location within the contaminant plume in the SZ. However, radionuclide transfer 
processes within the biosphere (e.g., redistribution of agricultural products, communal water 
supplies, etc.) would tend to average the overall dose received by the population of the 
community. This assumption is used in Section 6.3.3. This assumption needs no further 
confirmation, given that there is a regulatory basis for this approach to calculating average 
concentrations of radionuclides and radiological dose at 10 CFR 63.332 (10 CFR 63 
[156605]). 
5. The assumption is made that the horizontal anisotropy in permeability applies to the fractured 
and faulted volcanic units of the SZ system along the groundwater flow path from the 
repository to the south and east of Yucca Mountain. This assumption is carried forward from 
the Saturated Zone In-Situ Testing scientific analysis report (BSC 2003 [162415], Section 
6.2.6). The inferred flowpath from beneath the repository extends to the south and east. This 
is the area in which pumping tests were conducted at the C-holes well complex (BSC 2003 
[162415]), from which horizontal anisotropy was inferred. Given the conceptual basis for 
the anisotropy model, it is appropriate to apply anisotropy only to those hydrogeologic units 
that are dominated by groundwater flow in fractures. This assumption is used in Section 
6.5.2.10. This assumption needs no further confirmation, given the wide range of uncertainty 
in horizontal anisotropy used in the SZ Transport Abstraction Model. 
6. It is assumed that the change in groundwater flow in the SZ from one climatic state to 
another occurs rapidly and is approximated by an instantaneous shift from one steady-state 
flow condition to another steady-state flow condition. In reality, even an extremely rapid 
shift in climatic conditions would result in a transient response of the SZ flow system 
because of changes in groundwater storage associated with water table rise or fall and 
because of the response time in the UZ flow system. The assumption of instantaneous shifts 
to new steady-state conditions would tend to overestimate the rate of radionuclide transport 
in the TSPA calculations. The progression of climate states in the 10,000 years following 
repository closure is anticipated to be from drier to wetter climatic conditions and thus from 
slower to more rapid groundwater flow in the SZ. By assuming an instantaneous shift to 
higher groundwater flux in the SZ the simulations tend to overestimate the radionuclide 
transport velocities during the period of transition from drier conditions to wetter conditions. 
This assumption is used in Section 6.5. This assumption needs no further confirmation,

MDL-NBS-HS-000021, REV 00 30 July, 2003 
given that this simplified approach tends to underestimate the transport times for 
radionuclides in the SZ and is thus pessimistic with regard to repository performance. 
7. Groundwater flow pathways in the SZ from beneath the repository to the accessible 
environment are assumed not to be significantly altered for wetter climatic states. Scaling of 
present-day groundwater flux and radionuclide mass breakthrough curves by a 
proportionality factor implies that only the groundwater velocities are changed in the SZ 
system in response to climate change. This assumption is supported by the observation that 
the shape of the simulated potentiometric surface downgradient from Yucca Mountain 
remains basically the same under glacial-transition climatic conditions in simulations using 
the SZ regional-scale flow model (DAgnese et al. 1999 [120425], p. 30). Water table rise 
directly beneath the repository under wetter climatic conditions would tend to place volcanic 
units higher in the stratigraphic sequence at or just below the water table. These higher 
volcanic units (Prow Pass Tuff and Calico Hills Formation) have lower values of 
permeability than the underlying Bullfrog Tuff. This approximation of climate change with 
unaltered SZ flow paths is shown to underestimate radionuclide transport times in sensitivity 
studies documented in BSC 2003 [162419], Attachment V. This assumption is used in 
Section 6.5. This assumption needs no further confirmation, given that this simplified 
approach tends to underestimate the transport times for radionuclides in the SZ.

MDL-NBS-HS-000021, REV 00 31 July, 2003 
6. MODELS DISCUSSION 
6.1 MODELING OBJECTIVES 
The primary objective of the SZ Transport Abstraction Model and the SZ 1-D Transport Model 
is to provide a method of simulating radionuclide transport in the SZ for use in the TSPA Model 
of repository performance. Analyses of parameter uncertainty and multiple realizations of the 
SZ system using the SZ Transport Abstraction Model constitute an assessment of uncertainty in 
the SZ system for direct implementation in the TSPA model. The general approach to modeling 
radionuclide migration and the assessment of uncertainty in the SZ is also described by Arnold et 
al. 2003 [163857]. The objective of the SZ 1-D Transport Model is to provide a simplified, yet 
accurate representation of SZ transport for the simulation of four radionuclide decay chains for 
implementation with the TSPA model. 
In the TSPA analyses the convolution integral method is used by the SZ Transport Abstraction 
Model to determine the radionuclide mass flux at the SZ / biosphere interface, 18 km 
downgradient of the repository (10 CFR 63.302 (10 CFR 63 [156605])) as a function of the 
transient radionuclide mass flux at the water table beneath the repository. This computationally 
efficient method combines information about the unit response of the system, as simulated by the 
SZ Transport Abstraction Model, with the radionuclide source history from the UZ to calculate 
transient system behavior. The fundamental concepts of the convolution integral method, as 
applied to solute transport in groundwater, are presented by Jury et al. 1986 [164314], in which 
the method is called the transfer function model. The most important assumptions of the 
convolution method are linear system behavior and steady-state flow conditions in the saturated 
zone. 
The SZ 1-D Transport Model is used in the TSPA analyses for the purpose of simulating 
radioactive decay and ingrowth for four decay chains. This simplified model is required because 
the radionuclide transport methodology used in the SZ Transport Abstraction Model is not 
capable of simulating ingrowth by radioactive decay. Although it is not anticipated that the 
decay products from these radioactive decay chains are significant contributors to the total 
radiological dose, regulations concerning groundwater protection contained at 10 CFR 63.331 
(10 CFR 63 [156605]) require explicit analysis of their concentrations in the water supply of the 
critical group. Consequently, only the results for daughter-radionuclides from the SZ 1-D 
Transport Model are input to the TSPA simulations. Although transport of the parent 
radionuclides is also included in the SZ 1-D Transport Model, the results for parentradionuclides 
input to the TSPA simulations are those derived from the SZ Transport Abstraction 
Model. The SZ 1-D Transport Model for TSPA differs from the SZ Transport Abstraction 
Model in that it is implemented directly with the GoldSim v. 7.50.100 software code (STN: 
10344-7.50.100-00, BSC 2003 [161572]) in the TSPA model.

MDL-NBS-HS-000021, REV 00 32 July, 2003 
6.2 FEATURES, EVENTS, AND PROCESSES FOR THIS MODEL REPORT 
The development of a comprehensive list of FEPs potentially relevant to post-closure 
performance of the potential Yucca Mountain repository is an ongoing, iterative process based 
on site-specific information, design, and regulations. The approach for developing an initial list 
of FEPs in support of the TSPA-SR (CRWMS M&O 2000 [153246]) was documented by Freeze 
et al. 2001 [154365]. The initial FEPs list contained 328 FEPs, of which 176 were included in 
TSPA-SR models (CRWMS M&O 2000 [153246], Tables B-9 through B-17). To support the 
TSPA-LA, the FEPs list was re-evaluated in accordance with The Enhanced Plan for Features, 
Events, and Processes (FEPs) at Yucca Mountain (BSC 2002 [158966], Section 3.2). The 
included FEPs abstractions incorporated in the TSPA-LA model, which are implemented through 
specific process models or input parameters, are specifically addressed in saturated zone model 
reports (Table 6-1). The rationale for excluding a FEP from the TSPA-LA model will be given 
in the upcoming revision (REV02) of Features, Events, and Processes in SZ Flow and Transport 
(CRWMS M&O 2001 [153931]). The assignments of included FEPs to SZ reports for 
documentation are found in the Technical Work Plan For: Saturated Zone Flow and Transport 
Modeling and Testing, TWP-NBS-MD-000002 (BSC 2003 [163965], Section 2.5). 
Table 6-1. Included FEPs for the Saturated Zone TSPA-LA 
FEP Number FEP Name Responsible SZ Report 
1.2.02.01.0A Fractures this report 
1.2.02.02.0A Faults this report 
1.4.07.02.0A Wells this report 
2.2.03.01.0A Stratigraphy Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 
2.2.03.02.0A Rock Properties of Host 
Rock and Other Units 
this report 
2.2.07.12.0A Saturated Groundwater Flow 
in the Geosphere 
Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 
2.2.07.13.0A Water-Conducting Features 
in the SZ 
this report 
2.2.07.15.0A Advection and Dispersion in 
the SZ 
Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.07.16.0A Dilution of Radionuclides in 
Groundwater 
this report 
2.2.07.17.0A Diffusion in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.08.01.0A Chemical Characteristics of 
Groundwater in the SZ 
Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.08.06.0A Complexation in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.08.08.0A Matrix Diffusion in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.08.09.0A Sorption in the SZ Site-Scale Saturated Zone Transport, (BSC 2003 [162419]) 
2.2.08.10.0A Colloid Transport in the SZ this report

MDL-NBS-HS-000021, REV 00 33 July, 2003 
FEP Number FEP Name Responsible SZ Report 
2.2.08.11.0A Groundwater Discharge to 
Surface Within the 
Reference Biosphere 
this report 
2.2.10.03.0A Natural Geothermal Effects 
on Flow in the SZ 
Site-Scale Saturated Zone Flow Model, (BSC 2003 [162649]) 
2.2.12.00.0B Undetected Features in the 
SZ 
this report 
3.1.01.01.0A Radioactive Decay and 
Ingrowth 
this report 
Table 6-2 lists the FEPs included in the TSPA-LA for which this model report provides the 
technical basis and provides a summary of their disposition in TSPA-LA. Table 6-3 lists the 
FEPs that are partially addressed by the results of this model report. These results are used 
elsewhere (as shown in Table 6-1) to determine the include/exclude status of the FEP and/or its 
implementation in TSPA-LA. Details of the implementation of these FEPs are summarized in 
Sections 5, 6.3, 6.5, and 6.7.

MDL-NBS-HS-000021, REV 00 34 July, 2003 
Table 6-2. Saturated Zone Included FEPs for Which This Model Report Provides the Technical Basis 
FEP Number 
and Name 
FEP Description Section in 
Report Where 
FEP Discussed 
Disposition in TSPA-LA 
1.2.02.01.0A 
Fractures 
Groundwater flow in the Yucca Mountain region and 
transport of any released radionuclides may take place 
along fractures. The rate of flow and the extent of 
transport in fractures are influenced by characteristics 
such as orientation, aperture, asperity, fracture length, 
connectivity, and the nature of any linings or infills. 
6.5.2.1, 
6.5.2.4, 
6.5.2.5, 
6.5.2.9, 
6.5.2.10, 
6.5.2.12 
6.5.2.15 
The SZ Transport Abstraction Model includes fractures and 
uncertainty in the hydraulic and transport properties of the 
fracture system in volcanic units along the flow path from 
beneath the repository. The characteristics of the fracture 
properties such as fracture orientation, connectivity, aperture 
size, degree of infilling, and tortuosity are modeled in the SZ 
Transport Abstraction Model and the SZ 1-D Transport Model 
through the following probabilistically modeled parameters: 
flowing interval porosity (FPVO), flowing interval spacing 
(FISVO), groundwater specific discharge (GWSPD), 
longitudinal dispersivity (LDISP), horizontal anisotropy 
(HAVO), and colloid retardation (CORVO). 
1.2.02.02.0A 
Faults 
Numerous faults of various sizes have been noted in 
the Yucca Mountain Region and in the repository area 
specifically. Faults may represent an alteration of the 
rock permeability and continuity of the rock mass, 
alteration or short-circuiting of the flow paths and flow 
distributions close to the repository, and represent 
unexpected pathways through the repository. 
6.5.2.1 
6.5.2.10 
Geologic features and hydrostratigraphic units are explicitly 
included in the SZ Transport Abstraction Model in a 
configuration that accounts for the effects of existing faults, 
based on the hydrogeologic framework model. Model 
configuration of these discrete features is developed in the SZ 
Site-Scale Flow Model (BSC 2003 [162649], Section 6.3.2 ). 
The offsets of hydrostratigraphic units across major faults are 
incorporated into the model, and some key faults (e.g., 
Solitario Canyon fault, Highway 95 fault, and Fortymile Wash 
structure) are explicitly included as high- or low-permeability 
features. Model parameters, including horizontal anisotropy 
(HAVO) and groundwater specific discharge (GWSPD), 
implicitly include the potential impacts of faults on groundwater 
flow and are modeled probabilistically to account for the 
uncertainty in hydraulic properties associated with faults and 
fractures in the volcanic units.

MDL-NBS-HS-000021, REV 00 35 July, 2003 
FEP Number 
and Name 
FEP Description Section in 
Report Where 
FEP Discussed 
Disposition in TSPA-LA 
1.4.07.02.0A 
Wells 
One or more wells drilled for human use (e.g., drinking 
water, bathing) or agricultural use (e.g., irrigation, 
animal watering) may intersect the contaminant plume. 
5. 
6.3.3 
The effects of wells on the dose to members of the critical 
group are included through the volume of contaminated 
groundwater used by that group. The groundwater system in 
the vicinity of the hypothetical communitys well system is 
modeled assuming that all the contaminants discharged at the 
18-km boundary are intercepted by the communitys wells. 
The total volume extracted from all wells to be used by the 
farming community is 3,000 acre-feet per year (per guidance 
given in 10 CFR Part 63 Subpart 63.332, (3) [156605]). 
2.2.03.02.0A 
Rock Properties 
of Host Rock and 
Other Units 
Physical properties such as porosity and permeability 
of the relevant rock units, soils, and alluvium are 
necessary for the performance assessment. Possible 
heterogeneities in these properties should be 
considered. Questions concerning events and 
processes that may cause these physical properties to 
change over time are considered in other FEPs. 
6.5.2.1, 
6.5.2.2, 
6.5.2.3, 
6.5.2.4, 
6.5.2.5, 
6.5.2.7, 
6.5.2.8, 
6.5.2.9 
6.5.2.10 
Geologic features and heterogeneous hydrostratigraphic units 
are explicitly included in the SZ Transport Abstraction Model 
as cells with specific hydrologic parameter values in a 
configuration based on the hydrogeologic framework used in 
the SZ Site-Scale Flow Model (BSC 2003 [162649], Section 
6.3.2). Spatial variability in rock properties is encompassed 
within uncertainty distributions for key parameters, such as 
groundwater specific discharge (GWSPD), horizontal 
anisotropy (HAVO), flowing interval spacing (FISVO), and 
sorption coefficients. Uncertainty in the location of the contact 
between alluvium and volcanic units at the southern end of the 
site-scale model is modeled probabilistically using the 
parameters related to the northern and western boundaries of 
the alluvial uncertainty zone, respectively (FPLAN and 
FPLAW). 
2.2.07.13.0A 
Water- 
Conducting 
Features in the 
SZ 
Geologic features in the saturated zone may affect 
groundwater flow by providing preferred pathways for 
flow. 
6.5.2.1, 
6.5.2.4, 
6.5.2.5, 
6.5.2.9, 
6.5.2.10 
Groundwater flow in fractures of the volcanic units is an 
explicit feature of the SZ Transport Abstraction Model and the 
SZ 1-D Transport Model. These models simulate saturated 
flow and advective transport through flowing intervals, a 
subset of water-conducting features within the fracture system. 
The uncertainty in the system is represented in the model 
using probabilistic simulations of flowing interval porosity 
(FPVO), flowing interval spacing (FISVO), groundwater 
specific discharge (GWSPD), longitudinal dispersivity (LDISP), 
and horizontal anisotropy (HAVO). The ranges of uncertainty 
in these parameters encompass the possibility of channelized 
flow along preferred pathways.

MDL-NBS-HS-000021, REV 00 36 July, 2003 
FEP Number 
and Name 
FEP Description Section in 
Report Where 
FEP Discussed 
Disposition in TSPA-LA 
2.2.07.16.0A 
Dilution of 
Radionuclides in 
Groundwater 
Dilution due to mixing of contaminated and 
uncontaminated water may affect radionuclide 
concentrations in groundwater during transport in the 
saturated zone and during pumping at a withdrawal 
well. 
5., 
6.5.2.9, 
6.7.2 
The process of transverse hydrodynamic dispersion is 
explicitly incorporated in the SZ Transport Abstraction Model, 
leading to dilution of simulated contaminant concentrations. 
Dilution as a result of pumping is implicitly included in the 
TSPA exposure model. The SZ Transport Abstraction Model 
is used to estimate the flux of contaminants into the volume of 
water consumed in the regulatory-mandated exposure 
scenario. The volume of water (per guidance given in 10 CFR 
Part 63 Subpart 63.332, (3) [156605]) pumped from the 
hypothetical farming community is 3000 acre-feet (about 3.7 x 
109 liters) which is larger than the simulated volumetric flow of 
contaminated groundwater crossing the 18 km boundary. 
Therefore, the degree of dilution is the ratio of the flux of 
contaminated groundwater to volume of water pumped by the 
hypothetical farming community. 
2.2.08.10.0A 
Colloidal 
Transport in the 
SZ 
Radionuclides may be transported in groundwater in 
the SZ as colloidal species. Types of colloids include 
true colloids, pseudo colloids, and microbial colloids. 
6.3.1, 
6.5.1, 
6.5.2.11, 
6.5.2.12 
The colloid-facilitated transport of radionuclides is explicitly 
included in the SZ Transport Abstraction Model and the SZ 1- 
D Transport Model. Colloids are subject to advection in the 
fractures of tuff units and are excluded from diffusion into the 
rock matrix. Radionuclide transport in association with colloids 
is simulated to occur by two modes: 1) as reversibly sorbed 
onto colloids, and 2) as irreversibly attached to colloids. 
Reversible sorption of radionuclides may occur onto any 
colloidal material present in the groundwater, and 
measurements of natural colloids in groundwater of the SZ 
include mineral and microbial colloids. Colloids with 
irreversibly attached radionuclides originate from the 
degradation of the glass waste form in the repository. The 
parameters related to reversible sorption onto colloids are 
Kd_Am_Col, Kd_Pu_Col, Kd_Cs_Col, and Conc_Col. The 
parameters related to the retardation of colloids with 
irreversibly attached radionuclides are CORVO and CORAL. 
2.2.08.11.0A 
Groundwater 
Discharge to 
Surface Within 
the Reference 
Biosphere 
Radionuclides transported in groundwater as solutes 
or solid materials (colloids) from the far field to the 
biosphere will discharge at specific "entry" points that 
are at or near the receptor location. Surface discharge 
points may be to holding ponds, to unsaturated soils, 
or through wells used for irrigation, livestock, or 
drinking water supply. 
5, 
6.3.3 
The groundwater system in the vicinity of the hypothetical 
communitys well system is modeled such that all the 
contaminants discharged at the 18-km boundary are 
intercepted by the communitys wells. Direct discharge of 
groundwater to the surface via springs, unsaturated soils, etc. 
is not included, given the simplifying assumption of complete 
capture of the contaminant plume in the wells.

MDL-NBS-HS-000021, REV 00 37 July, 2003 
FEP Number 
and Name 
FEP Description Section in 
Report Where 
FEP Discussed 
Disposition in TSPA-LA 
2.2.12.00.0B 
Undetected 
Features in the 
SZ 
This FEP is related to undetected features in the SZ 
portion of the geosphere that can affect long-term 
performance of the disposal system. Undetected but 
important features may be present and may have 
significant impacts. These features include unknown 
active fracture zones, inhomogeneities, faults and 
features connecting different zones of rock, and 
different geometries for fracture zones. 
6.5.2.1, 
6.5.2.2, 
6.5.2.3, 
6.5.2.4, 
6.5.2.5, 
6.5.2.7, 
6.5.2.8, 
6.5.2.9, 
6.5.2.10 
Undetected features in the SZ, such as fracture zones, 
inhomogeneities, and faults and their potential impacts on 
groundwater flow are implicitly incorporated in the SZ 
Transport Abstraction Model and the SZ 1-D Transport Model. 
Such features could impact groundwater flow with regard to 
the specific discharge in the SZ system, the direction of 
groundwater flow from horizontal anisotropy, and/or the 
degree of groundwater flow focusing in flowing intervals. The 
impacts of such potential features are encompassed within 
uncertainty distributions for key parameters, such as 
groundwater specific discharge (GWSPD), horizontal 
anisotropy (HAVO), flowing interval spacing (FISVO). 
3.1.01.01.0A 
Radioactive 
Decay and 
Ingrowth 
Radioactivity is the spontaneous disintegration of an 
unstable atomic nucleus that results in the emission of 
subatomic particles. Radioactive isotopes are known 
as radionuclides. Radioactive decay of the fuel in the 
repository changes the radionuclide content in the fuel 
with time and generates heat. Radionuclide quantities 
in the system at any time are the result of the 
radioactive decay and the growth of daughter products 
as a consequence of that decay (i.e., ingrowth). Over 
a 10,000-year performance period, these processes 
will produce daughter products that need to be 
considered in order to adequately evaluate the release 
and transport of radionuclides to the accessible 
environment. 
6.3.1, 
6.5, 
6.5.1 
Radioactive decay during transport in the SZ is explicitly 
included in the convolution integral method used to couple the 
SZ Transport Abstraction Model with the TSPA model and in 
the SZ 1-D Transport Model. Ingrowth is accounted for in two 
different ways in the TSPA models. First, the initial inventory 
in the waste is adjusted to account for the radionuclide parents 
that obviously impact the simulated dose, resulting in a 
boosting of the initial inventory of some daughter products in 
the SZ Transport Abstraction Model. Second, a separate set 
of SZ transport simulations is run to calculate explicitly the 
decay and ingrowth for the four main radionuclide chains, 
using the SZ 1-D Transport Model.

MDL-NBS-HS-000021, REV 00 38 July, 2003 
Table 6-3. Saturated Zone Included FEPs Supported by the Results in This Model Report 
FEP Number and Name FEP Description 
Section in Report 
Where FEP is 
Discussed 
2.2.03.01.0A 
Stratigraphy 
Stratigraphic information is necessary information for the 
performance assessment. This information should include 
identification of the relevant rock units, soils and alluvium, and 
their thickness, lateral extents, and relationships to each other. 
Major discontinuities should be identified. 
6.5.2.1 
6.5.2.2 
2.2.07.15.0A 
Advection and 
Dispersion in the SZ 
Advection and dispersion processes affect contaminant 
transport in the SZ. 
6.5.2.1 
6.5.2.9 
6.5.2.10 
2.2.07.17.0A 
Diffusion in the SZ 
Molecular diffusion processes may affect radionuclide transport 
in the SZ. 
6.5.2.1 
6.5.2.4 
6.5.2.5 
6.5.2.6 
2.2.08.01.0A 
Chemical Characteristics 
of Groundwater in the 
SZ 
Chemistry and other characteristics of groundwater in the 
saturated zone may affect groundwater flow and radionuclide 
transport of dissolved and colloidal species. Groundwater 
chemistry and other characteristics, including temperature, pH, 
Eh, ionic strength, and major ionic concentrations, may vary 
spatially throughout the system as a result of different rock 
mineralogy. This FEP is included through distributions of Kd 
values. 
6.5.2.8 
6.5.2.11 
6.5.2.12 
2.2.08.06.0A 
Complexation in the SZ 
Complexing agents such as humic and fulvic acids present in 
natural groundwaters could affect radionuclide transport in the 
SZ. This FEP is included through distributions of Kd values. 
6.5.2.8 
6.5.2.11 
6.5.2.12 
2.2.08.08.0A 
Matrix Diffusion in the 
SZ 
Matrix diffusion is the process by which radionuclides and other 
species transported in the SZ by advective flow in fractures or 
other pathways move into the matrix of the porous rock by 
diffusion. Matrix diffusion can be a very efficient retarding 
mechanism, especially for strongly sorbed radionuclides, due to 
the increase in rock surface accessible to sorption. 
6.5.2.4 
6.5.2.5 
6.5.2.6 
2.2.08.09.0A 
Sorption in the SZ 
Sorption of dissolved and colloidal radionuclides in the SZ can 
occur on the surfaces of both fractures and matrix in rock or soil 
along the transport path. Sorption may be reversible or 
irreversible, and it may occur as a linear or nonlinear process. 
Sorption kinetics and the availability of sites for sorption should 
be considered. Sorption is a function of the radioelement type, 
mineral type, and groundwater composition. 
6.5.2.8 
6.5.2.11 
6.5.2.12

MDL-NBS-HS-000021, REV 00 39 July, 2003 
6.3 BASE-CASE CONCEPTUAL MODEL 
The base-case conceptual model for radionuclide transport, as implemented in the SZ Transport 
Abstraction Model, implicitly includes the conceptual models of groundwater flow and transport 
incorporated in the SZ Site-Scale Flow Model and the SZ Site-Scale Transport Model (BSC 
2003 [162649], Section 6.3; BSC 2003 [162419], Sections 5 and 6.3). The SZ Site-Scale Flow 
Model and alternative conceptualizations of groundwater flow are also described by Zyvoloski et 
al. 2003 [163341]. The base-case conceptual model for the SZ 1-D Transport Model also 
implicitly includes the conceptual models in these underlying models, with the conceptual 
simplifications in flow associated with representation by one-dimensional groundwater flow. 
The SZ Transport Abstraction Model and the SZ 1-D Transport Model also include the concept 
of uncertainty in key model parameters. The probabilistic analysis of uncertainty is implemented 
through Monte Carlo realizations of the SZ flow and transport system, in a manner consistent 
with the TSPA simulations. 
6.3.1 SZ Transport Abstraction Model 
The conceptual model of groundwater flow in the SZ includes steady-state flow conditions in a 
three-dimensional flow system (BSC 2003 [162649], Section 6.3.3). Groundwater flow occurs 
in a continuum fracture network in the fractured volcanic rocks beneath the repository site, at the 
scale of individual grid blocks in the SZ Transport Abstraction Model. The effective continuum 
conceptual model is appropriate, given the relatively large horizontal scale (500 m by 500 m) of 
the grid in the model. Grid resolution studies with the SZ Site-Scale Flow Model indicate that 
the 500 m grid resolution and the effective continuum conceptual model are adequate to capture 
the flow behavior of the SZ system and to calibrate the model (Bower et al. 2000 [149161]). 
Groundwater flow is conceptualized to occur in a continuum porous medium in the alluvium and 
valley-fill units of the SZ Transport Abstraction Model. Contrasting values of average 
permeability among hydrogeologic units influence the patterns of groundwater flow in the SZ 
(BSC 2003 [162649], Sections 6.3 and 6.6). 
Some of the major faults and other discrete geological features are conceptualized to impact the 
groundwater flow due to contrasts in permeability with surrounding hydrogeologic units. In 
addition, the prevailing structural fabric in the volcanic hydrogeologic units near Yucca 
Mountain may impart horizontal anisotropy in the permeability between the major faults in this 
area of the SZ system. 
Groundwater flow enters the SZ site-scale flow system primarily as underflow at the lateral 
boundaries of the model domain (BSC 2003 [162649], Section 6.3.2). The conceptual model of 
recharge to the SZ includes distributed recharge, primarily in the northern part of the model 
domain, and focused recharge along the Fortymile Wash channel (BSC 2003 [162649], Section 
6.3.2). Recharge within the area of the SZ Transport Abstraction Model domain constitutes a 
small fraction of the entire groundwater budget of the site-scale flow system. Groundwater flow 
paths from beneath Yucca Mountain to the south are conceptualized to occur near the water 
table, due to the generally small amount of recharge in this area. 
The conceptual model of the SZ flow system for future climatic conditions includes significant 
changes in the groundwater flow rates for potential wetter, cooler climate states. Increases in

MDL-NBS-HS-000021, REV 00 40 July, 2003 
recharge at both the local and regional scales for monsoonal and glacial-transition climatic 
conditions would increase the specific discharge of groundwater in the SZ. Given the likelihood 
of such climatic variations within the 10,000 year time period of regulatory concern, the 
conceptual model of SZ flow includes higher groundwater fluxes for the future. 
The conceptual model of radionuclide transport in the SZ includes the processes of advection, 
dispersion, matrix diffusion in fractured volcanic units, sorption, and colloid-facilitated transport 
(BSC 2003 [162419], Section 6.3). In addition, radionuclides are subject to radioactive decay 
and ingrowth during migration in the SZ in the TSPA analyses. These processes are illustrated 
in Figure 6-1 and Figure 6-2. 
Figure 6-1. Illustration of the Conceptual Model of Radionuclide Transport Processes in the Saturated 
Zone

MDL-NBS-HS-000021, REV 00 41 July, 2003 
Groundwater advection is the primary mechanism to drive the migration of contaminants from 
the SZ beneath the repository to the accessible environment. Advective transport of 
radionuclides is conceptualized to occur primarily within the fracture network of the volcanic 
hydrogeologic units (BSC 2003 [162419], Section 6.3) due to the very high contrast in 
permeability between the fractures and the rock matrix. The conceptual model of advection 
within the porous medium of the alluvium units envisions the flow of groundwater to be much 
more widely distributed, but excludes groundwater flow from zones or sedimentary facies of 
lower permeability material within the alluvium. 
Dispersion of contaminant mass during transport in the SZ is conceptualized to occur because of 
hydrodynamic dispersion and molecular diffusion. Hydrodynamic dispersion is the result of 
variations in groundwater flow rates induced by heterogeneities within the aquifer, both in 
fractured and porous media. The conceptual model of hydrodynamic dispersion distinguishes 
between longitudinal dispersion, which occurs in the direction of groundwater flow, and 
transverse dispersion, which occurs perpendicular to the direction of groundwater flow. 
Longitudinal dispersion is typically much greater than transverse dispersion (see Section 
6.5.2.9). Molecular diffusion also contributes to dispersion in radionuclide transport in the 
advective domain, but to a much lesser degree than hydrodynamic dispersion. 
The dual-porosity conceptual model of matrix diffusion in fractured media describes the transfer 
of radionuclide mass from the flowing groundwater within the fractures to the relatively stagnant 
groundwater contained in the pores of the rock matrix. This mass transfer, either into or out of 
the rock matrix, occurs by molecular diffusion, which is driven by differences in the 
concentration of the contaminant in the fractures and matrix. The simplified conceptual model 
of the spatial distribution of groundwater-conducting fractures and matrix is a set of parallel, 
uniformly-spaced fractures, separated by blocks of porous matrix (BSC 2003 [162419], Section 
6.5.2.4). This conceptual model considers that groundwater flow occurs only in the fractures and 
that the groundwater in the rock matrix has no advective groundwater movement. Although this 
aspect of the dual-porosity conceptual model is difficult to confirm, the contrast in permeability 
between the rock matrix and the fracture network in fractured tuff tends to support this approach. 
Groundwater flow is conceptualized to not necessarily occur in all fractures of the system, but is 
limited to those fractures that are interconnected in the through-going fracture network. The 
matrix diffusion process is controlled primarily by the effective diffusion coefficient in the rock 
matrix, the spacing between fractures carrying flowing groundwater, and the aperture of the 
fractures. 
The conceptual model of matrix diffusion also recognizes the possibility of groundwater flow in 
fracture zones, in which numerous, closely spaced fractures may transmit groundwater. Such 
fracture zones could exist along faults, which have experienced multiple episodes of 
displacement and potentially contain zones of rubblized bedrock. Diffusion of contaminants into 
the relatively small blocks of matrix within a fracture zone would be rapid in comparison to the 
matrix diffusion that would occur into the large blocks that exist between such zones. The 
contaminant storage capacity of the small blocks within such a fracture zone would be the total 
matrix porosity (and sorption capacity of mineral grains) of the blocks, corresponding to 
essentially complete matrix diffusion within the small matrix blocks.

MDL-NBS-HS-000021, REV 00 42 July, 2003 
The conceptual model of radionuclide sorption in the SZ is local equilibrium distribution of 
radionuclide mass between the aqueous phase and the mineral grains of the aquifer. This 
equilibrium distribution of contaminant mass is defined by the linear sorption coefficient 
relationship. In fractured media, sorption is conceptualized to occur in the rock matrix; no 
sorption is conceptualized to occur on the fracture surfaces or coatings. In the porous media of 
the alluvium, sorption is conceptualized to occur in that portion of the aquifer corresponding to 
the effective porosity of the alluvium. In other words, sorption can occur in that part of the 
alluvium through which significant groundwater flow occurs; zones or layers of low permeability 
are effectively excluded from the sorption process. 
In the conceptual model of colloid-facilitated transport radionuclide migration associated with 
colloids can occur by two modes (BSC 2003 [163932], Section 6.3), as illustrated in Figure 6-2. 
In the first mode, radionuclides that are reversibly attached to colloids are in equilibrium with the 
aqueous phase and the aquifer material. In this mode of transport, the effective retardation of 
these radionuclides during transport in the SZ is dependent on the sorption coefficient of the 
radionuclide onto colloids, the concentration of colloids in the groundwater, and the sorption 
coefficient of the radionuclide onto the aquifer material. In the second mode, radionuclides that 
are irreversibly attached to colloids are transported at the same rate as the colloids. The colloids 
with the irreversibly attached radionuclides are themselves retarded by interaction (attachment 
and detachment) with the aquifer material. Specifically, the colloids undergo reversible 
filtration, which is represented by a retardation factor in the model. 
The conceptual model of radioactive decay in the SZ Transport Abstraction Model is that 
radionuclides experience a decrease in mass during transport time using the first-order kinetic 
decay constant for that radionuclide. Because the ingrowth of radionuclides is not explicitly 
included in the SZ Transport Abstraction Model, a simplified approach is used to account for this 
process for those radionuclides that have parent radionuclides. In this simplified approach, the 
mass of the daughter radionuclide is boosted by the maximum mass of the parent radionuclide 
that would decay over the remaining TSPA simulation time. The boosting of the daughter 
radionuclide mass occurs for the input to the SZ Transport Abstraction Model (i.e., at the UZ  
SZ interface). The daughter radionuclides that are boosted in this manner are Pu-239 (from Am- 
243), Np-237 (from Am-241), U-236 (from Pu-240), U-238 (from Pu-242), and U-234 (from U- 
238 and Pu-238).

MDL-NBS-HS-000021, REV 00 43 July, 2003 
Figure 6-2. Illustration of the Conceptual Model of Colloid-Facilitated Radionuclide Transport in Fractured 
Tuff in the Saturated Zone

MDL-NBS-HS-000021, REV 00 44 July, 2003 
Homogeneous material properties are assigned to individual hydrogeologic units. The 
assumption of intra-unit homogeneity is justified primarily on the basis of scale in the SZ 
Transport Abstraction Model. The horizontal grid resolution of 500 m implies averaging of 
spatially variable properties over a very large volume. In addition, variations among realizations 
for stochastic parameters in the analysis encompass probable spatial variations in material 
properties within the model domain. 
It is also assumed that the groundwater flow conditions in the SZ system are in steady state. This 
approach is carried forward from the Site-Scale Saturated Zone Flow Model report (BSC 2003 
[162649], Section 5). The Site-Scale Saturated Zone Flow Model is a steady-state model of the 
flow conditions, reflecting the conclusion that a steady-state representation of the SZ system is 
accurate. This conclusion is supported by the lack of consistent, large-magnitude variations in 
water levels observed in wells near Yucca Mountain (Luckey et al. 1996 [100465], p. 29-32). 
The convolution integral method has been extended to incorporate multiple steady-state flow 
conditions for alternative climate states in the TSPA analyses. 
The conceptual model of matrix diffusion in the fractured volcanic units of the SZ assumes 
groundwater flow in evenly spaced, parallel-walled fractures separated by impermeable matrix. 
Although this dual-porosity conceptual model of radionuclide transport represents a significant 
simplification of the complex fracture network observed in fractured volcanic rocks at the site, it 
is an acceptable approximation at the scale of individual grid blocks in the SZ Transport 
Abstraction Model. Individual grid blocks in the transport model have horizontal dimensions of 
500 m by 500 m, in comparison to a geometric mean flowing interval spacing of approximately 
21 m. This comparison indicates that the grid blocks in the numerical model are more than an 
order of magnitude larger than the expected spacing between fracture zones that contain flowing 
groundwater. In addition, the relatively broad range of uncertainty in the flowing interval 
spacing used in this analysis encompasses the variability in spacing of the actual fracture 
network. Thus, the variability in flowing interval spacing among stochastic realizations in the 
TSPA simulations tends to capture the impact of variable spacing between fractures in an 
ensemble fashion. 
For transport of radionuclides reversibly attached to colloids in the SZ, it is assumed that 
equilibrium conditions exist among radionuclides sorbed onto colloids, the aqueous phase 
concentration, and those sorbed onto the aquifer material. This approach is carried forward from 
the Site-Scale Saturated Zone Transport model report (BSC 2003 [162419], Section 6.3) and is 
related to the general assumption regarding linear, equilibrium sorption presented in Section 5. 
This approach is consistent with laboratory observations of sorption onto colloids, particularly 
given the time scales of transport in the SZ. This modeling approach is appropriate, given the 
broad ranges of uncertainty applied to parameters underlying the simulated transport of 
radionuclides reversibly attached to colloids in the SZ. 
Pumping of groundwater by the hypothetical farming community is assumed not to alter 
significantly the groundwater pathways or radionuclide travel times in the SZ. Calibration of the 
SZ site-scale flow model is based on the present-day potentiometric surface observed in the 
model domain. Whereas the SZ site-scale model does not explicitly include the withdrawal of 
groundwater by pumping at the location of the hypothetical community, the model does 
implicitly account for the drawdown of water levels associated with pumping at the southern

MDL-NBS-HS-000021, REV 00 45 July, 2003 
boundary of the model domain. The values of specified head along the western part of the 
southern boundary reflect the lower water levels resulting from pumping in the Amargosa Farms 
region. Consequently, the model does implicitly include the influence of pumping in terms of 
increased hydraulic head gradients. 
6.3.2 SZ 1-D Transport Model 
Many components of the conceptual model for the SZ Transport Abstraction Model also apply to 
the SZ 1-D Transport Model. Representation of the groundwater flow processes in the threedimensional 
SZ Transport Abstraction Model is simplified to one-dimensional streamtubes in the 
SZ 1-D Transport Model. However, characteristics of the conceptual model of groundwater flow 
in the SZ Transport Abstraction Model are implicitly included in the SZ 1-D Transport Model 
because the average values of groundwater flow rate used in the SZ 1-D Transport Model are 
extracted from the three-dimensional flow model. The conceptual model of aquifer properties 
has also been simplified in the SZ 1-D Transport Model, relative to the SZ Transport Abstraction 
Model. Material properties in the SZ 1-D Transport Model streamtubes are for average fractured 
tuff or for alluvium; no distinctions among volcanic hydrogeologic units are made. 
The conceptual model of radionuclide transport in the SZ 1-D Transport Model includes the 
same processes of advection, dispersion, matrix diffusion in fractured volcanic units, sorption, 
and colloid-facilitated transport described in the previous section. The conceptualization of 
dispersion in the SZ 1-D Transport Model is simplified to the extent that transverse dispersion is 
precluded in the streamtube representation of the SZ system. The conceptual model of 
radionuclide decay in the SZ 1-D Transport Model includes both decay and ingrowth of 
radionuclides in decay chains. 
The final radionuclide daughter product in three of the radionuclide decay chains simulated in 
the one-dimensional radionuclide transport model is calculated to be in secular equilibrium with 
its parent radionuclide (see Section 6.5.1.2). This is a reasonable approach because it simplifies 
the analysis and the final daughter radionuclides have relatively short half lives (less than 25 
years). This approach overestimates the concentration of daughter products because it implies an 
instantaneous increase in the mass of the final daughter product to be in equilibrium with the 
mass of parent radionuclide present. 
The groundwater flux within each one-dimensional pipe segment used in the model is assumed 
to be constant along the length of the pipe. Each pipe segment used in the model consists of 
homogenous material properties, for which the radionuclide transport process is simulated. This 
constitutes a reasonable approach because the average groundwater flux along that portion of the 
radionuclide flowpath is derived from the corresponding region of the three-dimensional SZ 
Transport Abstraction Model.

MDL-NBS-HS-000021, REV 00 46 July, 2003 
6.3.3 Interfaces with the UZ and the Biosphere 
The source of radionuclides in the SZ Transport Abstraction Model is conceptualized to be a 
point source from the UZ transport model. The location of this source is treated as uncertain and 
constant for a given realization of the system. This conceptual model is consistent with a 
contaminant source to the SZ resulting from a single leaking waste package, focused 
groundwater flow in the UZ, or the human intrusion scenario in which a borehole intersects a 
waste package and extends to the water table (CRWMS M&O 2000 [153246], Section 4.4). 
The conceptual model of radionuclide releases from the SZ to the biosphere includes pumping of 
groundwater from wells by the hypothetical farming community. The location of this 
hypothetical farming community is specified in the regulations for the Yucca Mountain site (10 
CFR 63.302 (10 CFR 63 [156605])). In addition, the quantity of groundwater used by the 
hypothetical farming community is specified by the regulations to be 3,000 acre-ft/year (10 CFR 
63.332 (10 CFR 63 [156605])). The conceptualization of the pumping system is that the entire 
plume of radionuclides in the SZ would be captured by the pumping wells of the hypothetical 
farming community and that these contaminants would be homogeneously distributed in the 
specified volume of groundwater. Although variations in radionuclide concentration would 
probably exist among the pumping wells, the radiological dose among the population of this 
community would tend to be homogenized by exchange of radionuclides through various 
pathways within the biosphere. 
The interface between radionuclide transport in the UZ and the SZ is assumed to be a point 
source near the water table. This approach is physically consistent with a single leaking waste 
package and highly focused transport of radionuclides in the UZ flow system, as may occur early 
in the post-closure history of the repository. This approach is also consistent with the human 
intrusion scenario, in which a borehole penetrates a waste package and provides a direct pathway 
for radionuclide migration to the SZ. The approach of a point source for radionuclides in the SZ 
transport simulations, while not physically realistic for the situation in which multiple, dispersed 
leaking waste packages exist, provides a generally conservative approximation of the source 
term to the SZ. This approximation results in less dispersion of the radionuclide transport times 
through the SZ and thus to less attenuation of peaks in radionuclide discharge. Although in situ 
concentrations of radionuclides are not utilized in the analysis of SZ transport, a point source 
tends to maximize the simulated concentrations of radionuclides at the outlet to the accessible 
environment. 
The location of the point source of radionuclides for transport in the SZ site-scale flow and 
transport model is assumed to be randomly located within the four source regions defined at the 
water table. This approach implies that there are no consistent spatial patterns of waste package 
failure or delivery of radionuclides at the water table within each of the four source regions. 
Many of the processes that may lead to waste package failure are spatially random (e.g., 
manufacturing defects, seepage onto waste packages, etc.). The spatial pattern of preferential 
groundwater flow pathways in the UZ flow model is represented in a general sense by the 
locations of the four source regions (e.g., the southeastern source region corresponds to focused 
vertical groundwater flow along the Ghost Dance fault).

MDL-NBS-HS-000021, REV 00 47 July, 2003 
An assumption inherent to the convolution integral method is that the system being simulated 
exhibits a linear response to the input function. In the case of solute transport in the SZ system 
this approach implies, for example, that a doubling of the input mass flux results in a doubling of 
the output mass flux. This approach is valid for the SZ Transport Abstraction Model because the 
underlying transport processes (e.g., advection and sorption) are all linear with respect to solute 
mass (BSC 2003 [162419], Section 6.5.2). The processes of colloid filtration and sorption are 
both represented as equilibrium retardation processes. Simple retardation affects the timing of 
the release of radionuclides from the SZ, but still constitutes a linear relationship between mass 
input and mass output to the SZ. 
It is assumed that all radionuclide mass crossing the regulatory boundary (at approximately 18 
km distance from the repository) (10 CFR 63.302 (10 CFR 63 [156605])) in the SZ is captured 
by pumping wells of the hypothetical farming community. This approach implies that the total 
volumetric groundwater usage by the hypothetical community is large relative to the volumetric 
flow in the plume of contaminated groundwater in the SZ. This approach is justified on the basis 
of conservatism with respect to the analysis of repository performance. The total mass of 
radionuclides released to the biosphere for a given time period cannot be larger than the amount 
of radionuclide mass delivered by groundwater flow (for the nominal case). 
6.4 CONSIDERATION OF ALTERNATIVE CONCEPTUAL MODELS 
Two significant alternative conceptual models (ACMs) regarding groundwater flow and 
radionuclide transport in the SZ have been considered in this report. Both of these ACMs are 
encompassed in the range of uncertainty evaluated in the SZ Transport Abstraction Model and 
the SZ 1-D Transport model and are thus implicitly carried forward to the TSPA-LA modeling 
analyses. Consequently, these ACMs need not be separately evaluated from the base case. 
Information on ACMs is summarized in Table 6-4. The ACMs are consistent with available data 
and current scientific knowledge and appropriately consider their results and limitations. 
Table 6-4. Alternative Conceptual Models Considered 
Alternative 
Conceptual Model 
Key Assumptions Screening Assessment and Basis 
Minimal Matrix 
Diffusion 
Diffusion of radionuclides into the pore 
space of the rock matrix in the fractured 
volcanic units is extremely limited due 
to highly channelized groundwater flow, 
fracture coatings, or other factors. 
This ACM is implicitly included in the SZ 
Transport Abstraction Model and in the SZ 1-D 
Transport Model through the range of 
uncertainty in key input parameters. The 
uncertain input parameters influencing matrix 
diffusion include effective diffusion coefficient 
(DCVO), flowing interval spacing (FISVO), and 
flowing interval porosity (FPVO).

MDL-NBS-HS-000021, REV 00 48 July, 2003 
Alternative 
Conceptual Model 
Key Assumptions Screening Assessment and Basis 
Horizontal 
Anisotropy in 
Permeability 
Alternative interpretations of pump test 
results in the fractured volcanic units 
indicate preferential permeability along 
structural features oriented in the NNESSW 
direction or in the WNW-ESE 
direction. 
This ACM is implicitly included in the SZ 
Transport Abstraction Model and in the SZ 1-D 
Transport Model through the range of 
uncertainty in an input parameter. The 
uncertain input parameter influencing horizontal 
anisotropy in permeability in the volcanic units 
near Yucca Mountain is the ratio of N-S to E-W 
permeability (HAVO, see Section 6.5.2.10). 
This continuously distributed parameter varies 
from less than one to greater than one with 
most of the realizations greater than one. 
A sensitivity analysis using the SZ Transport Abstraction Model was conducted to show that the 
minimal matrix diffusion ACM is included within the range of parameter uncertainties 
considered. Figure 6-3 shows the solute mass breakthrough curves for a non-sorbing tracer, 
using the expected values of flow and transport parameters. The short-dashed line shows the 
simulated breakthrough curve for transport with no diffusion into the matrix of the fractured 
volcanic units, and the long-dashed line shows the breakthrough curve for maximum matrix 
diffusion. The solid line shows the simulated breakthrough curve using the 95th percentile value 
for flowing interval spacing (79.4 m) from the uncertainty distribution in this parameter. These 
results indicate that the breakthrough curve using the 95th percentile value of flowing interval 
spacing is very near the bounding case of no matrix diffusion. Similarly, low values of effective 
diffusion coefficient and low values of flowing interval porosity would produce breakthrough 
curves tending toward the no-matrix-diffusion case. This sensitivity analysis demonstrates that 
the minimal matrix diffusion ACM is captured within the range of uncertainty used in the model.

MDL-NBS-HS-000021, REV 00 49 July, 2003 
10 100 1000 10000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: The case of no matrix diffusion is shown with the short-dashed line. The case of maximum matrix diffusion 
is shown with the long-dashed line. The case for which flowing interval spacing is set to its 95th percentile 
value (79.4 m) is shown with the solid line. Mass breakthrough curves are for present climate and do not 
include radionuclide decay. 
Figure 6-3. Mass Breakthrough Curves at 18-km Distance Showing Sensitivity to Matrix Diffusion 
The incorporation of the horizontal anisotropy ACM into the SZ Transport Abstraction Model is 
inherent in the range of parameter values used for the parameter HAVO in the analyses. A 
complete discussion of uncertainty in horizontal anisotropy of permeability and the basis for the 
uncertainty distribution are provided in the Saturated Zone In Situ Testing scientific analysis 
report (BSC 2003 [162415], Section 6.2.6). The uncertainty distribution for HAVO indicates 
that there is a 10% probability that the direction of maximum horizontal permeability is east-west 
with a ratio between 1 and 20. The uncertainty distribution also indicates that there is a 90% 
probability that the direction of maximum horizontal permeability is north-south with a ratio 
between 1 and 20. The isotropic case, corresponding to a horizontal permeability ratio of 1, is 
included in this continuous uncertainty distribution for the parameter HAVO.

MDL-NBS-HS-000021, REV 00 50 July, 2003 
6.5 MODEL FORMULATION FOR BASE-CASE MODELS 
SZ Transport Abstraction Model 
The SZ Site-Scale Flow Model (BSC 2003 [162649]) and the SZ Site-Scale Transport Model 
(BSC 2003 [162419]) form the bases for the SZ Transport Abstraction Model. The progression 
in the development of models is from the SZ Site-Scale Flow Model to the SZ Site-Scale 
Transport Model to the SZ Transport Abstraction Model. The SZ Site-Scale Flow Model 
includes the implementation of the hydrogeologic framework, the numerical grid, and the 
boundary conditions for steady-state groundwater flow. The SZ Site-Scale Flow Model is 
calibrated to water-level measurements in wells and estimates of groundwater flow rates at the 
lateral boundaries. The SZ Site-Scale Transport Model begins with the SZ Site-Scale Flow 
Model and adds the model input files required for the simulation of radionuclide transport using 
the particle-tracking method. A set of representative parameter values for radionuclide transport 
is included in the SZ Site-Scale Transport Model and the range of behavior associated with 
parameter uncertainty is examined. Finally, the SZ Transport Abstraction Model begins with the 
SZ Site-Scale Transport Model and adds the capability to perform probabilistic uncertainty 
analyses using multiple Monte Carlo realizations of the SZ flow and transport system. The 
resulting radionuclide breakthrough curves are then used in the convolution integral method to 
couple the SZ Transport Abstraction Model with the TSPA model. 
The SZ Site-Scale Flow Model, the SZ Site-Scale Transport Model, and the SZ Transport 
Abstraction Model share a common model domain, hydrogeologic framework, numerical grid, 
and boundary conditions. The model domain is shown in Figure 6-4 with the blue dashed line 
overlain on a shaded relief map of the surface topography. The nodes that constitute the model 
grid form an orthogonal mesh with 500-m spacing in the north-south and east-west directions. 
The repository outline is shown with the bold blue line and the nodes that occur along the 
regulatory boundary of the accessible environment are shown as overlapping red crosses. 
The groundwater flow boundary conditions for the SZ Site-Scale Flow Model, the SZ Site-Scale 
Transport Model, and the SZ Transport Abstraction Model are specified head at the lateral 
boundaries and specified groundwater flux for recharge at the upper boundary. These boundary 
conditions are described in detail in BSC 2003 [162649], Section 6.3.2 and are the same for all 
three models with the following exception. For the SZ Transport Abstraction Model, the 
specified flux for recharge is scaled in proportion to the uncertainty in groundwater specific 
discharge (see Section 6.5.2.1). Scaling the recharge flux and the values of permeability in 
proportion to the groundwater specific discharge uncertainty factor maintains the calibration of 
the flow model with regard to water-level measurements.

MDL-NBS-HS-000021, REV 00 51 July, 2003 
530000 535000 540000 545000 550000 555000 560000 565000 
UTM Easting (m) 
4045000 
4050000 
4055000 
4060000 
4065000 
4070000 
4075000 
4080000 
4085000 
4090000 
UTM Northing (m) 
Source for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 
NOTE: The dashed blue line indicates the boundaries of the SZ Transport Abstraction Model, the solid blue line 
shows the outline of the repository, and the red crosses indicate the boundary to the accessible environment 
for radionuclide transport in the SZ. 
Figure 6-4. Model Domain of the SZ Site-Scale Flow Model, SZ Site-Scale Transport Model, and the SZ 
Transport Abstraction Model

MDL-NBS-HS-000021, REV 00 52 July, 2003 
Radionuclide transport is simulated in the SZ Transport Abstraction Model using a particle 
tracking method. This method, as implemented by the FEHM v. 2.20 software code (STN: 
10086-2.20-00, LANL 2003 [161725]), simulates advection along groundwater streamlines, 
random-walk dispersion, retardation due to sorption, and matrix diffusion. Each simulation uses 
500 particles, which results in a continuous, generally smooth cumulative mass breakthrough 
curve at the boundary of the accessible environment. The time-step size that determines output 
intervals varies from 10 years to 100 years, depending on the radionuclide. Internally, the 
simulation uses local flow conditions to determine time steps for dispersion and matrix diffusion 
calculations. This internal time step is controlled such that the particles take approximately 20 
internal time steps to traverse each cell in the model. 
In the TSPA analyses the convolution integral method used in the SZ Transport Abstraction 
Model provides an approximation of the transient radionuclide mass flux at a specific point 
downgradient in the SZ in response to the transient radionuclide mass flux from transport in the 
UZ. This coupling method makes full use of detailed SZ flow and transport simulations for a 
given realization of the system, without requiring complete numerical simulation of the SZ for 
the duration of each TSPA realization. The two input functions to the convolution integral 
method are: 1) a unit radionuclide mass breakthrough curve in response to a step-function mass 
flux source as simulated by the SZ Transport Abstraction Model; and, 2) the radionuclide mass 
flux history as simulated for transport in the UZ. The output function is the radionuclide mass 
flux history downgradient in the SZ. 
There are several important assumptions in the use of the convolution integral method. 
Groundwater flow in the SZ is assumed to be steady state. The transport processes in the SZ 
must be linear with respect to the solute source term (i.e., a doubling of the solute mass source 
results in a doubling of mass flux). In addition, the flow and transport processes in the UZ and 
the SZ must be independent of one another. 
Radioactive decay is also applied to radionuclide mass flux calculated with the convolution 
integral computer code SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 
[164180]) in the TSPA analyses. The convolution integral method consists of numerical 
integration that accounts for the contributions to the outlet radionuclide mass flux from a series 
of time intervals. Because the travel time for each contribution to radionuclide mass flux is 
known, the loss of radionuclide mass (and consequent decrease in mass flux) during transport is 
calculated by first-order decay for that time interval. 
The effects of climate change on radionuclide transport in the saturated zone are incorporated 
into the convolution integral analysis in the TSPA by assuming instantaneous change from one 
steady-state flow condition to another steady-state condition in the saturated zone. Changes in 
climate state are assumed to affect the magnitude of groundwater flux through the saturated zone 
system but have a negligible impact on flowpaths. The effect of changes in groundwater flux is 
incorporated into the convolution method by scaling the timing of radionuclide mass 
breakthrough curves proportionally to the change in saturated zone specific discharge. 
Three climate states are defined for the period from repository closure to 10,000 years in the 
future in the TSPA-SR calculations (CRWMS M&O 2000 [153246], p. 3-25). For the base-case 
TSPA analyses, present-day climatic conditions are modeled to occur from the present to 600

MDL-NBS-HS-000021, REV 00 53 July, 2003 
years in the future, monsoonal conditions are imposed from 600 years to 2000 years in the future, 
and glacial-transition climatic conditions occur from 2000 years to 10,000 years. The monsoonal 
climatic state is wetter than present-day conditions and the glacial-transition state is 
conceptualized to be wetter and cooler than present-day conditions. Note that the glacialtransition 
climate state is approximately equivalent to the long-term average climate state, as 
referenced in CRWMS M&O 1998 [100365], Table 8-16, p. T8-20. 
Estimates of the scaling factors for groundwater flux in the SZ under alternative climatic 
conditions are based on simulations using the SZ regional-scale flow model (DAgnese et al., 
1999 [120425]; CRWMS M&O 1998 [100365]) and on the infiltration for the UZ site-scale flow 
model (BSC 2003 [164431], Section 6.1.4). Simulations using the SZ regional-scale flow model 
were conducted for the past-climate state that likely existed about 21,000 years ago (DAgnese et 
al., 1999 [120425]). This climatic state approximately corresponds to the glacial-transition state, 
as defined for TSPA-SR calculations. A comparison of the groundwater flux in the SZ near 
Yucca Mountain under past-climate conditions (i.e., 21,000 years ago) using the SZ regionalscale 
model indicates that the simulated flux under the past-climate conditions was 
approximately 3.9 times the flux of present-day simulations, as shown in Table 6-5. 
Simulations of SZ flow under monsoonal climatic conditions have not been performed using the 
SZ regional-scale flow model. Information on the increased infiltration through the UZ sitescale 
flow model is used as the basis for estimating flux increases in the SZ for monsoonal 
conditions (DTN: LB990801233129.015 [118730]). Values of total infiltration in the area of the 
UZ site-scale flow model (second column of Table 6-5) are taken from the total of specified 
mass flow in the GENER card of the TOUGH2 input files pa_chm1.dat, pa_glam1.dat, 
and pa_monm1.dat. Similarly, the total infiltration through the UZ site-scale flow model for 
present and glacial-transition climatic conditions is calculated (DTN: LB990801233129.004 
[117129] and DTN: LB990801233129.009 [118717]). Note in Table 6-5 that the ratio of 
glacial-transition infiltration in the UZ model to the present-day infiltration is the same value as 
the estimate of increased SZ groundwater flux from the SZ regional-scale flow model (i.e., 3.9). 
This correspondence suggests that the UZ infiltration ratio provides a reasonable estimate of the 
flux ratio for the SZ. Thus, the values of the SZ groundwater flux ratio for TSPA simulations of 
future climatic states are derived from the estimates of increased UZ infiltration at Yucca 
Mountain. For monsoonal climatic conditions, the ratio of UZ infiltration to the infiltration for 
present-day conditions is 2.7 (see Table 6-5) and this value is applied to the SZ flux as well. The 
values of flux ratio used as scaling factors of SZ flow and transport for alternative climate states 
are given in the last column of Table 6-5.

MDL-NBS-HS-000021, REV 00 54 July, 2003 
Table 6-5. Groundwater Flow Scaling Factors for Climate Change 
Climate State 
Infiltration, UZ 
Model (Mean 
Case) (kg/s) 
Ratio to Present 
Climate, UZ 
Model 
SZ Groundwater Flux 
Ratio from SZ Regional- 
Scale Model 
SZ Groundwater 
Flux Ratio for TSPA 
Simulations 
Present-Day 5.64 a 1.0 1.0 1.0 
Glacial- 
Transition 22.0 b 3.9 3.9 d 3.9 
Monsoonal 15.2 c 2.7 N/A 2.7 
a DTN: LB990801233129.004 [117129] 
b DTN: LB990801233129.009 [118717] 
c DTN: LB990801233129.015 [118730] 
d CRWMS M&O 1998 [100365], Table 8-16, p. T8-20. 
SZ 1-D Transport Model 
The SZ 1-D Transport Model is implemented with the GoldSim v. 7.50.100 software code (STN: 
10344-7.50.100-00, BSC 2003 [161572]) in the TSPA simulator as a series of pipes. The 
same radionuclide transport processes that are simulated in the three-dimensional SZ Transport 
Abstraction Model (e.g., sorption, matrix diffusion in fractured units, and colloid-facilitated 
transport) are analyzed in the pipe segments, with the exception of transverse dispersion. 
Transverse dispersion is not very important to the modeling results, given the assumption that all 
radionuclide mass is captured by the wells of the receptor group. Although strict consistency 
between the SZ 1-D Transport Model and the three-dimensional SZ Transport Abstraction Model 
is not possible, average groundwater flow and transport characteristics of the SZ Transport 
Abstraction Model are used to define flow and transport properties within the pipe segments of 
the one-dimensional model. Average specific discharge along different segments of the flowpath 
is estimated using the 3-D SZ Transport Abstraction Model. The resulting values of average 
specific discharge are applied to the individual pipe segments in the one-dimensional transport 
model. 
6.5.1 Mathematical Description of Base-Case Conceptual Model 
6.5.1.1 SZ Transport Abstraction Model 
The mathematical descriptions of the processes of groundwater flow and radionuclide transport 
in the SZ Site-Scale Flow Model (BSC 2003 [162649], Section 6.5) and the SZ Site-Scale 
Transport Model (BSC 2003 [162419], Section 6.5.2) are presented in the corresponding reports

MDL-NBS-HS-000021, REV 00 55 July, 2003 
for these models. The SZ Site-Scale Flow Model forms the direct basis for the SZ Site-Scale 
Transport Model and the SZ Site-Scale Transport Model forms the direct basis for the SZ 
Transport Abstraction Model. Therefore, the mathematical bases for those models, as 
implemented by the FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]), 
apply to the SZ Transport Abstraction Model and are not reproduced here. 
The particle tracking method is used to simulate radionuclide transport in the SZ Transport 
Abstraction Model (see BSC 2003 [162419], Section 6.5.2 for description of the particle tracking 
method). This method exhibits very limited numerical dispersion relative to standard finitedifference 
and finite-element methods of solute transport simulation. Consequently, particle 
tracking is appropriate for use in the SZ Transport Abstraction Model, in which the spatial 
discretization (500 m) exceeds the values of dispersivity being simulated for many of the model 
realizations. 
Convolution Integral 
The convolution integral method is used to couple the radionuclide transport in the UZ with the 
simulations of mass transport in the SZ in the TSPA analyses. The convolution integral method 
takes the radionuclide mass breakthrough curve for a continuous, unitary mass source from the 
SZ and the time-varying radionuclide mass from the UZ as inputs. The output is the timevarying 
radionuclide mass exiting the SZ. 
The mathematical expression for the convolution integral method is written as: 
. ' 
' 
' - = 
t 
p 
sz 
uz sz t d 
m 
t M t t m t M 
0 
) ( 
) ( ) ( & (Equation 6-1) 
where Msz(t) is the radionuclide mass flux downstream in the SZ [M], t is time [T], ) (t muz & is the 
time dependent radionuclide mass flux entering the SZ from the UZ [M], t' is a time lag [T], and 
) (t M ' is the derivative of the downstream radionuclide mass flux-time response curve [M] to a 
step input of mass mp [M]. This expression is taken from the convolution integral for 
concentration (CRWMS M&O 1998 [100365], p. 8-39) and rewritten in terms of radionuclide 
mass. 
Correction of Retardation 
The retardation factor for linear sorption of radionuclides during transport in porous media is 
defined as (Freeze and Cherry 1979 [101173], p. 404):
d 
b 
f K R 
f 
. 
+ = 1 (Equation 6-2) 
where Rf is the retardation factor in the porous media [-], .b 
is the bulk density [M/L3], f is the 
porosity of the porous media [-], and Kd is the distribution coefficient [L3/M]. The FEHM v. 
2.20 software code (STN: 10086-2.20-00, LANL 2003 [161725]) to be used in the SZ Transport 
Abstraction Model automatically calculates Rf based on input values of .b 
, f, and Kd.

MDL-NBS-HS-000021, REV 00 56 July, 2003 
Effective porosity ( fe 
) [-] is a macroscopic parameter that helps account for discrete flow paths 
and channelized flow (see Section 6.5.2.3). The effective porosity parameter in the alluvium is 
used to correctly calculate the pore velocity of groundwater. Effective porosity is not intended to 
be used to estimate surface areas in Equation 6-2. Therefore, it is necessary to adjust another 
parameter in the equation to compensate for the lower effective porosity that is entered. If this 
were not done, then the calculated values of Rf would be overestimated, given that values of Kd 
used in Equation 6-2 are based on laboratory-scale measurements. For the SZ Transport 
Abstraction Model and the SZ 1-D Transport Model, the Kd values for the alluvium are adjusted 
according to the following relationship (CRWMS M&O 1998 [100365], Equation 8-4, p. 8-55): 
T
e 
d 
new 
d K K 
f
f 
 = (Equation 6-3) 
where Kd
new is the adjusted distribution coefficient [L3/M] and fT is the total porosity [-]. The 
total porosity is 0.30, which is the upper bound of the effective porosity uncertainty distribution 
and also documented in Section 6.5.2.14. 
Colloid-Facilitated Transport 
For colloid-facilitated radionuclide transport in which radionuclides are reversibly attached to 
colloids, a partition coefficient is defined to represent the potential for enhanced migration of 
radionuclides in association with colloids. This unitless constant, Kc , is defined as: 
coll 
coll 
d c C K K = (Equation 6-4) 
where Kd
coll is the sorption coefficient for the radionuclide onto colloids [L3/M] and Ccoll is the 
concentration of colloids in the groundwater [M/L3]. The conceptual model of colloid-facilitated 
transport of reversibly sorbed radionuclides is described in Section 6.3 and the underlying 
theoretical derivation of the model is presented in CRWMS M&O 1997 [124052], pp. 8-32 to 8- 
36. 
For equilibrium conditions in a porous medium, the effective sorptive capacity of the aquifer is 
reduced when the groundwater colloids carry a significant fraction of radionuclide mass in the 
system. The values of the sorption coefficient in the alluvium and undifferentiated valley fill 
hydrogeologic units for the colloid-facilitated transport of radionuclides with the Kc model are 
modified by the value of Kc , according to the relationship: 
) 1 ( c 
d adjusted 
d K 
K K 
+ 
= (Equation 6-5) 
as derived from Equation 6-2 and CRWMS M&O 1998 [100365], Equation 8-8, p. 8-54 and 8- 
56, and assigning the retardation factor for colloids with reversibly attached radionuclides a 
value of 1. Kd
adjusted is the adjusted distribution coefficient [L3/M] to account for reversible 
sorption onto colloids.

MDL-NBS-HS-000021, REV 00 57 July, 2003 
For transport in fractured media, the effective diffusion coefficient into the rock matrix is 
reduced due to the affinity of radionuclides for sorption onto colloids in the fractures. To 
evaluate this effect with constant velocity and dispersion, consider the one-dimensional 
advection-dispersion equation for a solute in the fractures (BSC 2003 [162419], Section 6.5.2) 
with a term for retardation and a final term added for diffusion into the matrix: 
b
q 
x
C v 
x
C D 
t 
C R f f - 
. 
. 
- 
. 
. 
= 
. 
. 
2 
2 
, (Equation 6-6) 
where f f R , is the retardation factor in the fractures [-], D is the dispersion coefficient in the 
fracture [L2/T], C is aqueous concentration of the solute [M/L3], t is time [T], x is distance [L], v 
is groundwater velocity in the fractures [L/T], q is the diffusive flux into the rock matrix 
[M/L2T], and b is the half-aperture of the fracture [L]. For that part of the solute mass that is 
sorbed onto colloids the advection-dispersion equation is: 
x 
C v 
x 
C D 
t 
C R 
coll coll coll 
coll . 
. 
- 
. 
. 
= 
. 
. 
2 
2 
(Equation 6-7) 
where coll R is the retardation factor of the colloids in the fractures [-] and coll C is the 
concentration of the solute in the groundwater [M/L3]. Adding the two advection dispersion 
equations and using the relationship that Kc = coll C /C, the combined advection-dispersion 
equation for colloid-facilitated transport of radionuclides reversibly sorbed onto colloids can be 
written as: 
) 1 ( 1 2 
2 
, 
c c 
coll c f f 
K b 
q 
x
C v 
x
C D 
t 
C 
K 
R K R 
+ 
- 
. 
. 
- 
. 
. 
= 
. 
. 
. .. 
. 
. .. 
. 
+
+ 
(Equation 6-8) 
As seen by comparing this equation with Equation 6-6, the term for diffusive mass flux into the 
rock matrix is modified by dividing by the factor (1+Kc) to account for the equilibrium colloidfacilitated 
transport. One approach would be to adjust the value of fracture half-aperture by 
multiplying by the factor (1+Kc). An alternative approach is possible based on examination of 
the . term in the analytical solution for transport in fractures with matrix diffusion by Sudicky 
and Frind 1982 [105043], Equation 34, p. 1638. In the . term, adjusting the value of b by 
multiplying it by the factor (1+Kc) is equivalent to dividing the effective diffusion coefficient in 
the matrix by the factor (1+Kc)2. In the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model the values of effective diffusion coefficient for radionuclides subject to the Kc 
model of colloid-facilitated transport are adjusted according to the relationship: 
2 ) 1 ( c 
e adjusted 
e K 
D D 
+ 
= (Equation 6-9) 
where De
adjusted is the adjusted effective diffusion coefficient in the rock matrix [L2/T] and De is 
the effective diffusion coefficient in the rock matrix [L2/T].

MDL-NBS-HS-000021, REV 00 58 July, 2003 
For colloid-facilitated radionuclide transport in which radionuclides are irreversibly attached to 
colloids, most of the colloids (and attached radionuclides) are delayed during transport in the SZ 
by a retardation factor. A small fraction of colloids with irreversibly attached radionuclides are 
subject to rapid transport without retardation, as described in BSC 2003 [163932], Section 6.6. 
In fractured volcanic units, the retardation factor for the majority of colloids is applied directly in 
the SZ Transport Abstraction Model input files as an input parameter. In porous medium, it is 
not possible to directly specify a retardation factor in the SZ Transport Abstraction Model; 
therefore, an effective sorption coefficient is specified that results in the sampled value of the 
retardation factor. In the porous medium of the alluvium, the colloid retardation factor in the 
alluvium units is converted to a value of effective sorption coefficient according to the 
relationship: 
b 
e f eff 
d 
R 
K 
. 
f ) 1 ( - 
= (Equation 6-10) 
where Kd
eff is the effective Kd in the porous media [L3/M]. 
Retardation in Fracture Zones 
As described in the conceptual model of transport in fractured media of the SZ (Section 6.3.1), 
relatively small blocks of rock matrix or rubblized material in fracture zones may participate in 
radionuclide transport via diffusion on a short time scale. The impact of rapid diffusion into 
small matrix blocks on the calculation of average linear velocity of groundwater is captured with 
a correspondingly larger value of flowing interval porosity for the volcanic units. In this 
conceptualization, the flowing interval porosity includes the fracture porosity with flowing 
groundwater plus it may include the matrix porosity of the small matrix blocks within the 
fracture zones. The possibility of small matrix blocks within fracture zones is encompassed 
within a range of uncertainty in transport behavior in fractured tuff. If this process of rapid 
diffusion occurs, the sorptive capacity of the small matrix blocks would also be important to the 
transport of sorbing radionuclides. This is handled in the following way. If the flowing interval 
porosity ( ff 
) [-] is less than the average fracture porosity ( avg 
f f) [-], then groundwater flow is 
conceptualized to occur only in fractures and no retardation due to sorption within small matrix 
blocks occurs. If the flowing interval porosity is greater than the average fracture porosity, then 
the retardation factor within the fracture domain due to sorption within small matrix blocks ( f R' ) 
is calculated as: 
m 
dm b 
f 
K fraction 
R 
f 
. ) * ( 
1+ = ' (Equation 6-11) 
where Kdm is the sorption coefficient in the rock matrix [L3/M], fm is the rock matrix porosity [-] 
and fraction is calculated as:

MDL-NBS-HS-000021, REV 00 59 July, 2003 
) ( 
) ( 
avg 
f m 
avg 
f f fraction 
f f 
f f 
-
- 
= (Equation 6-12) 
The term fraction [-] describes the fraction of the entire rock matrix that is accessible to rapid 
matrix diffusion within the small matrix blocks of the fracture zone. Typically, the value of 
fraction would be small for the range of uncertainty in flowing interval porosity. For example, if 
the flowing interval porosity is 0.01 (80th percentile from Figure 6-13), the rock matrix porosity 
is 0.20, and the average fracture porosity is 0.001, then the value of fraction is 0.045. This 
means that 4.5% of the total rock matrix is available for direct interaction with radionuclide 
advection and sorption in this example. 
6.5.1.2 SZ 1-D Transport Model 
The SZ 1-D Transport Model provides simulation results for several radionuclide chains that are 
not simulated in the SZ Transport Abstraction Model. The simplified decay chains considered 
(CRWMS M&O 2000 [153246], Figure 3.5-5, p. F3-67) consist of the following. 
1) Actinium series: 
Pa U Pu Am 231 235 239 243 . . . 
2) Neptunium Series: 
Th U Np Am 229 233 237 241 . . . 
3) Thorium Series: 
Th U Pu 232 236 240 . . 
4) Uranium Series: 
Ra Th U 
Pu 
U Pu 226 230 234 
238 
238 242 
. . . 
. 
The radionuclide decay chain analysis is simplified in a manner that overestimates the 
concentration of daughter radionuclides by calculating secular equilibrium between the final 
daughter products and their parents in three of these chains. 227Ac is in secular equilibrium with 
231Pa in the actinium chain at the downstream end of the SZ analysis. 228Ra is in secular

MDL-NBS-HS-000021, REV 00 60 July, 2003 
equilibrium with 232Th in the thorium series. 210Pb is in secular equilibrium with 226Ra in the 
uranium series. 
In the model setup, radionuclides 241Am, 243Am, 239Pu, 240Pu, and 242Pu are subject to transport as 
irreversibly attached to colloids; and 243aAm, 238Pu, 239aPu, 240aPu, 242aPu, 231Pa, 229Th, 230Th, and 
232Th are subject to the equilibrium colloid-facilitated transport mode. The one-dimensional 
model is set up using the Pathway Component of the Contaminant Transport Module in the 
GoldSim Graphical Simulation Environment. The pipe component is able to simulate advection, 
longitudinal dispersion, retardation, decay and ingrowth, and matrix diffusion (Figure 6-5) 
(Miller and Kossik 1998 [100449]). 
Figure 6-5. Transport Processes Simulated in One-Dimensional Pipe Pathways in the GoldSim v. 
7.50.100 Software Code (STN: 10344-7.50.100-00), BSC 2003 [161572] 
Each pipe in the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 
[161572]) represents a one-dimensional mass transport model with uniform properties. The ratio 
of the volumetric outflow rate to the cross-sectional area of each pipe pathway represents the 
specific discharge in the pipe. A mass flux loading at the beginning of the first pipe is the source 
of the radionuclides that are transported along the connected pipes. The GoldSim v. 7.50.100 
software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) also provides a graphical

MDL-NBS-HS-000021, REV 00 61 July, 2003 
container that isolates all of the model components in one compartment to better organize the 
model components graphically on screen. 
Transport from the four source regions in the SZ are represented by four sets of connected pipes 
in the SZ 1-D Transport Model. Each set of pipes consists of three pipe segments. The first 
segment extends from the center of the corresponding source region beneath the repository to a 
distance of 5 km. The second pipe segment extends from 5 km to the contact between the 
volcanic aquifer and the alluvium. The third pipe segment extends from the contact between the 
volcanic aquifer and the alluvium to the regulatory boundary with the accessible environment. 
The mathematical representation of radionuclide transport in the SZ 1-D Transport Model is the 
same as that in the SZ Transport Abstraction Model, as presented in Equation 6-2 to Equation 6- 
5 and Equation 6-9. There are some differences in the mathematical implementation between the 
models with regard to retardation in fractures, as described below. 
In the SZ 1-D Transport Model the retardation factor in fractures cannot be directly specified. 
The retardation in fractures for colloids with irreversibly attached radionuclides is calculated 
according to the retardation factor (CORVO) of the colloids using the fracture coating option in 
the GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]). The 
equation for calculating the retardation factor in the fracture with the coating on fracture surface 
is: 
) ( 1 , , c s c c 
p m 
s m K 
A
PT R f . 
f 
+ + = (Equation 6-13) 
where Rm,s is the retardation factor due to the coating [-], P is the perimeter of the fracture 
pathway [L], T is the thickness of the coating [L], Am is the cross-sectional area of the mobile 
zone [L2], p f is the porosity in the pipe (equal to 1.0 for fractures), .c 
is the dry bulk density of 
the coating material [M/L3], Kc,s is the sorption coefficient of the coating [L3/M], and c f is the 
porosity of the coating material [-]. For a given value of Rm,s, the sorption coefficient is specified 
by rearranging Equation 6-13: 
( ) .. 
. 
.. 
. 
- - = c s m 
p m 
c 
s c R 
PT 
A 
K f 
f 
. 
1 1 
, , (Equation 6-14) 
It should be noted that representation of retardation in the fractures using the coating option in 
GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) is for 
mathematical convenience only. The retardation factor for colloids with irreversibly attached 
radionuclides is specified as an input parameter in the SZ 1-D Transport Model and a 
corresponding value of the sorption coefficient of the fracture coating is calculated using 
Equation 6-14 within the parameter definitions used in the model. This does not constitute an 
inconsistency in the conceptual model between the SZ 1-D Transport Model and the SZ 
Transport Abstraction Model. The values of the parameters T and c f are chosen to be realistic, 
but are essentially irrelevant because they are only used to back-calculate the value of Kc,s . The 
value of the fracture perimeter is 2 m because the cross section of the pipes in the SZ 1-D

MDL-NBS-HS-000021, REV 00 62 July, 2003 
Transport Model is specified as 1 m by 1m and a single fracture within the pipe would have a 
corresponding perimeter of 2 m. 
There is no matrix diffusion in fractured media for colloids with irreversibly attached 
radionuclides. Consequently, there is no sorption in the matrix for radionuclides irreversibly 
attached to colloids. This is simulated by specifying an arbitrarily small value of matrix porosity 
(~10-10) and zero sorption coefficients for these species in the volcanic matrix. The matrix 
diffusion coefficient for those radionuclides that do experience matrix diffusion is implemented 
by calculating an effective tortuosity, based on the sampled value of effective diffusion 
coefficient and the free water diffusion coefficient. The free water diffusion coefficient is 
adjusted by a factor approximately equivalent to the volcanic matrix porosity, using the 
parameter Adjusted_Diffusion_Free to match results from the three-dimensional SZ Site-Scale 
Transport Model. 
Values of specific discharge for segments represented by pipe pathways in the SZ 1-D Transport 
Model vary along the flowpath from the repository. A plot of the particle paths in the SZ 
Transport Abstraction Model indicates that the flowpath length through the alluvium varies, 
depending on uncertainty in the SZ flow field (see Figure 6-6). This uncertainty is represented 
by variation in the geometry of the alluvial uncertainty zone in the SZ Transport Abstraction 
Model. Specifically, the lengths of the flow paths in the volcanic units and the alluvium are 
functions of the western boundary of the alluvial uncertainty zone (as controlled by the FPLAW 
stochastic parameter). Secondarily, this variability is the result of different flowpaths (i.e., width 
of the plume). The lengths of the flow paths are also functions of the anisotropy ratio in 
horizontal permeability of the volcanic units (as controlled by the HAVO stochastic parameter) 
(see Figure 6-6). In the one-dimensional radionuclide transport model, the length of the alluvium 
(out to 18-km distance) is varied from 2 km to 10 km as functions of the FPLAW and HAVO 
parameter values and the source region beneath the repository (see Table 6-7 and supporting 
text).

MDL-NBS-HS-000021, REV 00 63 July, 2003 
535000 540000 545000 550000 555000 560000 
UTM Easting (m) 
4050000 
4055000 
4060000 
4065000 
4070000 
4075000 
4080000 
4085000 
4090000 
UTM Northing (m) 
Source for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 
Note: Green lines, purple lines, blue lines, yellow lines, and red lines show simulated particle paths for horizontal 
anisotropy values of 0.05, 0.20, 1.0, 5.0, and 20.0, respectively. 
Figure 6-6. Simulated Particle Paths for Different Values of Horizontal Anisotropy in Permeability

MDL-NBS-HS-000021, REV 00 64 July, 2003 
The SZ 1-D Transport Model represents a significant simplification of the three-dimensional 
groundwater flow system, relative to the SZ Transport Abstraction Model. To accurately capture 
the three-dimensional characteristics of the SZ flow and transport system in this one-dimensional 
model, the SZ 1-D Transport Model is divided into three sets of pipe segments. The lengths 
and groundwater flow rates of these pipe segments are estimated from the SZ Transport 
Abstraction Model. 
Average specific discharge along different segments of the flow path is estimated using the SZ 
Transport Abstraction Model in the following way. 1000 particles are released beneath the 
repository in the simulation, matrix diffusion is not used, and all porosities are assigned a value 
of 1.0 for the assessment of average specific discharge. The "average specific discharge" is 
calculated by dividing the flow path length by the 50th percentile of travel times among the 
particles, for that flow path segment. The average specific discharge also varies as a function of 
the horizontal anisotropy (parameter HAVO). The resulting values of average specific 
discharge, as used in the SZ 1-D Transport Model, are shown in Table 6-6. The values in Table 
6-6 are input as a GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 
[161572]) look-up table in the SZ 1-D Transport Model. Also note that the values of specific 
discharge scale linearly with the groundwater specific discharge scaling factor (parameter 
GWSPD) for the consideration of uncertainty in specific discharge. The values of specific 
discharge within the three pipe segments are calculated within the model by interpolating 
between the values of HAVO and scaling by the value of GWSPD. The volumetric flow rate is 
the same for all segments in the SZ 1-D Transport Model and the variations in specific discharge 
along the flow path are incorporated by varying the cross-sectional areas of the pipe segments. 
Table 6-6. Average Specific Discharge in Flow Path Segments 
Average Specific Discharge (m/year) HAVO 
0-5 km 5-13 km 13-18 km 
0.05 0.312 7.50 1.936 
1.00 0.536 1.824 2.357 
5.00 0.722 2.694 2.793 
20.00 0.870 4.465 3.183 
The flow path length of each pipe segment in the SZ 1-D Transport Model varies as a function of 
FPLAW, HAVO, and the source region from which the radionuclide source originates beneath 
the repository. The first pipe segment is 5 km in length for all cases. The second pipe segment 
represents that portion of the flow path from 5 km distance to the contact between the volcanic 
units and the alluvium in the SZ. The third pipe segment represents the portion of the flow path 
from the contact between the volcanic units and the alluvium out to the regulatory boundary to 
the accessible environment. The lengths of the second and third pipe segments were estimated 
from the particle tracking results of the 3-D SZ Transport Abstraction Model, as shown in Figure 
6-6 and as summarized in Table 6-7. The estimated pipe segment lengths are shown in Table 6-7 
for differing values of HAVO and for the four source regions. Each entry in the table contains a 
range of values in length, where the minimum value shown for the 5-13 km pipe segment

MDL-NBS-HS-000021, REV 00 65 July, 2003 
(second pipe segment) corresponds to FPLAW equal to 1.0 and the maximum value corresponds 
to FPLAW equal to 0.0. By contrast, the minimum value of length for the 13-18 km pipe 
segment (third pipe segment) corresponds to FPLAW equal to 0.0 and the maximum value 
corresponds to FPLAW equal to 1.0. In other words, the maximum length of the flow path in the 
alluvium corresponds to the maximum westerly extent of the alluvium uncertainty zone and the 
minimum length of the flow path in the alluvium corresponds to the minimum westerly extent of 
the alluvium uncertainty zone. The values in Table 6-7 are input as a GoldSim v. 7.50.100 
software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) look-up table in the SZ 1-D 
Transport Model. 
Table 6-7. Flow Path Lengths of Pipe Segments 
Minimum and Maximum Flow Path Lengths of Pipe Segments (km) 
Source Region 1 Source Region 2 Source Region 3 Source Region 4 HAVO 
5-13 km 13-18 km 5-13 km 13-18 km 5-13 km 13-18 km 5-13 km 13-18 km 
0.05 12.0 - 
14.5 
7.5  10.0 12.0  
14.0 
7.0  9.0 13.0  
16.0 
3.0  6.0 12.5  
15.0 
3.5  6.0 
1.00 12.0  
14.0 
5.5  7.5 12.0  
14.5 
4.5  7.0 10.0  
13.5 
2.0  5.5 10.0  
12.0 
3.0  5.0 
5.00 12.5  
14.5 
3.0  5.0 11.5  
14.0 
3.0  5.5 10.5  
14.0 
1.0  4.5 10.5  
12.5 
2.0  4.0 
20.00 12.5  
14.5 
2.5  4.5 11.5  
14.0 
3.0  5.5 10.5  
14.0 
1.0  4.5 10.5  
12.5 
2.0  4.0 
6.5.2 Base-Case Model Inputs 
The SZ Transport Abstraction Model and the SZ 1-D Transport Model include uncertainty 
through stochastic simulations of uncertain parameters. Parameter uncertainties are quantified 
through uncertainty distributions, which numerically represent our state of knowledge about a 
particular parameter on a scale of the model domain. The uncertainty distribution (either 
cumulative distribution function (CDF) or probability density function (PDF)) of a parameter, 
represents what we know and what we do not know about the parameter and reflects the current 
knowledge of the range and likelihood of the appropriate parameter values when used in these 
models (BSC 2002 [158794], p. 45). The uncertainty distributions incorporate uncertainties 
associated with field or laboratory data, knowledge of how the parameter will be used in the 
model, and theoretical considerations. Geologic uncertainty is incorporated with regard to the 
location of the contact between the tuff and alluvium at the water table (see Section 6.5.2.2) In 
some cases, parameters are assigned constant values because radionuclide transport is relatively 
insensitive to the parameter or the uncertainty is relatively small. Constant parameters are

MDL-NBS-HS-000021, REV 00 66 July, 2003 
defined to vary from one hydrogeologic unit to another, but for a given hydrogeologic unit, the 
parameter remains constant for all realizations. The development and justification for the 
parameter uncertainty distributions are discussed below. See Table 6-8 for a comprehensive list 
of the models/analyses inputs used in the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model. The unit numbers given in Table 6-8 are defined by hydrogeologic unit in 
Table 6-9. Please note that parameter values are developed for the 19 hydrogeologic units in 
Table 6-9 for completeness; however, 18 units are included in the SZ Site-Scale Flow Model, the 
SZ Site-Scale Transport Model, and the SZ Transport Abstraction Model. The valley-fill 
confining unit has a very small volume relative to other units in the model domain and 
occurrences of this unit do not occur along the flow path from the repository. Consequently, it is 
not included in the models as a separate unit. 
Table 6-8. Model/Analyses Inputs Used in the SZ Transport Abstraction Model 
and SZ 1-D Transport Model 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
KDNPVO Neptunium 
sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 0.0 
0.05 1.0 
0.90 1.6 
1.0 6.0 
ml/g Epistemic 
KDNPAL Neptunium 
sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 1.8 
0.05 4.0 
0.95 8.7 
1.0 13.0 
ml/g Epistemic 
KDSRVO Strontium sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 20. 
Maximum 400. 
ml/g Epistemic 
KDSRAL Strontium sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 20. 
Maximum 400. 
ml/g Epistemic 
KDUVO Uranium sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 0.0 
0.05 5.4 
0.95 6.9 
1.0 20.0 
ml/g Epistemic

MDL-NBS-HS-000021, REV 00 67 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
KDUAL Uranium sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 1.7 
0.05 2.9 
0.95 6.3 
1.0 8.9 
ml/g Epistemic 
KDRAVO Radium sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 100. 
Maximum 1000. 
ml/g Epistemic 
KDRAAL Radium sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
Uniform: 
Minimum 100. 
Maximum 1000. 
ml/g Epistemic 
KD_Pu_Vo Plutonium sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 10. 
0.25 75. 
0.95 100. 
1.0 300. 
ml/g Epistemic 
KD_Pu_Al Plutonium sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
Beta: 
Mean 100. 
Standard Deviation 15. 
Minimum 50. 
Maximum 300. 
ml/g Epistemic 
KD_Am_Vo Americium 
sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 
1500. 
Minimum 1000. 
Maximum 10000. 
ml/g Epistemic 
KD_Am_Al Americium 
sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 5500. 
Standard Deviation 
1500. 
Minimum 1000. 
Maximum 10000. 
ml/g Epistemic 
KD_Cs_Vo Cesium sorption 
coefficient in 
volcanic units 
LA0302AM831341.001 
[163556] 
CDF: 
Probability Value 
0.0 100. 
0.05 3700. 
1.0 7500. 
ml/g Epistemic

MDL-NBS-HS-000021, REV 00 68 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
KD_Cs_Al Cesium sorption 
coefficient in 
alluvium 
LA0302AM831341.001 
[163556] 
Truncated Normal: 
Mean 728. 
Standard Deviation 464. 
Minimum 100. 
Maximum 1000. 
ml/g Epistemic 
FISVO Flowing interval 
spacing in 
volcanic units 
SN9907T0571599.001 
[122261] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.087 
0.05 0.588 
0.25 1.00 
0.50 1.29 
0.75 1.58 
0.95 1.90 
1.0 2.62 
m Epistemic 
CORAL Colloid retardation 
factor in alluvium 
LA0303HV831352.004 
[163559] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.903 
0.331 0.904 
0.50 1.531 
1.0 3.715 
NA Epistemic 
CORVO Colloid retardation 
factor in volcanic 
units 
LA0303HV831352.002 
[163558] 
CDF: (Log-transformed) 
Probability Value 
0.0 0.778 
0.15 0.779 
0.25 1.010 
0.50 1.415 
0.80 1.778 
1.0 2.903 
NA Epistemic 
HAVO Ratio of horizontal 
anisotropy in 
permeability 
SN0302T0502203.001 
[163563] 
CDF: 
Probability Value 
0.0 0.05 
0.0042 0.2 
0.0168 0.4 
0.0379 0.6 
0.0674 0.8 
0.10 1.0 
0.60 5. 
0.744 8. 
0.856 11. 
0.936 14. 
0.984 17. 
1.0 20. 
NA Epistemic

MDL-NBS-HS-000021, REV 00 69 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
LDISP Longitudinal 
dispersivity 
MO0003SZFWTEEP.000 
[148744] 
Truncated Normal: (Logtransformed) 
Mean 2.0 
Standard Deviation 0.75 
m Epistemic 
Kd_Pu_Col Plutonium sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e3 
0.04 5.e3 
0.12 1.e4 
0.37 5.e4 
0.57 1.e5 
0.92 5.e5 
1.0 1.e6 
ml/g Epistemic 
Kd_Am_Col Americium 
sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e4 
0.07 5.e4 
0.17 1.e5 
0.40 5.e5 
0.60 1.e6 
0.92 5.e6 
1.0 1.e7 
ml/g Epistemic 
Kd_Cs_Col Cesium sorption 
coefficient onto 
colloids 
SN0306T0504103.006 
[164131] 
CDF: 
Probability Value 
0.0 1.e2 
0.2 5.e2 
0.45 1.e3 
0.95 5.e3 
1.0 1.e4 
ml/g Epistemic 
Conc_Col Groundwater 
concentration of 
colloids 
SN0306T0504103.005 
[164132] 
CDF: (Log-transformed) 
Probability Value 
0.0 -9.0 
0.50 -7.0 
0.75 -6.0 
0.90 -5.0 
0.98 -4.3 
1.0 -3.6 
g/ml Epistemic 
R_U_Kd Correlation 
coefficient for U Kd 
in volcanic units 
and alluvium 
LA0302AM831341.001 
[163556] 
0.75 ml/g N/A 
R_Np_Kd Correlation 
coefficient for Np 
Kd in volcanic 
units and alluvium 
LA0302AM831341.001 
[163556] 
0.75 ml/g N/A

MDL-NBS-HS-000021, REV 00 70 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
R_Pu_Kd Correlation 
coefficient for Pu 
Kd in volcanic 
units and alluvium 
LA0302AM831341.001 
[163556] 
0.50 ml/g N/A 
R_U_Np Correlation 
coefficient for U Kd 
and Np Kd 
LA0302AM831341.001 
[163556] 
0.50 ml/g N/A 
FPLAW Western boundary 
of alluvial 
uncertainty zone 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 
FPLAN Northern 
boundary of 
alluvial uncertainty 
zone 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 
NVF19 Effective porosity 
in shallow 
alluvium 
Internal to this report Truncated Normal: 
Mean 0.18 
Standard Deviation 
0.051 
Minimum 0.00 
Maximum 0.30 
N/A Epistemic 
NVF7 Effective porosity 
in undifferentiated 
valley fill 
Internal to this report Truncated Normal: 
Mean 0.18 
Standard Deviation 
0.051 
Minimum 0.00 
Maximum 0.30 
N/A Epistemic 
FPVO Fracture porosity 
in volcanic units 
Internal to this report CDF: (Log-transformed) 
Probability Value 
0.0 -5.0 
0.05 -4.0 
0.50 -3.0 
0.80 -2.0 
1.0 -1.0 
N/A Epistemic 
DCVO Effective diffusion 
coefficient in 
volcanic units 
Internal to this report CDF: (Log-transformed) 
Probability Value 
0.0 -11.3 
0.08 -10.7 
0.50 -10.3 
0.83 -9.9 
1.0 -9.3 
m^2/s Epistemic

MDL-NBS-HS-000021, REV 00 71 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
GWSPD Groundwater 
specific discharge 
multiplier 
Internal to this report CDF: (Log-transformed) 
Probability Value 
0.0 -1.477 
0.10 -0.477 
0.50 0.0 
0.90 0.477 
1.0 1.0 
N/A Epistemic 
bulkdensity Bulk density of 
alluvium 
Internal to this report Normal: 
Mean 1910 
Standard Deviation 78 
kg/m3 Epistemic 
SRC1X 
SRC1Y 
SRC2X 
SRC2Y 
SRC3X 
SRC3Y 
SRC4X 
SRC4Y 
Source regions 
beneath the 
repository 
Internal to this report Uniform: 
Minimum 0.0 
Maximum 1.0 
N/A Epistemic 
and Aleatory 
Alluv_xmin1 UTM minimum 
easting, SW 
corner alluvial 
uncertainty zone 
Internal to this report 548285. m N/A 
Alluv_xmax1 UTM maximum 
easting, SW 
corner alluvial 
uncertainty zone 
Internal to this report 546669. m N/A 
Alluv_ymin1 UTM minimum 
northing, SW 
corner alluvial 
uncertainty zone 
Internal to this report 4057240. m N/A 
Alluv_ymax1 UTM maximum 
northing, SW 
corner alluvial 
uncertainty zone 
Internal to this report 4057620. m N/A 
Alluv_xmin2 UTM minimum 
easting, SE corner 
alluvial uncertainty 
zone 
Internal to this report 555550. m N/A 
Alluv_xmax2 UTM maximum 
easting, SE corner 
alluvial uncertainty 
zone 
Internal to this report 555550. m N/A 
Alluv_ymin2 UTM minimum 
northing, SE 
corner alluvial 
uncertainty zone 
Internal to this report 4055400. m N/A

MDL-NBS-HS-000021, REV 00 72 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
Alluv_ymax2 UTM maximum 
northing, SE 
corner alluvial 
uncertainty zone 
Internal to this report 4055400. m N/A 
Alluv_xmin3 UTM minimum 
easting, NE corner 
alluvial uncertainty 
zone 
Internal to this report 557424. m N/A 
Alluv_xmax3 UTM maximum 
easting, NE corner 
alluvial uncertainty 
zone 
Internal to this report 557758. m N/A 
Alluv_ymin3 UTM minimum 
northing, NE 
corner alluvial 
uncertainty zone 
Internal to this report 4065430. m N/A 
Alluv_ymax3 UTM maximum 
northing, NE 
corner alluvial 
uncertainty zone 
Internal to this report 4067430. m N/A 
Alluv_xmin4 UTM minimum 
easting, NW 
corner alluvial 
uncertainty zone 
Internal to this report 554192. m N/A 
Alluv_xmax4 UTM maximum 
easting, NW 
corner alluvial 
uncertainty zone 
Internal to this report 553579. m N/A 
Alluv_ymin4 UTM minimum 
northing, NW 
corner alluvial 
uncertainty zone 
Internal to this report 4065430. m N/A 
Alluv_ymax4 UTM maximum 
northing, NW 
corner alluvial 
uncertainty zone 
Internal to this report 4067430. m N/A 
A1_1_x UTM easting, SW 
corner source 
zone 1 
Internal to this report 547570. m N/A 
A1_1_y UTM northing, SW 
corner source 
zone 1 
Internal to this report 4078630. m N/A 
A1_2_x UTM easting, SE 
corner source 
zone 1 
Internal to this report 548500. m N/A 
A1_2_y UTM northing, SE 
corner source 
zone 1 
Internal to this report 4078630. m N/A 
A1_3_x UTM easting, NE 
corner source 
zone 1 
Internal to this report 548500. m N/A

MDL-NBS-HS-000021, REV 00 73 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
A1_3_y UTM northing, NE 
corner source 
zone 1 
Internal to this report 4081090. m N/A 
A1_4_x UTM easting, NW 
corner source 
zone 1 
Internal to this report 547570. m N/A 
A1_4_y UTM northing, NW 
corner source 
zone 1 
Internal to this report 4081090. m N/A 
A2_1_x UTM easting, SW 
corner source 
zone 2 
Internal to this report 548500. m N/A 
A2_1_y UTM northing, SW 
corner source 
zone 2 
Internal to this report 4078630. m N/A 
A2_2_x UTM easting, SE 
corner source 
zone 2 
Internal to this report 549320. m N/A 
A2_2_y UTM northing, SE 
corner source 
zone 2 
Internal to this report 4078630. m N/A 
A2_3_x UTM easting, NE 
corner source 
zone 2 
Internal to this report 549320. m N/A 
A2_3_y UTM northing, NE 
corner source 
zone 2 
Internal to this report 4081210 m N/A 
A2_4_x UTM easting, NW 
corner source 
zone 2 
Internal to this report 548500. m N/A 
A2_4_y UTM northing, NW 
corner source 
zone 2 
Internal to this report 4081210. m N/A 
A3_1_x UTM easting, SW 
corner source 
zone 3 
Internal to this report 547720. m N/A 
A3_1_y UTM northing, SW 
corner source 
zone 3 
Internal to this report 4076170. m N/A 
A3_2_x UTM easting, SE 
corner source 
zone 3 
Internal to this report 548500. m N/A 
A3_2_y UTM northing, SE 
corner source 
zone 3 
Internal to this report 4076170. m N/A 
A3_3_x UTM easting, NE 
corner source 
zone 3 
Internal to this report 548500. m N/A 
A3_3_y UTM northing, NE 
corner source 
zone 3 
Internal to this report 4078630. m N/A

MDL-NBS-HS-000021, REV 00 74 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
A3_4_x UTM easting, NW 
corner source 
zone 3 
Internal to this report 547720. m N/A 
A3_4_y UTM northing, NW 
corner source 
zone 3 
Internal to this report 4078630. m N/A 
A4_1_x UTM easting, SW 
corner source 
zone 4 
Internal to this report 548500. m N/A 
A4_1_y UTM northing, SW 
corner source 
zone 4 
Internal to this report 4076170. m N/A 
A4_2_x UTM easting, SE 
corner source 
zone 4 
Internal to this report 548890. m N/A 
A4_2_y UTM northing, SE 
corner source 
zone 4 
Internal to this report 4076170. m N/A 
A4_3_x UTM easting, NE 
corner source 
zone 4 
Internal to this report 548890. m N/A 
A4_3_y UTM northing, NE 
corner source 
zone 4 
Internal to this report 4078630. m N/A 
A4_4_x UTM easting, NW 
corner source 
zone 4 
Internal to this report 548500. m N/A 
A4_4_y UTM northing, NW 
corner source 
zone 4 
Internal to this report 4078630. m N/A 
Max_al_por Total alluvium 
porosity 
Internal to this report 0.30 N/A N/A 
Fpor Average fracture 
porosity in 
volcanic units 
Internal to this report 0.001 N/A N/A 
Mpor Average matrix 
porosity in 
volcanic units 
Internal to this report 0.22 N/A N/A 
Bdens Average bulk 
density in volcanic 
units 
Internal to this report 1.88 g/ml N/A 
Matrix 
porosity 
Expected values 
for matrix porosity 
per volcanic unit 
SN0004T0501399.003 
[155045] Units 15-13, 10 
and 8 
Units 12, 11, and 9 are 
Internal to this report 
Unit 15: 0.15 
Unit 14, 10 and 8: 0.25 
Unit 13: 0.23 
Unit 12: 0.18 
Unit 11: 0.21 
Unit 9: 0.21 
N/A N/A

MDL-NBS-HS-000021, REV 00 75 July, 2003 
Input Name Input Description Input Source (DTN, if 
applicable) 
Value or Distribution Units Type of 
Uncertainty 
Bulk Density Expected bulk 
density values per 
volcanic unit 
Units 15-13, 10, 8; 
SN0004T0501399.002 
[155046] and 
SN0004T0501399.003 
[155045] 
Units 17, 12, 11, 9 and 6- 
2 are internal to this 
report 
Unit 18: 2.50 
Unit 17, 6, 5, and 3: 2.77 
Unit 16: 2.44 
Unit 15: 2.08 
Unit 14, 10 and 8: 1.77 
Unit 13: 1.84 
Unit 12: 2.19 
Unit 11: 2.11 
Unit 9: 2.05 
Unit 4 and 2: 2.55 
Unit 1: 2.65 
g/cm3 N/A 
Effective 
Porosity 
Expected effective 
porosity values for 
other units (see 
Section 6.5.2.20) 
Units 18-16 and 1: 
MO0105HCONEPOR.00 
0 [155044] 
Units 6-2 Internal to this 
report 
Unit 18: 0.32 
Unit 17: 0.01 
Unit 16: 0.08 
Unit 6,5 and 3: 0.01 
Unit 4: 0.18 
Unit 2: 0.18 
Unit 1: 0.0001 
N/A N/A

MDL-NBS-HS-000021, REV 00 76 July, 2003 
Table 6-9. Hydrogeologic Unit Definition 
Hydrogeologic Unit 
Hydrogeologic 
Unit Identification 
Number 
Valley Fill 19 
Valley Fill Confining Unit 18 
Cenozoic Limestones 17 
Lava Flows 16 
Upper Volcanic Aquifer 15 
Upper Volcanic Confining Unit 14 
Lower Volcanic Aquifer Prow Pass 13 
Lower Volcanic Aquifer Bullfrog 12 
Lower Volcanic Aquifer Tram 11 
Lower Volcanic Confining Unit 10 
Older Volcanic Aquifer 9 
Older Volcanic Confining Unit 8 
Undifferentiated Valley Fill 7 
Upper Carbonate Aquifer 6 
Lower Carbonate Aquifer Thrust 5 
Upper Clastic Confining Unit 4 
Lower Carbonate Aquifer 3 
Lower Clastic Confining Unit 2 
Granites 1 
NOTE: Hydrogeologic Units adapted from USGS 2001 [158608], Table 6-2 
6.5.2.1 Groundwater Specific Discharge 
Uncertainty exists in the groundwater specific discharge in the SZ along the flow path from 
beneath the repository to the hypothetical point of release to the biosphere. This uncertainty was 
quantified as a distribution of specific discharge in the volcanic aquifer near Yucca Mountain by 
the SZ expert elicitation project (CRWMS M&O 1998 [100353], p. 3-43). Conclusions 
regarding the uncertainty in specific discharge by the expert elicitation panel primarily were 
based on single- and multi-well hydraulic testing of wells in the volcanic units near Yucca 
Mountain. The aggregate uncertainty distribution of specific discharge in the SZ from the expert 
elicitation had a median value of about 0.6 m/year, with a range of values from less than 0.01 
m/year to about 10 m/year (CRWMS M&O 1998 [100353], p. 3-43). 
More recently, estimates of groundwater specific discharge in the SZ have been obtained at 
another location in the SZ system from field testing at the alluvial tracer complex (ATC) (BSC 
2003 [162415], Section 6.5.4.3). The ATC is approximately located at the boundary of the 
accessible environment, as specified in regulations for the Yucca Mountain project, 10 CFR

MDL-NBS-HS-000021, REV 00 77 July, 2003 
63.302 (10 CFR 63 [156605]). The location of the ATC is approximately 18 km from Yucca 
Mountain and testing was performed in the alluvium aquifer. Estimates of groundwater specific 
discharge at the ATC range from 1.2 m/year to 9.4 m/year (DTN: LA0303PR831231.002, 
[163561]), using alternative means of analyzing the single-well tracer testing results. The 
simulated average specific discharge in this region of the SZ system using the SZ Transport 
Abstraction Model ranges from 1.9 m/year to 3.2 m/year for differing values of horizontal 
anisotropy in permeability, as shown in Table 6-6. Correspondingly, the simulated average 
specific discharge in the volcanic aquifer near Yucca Mountain using the SZ Transport 
Abstraction Model ranges from 0.31 m/year to 0.87 m/year for differing values of horizontal 
anisotropy in permeability. These results show that the average groundwater specific discharge 
tends to increase along the flow path from beneath Yucca Mountain to the south. This increase 
in the specific discharge is due to convergent groundwater flow in this region of the SZ system. 
These results also indicate that there is general consistency between the simulated specific 
discharge and the median values of uncertainty ranges estimated for the volcanic aquifer and the 
alluvial aquifer along the flow path. 
The additional data from the ATC constitutes new information on the specific discharge in the 
SZ and significantly reduces uncertainty in the specific discharge relative to the assessment by 
the expert elicitation panel. The range of estimated specific discharge at the ATC spans about a 
factor of 7.8 (i.e., 1.2 m/year to 9.4 m/year). This indicates range of uncertainty in specific 
discharge that is somewhat less than one order of magnitude, which is considerably less than the 
degree of uncertainty from the SZ expert elicitation project (CRWMS M&O 1998 [100353]). 
Consequently, the uncertainty distribution for the groundwater specific discharge factor 
(GWSPD) is reevaluated to reflect the reduced uncertainty. From this information, a discrete 
CDF of uncertainty in specific discharge is constructed, in which 80% of the probability is 
between 1/3 and 3 times the best estimate of specific discharge. The lower tail of the uncertainty 
distribution extends to 1/30 of the expected value and 10% of the probability is assigned to this 
lower tail. The upper tail of the uncertainty distribution extends to 10 times the expected value 
and 10% of the probability is assigned to this upper tail. The lower and upper tails of the 
uncertainty distribution approximately correspond to the greater uncertainty reflected in the SZ 
expert elicitation results. 
Uncertainty in the groundwater specific discharge is incorporated into the SZ Transport 
Abstraction Model using the continuously distributed GWSPD parameter. This parameter is a 
multiplication factor that is applied to all values of permeability and values of specified boundary 
fluxes in the SZ Transport Abstraction Model to effectively scale the simulated specific 
discharge in the model. Note that a separate steady-state groundwater flow field is simulated for 
each realization of the system, using the value of GWSPD (and the value of HAVO, for 
horizontal anisotropy). The sampling of GWSPD is performed on the log-transformed values of 
the specific discharge multiplication factor, as indicated in Table 6-8. The CDF of uncertainty in 
the groundwater specific discharge multiplier is shown in Figure 6-7.

MDL-NBS-HS-000021, REV 00 78 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-1.6 -1.4 -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 -0.0 0.2 0.4 0.6 0.8 1.0 
Cumulative Probability 
Log Groundwater Specific Discharge Multiplier 
DTN: SN0306T0502103.007 
Figure 6-7. CDF of Uncertainty in Groundwater Specific Discharge Multiplier 
6.5.2.2 Alluvium Uncertainty Zone 
Uncertainty in the geology below the water table exists along the inferred flowpath from the 
potential repository at distances of approximately 10 km to 20 km down gradient of the 
repository. The location at which groundwater flow moves from fractured volcanic rocks to 
alluvium is of particular significance from the perspective of repository performance assessment. 
This is because of contrasts between the fractured volcanic units and the alluvium in terms of 
groundwater flow (fracture dominated flow vs. porous medium flow) and in terms of sorptive 
properties of the media for some radionuclides. 
The uncertainty in the northerly extent of the alluvium in the SZ of the site-scale flow and 
transport simulations is abstracted as a polygonal region that is assigned radionuclide transport 
properties representative of the valley-fill aquifer hydrogeologic unit (Table 6-9). The 
dimensions of the polygonal region are randomly varied in the SZ Transport Abstraction Model 
for the multiple realizations. The northern boundary of the uncertainty zone is varied between 
the dashed lines at the northern end of the polygonal area shown in Figure 6-8. The western 
boundary of the uncertainty zone is varied between the dashed lines along the western side of the 
polygonal area shown in the figure. 
The uncertainty in the contact between volcanic rocks and alluvium at the water table along the 
northern part of the uncertainty zone is approximately bounded by the location of well UE-25

MDL-NBS-HS-000021, REV 00 79 July, 2003 
JF#3, in which the water table is below the contact between the volcanic rocks and the overlying 
alluvium, and by the location of well EWDP-10S, in which the water table is above the contact 
between the volcanic rocks and the alluvium. The uncertainty in the contact along the western 
part of the uncertainty zone is defined by the locations of wells EWDP-10S, EWDP-22S, and 
EWDP-19D1, in which the water table is above the contact between volcanic rocks and the 
overlying alluvium, and outcrops of volcanic bedrock to the west. 
The lower boundary of the alluvium uncertainty zone varies from an elevation of 670 m in the 
northwestern corner of the uncertainty zone to 400 m along the southern edge of the uncertainty 
zone. This corresponds to saturated alluvium thickness of approximately 50 m in the 
northwestern corner varying to about 300 m along the southern boundary of the uncertainty zone. 
The boundaries of the alluvium uncertainty zone are determined for a particular realization by 
the parameters FPLAW and FPLAN. These parameters have uniform distributions from 0.0 to 
1.0, where a value of 0.0 corresponds to the minimum extent of the uncertainty zone and 1.0 
corresponds to the maximum extent of the uncertainty zone in a westerly direction and northerly 
direction, respectively. A uniform distribution is appropriate for these uncertainty distributions 
because only the bounding values are known. A uniform distribution is the best statistically 
unbiased choice in this situation. These parameters are used to independently and uniformly 
vary the northern and western contacts of the volcanic rocks and alluvium at the water table. The 
maximum and minimum coordinates of the alluvium uncertainty zone, corresponding to the plot 
shown in Figure 6-8, are given in Table 6-8 (Alluv_xmin1 to Alluv_ymax4).

MDL-NBS-HS-000021, REV 00 80 July, 2003 
540000 545000 550000 555000 560000 
UTM Easting (m) 
4050000 
4055000 
4060000 
4065000 
4070000 
4075000 
4080000 
UTM Northing (m) 
NC-EWDP-2D 
NC-EWDP-19D 
NC-EWDP-22S 
NC-EWDP-10S 
UE-25 J-12 
UE-25 JF#3 
Source for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 
Source for well locations: DTN: GS010908312332.002 [163555] 
DTN: GS030108314211.001 [163483] 
Note: Repository outline is shown by the solid line and the minimum and maximum boundaries of the alluvium 
uncertainty zone are shown by the dashed lines. Key well locations and well numbers are shown with the cross 
symbols. 
Figure 6-8. Minimum and Maximum Extent of the Alluvium Uncertainty Zone

MDL-NBS-HS-000021, REV 00 81 July, 2003 
6.5.2.3 Effective Porosity of Alluvium 
For the TSPA-SR calculations, effective porosity in the alluvium was a truncated normal 
distribution with a mean of 0.18, a standard deviation of 0.051, a lower bound of 0, and an upper 
bound of 0.35 (CRWMS M&O 2000 [147972], Section 6.3). The basis for this parameter is 
from Bedinger et al. 1989 [129676], p. A18, Table 1. There were no site-specific data for 
effective porosity in the alluvium at the time of the TSPA-SR. Bedinger et al. 1989 [129676]) 
include a study of hydraulic characteristics of alluvium within the Southwest Basin and Range 
Province. This study is relevant to the local basin fill conditions and provides values for effective 
porosity as a stochastic parameter. Since TSPA-SR a site-specific value was determined for 
effective porosity from well EWDP-19D1 at the ATC based on a single-well pumping test (BSC 
2003 [162415], Sections 6.4 and 6.5). There are also total porosity values from the same well 
based on borehole gravimeter surveys, which are used in developing the upper bound of the 
effective porosity in the alluvium uncertainty distribution. 
Effective porosity is important in determining the average linear ground water velocities used in 
the simulation of radionuclide transport. They are customarily calculated by dividing the 
specific discharge of groundwater through a model grid cell by the porosity, fe 
. Groundwater 
velocities are rendered more accurate when dead end pores are eliminated from consideration 
because they do not transmit water. The effective porosity results from that elimination. As a 
result fe 
will always be less than or equal to total porosity, fT. The retardation coefficient, Rf, is 
also a function of porosity. Reducing total porosity to fe 
can erroneously raise the magnitude of 
this value within the model. The correction for this is detailed in the discussion in Section 6.5.1, 
Equation 6-3. 
Effective porosity is treated as an uncertain parameter for the two alluvium units (19 and 7) of 
the nineteen SZ model hydrogeologic units. Uncertain, in this sense, means that fe will be 
constant spatially for each unit for any particular model realization, but that value will vary from 
one realization to the next. In comparison, constant parameters are constant spatially and also do 
not change from realization to realization. 
The parameter input sources used in this analysis are described in Error! Reference source not 
found. and corroborative data are discussed in this section. The uncertainty distribution used for 
the analysis is the distribution used for TSPA-SR with a change to the upper bound. The 
effective porosity uncertainty distribution used for TSPA-SR is shown in Figure 6-9. Figure 6-9 
compares the distribution of Bedinger et al. 1989 [129676] (DTN: MO0105HCONEPOR.000 
[155044]) to distributions, ranges, and values from the other sources that were considered to 
develop the uncertainty distribution. The site-specific effective porosity data point from well 
EWDP-19D1 of 0.1 (BSC 2003 [162415], Section 6.4) is shown on Figure 6-9. This is 
considered a corroborative data point and falls within the uncertainty distribution for TSPA-SR.

MDL-NBS-HS-000021, REV 00 82 July, 2003 
0
1
2
3
4
5
6
7
8
9 
10 
0 0.1 0.2 0.3 0.4 0.5 0.6 
Porosity (effective or 'total') 
Frequency 
DTN: MO0003SZFWTEEP.000 [148744] 
BSC 2003 [162415], Section 6.5 
Burbey and Wheatcraft 1986 [129679], pp. 23-24 
DOE 1997 [103021], Table 8-1, p. 8-5 and Table 8-2, p. 8-6 
NOTE: The dashed black line is Neuman (MO0003SZFWTEEP.000 [148744]); the solid heavy blue line is 
MO0105HCONEPOR.000 [155044]; the solid pink line is Gelhar (MO0003SZFWTEEP.000 [148744]); the 
solid blue block is the effective porosity value calculated from EWDP-19D1 (BSC 2003 [162415], Section 
6.5). The single value data points do not have a y scale value, but do correspond to the x-axis. These 
points are shown for comparison purposes only. The solid black triangle is DOE 1997 [103021], Table 8-1, 
mean matrix porosity; the diamond outlined shapes are Burbey and Wheatcraft 1986 [129679] total 
porosity; the X is DOE 1997 [103021], Table 8-2, total porosity and the square outlined shape is DOE 1997 
[103021], Table 8-1 mean bulk porosity. 
Figure 6-9. Effective Porosity Distributions and Values Compared 
The upper bound of the uncertainty distribution for effective porosity is re-evaluated because of 
new site-specific data obtained since TSPA-SR. The new upper bound is based on the total 
porosity values from well EWDP-19D1 and the average of the total porosity values from the 
Cambric study (Burbey and Wheatcraft 1986 [129679], p. 23 and 24) within the Nevada Test 
Site (NTS) but several kilometers to the east, in Frenchman Flat; and total porosity shown in 
Tables 8-1 and 8-2 of the DOE 1997 [103021] report, pp. 8-5 and 8-6, see Table 6-10. The 
computed total porosity values from 19-D1 are shown in Table 6-11, which have an average 
value of 0.24.

MDL-NBS-HS-000021, REV 00 83 July, 2003 
Table 6-10. Total Porosity Summary( fT) 
Reference Total Porosity Comments 
DOE 1997 [103021], Table 8-1, p. 
8-5 0.36 Mean bulk porosity 
DOE 1997 [103021], Table 8-2, p. 
8-6 0.35 Total porosity 
Burbey and Wheatcraft 1986 
[129679], pp. 23-24 0.34 Average of porosity values from 
Table 3 of that study 
average of above 0.35 N/A 
The average of the total porosity values in Table 6-10 and the average of the site-specific data 
from well EWDP-19D1 were used to develop the upper bound of the effective porosity 
uncertainty distribution. The average total porosity value of 0.35 and the average value from 
EWDP-19D1 of 0.24 result in a mean of 0.30. Figure 6-10 shows the truncated normal 
distribution developed in this analysis for effective porosity in the alluvium (parameter NVF19 
and NVF7) with a mean of 0.18, standard deviation of 0.051, a lower bound of 0, and an upper 
bound of 0.30. Note that parameter NVF7 has the same distribution as NVF19 and is sampled 
independently. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.00 0.05 0.10 0.15 0.20 0.25 0.30 
Cumulative Probability 
Effective Porosity in Alluvium 
DTN: SN0306T0502103.007 
Figure 6-10. CDF of Uncertainty in Effective Porosity in the Alluvium

MDL-NBS-HS-000021, REV 00 84 July, 2003 
6.5.2.4 Flowing Interval Spacing 
The flowing interval spacing is a key parameter in the dual porosity model that is included in the 
SZ Transport Abstraction Model. A flowing interval is defined as a fractured zone that transmits 
fluid in the SZ, as identified through borehole flow meter surveys (see Figure 6-11). This figure 
shows a borehole that is intersected by multiple, irregularly spaced fractures. The figure also 
shows several black bands, labeled as flowing intervals, in which a flow meter survey has 
detected groundwater flow into (or out of) the borehole. The analysis uses the term flowing 
interval spacing as opposed to fracture spacing, which is typically used in the literature. 
Fracture spacing was not used because field data identified zones (or flowing intervals) that 
contain fluid-conducting fractures but do not distinguish how many or which fractures comprise 
the flowing interval. These data also indicate that numerous fractures between flowing intervals 
do not transmit significant amounts of groundwater. The flowing interval spacing is the distance 
between the midpoints of each flowing interval. 
Figure 6-11. Example of Flowing Interval Spacing (BSC 2001 [156965]) for a Typical Borehole 
There is considerable uncertainty regarding the flowing interval spacing parameter due to the 
limited number of data points available. The data set used for the analysis consisted of borehole 
flow meter survey data. This analysis is described in detail in BSC 2001 [156965], Probability 
Distributions for Flowing Interval Spacing. 
There are no new data available to reevaluate the uncertainty distribution for this parameter, 
therefore a CDF based on the log-normal distribution (BSC 2001 [156965], Section 7) that was 
used in TSPA-SR is used as input to the TSPA-LA model and is shown in Figure 6-12. The 
Typical Flowing Interval Spacing 
Flowing interval 
Borehole 
Fractures 
Typical Fracture Spacing

MDL-NBS-HS-000021, REV 00 85 July, 2003 
flowing interval spacing parameter is specified for a particular realization by the parameter 
FISVO. See Table 6-8 for the associated probabilities for the flowing interval spacing CDF. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 
Cumulative Probability 
Log Flowing Interval Spacing (m) 
DTN: SN0306T0502103.007 
Figure 6-12. CDF of Uncertainty in Flowing Interval Spacing 
6.5.2.5 Flowing Interval Porosity 
The flowing interval porosity is defined as the volume of the pore space through which 
significant groundwater flow occurs, relative to the total volume. At Yucca Mountain, rather 
than attempt to define the porosity within all fractures, a flowing interval is defined as the region 
in which significant groundwater flow occurs at a well. The fracture porosity then characterizes 
these flowing intervals rather than all fractures. The advantage to this definition of fracture 
porosity is that in situ well data may be used to characterize the parameter. The flowing interval 
porosity may also include the matrix porosity of small matrix blocks within fracture zones that 
potentially experience rapid matrix diffusion. 
For the TSPA-SR calculations, the flowing interval (fracture) porosity probability distribution 
was a uniform distribution with an upper bound of log10 (flowing interval porosity) of -1.0 and a 
lower bound of log10 (flowing interval porosity) of -5.0 (CRWMS M&O 2000 [147972], Section 
6.7). The basis for this uncertainty distribution includes estimates of fracture porosity in intact

MDL-NBS-HS-000021, REV 00 86 July, 2003 
cores of volcanic rock and the results of pumping tests and tracer tests in the Bullfrog Tuff at the 
C-wells Complex (CRWMS M&O 2000 [147972], Section 6.7). 
The TSPA-SR probability distribution for the flowing interval porosity has been modified based 
on new sources of information about flowing interval porosity. New information has been 
derived from tests in unsaturated tuff in the Exploratory Studies Facility (ESF). Fracture 
porosity has been estimated in unsaturated volcanic tuff in the ESF for the middle nonlithophysal 
welded tuff (UZ model layer tsw34) using gas tracer testing. The assumptions used in obtaining 
the fracture porosity from gas tracer tests are that the diffusion of gas into the rock matrix is 
negligible compared to the flow through the fractures, that the fracture network is well 
connected, and that the gas flow is approximately radial toward the pumped borehole. This 
calculation of fracture porosity is documented in the Analysis of Hydrologic Properties Data 
AMR (BSC 2003 [161773], p. 41). The estimated average value of fracture porosity is 0.01. 
Fracture porosity has also been estimated using the residence time of conservative tracers during 
cross-hole tracer tests at the C-wells Complex (CRWMS M&O 1997 [100328], p. 2-4). This 
method assumes that the mean tracer arrival time is equal to the time required to drain a 
homogenous, fractured cylinder of rock with a radius equal to the distance between the pumping 
well and the tracer-injection well. A large range in estimated fracture porosity for the saturated 
Bullfrog Tuff resulted from this method because the tracers were interpreted to have traveled 
along two paths with different travel times. The path with the longer travel time resulted in a 
larger estimate of fracture porosity. The resulting lower and upper bounds of fracture porosity 
were 0.004 and 0.125, respectively (CRWMS M&O 1997 [100328], p. 28). 
The Nevada Environmental Restoration Project (DOE 1997 [103021]) evaluated the fracture 
spacing and apertures in seven cores from wells at Pahute Mesa. The volcanic rocks in these 
cores include the Timber Mountain tuff, Tuff Cones, Belted Range Aquifer and undistinguished 
welded tuff deposits. The estimated open fracture porosities based on the assumption of parallel 
plates, range from 6.1  10-6 to 4.7  10-4 in the welded tuffs and 2.6  10-6 to 4.7  10-4 in the 
tuff cores (DOE 1997 [103021], p. 5-14). Similarly, data compiled for TSPA-1993 (Wilson et al. 
1994 [100191], Volume 1, Chapter 7, Table 7-19, p. 7-30) indicate average fracture porosities of 
8.010-5 to 2.810-3, in core from USW G-1, USW GU-3, USW G-4 and UE25a#1e, when 
parallel plate fracture geometry is assumed. There is large uncertainty in the flowing interval 
porosity parameter. 
Given the estimates of this parameter from values based on theoretical models, pumping tests, 
and tracer data, the parameter uncertainty ranges over 4 orders of magnitude. To estimate the 
lower bound of flowing interval porosity the estimates of fracture porosity of intact cores of 
volcanic rock were used. The upper bound of uncertainty in the flowing interval porosity is 
based on interpretations of pumping test and tracer data. The new data from the ESF provide an 
estimate of flowing interval porosity that falls in the upper half of the distribution used for this 
parameter (CRWMS M&O 2000 [147972], Section 6.7) in the TSPA-SR. 
For the TSPA-LA calculations, a cumulative distribution with a lower bound of log10 (flowing 
interval porosity) of -5.0, an upper bound of log10 (flowing interval porosity) -1.0 is selected for 
this parameter as shown in Figure 6-13. This distribution places more weight in the middle of 
the distribution range compared to the TSPA-SR uniform distribution (CRWMS M&O 2000

MDL-NBS-HS-000021, REV 00 87 July, 2003 
[147972], Section 6.7) that results in equal probabilities for the given range. The 0.5 probability 
value of -3.0 is representative of the smallest values of fracture porosity estimated from the new 
data from the ESF and previous field tests. See Table 6-8 for the associated probabilities for the 
flowing interval porosity CDF. The flowing interval porosity parameter is specified for a 
particular realization by the parameter FPVO. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-5 -4 -3 -2 -1 
Cumulative Probability 
Log Flowing Interval Porosity in Volcanic Units 
DTN: SN0306T0502103.007 
Figure 6-13. CDF of Uncertainty in Flowing Interval Porosity 
6.5.2.6 Effective Diffusion Coefficient 
Matrix diffusion is a process in which diffusing particles move, via Brownian motion, through 
both mobile and immobile fluids. Diffusion is a Fickian process, that is, diffusing species move 
from high to low concentrations. It is dependent on the free water molecular diffusion 
coefficient for individual constituents and the characteristics of the flow path in which the 
diffusing species passes. Because diffusion through porous media is less than free water 
molecular diffusion, it is quantitatively defined as the effective diffusion coefficient, De. 
Matrix diffusion has been demonstrated to occur in the volcanic rocks within the vicinity of 
Yucca Mountain (Reimus et al. 2002 [162956]; Reimus et al. 2002 [163008]). Thus, it is 
modeled in the volcanic units of the SZ Transport Abstraction Model and the SZ 1-D Transport 
Model for TSPA-LA. It is the transport mechanism that occurs in the rock matrix portion of the

MDL-NBS-HS-000021, REV 00 88 July, 2003 
volcanic units. Consequently, it can be an important process that physically retards net 
radionuclide transport in fractured media. 
The variability in De in saturated media is caused by the variability in: 1) the individual 
constituents size (atom, ion, or molecule) and charge; 2) fluid temperature; and, 3) the unique 
properties of a porous medias lithology at a microscopic scale. The contribution of these 
uncertainties and variabilities in deriving a value of De is evaluated in the following subsections. 
Variability between Lithologic Units 
There are several derived lumped parameters, used as adjustments to the free water molecular 
diffusion, to account for the impact of lithology on molecular diffusion. Tortuosity, formation, 
and constrictivity factors are common adjustment parameters. These lumped parameters are 
based on various linear regression models, fit to field and laboratory experimental results and 
measured properties of the host rock, such as porosity, permeability, and formation electrical 
resistivity (from geophysical logs). 
Diffusion cell experiments have demonstrated that De is more affected by the structural 
properties of the porous medium, such as porosity, pore size distribution, and pore geometry, 
than by the mineralogy or geochemistry (Skagius and Neretnieks 1986 [156862], p. 389-398). 
Specific to Yucca Mountain, diffusion cell experiments documented by Coen 1987 [162960] on 
dilute sodium halite salt solutions diffusing through NTS tuff samples demonstrated De was 
directly proportional to the variability in matrix porosity and pore size distributions. Buchholtz 
ten Brink et al. 1991 [162954]) found De for 238U on various Yucca Mountain tuff samples to be 
dependent on the pore size distribution of the hydrostratigraphic units. 
Many mathematical models have been formulated to derive a value of De. Most, if not all, rely 
on porosity, with some adding other lumped parameters. As an example, Bear 1972 [156269], 
Sections 4.8.2 and 4.8.3 relate effective matrix diffusion to porosity, formation factor (derived 
from geophysical logs), and the free water molecular diffusion coefficient as follows: 
F 
D 
Dm f
0 = (Equation 6-15) 
where Dm is the effective diffusion coefficient in a porous medium [L2/T], 0 D is the diffusion 
coefficient in water [L2/T] and F is the formation factor [-]. The formation factor is defined by 
the electrical resistivity of the porous medium saturated with electrolyte divided by the resistivity 
of the electrolyte. This method has limitations in that it relies on formation factor measurements.

MDL-NBS-HS-000021, REV 00 89 July, 2003 
Domenico and Schwartz 1990 [100569], p. 368 document the relationship between porosity and 
effective diffusion with the following: 
0 ) / ( D Dm t f = (Equation 6-16) 
where t (= Le/L) is the tortuosity [-], Le is the length of the channel for the fluid particle [L], L is 
the length of the porous media channel [L]. This method has limitations in that it relies on 
multiple diffusion cell measurements on a wide variety of rock samples to derive a global value 
for t . 
Domenico and Schwartz, 1990 [100569], p. 368 define a range for Dm with the following 
empirical equation: 
Dm = 
2
0 Df 
to 
2 
0 2 . .. 
. 
. .. 
. 
- f 
f D (Equation 6-17) 
Bound 1 Bound 2 
This relationship captures the uncertainty and range of Dm in a heterogeneous system. It is only 
dependent on porosity and, because there are many matrix porosity measurements on Yucca 
Mountain tuffs, site specific data can be used as input. 
Using Equation 6-17 and site specific porosity data a range in effective diffusion coefficient in 
the volcanic rock matrix (De) can be calculated. Mean porosity values were calculated using the 
relative humidity (RH) porosities found in DTN MO0109HYMXPROP.001 [155989] for the SZ 
hydrostratigraphic units defined in Characterization of Hydrogeologic Units Using Matrix 
Properties, Yucca Mountain, Nevada (Flint 1998 [100033]) as input. RH porosity is measured 
by drying the sample in an oven for 48 hours at 60oC and 65% relative humidity. (Note, Flints 
hydrostratigraphic units are subunits of the SZ 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 her units are heavily based on matrix rather than fracture properties, 
and it is the matrix properties that are important to diffusion in the SZ. 
Using RH porosity values in MO0109HYMXPROP.001 [155989], the minimum average 
porosity is 0.042, located in the Calico Hills-vitric unit (a subunit of the SZs Upper Volcanic 
Confining, Unit 14), the maximum average is 0.321, located in unit TC (Tiva Canyon tuff, a 
subunit of the SZ Upper Volcanic Aquifer, Unit 15). For this exercise 0 D is that of 3HHO 
(tritiated water), 2.44105 cm2/s. The resulting range in De is between 3.9210-6 and 
1.1210-8 cm2/s when the largest porosity in used as input in bound 1, and the smallest porosity 
is used as input to bound 2. The variability in De is a factor of: 
350 
/ 10 12 . 1 
/ 10 3.92 
2 8 
2 6 
= 

 
-
- 
s cm 
s cm 
(Equation 6-18)

MDL-NBS-HS-000021, REV 00 90 July, 2003 
Reimus et al. 2002 [163008] have developed an empirical relationship between De and porosity 
and permeability measurements based on diffusion cell experiments on rock samples from the 
Yucca Mountain area. Diffusing species are 99Tc (as TcO4
-), 14C (as HCO3
-) and 3HHO. Rock 
samples were taken from within the vicinity of Yucca Mountain, under Pahute Mesa and Area 25 
of the Nevada Test Site. Based on these experiments Reimus et al. 2002 [163008] described 
three different approaches in deriving De. Two are dependent on linear regression relationships 
fitting the experimental results to diffusion cell measurements for: 1) both matrix porosity and 
permeability, and 2) only matrix porosity measurements. The third approach is simply 
compiling a cumulative distribution function based on their numerous diffusion cell results. 
Reimus et al. 2002 [163008], Section 4 found that differences in rock type account for the largest 
variability in the effective diffusion coefficients, rather than variability between diffusing 
species, size, and charge. The highest predictability in determining a value of De occurs when 
both matrix porosity and log permeability are known, with log permeability as the most 
important predictive variable. 
The following equation defines their linear regression relationship based on porosity and 
permeability values and diffusion cell results (Reimus et al. 2002 [163008], p. 2.25): 
) (log 165 . 0 38 . 1 49 . 3 ) ( log 10 10 m m e k D + + - = f (Equation 6-19) 
where e D is in units of cm2/s and m k is matrix permeability [L2] in units of m2. 
Again, using matrix properties base on 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 [155989] within the Flint defined set of 
hydrostratigraphic units (listed as hydraulic conductivities in DTN: 
MO0109HYMXPROP.001 [155989], then converted to permeability). 
 Determine the maximum and minimum average porosity within the Flint defined set 
of hydrostratigraphic units (listed as RH porosities in DTN: 
MO0109HYMXPROP.001 [155989]). 
The highest mean log permeability is -13.25 in Calico Hill-vitric unit (a subunit of the SZ HFM 
Unit 14), the lowest mean log permeability is -19.39 in unit TLL (a subunit of SZ HFM Unit 
15). The largest porosity, 0.321, is in Calico Hill-vitric unit; the smallest porosity, 0.042, is in 
unit TC (Tiva Canyon tuff).

MDL-NBS-HS-000021, REV 00 91 July, 2003 
The variation in De using Equation 6-19 and average maximum and minimum permeabilities 
and porosities values, expressed as a ratio of maximum to minimum estimated De, is as: 
25 
/ 10 34 . 2 
/ 10 84 . 5 
2 7 
2 6 
= 

 
-
- 
s cm 
s cm 
(Equation 6-20) 
Variability from Ionic Radius and Charge 
Empirical correlations exist in the literature to adjust free diffusion coefficients dependent on 
species size and charge. For this analysis, general guidance provided by Newman 1973 
[148719], Table 75-1, p. 230, which lists diffusion coefficients for ions and cations of varying 
charges and size, is adopted in the scaling of radionuclide diffusion coefficients. 
Diffusion coefficients listed for the simple monovalent ions Br- and I- are the largest values 
listed by Newman. Consequently, diffusion coefficient scaling factors for all other ions and 
cations are relative to those listed for Br- and I- . The rationale for specific scaling factors is given 
below. 
1. Simple monovalent cations tend to be more hydrated than anions, resulting in larger 
effective radii than anions, and concomitantly, diffusion coefficients are about 0.90 and 
0.95 times that of simple monovalent anions such as Br- and I-. PuO2
+ and NpO2
+ would 
fall into this category, since they both have relatively low charge to mass ratios and 
should not be highly hydrated. 
2. Cations, such as Na+ and Li+, with high charge to mass ratios have a diffusion coefficient 
between 0.65 and 0.5 times that of Br- and I-. 
3. Multivalent anions (which are generally multi-atom species) tend to have diffusion 
coefficients of 0.4 to 0.6 times that of Br- and I-. 
4. Multivalent cations have diffusion coefficients between 0.3 to 0.4 times that of Br- and I-. 
5. Diffusion coefficients of organic molecules can be considered reasonable lower bounds 
for diffusion coefficients of large anionic radionuclide complexes. An example is the 
large monovalent anions, such as pentafluorobenzoate, which have diffusion coefficients 
about 0.33 times that of Br- and I- (Callahan et al. 2000 [156648], Tables 5 and 6, p. 
3553). 
6. Cations with charges of +3 typically hydrolyze or form complexes in solution, resulting 
in a lower charge and higher mass species (e.g., hydroxyl or carbonate complexes). 
Consequently, the multivalent and complexed species could diffuse between 0.3 and 0.25 
times that of Br- and I- .

MDL-NBS-HS-000021, REV 00 92 July, 2003 
Concluding from the above, the variation between the diffusion coefficients for simple, and 
relatively small monovalent ions and the larger multivalent complexed cations can be as much 
as 
0 . 4 
25 . 0
1 = (Equation 6-21) 
The variability in De due to ionic charge and species size can be as much as a factor of 4.0. 
Variability from Temperature 
The uncertainty and variability in diffusion due solely to temperature variations (over space and 
time) will affect all contaminants equally. Hence the uncertainty in temperature will not affect 
the decision to use a single diffusion coefficient. The Stokes-Einstein relationship can be used to 
approximate the molecular diffusion of ions in water with concentrations of ions as high as 
seawater and with temperatures ranging from 0 to 100oC (Li and Gregory 1974 [129827], p.704; 
Simpson and Carr 1958 [139449], p. 1201). Using the Stokes-Einstein relationship, the 
molecular diffusion coefficient for a given temperature, can be estimated as a function of the 
diffusion coefficient at a reference absolute temperature ( 0 T ) and the relative change in 
temperature and water viscosity, ( .) [M/(LT)] (Li and Gregory 1974 [129827], p. 704): 
) ( ) ( 0 0 
1
0 
0
1 
1 0 T D 
T
T T D 
.
. 
= (Equation 6-22) 
Given the maximum potential range in temperature for the Yucca Mountain groundwater along 
the transport pathway of 20 to 50 oC (293.15 to 323.15 K and the viscosity of water at those 
temperatures (Viswanath and Natarajan 1989 [129867], p. 714), Equation 6-22 can be rewritten 
and solved as follows: 
15 . 2 
/ 516 . 0 
/ 007 . 1 
15 . 293 
15 . 323 
) ( 
) ( 
2
2 
1
0 
0
1 
0 0 
1 0 = = = 
m Ns 
m Ns 
K
K 
T
T 
T D 
T D 
.
. 
(Equation 6-23) 
Thus 0 D can vary by a factor of about 2.2 due to changes in water temperature. 
Effective Diffusion Coefficients for Yucca Mountain Volcanic Units 
Given the above arguments, it is demonstrated that the largest variability in De is due to 
differences in lithology. The variability in De using Equation 6-19 is not as high as that derived

MDL-NBS-HS-000021, REV 00 93 July, 2003 
using Equation 6-17. However, Equation 6-19 will be adopted in deriving the uncertainty 
distribution of De for the following reasons: 
1. Because Equation 6-19 is derived based on site-specific data it is more appropriate in 
determining the range of De due to lithology specific to Yucca Mountain. 
2. There are a large number of permeability and porosity measurements taken from the 
saturated zone hydrogeologic units where flow is expected to take place. Averages of 
these measurements can be used as input to Equation 6-19. 
3. Using maximum and minimum averages from matrix porosity and permeability as 
input yields a range in De that approaches that of the few laboratory derived De 
measurements specific to Yucca Mountain tuffs for TcO4
- (1.010-7 to 2.010-6) and 
HTO- (1.210-7 to 3.510-6) (see Triay et al. 1993 [145123]; Rundberg et al. 1987 
[106481]) as indicated on the Flint_Reim_TrRnd spreadsheet in the EXCEL 
workbook Eff_MtrxDif_11.xls file (DTN: SN0306T0502103.006). 
The CDF for uncertainty in the effective diffusion coefficient used in this analysis is derived as 
follows: 
1. Mean porosity and permeability values (calculated from values found in DTN: 
MO0109HYMXPROP.001 [155989]) were calculated for the volcanic hydrostratigraphic 
units TC, TR, TUL, TMN, TLL, TM2, TM1, CHV, CHZ, PP4, PP3, PP2, PP1, BF3 and 
BF2 , defined by Flint, 1998 [100033]. These are subunits of the more broadly defined 
SZ HFM Units 11, 12, 13, 14 and 15, and are units where flow and transport are 
expected to take place. Mean porosity and permeability values are given on the 
spreadsheets LVA (12 &11), LVA (13), UVC (14), and UVA (15) in the 
EXCEL file Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 
2. A CDF for De was calculated with Equation 6-19 using the mean permeability and 
porosity values for the above hydrostratigraphic units as input. These values are given on 
the spreadsheet drns_all_straight, (Column AG, Rows 34 through 49) in the EXCEL 
file Eff_MtrxDf_11.xls (DTN: SN0306T0502103.006). 
3. The derived CDF was then scaled down to account for the variability in De to account for 
ionic charge and size. The scaling factors used are: 1) 0.9, to represent diffusion of 
simple monovalent cations, 2) 0.65 and 0.50, to represent cations with a high charge to 
mass ratios, 3) 0.3 to represent large monovalent anions, and 4) 0.25, to represent 
multivalent and complexed cations (Figure 6-14). Note, the rationale for the above 
scaling factors were discussed in the subsection Variability from Ionic Radius and 
Charge. These values are given on the spreadsheet drns_all_straight in the EXCEL 
file Eff_MtrxDf_11.xls (Column AG, Rows 50 through 109) (DTN: 
SN0306T0502103.006). 
The resulting CDF yields a distribution given in Figure 6-14 with a range in log space of 5.3 
to 7.12 cm2/s. The range captures laboratory 3HHO and TcO4
- measured values of De on 
Yucca Mountain Tuffs reported by Triay et al. 1993 [145123] and Rundberg et al. 1987

MDL-NBS-HS-000021, REV 00 94 July, 2003 
[106481] and 3HHO, TcO4, and 14C De reported by Reimus et al. 2002 [163008] and 2003 
[162950]). Additionally, this range incorporates the interpreted diffusion coefficients 
(6.010-6 cm2/s and 1.310-7 cm2/s) derived from field tests using Br-, PFBA (a fluorinated 
organic acid) as the diffusing species (Reimus et al. 2003 [162950]). 
The distribution for the derived values of effective diffusion coefficient using Equation 6-19 
is about half an order of magnitude lower than the distribution of values from laboratory and 
field results. This is because the derived distribution scales effective diffusion coefficient to 
take into account species not measured in laboratory or field experiments, as described in 
step 3 above. The lowest values of effective diffusion coefficient are those for hydrolyzed or 
complexed ions having a low charge and high mass, which would have diffusion coefficients 
about 0.25 times the values for Br- and I- ions. 
To account for uncertainties in De at the lower end the uncertainty range is expanded to span 
a full 2 orders of magnitude (log 5.3 to 7.3 cm2/s), with the 50 percentile set at 6.3. cm2/s. 
Converted to m2/s results in a log De range of 9.3 to 11.3 m2/s, with the 50 percentile set at 
10.3. m2/s (See Figure 6-15). The effective matrix diffusion coefficient is determined for a 
particular realization by the parameter DCVO. See Table 6-8 for the associated probabilities 
for the effective matrix diffusion coefficient CDF.

MDL-NBS-HS-000021, REV 00 95 July, 2003 
Note: The CDF to the left represents values of effective diffusion coefficient derived using Equation 6-19. Included in 
the plot are laboratory measurements of effective diffusion coefficient from Triay 1993 [145126] and Rundberg 
et al. 1987 [106481] to demonstrate the reasonableness of the derived values of effective diffusion coefficient. 
The CDF to the right represents laboratory and field-derived estimates. Triangles - 14C laboratory values; 
Squares - 3HHO laboratory values; Diamonds  TcO4 laboratory values; Circles  Br- and PFBA field values 
(Reimus et al., 2002 [163008] and Reimus et al., 2003 [162950]). 
DTN: SN0306T0502103.006 
Figure 6-14. CDFs of Data Used in the Assessment of Uncertainty in Effective Diffusion Coefficient 
0.00 
0.20 
0.40 
0.60 
0.80 
1.00
-7.50 -7.00 -6.50 -6.00 -5.50 -5.00 -4.50 
Log Effective Diffusion Coefficient (cm2/sec) 
Cumulative Probability 
TcO4 labmatrix diffusion - 
red dots 
(Rundberg et al. 1987 
[106481] and Triay 1993 
[145126]) 
3HHO lab matrix diffusion - 
green squares 
(Rundberg et al. 1987 
[106481] and Triay 1993 
[145126])

MDL-NBS-HS-000021, REV 00 96 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0 
-11.4 -11.2 -11.0 -10.8 -10.6 -10.4 -10.2 -10.0 -9.8 -9.6 -9.4 -9.2 
Cumulative Probability 
Log Effective Diffusion Coefficient (m^2/s) 
DTN: SN0306T0502103.007 
Figure 6-15. CDF of Uncertainty in Effective Diffusion Coefficient 
6.5.2.7 Bulk Density of Alluvium 
For the TSPA-SR, the dry bulk density was considered to be a constant and set to 1.27 g/cm3 
(CRWMS M&O 2000 [147972], Section 6.9). The basis for this parameter value is a set of tests 
performed on four five-foot alluvial intervals from each of the EWDP boreholes 2D, 9S, and 3S 
at depths of 395 to 415 feet, 145 to 165 feet, and 60 to 80 feet, respectively (DTN: 
LA0002JC831341.001 [147081]). These samples were drill cuttings and thus highly disturbed 
from their condition in the aquifer. The range of the dry bulk density values in laboratory 
columns packed with alluvium from these wells was 1.2 to 1.3 g/cm3. The data are presented in 
Unsaturated Zone and Saturated Zone Transport Properties (U0100) (CRWMS M&O 2000 
[152773], p. 86) with a note stating that densities were measured in the laboratory and do not 
represent in situ conditions. 
The values used in the TSPA-SR were low compared to dry bulk densities measured in alluvium 
at Frenchman Flat and the NTS near Yucca Mountain (Howard 1985 [153266], Table 3, p. 31, 
and Table A-1, p. 38). Similarly, a comparison to the range of dry bulk densities of alluvial 
material in general (Manger 1963 [154474], pp. E41 to E42) led to the conclusion that the values 
used in the TSPA-SR were likely an underestimate of the true bulk density. Consequently, bulk 
density in the alluvium and its uncertainty has been reevaluated using data from the Yucca 
Mountain area that have been measured at a larger, more representative scale.

MDL-NBS-HS-000021, REV 00 97 July, 2003 
The dry bulk density of the alluvium is used in the computation of the retardation of sorbing 
radionuclides. The dry bulk density is related to the matrix retardation coefficient as indicated in 
Equation 6-2. 
Borehole gravimeter surveys were conducted by EDCON 2000 [154704], pp. 1 to 23 at well 
EWDP-19D1 directly south of Yucca Mountain near U.S. Highway 95. A total of 36 values of 
saturated bulk density were estimated based on the geophysical measurements taken from this 
well (EDCON 2000 [154704], p. 3). Seventeen measurements were taken from a depth 
corresponding to the inferred depth of the flow path through the alluvium near Yucca Mountain 
(401.5 to 776 feet). The wet bulk density computed from gravimeter measurements is presented 
in Table 6-11 as well as the porosity and dry bulk density computed from Freeze and Cherry 
1979 [101173], p. 337: 
grain w 
grain sat 
. . 
. . 
f 
-
- 
= T (Equation 6-24) 
( ) T f. . - = 1 grain b (Equation 6-25) 
where .sat is the saturated bulk density [M/L3], .grain is the average grain density for these samples 
[M/L3] (2.52 g/cm3), and .w is the density of water (1.0 g/cm3). 
The average grain density was computed to be 2.52 g/cm3 (2520 kg/m3) from alluvial samples 
from other boreholes in the vicinity of Yucca Mountain (USGS n.d. [154495], pp. 3 to 4). The 
grain density varied little (2.49 to 2.55 g/cm3), and so the average was used in the computation of 
the porosity and dry bulk density. 
The mean dry bulk density for this set of measurements was 1.91 g/cm3 (1910 kg/m3). This 
value is close to dry bulk density values previously measured at Frenchman Flat and the NTS in 
similar material at similar depth (Howard 1985 [153266], Table 3, p. 31, and Table A-1, p. 38), 
and it is the value used as the mean in the uncertainty distribution. The computed standard 
deviation for these measurements is 0.078 g/cm3. A normal distribution was selected to 
characterize the uncertainty in the dry bulk density based on the frequency plot shown in Figure 
6-16. The relatively large volume of the medium interrogated by the borehole gravimeter 
method suggests that the variability observed is appropriate for the uncertainty in this parameter 
at the scale of individual grid cells in the SZ Transport Abstraction Model. The CDF of 
uncertainty in bulk density of the alluvium is shown in Figure 6-17. The bulk density in the 
alluvium is specified for a particular realization by the parameter bulkdensity.

MDL-NBS-HS-000021, REV 00 98 July, 2003 
Table 6-11. Measured Saturated Density, Computed Porosity, and Computed Dry Bulk Density for 
Depths from 402 to 776 Feet Below the Surface at the Nye County Well EWDP-19D1 . 
Sample Depth 
(ft) 
Drift-Corrected Saturated Bulk 
Density, .sat (g/cm3) 
Computed Total 
Porosity, T f Computed Dry Bulk 
Density, .b (g/cm3) 
402 2.231 0.190 2.04 
422 2.156 0.239 1.92 
442 2.180 0.224 1.96 
485 2.163 0.235 1.93 
505 2.174 0.228 1.95 
525 2.214 0.201 2.01 
569.95 2.148 0.245 1.90 
589.9 2.142 0.249 1.89 
610 2.105 0.273 1.83 
630 2.079 0.290 1.79 
649.95 2.077 0.291 1.79 
669.95 2.133 0.255 1.88 
690 2.121 0.262 1.86 
715.95 2.158 0.238 1.92 
736 2.143 0.248 1.90 
756 2.105 0.273 1.83 
776 2.239 0.185 2.05 
Source DTN: MO0105GPLOG19D.000 [163480]

MDL-NBS-HS-000021, REV 00 99 July, 2003 
1.6 1.7 1.8 1.9 2 2.1 2.2 
Dry BulkDensity (g/cm3) 
0
1
2
3
4
5 
Frequency 
Note: Normal distribution fit to the data shown with the dashed line. 
Figure 6-16. Histogram of Dry Bulk Density from Borehole Gravimeter Data

MDL-NBS-HS-000021, REV 00 100 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0 
1500 1600 1700 1800 1900 2000 2100 2200 2300 
Cumulative Probability 
Bulk Density of Alluvium (kg/m^3) 
DTN: SN0306T0502103.007 
Figure 6-17. CDF of Uncertainty in Bulk Density of Alluvium 
6.5.2.8 Sorption Coefficients 
Sorption or adsorption is the process by which dissolved radionuclides temporarily adhere or 
bond to rock and alluvial substrate along a transport path. Sorption occurs because of the 
electrochemical affinity between the dissolved species and the substrate. The significance of 
sorption to the SZ Transport Abstraction Model and the SZ 1-D Transport Model is that sorption 
results in a retardation of the radionuclide because part of the radionuclide transport time is spent 
on an immobile surface. 
A linear, equilibrium, sorption coefficient, Kd, is considered appropriate for the radionuclides 
that exhibit sorption during transport. The Kd model also depends on chemical equilibrium 
between the aqueous phase and sorbed phase of a given species.

MDL-NBS-HS-000021, REV 00 101 July, 2003 
The Kd relationship is defined as follows (Domenico and Schwartz 1990 [100569], p. 441): 
C K S d = (Equation 6-26) 
where S [moles/M] is the mass sorbed on the surface of the substrate, and C [moles/L3] is the 
concentration of the dissolved mass. The Kd model determines transport retardation as described 
earlier per Equation 6-2. 
A detailed discussion of the uncertainty distributions for sorption coefficients used in the SZ 
Transport Abstraction Model and the SZ 1-D Transport Model is given by BSC 2003 [162419], 
Attachment I. The documentation provided by BSC 2003 [162419], Attachment I includes the 
technical bases for the values of sorption coefficient for the relevant radionuclides in volcanic 
units and alluvium at Yucca Mountain. 
6.5.2.9 Dispersivity 
Longitudinal dispersion is the mixing of a solute in groundwater that occurs along the direction 
of flow. This mixing is a function of many factors including the relative concentrations of the 
solute, the velocity pattern within the flow field, and the host rock properties. An important 
component of this dispersion is the dispersivity, a coarse measure of solute (mechanical) 
spreading properties of the rock. The dispersion process causes spreading of the solute in 
directions transverse to the flow path as well as in the longitudinal flow direction (Freeze and 
Cherry 1979 [101173], p. 394). Longitudinal dispersivity will be important only at the leading 
edge of the advancing plume, while transverse dispersivity (horizontal transverse and vertical 
transverse) is the strongest control on plume spreading and possible dilution for the Yucca 
Mountain repository (CRWMS M&O 1998 [100353], p. LG-12). 
Temporal changes in the groundwater flow field may significantly increase the apparent 
dispersivity displayed by a contaminant plume, particularly with regard to transverse dispersion. 
However, observations of water levels in wells at Yucca Mountain have not indicated large or 
consistent variations (Luckey et al. 1996 [100465], p. 29-32), suggesting that transience in the 
SZ flow system would not lead to much greater dispersion. The thick UZ in the area of Yucca 
Mountain likely dampens the response of the SZ flow system to seasonal variations or transience 
in infiltration on time scales of less than centuries. 
These dispersivities (longitudinal, vertical transverse, and horizontal transverse) are used in the 
advection-dispersion equation governing solute transport and are implemented into the SZ 
Transport Abstraction Model as stochastic parameters. Recommendations from the expert 
elicitation were used as the basis for determining the distribution for longitudinal and transverse 
dispersivity. As part of the expert elicitation, Dr. Lynn Gelhar provided statistical distributions 
for longitudinal dispersivity at 5 km and 30 km (CRWMS M&O 1998 [100353], p. 3-21). These 
distributions for longitudinal dispersivity are consistent with his previous work (Gelhar 1986 
[101131], pp. 135s-145s). CRWMS M&O 2000 [152259], p. 53 provided estimates of the 
transverse and longitudinal dispersion that may occur at the sub gridblock scale within the SZ

MDL-NBS-HS-000021, REV 00 102 July, 2003 
site-scale model. The estimation of dispersivity using sub-gridblock scale modeling is also 
described in McKenna et al. 2003 [163578]. The results from the sub-gridblock scale modeling 
(CRWMS M&O 2000 [152259], p. 55) are in general agreement with the estimates by the expert 
elicitation panel (CRWMS M&O 1998 [100353], p. 3-21). However, it should be noted that 
there is a significant difference in the spatial scale at which the analyses in CRWMS M&O 2000 
[152259] (500 m) were conducted and the scales at which the expert elicitation (CRWMS M&O 
1998 [100353]) estimates were made (5 km and 30 km). Nonetheless, both sources of 
information on dispersivity are mutually supportive. 
In the SZ Transport Abstraction Model, the longitudinal dispersivity parameter is sampled as a 
log-transformed parameter and the transverse dispersivities are then calculated as indicated by 
CRWMS M&O 1998 [100353], p. 3-21 according to the following relationships: 
200 
L 
h 
a 
a = (Equation 6-27) 
20000 
L 
v 
a 
a = (Equation 6-28) 
where L a is the longitudinal dispersivity [L], h a is the transverse horizontal dispersivity [L] and 
v a is transverse vertical dispersivity [L]. 
The longitudinal dispersivity is specified for a particular realization by the parameter LDISP. 
The statistical distribution is a log-normal distribution: E[log10( L a )]: 2.0 and S.D.[log10( L a )]: 
0.75. The CDF of uncertainty in longitudinal dispersivity is shown in Figure 6-18.

MDL-NBS-HS-000021, REV 00 103 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-2 -1 0 1 2 3 4 5 6 
Cumulative Probability 
Log Longitudinal Dispersivity (m) 
DTN: SN0306T0502103.007 
Figure 6-18. CDF of Uncertainty in Longitudinal Dispersivity 
Effective Longitudinal Dispersivity in the SZ Transport Abstraction Model 
Longitudinal dispersivity for radionuclide transport simulations in the SZ Transport Abstraction 
Model is specified as a transport parameter. The dispersion process is simulated by the randomwalk 
displacement algorithm on the local scale for each time step in the transport simulation. In 
addition, the spatial distribution of hydrogeologic units of contrasting permeability within the 
model imparts additional dispersion to the simulated transport of particles as the flow paths 
diverge during transport. The effective longitudinal dispersivity simulated by the SZ Transport 
Abstraction Model may be significantly larger than the specified value due to the additive effects 
of these two processes. 
The effective longitudinal dispersivity in the SZ Transport Abstraction Model is analyzed for a 
range of values of specified longitudinal dispersivity to evaluate this effect. A point source 
beneath the repository is used for the analysis. Neither sorption nor matrix diffusion is included 
in the simulations. Effective longitudinal dispersivity is estimated using the relationship from 
Kreft and Zuber 1978 [107306]:

MDL-NBS-HS-000021, REV 00 104 July, 2003 
2 
2 . .. 
. 
. .. 
. 
= 
t
t f 
L m 
L s 
a (Equation 6-29) 
where Lf is the flow path length [L], st 
is the standard deviation in travel time [T], and mt is the 
mean travel time [T]. The standard deviation is estimated from the particle mass breakthrough 
curve at 18 km distance by taking the difference in time between the arrival of 0.159 fraction of 
the mass (the mean minus one standard deviation for a Gaussian distribution) and the arrival of 
0.841 fraction of the mass (the mean plus one standard deviation for a Gaussian distribution) and 
dividing by 2. The mean travel time is estimated using the arrival time of 0.500 fraction of the 
mass. 
The results of this analysis are shown in Figure 6-19 with the plotted open circles. The effective 
simulated longitudinal dispersivity is consistently about one order of magnitude higher (bold 
dashed line) than the specified longitudinal dispersivity (for values of specified longitudinal 
dispersivity of less than 1000 m). These results indicate that the heterogeneous distribution of 
permeability in the SZ Transport Abstraction Model in the region along the flow path is 
contributing approximately one order of magnitude of dispersivity relative to the specified value. 
1 10 100 1000 10000 100000 
Specified Longitudinal Dispersivity (m) 
1 
10 
100 
1000 
10000 
100000 
Effective Simulated Longitudinal Dispersivity (m) 
Figure 6-19. Effective Simulated Longitudinal Dispersivity Versus the Specified Longitudinal Dispersivity 
in the SZ Transport Abstraction Model

MDL-NBS-HS-000021, REV 00 105 July, 2003 
These results indicate that the effective longitudinal dispersivity in the SZ Transport Abstraction 
Model is significantly higher than the value input to the model. In order to avoid the excessive 
effective dispersion in the SZ Transport Abstraction Model, the input value of longitudinal 
dispersivity can be reduced. Based on these results, the value of specified longitudinal 
dispersivity used in the SZ Transport Abstraction Model for the TSPA abstraction simulations is 
adjusted to yield the correct value of effective simulated longitudinal dispersivity. This is 
accomplished by scaling the input value of longitudinal dispersivity down by one order of 
magnitude (i.e., dividing the longitudinal dispersivity by 10) in the input files for each 
realization. 
6.5.2.10 Horizontal Anisotropy in Permeability 
Although a detailed description of the analysis and derivation of the distribution of anisotropy 
ratio in the saturated zone near the C-Wells complex is presented in the Saturated Zone In Situ 
Testing report (BSC 2003 [162415], Section 6.2.6), some background information and a short 
summary are presented here. Interpretation of well test data with analytical solutions consists of 
inferring the hydraulic properties of the system from its measured responses based on an 
assumed flow geometry (i.e., radial). The problem becomes more complicated, however, when 
the system geometry cannot be specified with reasonable certainty. In a layered sedimentary 
system lacking extreme heterogeneity, flow might reasonably be expected to be radial during a 
hydraulic test. When hydraulic tests are conducted at some arbitrary point within a threedimensional 
(3-D) fractured rock mass, however, the flow geometry is complex. Radial flow 
would occur only if the test were performed in a single uniform fracture of effectively infinite 
extent or within a network of fractures confined to a planar body in which the fractures were so 
densely interconnected that the network behaves like an equivalent porous medium. More likely, 
flow in fractured tuff is nonradial and variable, as fracture terminations and additional fracture 
intersections were reached. Therefore, it must be emphasized that assumptions required in the 
analytical treatment of anisotropy may not be strictly consistent with site geology. 
Through the fractured tuff and alluvium near Yucca Mountain, there is significant heterogeneity 
in hydraulic properties, which not only vary spatially, but also differ depending upon the 
direction in which they are measured (both horizontally and vertically). In this analysis, 
transmissivity and storativity are the hydrologic parameters required to calculate and define 
large-scale anisotropy, and their measured values reflect the heterogeneity of the media. The 
concept of anisotropy is typically associated with a homogeneous 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 BSC 2003 
[162415], Section 6.2.6. After filtering the drawdown data in response to pumping at UE-25 
c#3, transmissivity and storativity were calculated at four distant wells (USW H-4, UE-25 
ONC1, UE-25 wt#3, and UE-25 wt#14).

MDL-NBS-HS-000021, REV 00 106 July, 2003 
A distribution of anisotropies must be specified so that an anisotropy ratio can be selected for 
each of the 200 stochastic model realizations used as input to the SZ Transport Abstraction 
Model. Because the current version of the FEHM v. 2.20 software code (STN: 10086-2.20-00, 
LANL 2003 [161725]) can only implement anisotropy oriented in alignment with the grid 
direction, principal directions discussed above are not directly applicable in the model. The net 
result of being unable to specify a principal direction is that uncertainty in the anisotropy ratio 
increases. For example, the analytical result for anisotropy using the Cooper-Jacob 1946 
[150245] method is a ratio of 3.3 in a direction 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, the YMP Parameters Team, scientific judgment, and 
results from the analytical anisotropy analyses, Figure 6-20a represents the best estimate of the 
PDF for the anisotropy ratio (north-south / east-west) in the saturated zone near the C-wells 
complex. Figure 6-20b is the corresponding CDF. 
DTN: SN0302T0502203.001 [163563] 
Figure 6-20. Probability Density Function (a) and Corresponding Cumulative Distribution 
Function (b) for the Uncertainty in North-South/East-West Anisotropy Ratio

MDL-NBS-HS-000021, REV 00 107 July, 2003 
There are several noteworthy points based on three distinct regions of the anisotropy ratio 
distribution (DTN: SN0302T0502203.001 [163563]). 
 Anisotropy ratio between 5 and 20. The maximum anisotropy ratio of 20:1 is based upon 
the highest calculated anisotropy ratio of 17:1 reported by Ferrill et al. 1999 [118941], p. 
7. The maximum reported value of 17:1 was rounded to 20:1 and set as the upper limit 
for horizontal anisotropy. Furthermore, although features such as high transmissivity 
zones and fractures may yield very large anisotropy ratios locally, globally, their effects 
are attenuated, and 20 is a reasonable maximum. The 5.5 anisotropy ratio calculated by 
the second approach of the modified Papadopulos-PEST method (see BSC 2003 
[162415], Section 6.2.6) lies in this range near its highest probability point. Therefore, 
between 5 and 20, a triangular distribution of anisotropy ratio is constructed that 
decreases to zero probability at 20. A 40% probability is assigned to this portion of the 
probability density function. 
 Anisotropy ratio between 0.05 and 1. Discussions among Sandia National Laboratories 
(SNL) and USGS staff established that, although it is likely the SZ is anisotropic with 
principal direction approximately northeast, it is possible the media could be isotropic, as 
well as a small probability that the principal direction could be significantly different 
from north-northeast. Correspondingly, an anisotropy ratio of less than one is possible, 
and the minimum anisotropy ratio is set equal to the inverse of the maximum, 1:20, with 
a triangular distribution of 10% probability decreasing to zero at a ratio of 0.05. An 
additional Papadopulos solution yielding an anisotropy ratio of 3.5 at 79 west of north 
(BSC 2003 [162415], Section 6.2.6) falls in this range. 
 Anisotropy ratio between 1 and 5. A uniformly distributed 50% probability is assigned to 
the range of anisotropy ratio between 1 and 5. This interval comprises the more likely 
values of anisotropy ratios with no specific value more likely than another. It should be 
noted that in a previous model of the saturated zone near Yucca Mountain (CRWMS 
M&O 2000 [147972], Section 6.12), anisotropy was binomially distributed with a 50% 
probability of isotropy (1:1) and a 50% probability of a 5:1 ratio. 
It is assumed that the potential anisotropy of permeability in the horizontal direction is 
adequately represented by a permeability tensor that is oriented in the north-south and east-west 
directions. This approach is carried forward from the Saturated Zone In-Situ Testing scientific 
analysis report (BSC 2003 [162415], Section 6.2.6). The numerical grid in the SZ site-scale flow 
and transport model is aligned in the north-south and east-west directions and values of 
permeability may only be specified in directions parallel to the grid. Analysis of the probable 
direction of horizontal anisotropy shows that the direction of maximum transmissivity may be 
about N 15o E, indicating that the anisotropy applied on the SZ Transport Abstraction Model grid 
is within approximately 15o of the inferred anisotropy. 
Figure 6-20(a) and Figure 6-20(b) are the best estimates for the PDF and the CDF, respectively, 
of north-south anisotropy ratios in the saturated zone to be modeled with the FEHM v. 2.20 
software code (STN: 10086-2.20-00, LANL 2003 [161725]) in the SZ Transport Abstraction 
Model. Horizontal anisotropy in permeability is determined for a particular realization by the 
parameter HAVO.

MDL-NBS-HS-000021, REV 00 108 July, 2003 
6.5.2.11 Retardation of Colloids with Irreversibly Sorbed Radionuclides 
For TSPA-LA, colloid-facilitated transport of radionuclides in the SZ is simulated to occur by 
two basic modes. In the first mode, radionuclides that are irreversibly attached to colloids are 
transported at the same rate as the colloids, which are themselves retarded by interaction with the 
aquifer material. In the second mode, radionuclides that are reversibly attached to colloids are in 
equilibrium with the aqueous phase and the aquifer material. In this mode of transport, the 
effective retardation of these radionuclides during transport in the SZ is dependent on the 
sorption coefficient of the radionuclide onto colloids, the concentration of colloids, and the 
sorption coefficient of the radionuclide onto the aquifer material. This section deals with the first 
mode of colloid-facilitated transport and Section 6.5.2.12 addresses the second mode. 
The SZ transport simulations of radionuclides that are irreversibly attached to colloids are 
conducted for radioisotopes of Pu and Am. The retardation of colloids with irreversibly 
attached radionuclides is a kinetically controlled process, which approaches equilibrium behavior 
for long transport times. For transport of colloids through the SZ, equilibrium behavior is nearly 
achieved. However, non-equilibrium behavior results in unimpeded migration of some of the 
colloids. Consequently, a small fraction of these colloids are transported through the SZ with no 
retardation; whereas the larger fraction is delayed by a retardation factor. For the SZ transport 
simulations, a small (uncertain) fraction of the radionuclide mass irreversibly attached to colloids 
is transported without retardation and the remaining fraction of the radionuclide mass is retarded. 
A discussion of the fraction of colloids transported with no retardation is in BSC 2003 [163932], 
Section 6.6. The fraction of irreversibly sorbed to reversibly sorbed radionuclides is determined 
in the waste-form component of TSPA-LA and is used as input to the SZ Transport Abstraction 
Model and the SZ 1-D Transport Model. 
The processes important to the transport of irreversible colloids in the volcanic units of the SZ 
are as follows: advection and dispersion of colloids in the fracture water, exclusion of the 
colloids from the matrix waters, and chemical filtration or adsorption of the colloids onto the 
fracture surfaces. 
Modeling of the advective/dispersive processes is handled as if the colloids were solute in the SZ 
Transport Abstraction Model and the SZ 1-D Transport Model. Matrix exclusion in the volcanic 
units is considered to be appropriate because of the large size and small diffusivities of the 
colloids compared to the solute, plus the possibility of similar electrostatic charge of the colloids 
and the tuff matrix. Matrix exclusion is implemented by reducing the values of the effective 
diffusion coefficients for radionuclides (see Section 6.5.2.6 for a discussion of the solute 
diffusion coefficient) by ten orders of magnitude, thus preventing essentially all matrix diffusion. 
Chemical (i.e., reversible) filtration of irreversible colloids is modeled by applying a retardation 
factor to the transport in the fractures. The implementation of the retardation factor in the SZ 
Transport Abstraction model is described in Section 6.5.1 
BSC 2003 [163932], Section 6.4 describes the development of colloid retardation factors for 
fractured tuff from field and experimental data. Figure 6-21 shows the CDF used for retardation 
factors in the volcanic units for the SZ Transport Abstraction model and Table 6-8 provides the

MDL-NBS-HS-000021, REV 00 109 July, 2003 
associated probabilities. This CDF is based on the uncertainty distribution developed by BSC 
2003 [163932], Table 7. A log cumulative probability distribution is used because the 
retardation factors span slightly more than 2 orders of magnitude. Retardation of colloids with 
irreversibly sorbed radionuclides in the volcanic units is specified for a particular realization by 
the parameter CORVO. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 
Cumulative Probability 
Log Colloid Retardation Factor in Volcanic Units 
DTN: LA0303HV831352.002 [163558] 
Figure 6-21. CDF of Uncertainty in Colloid Retardation Factor in Volcanic Units 
The processes modeled for irreversible colloids in the alluvium are the same as those modeled 
for irreversible colloids in the volcanic units, with the exception of matrix exclusion, because the 
alluvium is modeled as a single porous medium. BSC 2003 [163932], Section 6.5 describes the 
development of colloid retardation parameters for the alluvium using experimental data specific 
to colloid transport in alluvial material from Yucca Mountain as well as bacteriophage field 
studies in alluvial material, which are thought to be good analogs for colloid transport. As with 
irreversible colloids in the volcanic units, filtration in the alluvium is modeled by applying a 
retardation factor to transport in the porous medium. Figure 6-22 shows the CDF used for 
retardation factors in the alluvium for the SZ Transport Abstraction model and Table 6-8 
provides the associated probabilities. This CDF is based on the uncertainty distribution 
developed by BSC 2003 [163932], Table 8. A log cumulative probability distribution is used 
because the retardation factors span slightly more than 3 orders of magnitude. The 
implementation of the retardation factor in the SZ Transport Abstraction model is described in 
Section 6.5.1. Retardation of colloids with irreversibly sorbed radionuclides in the alluvium is 
specified for a particular realization by the parameter CORAL.

MDL-NBS-HS-000021, REV 00 110 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0.0 1.0 2.0 3.0 4.0 
Cumulative Probability 
Log Colloid Retardation Factor in Alluvium 
DTN: LA0303HV831352.004 [163559] 
Figure 6-22. CDF of Uncertainty in Colloid Retardation Factor in Alluvium 
6.5.2.12 Transport of Radionuclides Reversibly Sorbed on Colloids 
Radionuclides that are reversibly sorbed onto colloids are modeled to be temporarily attached to 
the surface of colloids. Thus, these radionuclides are available for dissolution in the aqueous 
phase and their transport characteristics are a combination of the transport characteristics of 
solute and colloids. The SZ transport simulations of radionuclides that are reversibly attached to 
colloids are conducted for radioisotopes of Pu, Am, Th, Pa, and Cs, which is consistent with the 
radionuclides selected for reversible sorption (BSC 2003 [161620], Section 6.3.3.1). For these 
transport simulations, radioisotopes of Pu are transported as one group, radioisotopes of Am, Th, 
and Pa are transported as a second group, and Cs is transported as a third species. Americium 
and plutonium can also be transported as irreversibly sorbed onto colloids, see Section 6.5.2.11. 
The Kc parameter is a distribution coefficient that represents the equilibrium partitioning of 
radionuclides between the aqueous phase and the colloidal phase, as given in Equation 6-4. The 
Kc is a function of only radionuclide sorption properties, colloid substrate properties, and colloid 
mass concentration, and not any properties of the immobile media through which transport 
occurs; thus the same Kc applies to transport of a radionuclide in both the volcanic units and the 
alluvium. 
For TSPA-LA, the coll 
d K uncertainty distributions for Pu, Am, Th, Pa, and Cs were developed by 
BSC 2003 [161620], Table 10. Figure 6-23 to Figure 6-25 show the uncertainty distributions

MDL-NBS-HS-000021, REV 00 111 July, 2003 
input to the SZ Transport Abstraction Model for sorption coefficients onto colloids. The Ccol 
uncertainty distribution was also developed by BSC 2003 [161620], Table 5 (see Figure 6-26). 
Retardation of colloids with reversibly sorbed radionuclides is determined for a particular 
realization by the following uncertain parameters: Conc_Col for groundwater colloid 
concentrations; Kd_Cs_Col for cesium sorption coefficient onto colloids; Kd_Am_Col for 
americium, thorium and protactinium sorption coefficients onto colloids; Kd_Pu_Col plutonium 
sorption coefficient onto colloids. Implementation of the Kc model in the SZ Transport 
Abstraction Model is discussed in Section 6.5.1 Note that the values given for the parameter 
vectors of Kd_Pu_Col, Kd_Am_Col, and Kd_Cs_Col in Attachment I are the log10-transformed 
values. 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 2.0e05 4.0e05 6.0e05 8.0e05 1.0e06 
Cumulative Probability 
Plutonium Sorption Coefficient onto Colloids (ml/g) 
DTN: SN0306T0504103.006 [164131], Table 1 
Figure 6-23. CDF of Uncertainty in Plutonium Sorption Coefficient onto Colloids

MDL-NBS-HS-000021, REV 00 112 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 2.0e06 4.0e06 6.0e06 8.0e06 1.0e07 
Cumulative Probability 
Americium Sorption Coefficient onto Colloids (ml/g) 
DTN: SN0306T0504103.006 [164131], Table1 
Figure 6-24. CDF of Uncertainty in Americium Sorption Coefficient onto Colloids 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
0 1.0e03 2.0e03 3.0e03 4.0e03 5.0e03 6.0e03 7.0e03 8.0e03 9.0e03 1.0e04 Cumulative Probability 
Cesium Sorption Coefficient onto Colloids (ml/g) 
DTN: SN0306T0504103.006 [164131], Table 1 
Figure 6-25. CDF of Uncertainty in Cesium Sorption Coefficient onto Colloids

MDL-NBS-HS-000021, REV 00 113 July, 2003 
0.0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9 
1.0
-9 -8 -7 -6 -5 -4 -3 
Cumulative Probability 
Log Groundwater Colloid Concentrations (g/ml) 
DTN: SN0306T0504103.005 [164132], Table 3 
Figure 6-26. CDF of Uncertainty in Groundwater Colloid Concentrations 
Accompanying the Kc model is the partitioning of radionuclides between the aqueous phase and 
the sorbed phase onto the tuff matrix and the alluvium, as described by Kd for the radionuclide 
onto the aquifer material. The Kd uncertainty distributions for americium, plutonium, and cesium 
are described in Table 6-8 (DTN: LA0302AM831341.001, [163556]). 
6.5.2.13 Source Regions 
Variations in radionuclide transport pathways and travel times in the SZ from various locations 
beneath the repository are considered by defining four radionuclide source regions at the water 
table. For any particular TSPA realization a point source of radionuclides is defined within each 
of the four regions for simulation of radionuclide transport in the SZ Transport Abstraction 
Model. A point source of radionuclides in the saturated zone is appropriate for a single leaking 
waste package or for highly focused groundwater flow along a fault or single fracture in the 
unsaturated zone. Whereas a more diffuse source of radionuclides at the water table may be 
more physically realistic for later times when numerous leaking waste packages occur, use of a 
point source in the SZ is an approach that tends to overestimate the concentration of 
radionuclides near the source. 
The SZ source region locations are based on the extent of the repository design and on the 
general pattern of groundwater flow in the unsaturated zone as simulated by the UZ site-scale 
flow and transport model. Variations in the pattern of groundwater flow from the repository to

MDL-NBS-HS-000021, REV 00 114 July, 2003 
the water table exist among infiltration models, alternative conceptual models, and climate states 
for the UZ site-scale model (BSC 2003 [164431], Section 6.6). The UZ flow and transport 
simulations indicate varying degrees of lateral diversion of groundwater to the east of the 
repository and downward redirection by interception of flow at major faults. The SZ source 
region locations are defined to accommodate the general range in UZ transport pathways 
simulated by the suite of UZ site-scale flow model simulations. 
The four SZ radionuclide source regions are shown in Figure 6-27. Note that the CORPSCON 
software code (v. 5.11.08, STN: 10547-5.11.08-00, LANL 2001 [155082]) was used to convert 
the coordinates of the repository design (given in state plane coordinates in meters) to UTM 
coordinates. The coordinates of the corners of the source regions are given in Table 6-8. Source 
regions 1, 3, and part of 2 are located directly below the repository to capture radionuclide 
transport that occurs vertically downward in the UZ site-scale flow and transport model. In 
addition, regions 1, 2, and 3 are appropriate source locations for radionuclides arriving at the 
water table in the human intrusion scenario (see CRWMS M&O 2000 [153246], Section 4.4) , in 
which a hypothetical borehole penetrates the repository and extends to the saturated zone. 
Source regions 2 and 4 are located to the east of the repository to capture radionuclide transport 
that is subject to lateral diversion of groundwater to the east along dipping volcanic strata in the 
unsaturated zone. Also note that the northern part of source region 2 underlies a northeasterly 
extension of the repository. 
The random locations of the radionuclide source term for each realization are defined by eight 
stochastic parameters. The parameters SRC1X, SRC1Y, SRC2X, SRC2Y, SRC3X, SRC3Y, 
SRC4X, SRC4Y determine the x coordinate and y coordinate for the source location within 
regions 1 to 4, respectively. These parameter values are drawn from independent, uniform 
distributions from 0.0 to 1.0. The result is a randomly located point source within each of the 
four source regions for each realization of the SZ Transport Abstraction Model.

MDL-NBS-HS-000021, REV 00 115 July, 2003 
546000 547000 548000 549000 550000 551000 
UTM Easting (m) 
4075000 
4076000 
4077000 
4078000 
4079000 
4080000 
4081000 
4082000 
UTM Northing (m) 
1 
2 
3 4 
Sources for repository outline: 800-IED-EBS0-00401-000-00C, BSC 2003 [162289] 
800-IED-EBS0-00402-000-00B, BSC 2003 [161727] 
Note: Repository outline is shown by the solid blue line and the four source regions are shown by the dashed red 
lines. 
Figure 6-27. Source Regions for Radionuclide Release in the SZ Transport Abstraction Model 
6.5.2.14 Maximum Alluvial Porosity 
The value of maximum or total alluvial porosity is used to calculate the adjusted (or new) Kd 
value in the effective porosity conceptualization of transport in the alluvium (see Equation 6-3). 
The average total porosity of alluvium from corroborative data given in Table 6-10 is 0.35. The 
calculated value of average total porosity in alluvium from the borehole gravimeter data from 
well EWDP-19D1 is significantly lower, as shown in Table 6-11. The approximate average 
value of maximum alluvial porosity from these two sources is 0.30. Note that the uncertainty 
distribution in effective porosity of alluvium is truncated at a maximum value of 0.30 (Figure 
6-10).

MDL-NBS-HS-000021, REV 00 116 July, 2003 
6.5.2.15 Average Fracture Porosity 
The value of average fracture porosity of volcanic rocks is used to calculate the retardation factor 
of sorbing radionuclides in the rubblized material of fracture zones. This retardation factor in the 
fracture zones only applies when the flowing interval porosity exceeds the average fracture 
porosity. The average fracture porosity is conceptualized to be the total fracture porosity of the 
volcanic units, not including any matrix porosity in the rubblized material of fracture zones. The 
average fracture porosity is taken as the median of the uncertainty distribution assigned to the 
flowing interval porosity (FPVO) (see Table 6-8), which is equal to 0.001. 
6.5.2.16 Average Matrix Porosity 
The value of average matrix porosity of volcanic rocks is used to calculate the retardation factor 
of sorbing radionuclides in the SZ 1-D Transport Model and in the rubblized material of fracture 
zones. This retardation factor in the fracture zones only applies when the flowing interval 
porosity exceeds the average fracture porosity. The average matrix porosity of volcanic rocks is 
calculated as the average of matrix porosity in hydrogeologic units numbered 11 through 14, as 
given in Table 6-12. The calculated average matrix porosity is 0.22. 
6.5.2.17 Average Bulk Density of Volcanic Matrix 
The value of average bulk density of the matrix in volcanic rocks is used to calculate the 
retardation factor of sorbing radionuclides in the SZ 1-D Transport Model and in the rubblized 
material of fracture zones. This retardation factor in the fracture zones only applies when the 
flowing interval porosity exceeds the average fracture porosity. The average bulk density of 
volcanic matrix is calculated as the weighted average of bulk density in hydrogeologic Units 
numbered 13 through 15, as given in Table 6-13, with double weighting given to Unit 13. The 
calculated average bulk density is 1.88 g/cm3. 
6.5.2.18 Matrix Porosity of Volcanic Units (Constant) 
Matrix porosity ( fm) is treated as a constant parameter for eight units of the nineteen SZ model 
hydrogeologic units. Constant, in this sense, means that fm will vary from one unit to another, 
but, given a particular unit, the porosity is constant for all realizations. The porosity also remains 
spatially constant for each unit. The parameter values and input source(s) are shown in Section 
4, Error! Reference source not found. and discussed below. 
The following discussion covers data sources used in constant porosity inputs for the affected 
hydrogeologic units. The volcanic Units 11 through 15 do lie in the expected flow paths per 
BSC 2003 [162649], Section 6.6.2. All of the remaining units are expected to lie outside of any 
expected SZ model transport paths and thus the values of matrix porosity assigned to the

MDL-NBS-HS-000021, REV 00 117 July, 2003 
remaining units have no impact on the transport simulations. However, the model requires 
values for fm for all units whether they play a role in transport simulations or not. Therefore 
values as representative as possible were used. 
For the case of Units 15-13, the matrix porosity is based on the values from 
SN0004T0501399.003. The matrix porosity value for Units 12 and 11 were derived from matrix 
porosity data from the boreholes; UE-25P#1, USW H-3, SD7, USW G-3, USW H-1, USW G-4, 
USW H-5, and USW H-6 (DTN: SN0004T0501399.003 [155045], MO0109HYMXPROP.001 
[155989], MO0010CPORGLOG.002 [155229]). Simple averages of the wells described above 
were calculated from the data for Units 12 and 11, as shown in spreadsheet 
bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006). 
Units 10 and 8 are both volcanic confining units. The value of fm for these units was obtained 
from the value for Unit 14, which is a volcanic confining unit for which there are site-specific 
data. The fm value for Unit 9 (volcanic unit) was obtained by averaging the values for the three 
overlying Crater Flat group Units (11-13). These averages were used as the matrix porosity 
inputs to the SZ site-scale model for their respective units as shown in Table 6-12. 
Table 6-12. Values of Matrix Porosity ( fm) for Several Units of the SZ Model 
SZ Unit Name SZ Unit Number Matrix Porosity ( fm) 
Upper Volcanic Aquifer (Topopah) 15 0.15 
Upper Volcanic Confining Unit 
(Calico Hills) 
14 0.25 
Lower Volcanic Aquifer, Prow Pass 13 0.23 
Lower Volcanic Aquifer, Bullfrog 12 0.18 
Lower Volcanic Aquifer, Tram 11 0.21 
Lower Volcanic Confining Unit 10 0.25 
Older Volcanic Aquifer 9 0.21 
Older Volcanic Confining Unit 8 0.25 
DTN: SN0306T0502103.008 
6.5.2.19 Bulk Density of Volcanic Matrix 
Bulk density ( .b 
) is defined by Freeze and Cherry (1979 [101173], p. 337) as the oven-dried 
mass of the sample divided by its field volume. It is a factor in Equation 6-2, used to determine 
retardation of a solute due to chemical adsorption in groundwater. That equation is employed in 
the SZ site-scale flow and transport model as part of the FEHM code (Zyvoloski et al. 1997 
[110491], p. 42). 
Bulk density is treated as a constant parameter for seventeen of the nineteen units of the SZ 
model hydrogeologic units. Constant, in this sense, means that .b 
varies from one unit to 
another, but, given a particular unit, the bulk density stays the same for all realizations. The bulk

MDL-NBS-HS-000021, REV 00 118 July, 2003 
density also remains spatially constant for each unit. Bulk density in hydrogeologic Units 19 and 
7 is treated as an uncertain parameter and is discussed in Section 6.5.2.7. The parameter values 
and input source(s) are described in Section 4. This section contains a discussion of the analyses 
used to develop the values. The volcanic Units 11 through 15 do lie in the expected flow paths 
per BSC 2003 [162649], Section 6.6.2. All of the remaining units are expected to lie outside of 
any expected SZ model transport paths and thus the values of bulk density assigned to the 
remaining units have no impact on the transport simulations. 
Estimates for bulk density were either based on the use of an analogous unit, or a calculation was 
required, as discussed below. For some units, including part of the volcanic units and the 
carbonate units, the calculation involved averaging a group of referenced bulk density values. 
Some of the volcanic units required the use of a referenced graph to calculate bulk density as a 
certain function of matrix porosity (for which values had already been determined). Finally, two 
units (granite and lava flows) required the use of a general equation that relates bulk density to 
porosity. Many of the calculations required referencing either the matrix porosities or the 
effective porosities that were tabulated in Table 6-12 and Table 6-14, respectively. 
The estimated bulk densities are summarized in Table 6-13 and the methods used to obtain these 
values are summarized in the discussion below. 
Table 6-13. Values of Bulk Density ( .b) for All Units of the SZ Site-Scale Model 
SZ Unit Name SZ Unit Number Bulk Density (.b) 
(g/cm3) 
Valley Fill Confining Unit 18 2.50 
Cenozoic Limestone 17 2.77 
Lava Flows 16 2.44 
Upper Volcanic Aquifer 
(Topopah) 
15 2.08 
Upper Volcanic Confining Unit 
(Calico Hills) 
14 1.77 
Lower Volcanic Aquifer, Prow Pass 13 1.84 
Lower Volcanic Aquifer, Bullfrog 12 2.19 
Lower Volcanic Aquifer, Tram 11 2.11 
Lower Volcanic Confining Unit 10 1.77 
Older Volcanic Aquifer 9 2.05 
Older Volcanic Confining Unit 8 1.77 
Upper Carbonate Aquifer 6 2.77 
Lower Carbonate Aquifer Thrust 5 2.77 
Upper Clastic Confining Unit 4 2.55 
Lower Carbonate Aquifer 3 2.77 
Lower Clastic Confining Unit 2 2.55 
Granites 1 2.65 
Note: Units 19 and 7 are treated as uncertain parameters and discussed in Section 6.5.2.7.

MDL-NBS-HS-000021, REV 00 119 July, 2003 
Carbonates Units 3, 5, 6, and 17 - Bulk density for Units 3, 5, 6 and 17 is determined from an 
average of a series of bulk density values from the Roberts Formation and the Lone Formation of 
borehole UE-25p#1 (DTN: MO0010CPORGLOG.002 [155229]). A simple average was 
calculated using these values (see spreadsheet bulkd_matr_eff_La.xls (DTN: 
SN0306T0502103.006)). 
Clastic Units 2, 4, and 18 - Bulk density values for Unit 4 are determined from an average of a 
series of sedimentary deposit formation bulk densities from borehole UE-25P#1 (DTN: 
MO0010CPORGLOG.002 [155229]). There are no bulk density data available for the Clastics 
hydrogeologic units. A simple average was calculated using these values (see spreadsheet 
bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). The bulk density assigned to Unit 4 
was used as an analogous value for Unit 2, because Unit 2 is also a clastic confining unit. Unit 4 
is also used as an analogous unit for Unit 18 because data do not exist for this unit and the value 
was rounded to 2.5. 
Volcanic Units 8, 10, 13, 14, and 15 - The Rock Properties Model (BSC 2002 [159530]) 
contains a graph (Figure 24b, on page 71) that relates point values of .b 
to fm in volcanic tuff. 
The graph demonstrates a strong linear correlation between the two parameters. The equation 
for the straight-line fit to the scatterplot is shown below (DTN: SN0004T0501399.002 [155046]) 
m b f .  - = 8924 . 2 5019 . 2 (Equation 6-30) 
Table 6-8 lists the values of fm for the Units (13-15) that were used to calculate .b 
. 
Hydrogeologic Units 8 and 10 are volcanic confining units. The value of .b 
for these units was 
obtained from the value for Unit 14, which is a volcanic confining unit for which we have sitespecific 
data. 
Volcanic Units 11 and 12 - Bulk density for Units 11 and 12 is determined from values of the 
so-called middle volcanic aquifer, which is equivalent to the SZ Units 11 and 12 (DTN: 
MO0109HYMXPROP.001 [155989] and MO0010CPORGLOG.002 [155229]). The bulk 
density values come from the boreholes SD7, USW H-1, UE-25b#1, J-13, UE-25a#1, USW GU- 
3, USW G-3, USW G-4, UE-25p#1, and USW G-1. A simple average was calculated from those 
values (see spreadsheet bulkd_matr_eff_La.xls (DTN: SN0306T0502103.006)). 
Volcanic Unit 9 - Unit 9 is a volcanic aquifer. Its value was obtained by averaging the values 
for the three overlying volcanic Crater Flat group Units (11-13) and Unit 15. 
Lava Flows (Unit 16) and Granites (Unit 1) - Rearrangement of the terms from an equation by 
Hillel 1980 [101134], p. 12, Equation 2.14) yields the following general relationship between 
bulk density and porosity: 
( ) grain T b . f .  - = 1 (Equation 6-31)

MDL-NBS-HS-000021, REV 00 120 July, 2003 
where .grain equals particle density [M/L3]. The same text reference considers it appropriate that 
.grain can be equal to 2.65g/cm3 (Hillel 1980 [101134], p. 9). As both of these units are not in the 
transport model path, it is suitable to use the particle density value and effective porosity to 
calculate bulk density (Equation 6-31) (see spreadsheet bulkd_matr_eff_La.xls (DTN: 
SN0306T0502103.006)). The effective porosity values were used for Equation 6-31 because the 
effective porosity is very similar to the total porosity for the lava flow and granite units. The 
porosity values were taken from Table 6-12. The lava flow unit has an effective porosity of 0.08 
and the granite unit has a porosity of 0.0001. Therefore the bulk densities assigned for those 
units are 2.44 and 2.65 g/cm3 respectively. 
6.5.2.20 Effective Porosity 
Effective Porosity ( fe 
) is treated as a constant parameter for nine of the nineteen SZ model 
hydrogeologic units. Constant, in this sense means that fe 
varies from one unit to another, but, 
given a particular unit, the porosity is the same for all realizations. The effective porosity is also 
homogeneous within each unit. The input source(s) are described in Section 4, Error! 
Reference source not found.. 
The nine hydrogeologic units discussed in this Section do not occur within the flow path from 
beneath the repository; therefore, these values do not impact the simulated transport of 
radionuclides. However, representative values are used. The Bedinger et al. 1989 [129676], 
Table 1, p. A18 report includes hydrogeologic data for the Basin and Range Province of the 
Southwestern U.S. The Bedinger et al. report covers a region that extends into eight states and 
includes the Yucca Mountain site. Bedinger et al. 1989 [129676] was used as the source for data 
on the Valley Fill Confining Unit (18), the Cenozoic Limestone Unit (17), Lava Flow Unit (16), 
Upper Carbonate Aquifer Unit (6), Lower Carbonate Aquifer Thrust Unit (5), Upper Clastic 
Confining Unit (4), Lower Carbonate Aquifer Unit (3), Lower Clastic Confining Unit (2) and the 
Granites Unit (1). All of the carbonate units were assigned the same value. 
The effective porosity values from Bedinger et al. 1989 [129676], Table 1 page A18 (DTN: 
MO0105HCONEPOR.000 [155044]) are used for all of the hydrogeologic units described in this 
paragraph. The upper and lower carbonate aquifer, the lower carbonate thrust aquifer and the 
cenozoic limestone units (designated as Units 6, 3, 5 and 17) respectively, use the mean value of 
Carbonate Rocks. The Cenozoic Limestone Unit is assigned the same value as the carbonate 
units because it is a similar rock type to the carbonate rocks. The value for granites (Unit 1) is 
set equal to the estimate for Metamorphic rock with a depth more than 300 m. Unit 16 is 
assigned the average of the Lava Flows, fractured and moderately dense, from the 
MO0105HCONEPOR.000 [155044] source. Units 4 and 2 utilize the mean value from the 
Clastic Sedimentary Units. Unit 18, utilizes the Basin fill mean value for fine-grained clay and 
silt cited in Table 1 of Bedinger et al. 1989 [129676]. This information is summarized in the 
spreadsheet geonames.xls (DTN: SN0306T0502103.006). Table 6-14 lists the constant values 
used for each unit, for the SZ Transport Abstraction Model for TSPA-LA.

MDL-NBS-HS-000021, REV 00 121 July, 2003 
Table 6-14. Values of Effective Porosity ( fe) for Several Units of the SZ Transport Abstraction Model 
SZ Unit Name SZ Unit Number Effective Porosity (fe) 
Valley Fill Confining Unit 18 0.32 
Cenozoic Limestone 17 0.01 
Lava Flows 16 0.08 
Upper Carbonate Aquifer 6 0.01 
Lower Carbonate Aquifer Thrust 5 0.01 
Upper Clastic Confining Unit 4 0.18 
Lower Carbonate Aquifer 3 0.01 
Lower Clastic Confining Unit 2 0.18 
Granites 1 0.0001 
DTN: SN0306T0502103.007 
6.5.3 Summary of Computational Models 
Both the SZ Transport Abstraction Model and the SZ 1-D Transport Model are intended for use 
in the analyses for TSPA-LA. The results of the multiple realizations of SZ transport with the 
SZ Transport Abstraction Model, in the form of multiple breakthrough curves, are coupled with 
the TSPA simulations using the convolution integral method. The SZ 1-D Transport Model is 
intended for direct incorporation into the TSPA model. The SZ 1-D Transport Model is 
developed independently of the TSPA model, but contains the elements necessary for 
implementation within the TSPA model. 
6.5.3.1 SZ Transport Abstraction Model 
The groups of radioelements for simulated transport in the SZ Transport Abstraction Model are 
summarized in Table 6-15. There are nine groupings of radionuclides indicated by the first 
column in Table 6-15. The modes of radioelement transport are as: 1) solute, 2) colloidfacilitated 
transport of radionuclides reversibly attached to colloids, and 3) colloid-facilitated 
transport of radionuclides irreversibly attached to colloids. As indicated in Table 6-15, the nonsorbing 
radioelements of carbon, technetium, and iodine are grouped together because their 
migration is identical. Americium, thorium, and protactinium reversibly attached to colloids are 
grouped together because of their similar sorption characteristics. Note that plutonium and 
americium may be transported both reversibly and irreversibly attached to colloids.

MDL-NBS-HS-000021, REV 00 122 July, 2003 
Table 6-15. Radioelements Transported in the SZ Transport Abstraction Model 
Radionuclide 
Number 
Transport Mode Radioelements 
1 Solute Carbon, Technetium, Iodine 
2 Colloid-Facilitated 
(Reversible) 
Americium, Thorium, Protactinium 
3 Colloid-Facilitated 
(Reversible) 
Cesium 
4 Colloid-Facilitated 
(Reversible) 
Plutonium 
5 Solute Neptunium 
6 Colloid-Facilitated 
(Irreversible) 
Plutonium, Americium 
7 Solute Radium 
8 Solute Strontium 
9 Solute Uranium 
DTN: SN0306T0502103.008 
The radioelement breakthrough curves from the SZ Transport Abstraction Model for the 200 
Monte Carlo realizations of SZ flow and transport are generated in the following manner. A 
steady-state groundwater flow field is produced for each of the 200 realizations prior to transport 
simulations. Variations in the groundwater specific discharge are included by scaling all values 
of permeability in the base case SZ Site-Scale Flow Model (BSC 2003 [162649]) and the values 
of specified recharge, using the value of the GWSPD parameter. Variations in horizontal 
anisotropy in permeability are included by scaling the values of north-south and east-west 
permeability within the zone of volcanic rocks influenced by anisotropy, using the value of the 
HAVO parameter. Each steady-state groundwater flow solution is stored to be used as the initial 
conditions in the radionuclide transport simulations. The SZ_Pre v. 2.0 software code (STN: 
10914-2.0-00, SNL 2003 [163281]) is a pre-processor that is used to prepare the FEHM v. 2.20 
software code (STN: 10086-2.20-00, LANL 2003 [161725]) input files for each of the 200 
realizations. The pre-processor reads the values of the parameters from an input file containing a 
table of values for all 200 realizations, performs relevant parameter transformations, and writes 
the appropriate values to the various FEHM v. 2.20 software code (STN: 10086-2.20-00, LANL 
2003 [161725]) input files. A total of 7200 individual simulations (200 realizations  9 
radioelement groups  4 source regions) of SZ transport are conducted and the particle tracking 
output files are saved. The particle tracking simulations of matrix diffusion use the type curves 
of the analytical solution for matrix diffusion in DTN: LA0302RP831228.001 [163557]. The 
SZ_Post v. 3.0 software code (STN: 10915-3.0-00, SNL 2003 [163571]) is a post-processor that 
is used to extract the breakthrough curves from the FEHM v. 2.20 software code (STN: 10086- 
2.20-00, LANL 2003 [161725]) output files and concatenate all 200 realizations into a single file 
for input to the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]) 
for use in the TSPA-LA.

MDL-NBS-HS-000021, REV 00 123 July, 2003 
For implementation of the SZ Transport Abstraction Model in the TSPA model, the specific 
radionuclides and the timing of climate change events must be specified in the control file for the 
SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]). The 
radionuclides for each radioelement and their corresponding values of half-life are specified in 
order for the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 [164180]) to 
calculate the decay of these radionuclides during simulated transport in the SZ. The number of 
climate states and the times at which climate changes occur during the TSPA model simulation 
are also specified in the control file for the SZ_Convolute v. 3.0 software code (STN: 10207-3.0- 
00, SNL 2003 [164180]). The multiplier of groundwater flow rate in the SZ (relative to present 
conditions) for each climate state is also specified for the TSPA simulation. The values for this 
factor are given in Table 6-5. 
6.5.3.2 SZ 1-D Transport Model 
Implementation of the SZ 1-D Transport Model in the TSPA Model requires that the standalone 
version of the model developed in this report be correctly integrated into the TSPA 
Model. The SZ 1-D Transport Model was developed in anticipation of integration into the TSPA 
Model, but the following aspects of the integration must be checked for implementation in the 
TSPA Model. The radionuclide flux into and out of the SZ 1-D Transport Model must be 
properly linked to the other components of the TSPA Model. The radionuclide decay and 
ingrowth chains and the corresponding half-life values of radionuclides must be consistent with 
the other components of the TSPA Model. The parameter values for the 200 realizations of the 
SZ Transport Abstraction Model are stored as a table in the TSPA Model and the SZ 1-D 
Transport Model must be correctly linked with this table of values to ensure consistency with the 
SZ Transport Abstraction Model on a realization-by-realization basis. The parameter vectors 
used in the SZ Transport Abstraction Model that need to be incorporated into the table values 
used by the SZ 1-D Transport Model are contained in Attachment I of this AMR and in DTN: 
SN0306T0502103.007. The variable controlling changes in climate state in the TSPA Model 
must be correctly linked with the SZ 1-D Transport Model.

MDL-NBS-HS-000021, REV 00 124 July, 2003 
6.6 BASE-CASE MODEL RESULTS 
Base-case model results from the SZ Transport Abstraction Model consist of radionuclide mass 
breakthrough curves at the accessible environment of the biosphere, approximately 18 km down 
gradient from the repository. A suite of breakthrough curves is generated for each species or 
class of radionuclides based on multiple realizations of the model. Variability in the results 
among these multiple realizations reflects uncertainty in groundwater flow and radionuclide 
transport behavior in the SZ. Variations in transport behavior among the species are also 
represented in these results. 
6.6.1 Overview 
The results of the 200 SZ Transport Abstraction Model realizations are shown in Figure 6-28 to 
Figure 6-36. Each figure shows the relative mass arriving at the accessible environment as a 
function of time and a histogram of median transport times, for a given category of radionuclides 
from Table 6-15. Note that the breakthrough curves and transport times shown in these figures 
are for a continuous, steady source at the water table below the repository (source region 1), 
initiated at time equal to zero. Also note that the breakthrough curves shown in these figures are 
for present climatic conditions and do not include the effects of radioactive decay. Recall that 
the process of radioactive decay is implemented in the SZ_Convolute v. 3.0 software code (STN: 
10207-3.0-00, SNL 2003 [164180]). 
Although individual breakthrough curves may be difficult to discern in some of the figures, both 
the timing and the shapes of the breakthrough curves vary among the realizations. Variability in 
the timing of the breakthrough is reflected in the histograms of median transport time, for the 
bulk of the radionuclide mass arrival at the accessible environment. Variability in the shapes of 
the breakthrough curves is a function of differences in matrix diffusion and dispersivity among 
the realizations.

MDL-NBS-HS-000021, REV 00 125 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-28. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Carbon, Technetium, and Iodine at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 126 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-29. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Americium, Thorium, and Protactinium on Reversible Colloids at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 127 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-30. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Cesium on Reversible Colloids at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 128 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-31. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Plutonium on Reversible Colloids at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 129 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-32. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Neptunium at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 130 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-33. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Plutonium and Americium on Irreversible Colloids at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 131 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-34. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Radium at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 132 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-35. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Strontium at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 133 July, 2003 
1 10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
1 10 100 1000 10000 100000 
Time (years) 
0 
10 
20 
30 
Frequency 
DTN: SN0306T0502103.008 
Figure 6-36. Mass Breakthrough Curves (Upper) and Median Transport Times (lower) 
for Uranium at 18-km Distance 
Note: Mass breakthrough curves and median transport times are for present climate and do not include radionuclide 
decay. Results shown for 200 realizations.

MDL-NBS-HS-000021, REV 00 134 July, 2003 
6.7 DESCRIPTION OF BARRIER CAPABILITY 
The SZ forms a barrier to the migration of radionuclides and the exposure of the potential 
receptor population to these radionuclides in two ways. Delay in the release of radionuclides to 
the accessible environment during transport in the SZ allows radioactive decay to diminish the 
mass of radionuclides that are ultimately released. Dilution of radionuclide concentrations in 
groundwater used by the potential receptor population occurs during transport in the SZ and in 
the process of producing groundwater from wells. Further discussion of the SZ flow system as a 
barrier to radionuclide migration at Yucca Mountain is found in Eddebbarh et al. 2003 [163577]. 
6.7.1 Analyses of Barrier Capability 
The simulated transport times of radionuclides in the SZ give a direct indication of the barrier 
capability of the SZ with regard to the delay in the release of radionuclides to the accessible 
environment. Uncertainty in the radionuclide transport times in the SZ is represented in the 
multiple realizations of the SZ system with the SZ Transport Abstraction Model and shown in 
the breakthrough curves for various radionuclides in Figure 6-28 to Figure 6-36. As shown by 
these figures, the effectiveness of the SZ as a barrier to transport varies significantly among the 
classes of radionuclides included in the analyses. The ranges of median transport times and the 
median transport times from all realizations for the various radionuclides are summarized in 
Table 6-16. 
Variations in the radionuclide transport time among the realizations shown in Figure 6-28 to 
Figure 6-36 reflect the aggregate uncertainty in the underlying input parameters to the SZ 
Transport Abstraction Model. Although formal sensitivity analyses have not been applied to 
these results, sensitivity analyses have been performed on previous SZ transport modeling results 
(Arnold et al. 2003 [163857]). Those analyses indicate that uncertainties in groundwater specific 
discharge, sorption coefficients, and retardation of colloids are major factors in the simulated 
uncertainty in radionuclide transport times. Parameters related to matrix diffusion and geologic 
uncertainty have significant, but secondary importance with regard to the uncertainty in 
radionuclide transport times. 
For non-sorbing species, such as carbon, technetium, and iodine, the delay afforded by the SZ 
may be less than 100 years to as much as 100,000 years, within the range of uncertainty 
indicated by the simulation results shown in Figure 6-28. The median transport time for nonsorbing 
species among all realizations is about 620 years. For the moderately sorbing species of 
neptunium, simulated median transport times range from about 200 years to greater than 100,000 
years, with a median transport time among all realizations of 17,100 years (see Table 6-16). For 
the strongly sorbing species of radium, simulated median transport times range from 80,200 to 
greater than 100,000 years, with a median transport time among all realizations of greater than 
100,000 years (see Table 6-16). 
Analyses with the SZ Transport Abstraction Model indicate that there is considerable uncertainty 
in the delay to release of radionuclides to the accessible environment for all radionuclides. The 
upper bounds of uncertainty in the transport times are greater than 100,000 years (the upper limit

MDL-NBS-HS-000021, REV 00 135 July, 2003 
of time in the transport simulations) for all radionuclides. The lower bounds of the uncertainty in 
transport times are indicated by the ranges given in Table 6-16. 
It should be noted that the summary of simulated transport times presented in Table 6-16 is given 
for SZ groundwater flow under present climatic conditions. Under glacial-transition climatic 
conditions that are expected to occur within the next 10,000 years the groundwater flow rate 
would be significantly higher. Groundwater flow rates in the SZ are estimated to be 3.9 times 
higher under glacial-transition climate conditions (see Section 6.5.1), corresponding to transport 
times of approximately 3.9 shorter than those presented in Table 6-16.

MDL-NBS-HS-000021, REV 00 136 July, 2003 
Table 6-16. Summary of Simulated Transport Times in the SZ Under Present Climatic Conditions 
Species Range of Median Transport 
Time (years) 
Median Transport 
Time Among All 
Realizations (years) 
Carbon 
Technetium 
Iodine 
20 - >100,000 620 
Reversible Colloids: 
Americium 
Thorium 
Protactinium 
25,000 - >100,000 >100,000 
Reversible Colloids: 
Cesium 
80,000 - >100,000 >100,000 
Reversible Colloids: 
Plutonium 
5,000 - >100,000 >100,000 
Neptunium 200 - >100,000 17,100 
Irreversible Colloids: 
Plutonium 
Americium 
200 - >100,000 19,400 
Radium 80,200 - >100,000 >100,000 
Strontium 3,300 - >100,000 >100,000 
Uranium 600 - >100,000 23,300 
6.7.2 Summary of Barrier Capability 
Taken as a whole, these analyses indicate that the SZ is expected to be a significant barrier to the 
transport of radionuclides to the accessible environment within the 10,000-year period of 
regulatory concern for the repository at Yucca Mountain. The expected behavior of the SZ 
system is to delay the transport of sorbing radionuclides and radionuclides associated with 
colloids for many thousands of years, even under future wetter climatic conditions. Non-sorbing 
radionuclides are expected to be delayed for hundreds of years during transport in the SZ. 
However, analyses of uncertainty in radionuclide transport in the SZ indicate that delays in the 
release of non-sorbing radionuclides could be as small as tens of years. The transport times in 
the SZ of neptunium, uranium, and of plutonium and americium irreversibly attached to colloids 
could be as small as hundreds of years, based on the analyses of uncertainty conducted with the 
SZ Transport Abstraction Model. It is important to note that ranges of uncertainty based on 
analyses with 200 Monte Carlo realizations extend to relatively low probability (approximately 
0.5% probability) and thus include relatively unlikely results. Nonetheless, lower values in the 
ranges of transport time are possible, given the degree of uncertainty included in the model. 
The radioactive decay of radionuclides during transport in the SZ enhances the barrier capability 
of the SZ by reducing the mass of radionuclides ultimately released to the accessible

MDL-NBS-HS-000021, REV 00 137 July, 2003 
environment. The effectiveness of the decay process in attenuating releases from the SZ is 
related to the delay in the SZ and the half-life of the radionuclide. For radionuclides with longer 
transport times in the SZ and relatively short half-lives, this process renders the SZ an extremely 
effective barrier. Sr-90 and Cs-137 transport times would exceed several thousand half-lives, i.e. 
greater than 100,000 years, based on the median transport time among all realizations (Table 
6-16). For comparison, the reduction in radioactivity after 20 half-lives is more than six orders 
of magnitude. For some radionuclides there would be a modest reduction in radionuclide mass 
during transport in the SZ. Pu-239 that is irreversibly attached to colloids would be expected to 
experience about 0.8 half-lives, based on the median transport time among all realizations (Table 
6-16). Several radionuclides would experience little attenuation due to radioactive decay during 
transport in the SZ. Tc-99, I-129, and Np-237 would have only very small reductions in mass 
during the delay in release afforded by the SZ, due to their long half-lives (2.13105 years for 
Tc-99 to 1.59107 years for I-129). 
The dilution of radionuclides in the SZ and during pumping from wells by the future 
hypothetical farming community is not quantitatively assessed with the transport modeling 
approach used in the SZ Transport Abstraction Model. The relatively low values of transverse 
dispersivity in the uncertainty distribution for this parameter suggests that a large amount of 
dilution in radionuclide concentration during transport from beneath the repository to the 
accessible environment in the SZ is not expected. It is likely that the amount of dilution implicit 
in capturing the contaminant plume in 3000 acre-ft/year for use by the hypothetical farming 
community would be greater than the dilution during transport in the SZ.

MDL-NBS-HS-000021, REV 00 138 July, 2003 
7. VALIDATION 
This section of the report documents the validation of both the SZ Transport Abstraction Model 
and the SZ 1-D Transport Model. For the SZ Transport Abstraction Model, a comparison is 
made between the abstraction model and the underlying process model, which is discussed in the 
report Site-Scale Saturated Zone Transport (BSC 2003 [162419]). This comparison tests the 
appropriateness and accuracy of the convolution integral method used in the SZ Transport 
Abstraction Model. Similarly, the validation of the SZ 1-D Transport Model consists of a 
qualitative comparison between the abstraction model and the site-scale process model 
mentioned above (BSC 2003 [162419]). In both cases, the validations of these models are 
performed for a range of behavior that is representative of the uncertainties being evaluated for 
the TSPA analyses. 
7.1 VALIDATION PROCEDURES 
As discussed above, validation of both the SZ Transport Abstraction Model and the SZ 1-D 
Transport Model involves comparison with the underlying process model (BSC 2003 [162419]). 
In making these comparisons, three cases for radionuclide transport are defined for 
implementation: median case, fast case, and slow case. The median case uses median values 
from uncertainty distributions for the relevant flow and transport parameters. The fast case uses 
parameter values set at the 90th percentile or the 10th percentile, depending on the parameter, that 
result in more rapid transport of radionuclides through the SZ. For example, the flowing interval 
spacing is set to its 90th percentile value, and the sorption coefficient is set to its 10th percentile 
value for transport of neptunium in the fast case. The slow case uses parameter values set at the 
90th percentile or 10th percentile that result in less rapid transport of radionuclides through the 
SZ. These three cases approximately span the range of uncertainty in results of the SZ Transport 
Abstraction Model with regard to radionuclide transport in the SZ, as shown in Figure 6-28 and 
Figure 6-32. The parameter values used in the median, fast, and slow cases are summarized in 
Table 7-1. 
The SZ Site-Scale Transport Model (BSC 2003 [162419]) was run for each of the three model 
validation cases by varying the input parameters to conform to the values given in Table 7-1. 
The steady-state groundwater flow solution for each case was first established by running the 
flow model (BSC 2003 [162649]) to equilibrium with the specified values of the parameters 
GWSPD and HAVO. The particle-tracking algorithm in the FEHM v. 2.20 software code (STN: 
10086-2.20-00, LANL 2003 [161725]) was then used to obtain the simulated mass breakthrough 
curves with the SZ site-scale transport model at the regulatory boundary of the accessible 
environment.

MDL-NBS-HS-000021, REV 00 139 July, 2003 
Table 7-1. Parameter Values in the Three Cases for SZ Transport Model Validation 
Parameter 
Name 
Parameter Description Median Case Fast Case Slow Case 
FISVO Flowing interval spacing in 
volcanic units 
1.29 
(19.5 m) 
1.82 
(66.1 m) 
0.67 
(4.68 m) 
HAVO Ratio of horizontal anisotropy 
in permeability 
4.2 16.25 1.0 
LDISP Longitudinal dispersivity 2.0 
(100 m) 
2.96 
(920 m) 
1.03 
(10.9 m) 
FPLAW Western boundary of the 
alluvial uncertainty zone 
0.5 0.1 0.9 
FPLAN Northern boundary of the 
alluvial uncertainty zone 
0.5 0.1 0.9 
NVF19 Effective porosity in shallow 
alluvium 
0.18 0.114 0.245 
NVF7 Effective porosity in 
undifferentiated valley fill 
0.18 0.114 0.245 
FPVO Fracture porosity in volcanic 
units 
-3.0 
(10-3) 
-3.89 
(1.29x10-4) 
-1.50 
(0.0316) 
DCVO Effective diffusion coefficient in 
volcanic units 
-10.3 
(5.0x10-11 m2/s) 
-10.68 
(2.08x10-11 m2/s) 
-9.65 
(2.22x10-10 m2/s) 
GWSPD Groundwater specific 
discharge multiplier 
0.0 
(1.0) 
0.477 
(3.0) 
-0.477 
(0.333) 
bulkdensity Bulk density of alluvium 1910 kg/m3 1810 kg/m3 2010 kg/m3 
KDNPVO Neptunium sorption coefficient 
in volcanic units 
1.3 ml/g 1.04 ml/g 1.6 ml/g 
KDNPAL Neptunium sorption coefficient 
in alluvium 
6.35 ml/g 4.26 ml/g 8.44 ml/g 
NOTE: Values in parentheses are the parameter values from log-transformed uncertainty distributions.

MDL-NBS-HS-000021, REV 00 140 July, 2003 
7.1.1 SZ Transport Abstraction Model 
Validation of the SZ Transport Abstraction Model is accomplished by running this model using 
the breakthrough curves for the three validation cases from the SZ Site-Scale Transport Model 
(BSC 2003 [162419]). The SZ Transport Abstraction Model uses the convolution integral 
method as implemented by the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 
2003 [164180]) to produce the radionuclide mass breakthrough to the accessible environment, 
given the time-varying input of mass at the water table below the repository for the TSPA. Note 
that model validation tests were performed with the SZ_Convolute v. 2.2 software code (STN: 
10207-2.2-00, SNL 2003 [163344]). 
For the first validation test, a constant input of 1 g/year from the UZ is applied at the upstream 
boundary of the SZ Transport Abstraction Model. This is essentially the same transport 
boundary condition used in the SZ Site-Scale Transport Model (BSC 2003 [162419]) to derive 
the SZ breakthrough curves for input to the abstraction model. Consequently, the output of the 
SZ Transport Abstraction Model should reproduce the breakthrough curve used as the input in 
the validation test. This validation test is conducted for both a non-sorbing species and for 
neptunium. The validation test is also run for the three validation cases described in the previous 
section. To facilitate comparison of the results, the transport simulations in both the SZ Site- 
Scale Transport Model and the SZ Transport Abstraction Model are performed without 
radioactive decay. 
As a second validation test, the mass balance of radionuclides transported in the SZ Transport 
Abstraction Model is checked. This check is performed by setting the upstream boundary 
condition equal to 1 g/year for time up to 1000 years and reducing this to 0 g/year for the 
remainder of the simulation. Thus, the total radionuclide mass input to the SZ Transport 
Abstraction Model is 1000 grams. Since radioactive decay is not included in this validation test, 
the cumulative output of the model over a long simulation time should also be 1000 grams. This 
second validation test is also run for the three validation cases described in the previous section 
(Table 7-1). 
It should be noted that several additional test cases for the SZ_Convolute v. 2.2 software code 
(STN: 10207-2.2-00, SNL 2003 [163344]) have been conducted for the purposes of software 
verification (BSC 2003, Validation Test Report for SZ_Convolute, V 2.2, SDN: 10207-VTR-2.2- 
00, MOL.20021202.0341 [163587]). These tests verify the ability of the convolution integral 
method, as implemented by the SZ_Convolute v. 2.2 software code (STN: 10207-2.2-00, SNL 
2003 [163344]), to simulate accurately radionuclide transport with variable input boundary 
conditions, radioactive decay, and variations in groundwater flux with climate change. Although 
not directly applied to the radionuclide transport results of the SZ Transport Abstraction Model 
presented in this report, the numerical testing of the software code used in this model provides 
additional confidence in the validity of the model. 
7.1.2 SZ 1-D Transport Model 
Validation of the SZ 1-D Transport Model is conducted by running this model and comparing 
the results to the output of the SZ Site-Scale Transport Model (BSC 2003 [162419] and DTN: 
LA0306SK831231.001 [164362]). The SZ 1-D Transport Model is implemented using the

MDL-NBS-HS-000021, REV 00 141 July, 2003 
GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]). 
Ultimately, the SZ 1-D Transport Model is fully integrated into the TSPA model; however, for 
the purposes of model development and validation, a stand-alone version of this model is used. 
For the validation test, a constant input of 1 g/year from the UZ is applied at the upstream 
boundary of the SZ 1-D Transport Model. This is the same radionuclide mass boundary 
condition used in the SZ Site-Scale Transport Model (BSC 2003 [162419]). The breakthrough 
curves from the SZ 1-D model should approximately match the output of the site-scale transport 
model. This validation test is conducted for both a non-sorbing species and for neptunium, and 
is run for the three validation cases described in the previous section. To facilitate comparison of 
the results, the transport simulations in both the SZ Site-Scale Transport Model and the SZ 1-D 
Transport Model are performed without radioactive decay. 
It should be noted that several additional test cases for the GoldSim v. 7.50.100-00 software code 
(STN: 10344-7.50.100-00), BSC 2003 [161572] have been conducted for the purposes of 
software verification (BSC 2002, Validation Test Report(VTR) for GoldSim, V 7.50.100, SDN: 
10344-VTR-7.50.100-00, MOL.20030312.0227 [163962]). These tests verify the ability of the 
GoldSim v. 7.50.100-00 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) to 
accurately simulate radioactive decay and ingrowth. Although not directly applied to the 
radionuclide transport results of the SZ 1-D Transport Model presented in this report, the 
numerical testing of the software code used in this model provides additional confidence in the 
validity of the model. 
Groundwater flow rates and flow-path lengths derived from the SZ Site-Scale Transport Model 
(BSC 2003 [162419]) were used in the development of the SZ 1-D Transport Model. However, 
both the approximate nature of the equivalency between the two models and the reduction in 
dimensionality in the 1-D transport model limit the ability of the 1-D model to match the results 
of the site-scale transport model. 
7.2 VALIDATION CRITERIA 
Model validation follows the Technical Work Plan for: Saturated Zone Flow and Transport 
Modeling and Testing (BSC 2003 [163965], Section 2.5). The TWP states that Level-II 
validation will be achieved by satisfying the criteria listed as items a) through f) in Appendix B 
of the Scientific Processes Guidelines Manual (BSC 2002 [160313] and implementing one postdevelopment 
validation method. In this case, the post-development method was chosen to be the 
corroboration of the abstraction model results to the results of the validated process model from 
which the abstraction was derived (BSC 2003 [163965], Section 2.5). In addition, the TWP 
validation plan for the SZ Flow and Transport Abstraction Model includes a check of output for 
mass balance. 
The acceptance criterion for validation of both the SZ Transport Abstraction Model and the SZ 
1-D Transport Model is a favorable qualitative comparison between the simulated SZ 
breakthrough curves from these two models and the breakthrough curve from the SZ Site-Scale 
Transport Model (BSC 2003 [162419] and DTN: LA0306SK831231.001 [164362]). The 
breakthrough curves are compared at 10%, 50%, and 90% mass breakthrough in the evaluation 
of this criterion. Breakthrough curves are compared for a non-sorbing species and for

MDL-NBS-HS-000021, REV 00 142 July, 2003 
neptunium. Breakthrough curves for the median, fast, and slow cases outlined above are 
compared. Qualitative comparison of breakthrough curves is conducted by visual examination 
of graphs made of the breakthrough curves. 
An additional acceptance criterion for the validation of the SZ Transport Abstraction Model is a 
check of the radionuclide mass balance in the model. The mass input to the model should equal 
the mass output from the model over long time periods. Discrepancies of a few percent are 
acceptable due to both less-than-complete discharge of radionuclide mass from the model and 
numerical (truncation) errors in the computer software implementing the numerical integration 
used in the convolution integral method. 
These acceptance criteria reflect the essential functions of the SZ system with regard to the 
transport time and radionuclide mass delivery to the accessible environment. 
7.3 RESULTS OF VALIDATION ACTIVITIES 
The numerical results of the model validation activities described above are presented primarily 
as a series of plots of simulated breakthrough curves. A quantitative comparison of models with 
regard to radionuclide mass balance is also presented for the SZ Transport Abstraction Model. 
7.3.1 SZ Transport Abstraction Model Validation Results 
Results of the SZ Transport Abstraction Model and the SZ Site-Scale Transport Model (BSC 
2003 [162419]) for a non-sorbing species are shown as simulated breakthrough curves in Figure 
7-1. This figure shows results for the median, fast and slow cases of SZ transport. Note that all 
simulations were conducted without radioactive decay. The simulated breakthrough curves from 
the SZ Site-Scale Transport Model are shown with the solid and dashed lines for the three cases. 
The results from the SZ Transport Abstraction Model are shown as the open symbols that are 
superimposed on the breakthrough curves from the site-scale model.

MDL-NBS-HS-000021, REV 00 143 July, 2003 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ Site-scale Transport Model (BSC 2003 [162419]) are shown for the median case (solid 
line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ Transport 
Abstraction Model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-1. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction 
Model and the SZ Site-Scale Transport Model for a Non-Sorbing Radionuclide 
Visual comparison of the open symbols and the lines in Figure 7-1 indicates very close 
agreement in the results from the SZ Transport Abstraction Model and the SZ Site-Scale 
Transport Model for all three cases of SZ transport. The one exception is the first point in the 
results of the SZ Transport Abstraction Model for the fast case, which is lower than the 
corresponding breakthrough curve from the SZ Site-Scale Transport Model. It should be noted 
that the time step used in the abstraction model is 20 years, which differs from the 10-year time 
step used in the site-scale model for the fast case. This difference in time-step size accounts for 
the small discrepancy between the models at the first time step. 
Results of the SZ Transport Abstraction Model and the SZ Site-Scale Transport Model (BSC 
2003 [162419] and DTN: LA0306SK831231.001 [164362]) for neptunium are shown as 
simulated breakthrough curves in Figure 7-2. This figure shows results for the median, fast, and 
slow cases of SZ transport. Note that all simulations were conducted without radioactive decay. 
The simulated breakthrough curves from the SZ Site-Scale Transport Model are shown with the 
solid and dashed lines for the three cases. The results from the SZ Transport Abstraction Model

MDL-NBS-HS-000021, REV 00 144 July, 2003 
are shown as the open symbols that are superimposed on the breakthrough curves from the sitescale 
model. 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ Site-Scale Transport Model (BSC 2003 [162419]) are shown for the median case (solid 
line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ Transport 
Abstraction Model are shown for the median case (open circle), fast case (open square), and slow case 
(open triangle). Breakthrough curves do not include radioactive decay. 
Figure 7-2. Simulated Breakthrough Curves Comparing the Results of the SZ Transport Abstraction 
Model and the SZ Site-Scale Transport Model for Neptunium 
Visual comparison of the open symbols and the lines in Figure 7-2 indicates very close 
agreement in the results from the SZ Transport Abstraction Model and the SZ Site-Scale 
Transport Model for all three cases of SZ transport of neptunium. 
Figure 7-3 shows the simulated breakthrough curve from the SZ Transport Abstraction Model of 
a non-sorbing species for the median case. This simulation applies a radionuclide mass influx 
boundary condition of 1 g/year for the first 1000 years of the simulation, which results in a total 
mass input of 1000 grams. The mass balance in the SZ Transport Abstraction Model is checked 
by summing the total mass output from the simulated breakthrough curve shown in Figure 7-3 
over the 100,000 years of the simulation. The output sum is 981 grams, which is 98.1% of the 
input mass. Examination of the simulated breakthrough curve from the SZ Site-Scale Transport 
Model for the median case indicates that 98 % of the mass has reached the accessible

MDL-NBS-HS-000021, REV 00 145 July, 2003 
environment within 100,000 years. Consequently, the discrepancy between total input mass and 
total output mass can be explained as the radionuclide mass retained in the SZ system after 
100,000 years. The total output mass from the SZ Transport Abstraction Model for the fast case 
and the slow case is 99.8% and 99.5% of the input mass, respectively. Mass breakthrough for 
the median case has a longer tail than the slow and fast cases due to matrix diffusion. 
Consequently, the total mass output is somewhat lower for the median case than the slow and 
fast cases in this validation test. 
10 100 1000 10000 100000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
NOTE: Results from the SZ Transport Abstraction Model are shown for the median case. The breakthrough curve 
does not include radioactive decay. 
Figure 7-3. Simulated Breakthrough Curve for a Non-Sorbing Radionuclide from a 
1000-Year-Duration Source 
7.3.2 SZ 1-D Transport Model Validation Results 
Results of the SZ 1-D Transport Model and the SZ Site-Scale Transport Model for a non-sorbing 
species are shown as simulated breakthrough curves in Figure 7-4. This figure shows results for 
the median, fast, and slow cases of SZ transport. Note that all simulations were conducted 
without radioactive decay. The simulated breakthrough curves from the SZ Site-Scale Transport 
Model are shown with the solid and dashed lines for the three cases. The results from the SZ 1D

MDL-NBS-HS-000021, REV 00 146 July, 2003 
Transport Model are shown as the open symbols superimposed on the breakthrough curves from 
the SZ Site-Scale Transport Model. 
Visual comparison of the open symbols and the lines in Figure 7-4 indicates close agreement in 
the results for a non-sorbing species from the SZ 1-D Transport Model and the SZ Site-Scale 
Transport Model for the median case of SZ transport. There is generally close comparison in the 
overall shapes of the breakthrough curves from the SZ 1-D Transport Model and the SZ Site- 
Scale Transport Model, as indicated by the times of 10%, 50%, and 90% of mass breakthrough, 
with somewhat greater deviation for the upper tails of the breakthrough curves. 
Results of the SZ 1-D Transport Model and the SZ Site-Scale Transport Model for neptunium 
are shown as simulated breakthrough curves in Figure 7-5. This figure shows results for the 
median, fast and slow cases of SZ transport. Note that all simulations were conducted without 
radioactive decay. The simulated breakthrough curves from the SZ Site-Scale Transport Model 
are shown with the solid and dashed lines for the three cases. The results from the SZ 1-D 
Transport Model are shown as the open symbols superimposed on the breakthrough curves from 
the SZ Site-Scale Transport Model. 
Visual comparison of the open symbols and the lines in Figure 7-5 indicates close agreement in 
the results for neptunium from the SZ 1-D Transport Model and the SZ Site-Scale Transport 
Model for the median case of SZ transport. The comparison is slightly less close for the fast case 
and slow case. There is generally close comparison in the overall shapes of the breakthrough 
curves from the SZ 1-D Transport Model and the SZ Site-Scale Transport Model.

MDL-NBS-HS-000021, REV 00 147 July, 2003 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
Output DTN: SN0306T0502103.005 
NOTE: Results from the SZ Site-Scale Transport Model (BSC 2003 [162419]) are shown for the median case (solid 
line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D Transport 
Model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). 
Breakthrough curves do not include radioactive decay. 
Figure 7-4. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and 
the SZ Site-Scale Transport Model for a Non-Sorbing Radionuclide

MDL-NBS-HS-000021, REV 00 148 July, 2003 
10 100 1000 10000 100000 1000000 
Time (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Relative Mass 
Output DTN: SN0306T0502103.005 
NOTE: Results from the SZ Site-Scale Transport Model (BSC 2003 [162419]) are shown for the median case (solid 
line), fast case (short-dashed line), and slow case (long-dashed line). Results from the SZ 1-D Transport 
Model are shown for the median case (open circle), fast case (open square), and slow case (open triangle). 
Breakthrough curves do not include radioactive decay. 
Figure 7-5. Simulated Breakthrough Curves Comparing the Results of the SZ 1-D Transport Model and 
the SZ Site-Scale Transport Model for Neptunium 
7.4 CONCLUSIONS 
7.4.1 SZ Transport Abstraction Model Validation 
Validation testing of the SZ Transport Abstraction Model indicates good agreement with the SZ 
Site-Scale Transport Model (BSC 2003 [162419]). Acceptance criteria established for the model 
validation regarding the qualitative comparison of simulated breakthrough curves and the 
quantitative evaluation of radionuclide mass balance are met. Results of the validation testing 
indicate that the SZ Transport Abstraction Model is valid for the approximate range of 
uncertainty incorporated into the model through parameter uncertainty distributions. Results also 
indicate that the SZ Transport Abstraction Model is valid for both non-sorbing and sorbing 
radionuclide species for its intended use.

MDL-NBS-HS-000021, REV 00 149 July, 2003 
It should be noted that the SZ is more effective as a barrier for highly sorbing, short-lived 
radionuclides such as Sr-90 and Cs-137, relative to neptunium, as used in this validation testing. 
The validation testing does not demonstrate the delay afforded by the SZ in the migration of 
these radionuclides; nor does it demonstrate the impact of radionuclide decay. However, the 
importance of the SZ as a barrier to Sr-90 and Cs-137 transport, with regard to both delay and 
decay, is discussed in Section 6.7. 
The small deviation from the SZ Site-Scale Transport Model results at early times for the fast 
case is a result of the time-step size used in the simulation. Such deviations in the abstraction 
model for realizations with very fast transport in the SZ would not be significant within the 
context of the TSPA analyses using this model. The discrepancy in radionuclide mass balance 
identified in the validation testing is a small percentage and is readily understood with regard to 
long-term mass retention in the SZ due to the matrix diffusion process. No future activities are 
needed to complete this model validation for its intended use. 
7.4.2 SZ 1-D Transport Model Validation 
Validation testing of the SZ 1-D Transport Model indicates acceptable agreement with the SZ 
Site-Scale Transport Model (BSC 2003 [162419]). Qualitative acceptance criteria regarding the 
comparison of the simulated breakthrough curves with the results of the SZ Site-Scale Transport 
Model are met. Results of the validation testing indicate that the SZ 1-D Transport Model is 
valid for the approximate range of uncertainty incorporated into the model through parameter 
uncertainty distributions. Results also indicate that the SZ 1-D Transport Model is valid for both 
non-sorbing and sorbing radionuclide species for its intended use. 
It is relevant to consider the purpose and use of the SZ 1-D Transport Model in the evaluation of 
validation testing results. This model is used for the purpose of simulating radioactive decay and 
ingrowth for four decay chains. This simplified model is required because the SZ Transport 
Abstraction Model is not capable of simulating ingrowth by radioactive decay. It is not 
anticipated that the decay products in these decay chains would be significant contributors to 
total radiological dose; however, groundwater protection regulations require assessment of 
groundwater concentrations for some of these daughter products. The results of the SZ 1-D 
Transport Model are used only for the daughter products in these decay chains within the TSPA 
analyses. 
It must also be considered that there are fundamental differences between the SZ 1-D Transport 
Model and the SZ Site-Scale Transport Model that limit the degree of consistency that can be 
expected between these two models. Groundwater flow and radionuclide transport simulation in 
the SZ Site-Scale Transport Model occur in three dimensions with a relatively complex 
representation of geological heterogeneity from the hydrogeologic framework model. 
Radionuclide transport in the SZ 1-D Transport Model is simulated in a significantly simplified 
representation of the SZ system consisting of three pipe segments. Each pipe segment has 
properties that represent the average characteristics in that area of the SZ Site-Scale Transport 
Model.

MDL-NBS-HS-000021, REV 00 150 July, 2003 
Considering these factors, the SZ 1-D Transport Model provides a very good approximation of 
simulated radionuclide transport in the three-dimensional system of the SZ. No future activities 
are needed to complete this model validation for its intended use.

MDL-NBS-HS-000021, REV 00 151 July, 2003 
8. CONCLUSIONS 
8.1 SUMMARY OF MODELING ACTIVITY 
The SZ Transport Abstraction Model and the SZ 1-D Transport Model are developed for use in 
the TSPA analyses. In addition, analyses of uncertainty in input parameters for these models are 
conducted and the results are documented as uncertainty distributions. Values of uncertain 
parameters are sampled for 200 realizations of the SZ flow and transport system. Simulations 
are conducted for these 200 realizations with the SZ Transport Abstraction Model and the results 
are documented. 
Analyses of parameter uncertainty and multiple realizations of the SZ system using the SZ 
Transport Abstraction Model constitute an assessment of uncertainty in the SZ system for direct 
implementation in the TSPA model. The simulated radionuclide mass breakthrough curves from 
the SZ Transport Abstraction Model are coupled to the TSPA analyses using the convolution 
integral method (via the SZ_Convolute v. 3.0 software code (STN: 10207-3.0-00, SNL 2003 
[164180])). 
In addition, the SZ 1-D Transport Model is developed for direct implementation with the 
GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) in the 
TSPA. The uncertain input parameters defined for the SZ Transport Abstraction Model are to be 
used in the SZ 1-D Transport Model for consistency between the two models when used in the 
probabilistic analyses of TSPA. 
Both the SZ Transport Abstraction Model and the SZ 1-D Transport Model are validated and the 
results of these validation activities are documented in this report. Validation of the SZ 
Transport Abstraction Model indicates very close agreement with the underlying SZ Site-Scale 
Transport Model using the convolution integral method. Although the SZ 1-D Transport Model 
is significantly simplified relative to the three-dimensional SZ Transport Abstraction Model, 
validation of the SZ 1-D Transport Model indicates close agreement between the models for 
representative radionuclides over a broad range of uncertainty in SZ transport behavior. 
The technical bases of FEPs included in the models are presented in this report and related to 
parameters and components of the SZ Transport Abstraction Model and the SZ 1-D Transport 
Model. The role of the SZ as a natural barrier to the transport of radionuclides is assessed in 
relation to the results of the SZ Transport Abstraction Model. In addition, the model 
development and analyses presented in this AMR are related to acceptance criteria specified in 
the YMRP (NRC 2003 [163274]). 
Information on the correlation between distribution coefficients (Kd s) used in the sampling of 
uncertain parameters for the SZ Transport Abstraction Model and the SZ 1-D Transport Model is 
given in Table 4-1 and Table 6-8. Positive correlation between the distribution coefficient for 
uranium in volcanic units and alluvium is specified, based on the potentially similar

MDL-NBS-HS-000021, REV 00 152 July, 2003 
hydrochemical conditions in both aquifers. Positive correlation between the distribution 
coefficient for neptunium in volcanic units and alluvium is specified, based on the potentially 
similar hydrochemical conditions in both aquifers. Positive correlation between the distribution 
coefficient for plutonium in volcanic units and alluvium is specified, based on the potentially 
similar hydrochemical conditions in both aquifers. Positive correlation between the distribution 
coefficients for uranium and neptunium is specified, based on similarities in the chemical 
behavior of these radioelements. The technical bases for correlations between distribution 
coefficients (or the lack thereof) are documented in BSC 2003 [162419], Attachment I, Section 
I.10. 
Evaluation of uncertainty in horizontal anisotropy of permeability is summarized in Section 
6.5.2.10. Complete documentation of the technical basis for this evaluation of uncertainty is 
given in BSC 2003 [162415], Section 6.2.6. Results of this evaluation indicate that there is a 
greater probability of enhanced permeability in the north-south direction, but a small probability 
of greater permeability in the east-west direction. Implementation of uncertainty in horizontal 
anisotropy in the SZ Transport Abstraction Model and the SZ 1-D Transport Model is discussed 
in Section 6.5.3.1 and Section 6.5.1.2, respectively. 
The impacts of spatial variability of parameters affecting radionuclide transport in the alluvium 
are incorporated in the evaluation of uncertainties in model parameters in Section 6.5.2.3, 
Section 6.5.2.7, Section 6.5.2.8, Section 6.5.2.9, and Section 6.5.2.11. Uncertainties in 
individual parameters affecting radionuclide transport, as influenced by spatial variability, are 
combined in the probabilistic analyses with the SZ Transport Abstraction Model. The technical 
bases for uncertainty in distribution coefficients are documented in BSC 2003 [162419], 
Attachment I. 
Information on the geological uncertainty in the location of the contact between tuff and 
alluvium and the consequent uncertainty in the flow path lengths in the alluvium is presented in 
Section 6.5.2.2. This evaluation of uncertainty includes currently available information from the 
Nye County drilling program. Reevaluation of the uncertainty in the northern and western extent 
of the alluvium resulted in significant reduction in this uncertainty relative to the previous 
evaluation in CRWMS M&O 2000 [147972], Section 6.2. 
The sensitivity analysis of matrix diffusion in the SZ Transport Abstraction Model is presented 
in the assessment of alternative conceptual models in Section 6.4. The results of this sensitivity 
analysis indicate that a minimal matrix diffusion ACM is captured within the range of 
uncertainty used in the SZ Transport Abstraction Model.

MDL-NBS-HS-000021, REV 00 153 July, 2003 
8.2 MODEL OUTPUTS 
8.2.1 Developed Output 
The technical output from this report is contained in four DTNs that are summarized in Table 
8-1. 
Table 8-1. Summary of Developed Output 
Output DTN Description 
SN0306T0502103.007 Uncertainty distributions for parameters used in the SZ Transport Abstraction Model. 
Sampling output of uncertain parameters for 200 realizations is also included (see 
Attachment I). This DTN also includes a description of each uncertain parameter. 
SN0306T0502103.008 Input and output files for the SZ Transport Abstraction Model. This DTN also contains the 
output breakthrough curves for use in the TSPA analyses. 
SN0306T0502103.005 Input and output files for the SZ 1-D Transport Model. 
SN0306T0502103.006 Data spreadsheets to support data uncertainty development. 
Results of the parameter uncertainty analyses from this AMR are contained in DTN: 
SN0306T0502103.007. These results include the uncertainty distributions for parameters that 
were developed in this analysis or incorporated from other analyses and the input file for the 
GoldSim v. 7.50.100 software code (STN: 10344-7.50.100-00) for sampling 200 realizations 
from these uncertainty distributions. This DTN also contains the output file from the GoldSim v. 
7.50.100 software code (STN: 10344-7.50.100-00) containing the parameter vectors to be used in 
the SZ Transport Abstraction Model. 
Results of the SZ Transport Abstraction Model from this AMR are contained in DTN: 
SN0306T0502103.008. These results consist of the input and output files from the FEHM v. 
2.20 software code (STN: 10086-2.20-00), the SZ_Pre v. 2.0 software code (STN: 10914-2.0- 
00), and the SZ_Post v. 3.0 software code (STN: 10915-3.0-00) used in the analyses. The results 
that form a direct input to the TSPA model are the files containing the breakthrough curves from 
the SZ Transport Abstraction Model for the 200 realizations of radionuclide transport. The 
breakthrough curves for use in the TSPA model (i.e., the breakthrough curves at the regulatory 
boundary of the accessible environment) are defined by the first column (time) and the third 
column (relative mass) in the output files.

MDL-NBS-HS-000021, REV 00 154 July, 2003 
The input and output files for the SZ 1-D Transport Model are contained in DTN: 
SN0306T0502103.005. The input file of the SZ 1-D Transport Model for the GoldSim v. 
7.50.100 software code (STN: 10344-7.50.100-00, BSC 2003 [161572]) is intended for 
incorporation into the TSPA model. 
The data spreadsheets contained in DTN: SN0306T0502103.006 contain the data used and 
support the analyses of parameter uncertainty summarized in this report and in DTN: 
SN0306T0502103.007. The spreadsheets mentioned by filename in this report are contained in 
DTN: SN0306T0502103.006. 
8.2.2 Output Uncertainties and Limitations 
The assessment of uncertainty in model parameters and model outputs is an integral part of the 
analyses performed in this AMR. Uncertainty in model parameters is quantitatively represented 
with the statistical distributions developed and contained in DTN: SN0306T0502103.007. 
Uncertainty in radionuclide transport in the SZ Transport Abstraction Model is embodied in the 
breakthrough curves for the 200 realizations contained in DTN: SN0306T0502103.008. The SZ 
1-D Transport Model is intended for incorporation into the TSPA Model, with which uncertainty 
will be assessed using Monte Carlo probabilistic analyses. 
All relevant uncertainties in data and model parameters, as they affect groundwater flow and 
radionuclide transport, have been included in the SZ Transport Abstraction Model and the SZ 1- 
D Transport Model. Uncertainties have been propagated through the results of the SZ Transport 
Abstraction Model (i.e., the radionuclide breakthrough curves for multiple realizations) 
documented in this report. These output uncertainties meet the YMRP (NRC 2003 [163274]) 
acceptance criterion 3 for the propagation of data uncertainty through model abstraction for flow 
paths in the saturated zone and for radionuclide transport in the saturated zone. 
Use of the SZ Transport Abstraction Model and the SZ 1-D Transport Model is subject to the 
limitations and restrictions imposed by the assumptions listed in Sections 5, 6.3, and 6.5 of this 
model report. Limitations in knowledge of specific parameter values are addressed in the 
analysis of parameter uncertainties in this report. The radionuclide breakthrough curves 
generated for the SZ Transport Abstraction model are limited to 100,000 years duration for 
present climatic conditions. This limits the time period that can be simulated with the TSPA 
model using these breakthrough curves for the SZ. Because the SZ breakthrough curves are 
scaled for higher groundwater flow rates under future climatic conditions, the time period that 
can be simulated with the TSPA model would be significantly less than 100,000 years. If the 
glacial-transition climate state is applied for most of simulation period in the TSPA model, the 
SZ breakthrough curves would be scaled by a factor of approximately 4, limiting the TSPA 
model simulation time to about 25,000 years.

MDL-NBS-HS-000021, REV 00 155 July, 2003 
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Kotra, J.P.; Lee, M.P.; Eisenberg, N.A.; and DeWispelare, A.R. 1996. Branch Technical 
Position on the Use of Expert Elicitation in the High-Level Radioactive Waste Program. 
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Kreft, A. and Zuber, A. 1978. "On the Physical Meaning of the Dispersion Equation and Its 
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(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. 
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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 
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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 
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McKenna, S.A.; Walker, D.D.; and Arnold, B. 2003. "Modeling Dispersion in Three- 
Dimensional Heterogeneous Fractured Media at Yucca Mountain." Journal of Contaminant 
Hydrology, 62-63, 577-594. New York, New York: Elsevier. TIC: 254205. [163578]

MDL-NBS-HS-000021, REV 00 161 July, 2003 
Miller, I. and Kossik, R. 1998. Repository Integration Program RIP Integrated Probabilistic 
Simulator for Environmental Systems Theory Manual and 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] 
Reimus, Paul W.; M. J. Haga; A. I. Adams; T. J. Callahan; H.J. Turin; and D. A. Counce 2003. 
"Testing and Parameterizing a Conceptual Solute Transport Model in Saturated Fractured Tuffs 
Using Sorbing and Nonsorbing Tracers in Cross-Hole Tracer Tests." Journal of Contaminant 
Hydrology, 62-63, (April - May 2003), 613-636. New York, New York: Elsevier. [162950] 
Reimus, P.W.; Haga, M.J.; Humphrey, A.R.; Counce, D.A.; Callahan, T.J.; and Ware, S.D. 
2002. Diffusion Cell and Fracture Transport Experiments to Support Interpretations of the 
BULLION Forced-Gradient Experiment. LA-UR-02-6884. [Los Alamos, New Mexico]: Los 
Alamos National Laboratory. TIC: 253859. [162956] 
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and Gonzales, D. 2002. Diffusive and Advective Transport of {superscript 3}H, {superscript 
14}C, and {superscript 99}Tc in Saturated, Fractured Volcanic Rocks from Pahute Mesa, 
Nevada. LA-13891-MS. Los Alamos, New Mexico: Los Alamos National Laboratory. TIC: 
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Nonsorbing Tracers in Yucca Mountain Tuff. Milestone R524. Los Alamos, New Mexico: Los 
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in Crystalline Rocks." Water Resources Research, 22, (3), 389-398. [Washington, D.C.]: 
American Geophysical Union. TIC: 225291. [156862]

MDL-NBS-HS-000021, REV 00 162 July, 2003 
Triay, I.R.; Birdsell, K.H.; Mitchell, A.J.; and Ott, M.A. 1993. "Diffusion of Sorbing and Non- 
Sorbing Radionuclides." High Level Radioactive Waste Management, Proceedings of the Fourth 
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Grange Park, Illinois: American Nuclear Society. TIC: 208542. [145123] 
USGS (U.S. Geological Survey) 2001. Hydrogeologic Framework Model for the Saturated- 
Zone Site-Scale Flow and Transport Model. ANL-NBS-HS-000033 REV 00 ICN 02. Denver, 
Colorado: U.S. Geological Survey. ACC: MOL.20011112.0070. [158608] 
USGS (U.S. Geological Survey) 2001. Water-Level Data Analysis for the Saturated Zone Site- 
Scale Flow and Transport Model. ANL-NBS-HS-000034 REV 01. Denver, Colorado: U.S. 
Geological Survey. ACC: MOL.20020209.0058. [157611] 
USGS (U.S. Geological Survey) n.d. Bulk Density. [Denver, Colorado: U.S. Geological 
Survey]. ACC: NNA.19940406.0076. [154495] 
Viswanath, D.S. and Natarajan, G. 1989. Data Book on the Viscosity of Liquids. 714-715. New 
York, New York: Hemisphere Publishing Corporation. TIC: 247513. [129867] 
Wilson, M.L.; Gauthier, J.H.; Barnard, R.W.; Barr, G.E.; Dockery, H.A.; Dunn, E.; Eaton, R.R.; 
Guerin, D.C.; Lu, N.; Martinez, M.J.; Nilson, R.; Rautman, C.A.; Robey, T.H.; Ross, B.; Ryder, 
E.E.; Schenker, A.R.; Shannon, S.A.; Skinner, L.H.; Halsey, W.G.; Gansemer, J.D.; Lewis, L.C.; 
Lamont, A.D.; Triay, I.R.; Meijer, A.; and Morris, D.E. 1994. Total-System Performance 
Assessment for Yucca Mountain  SNL Second Iteration (TSPA-1993). SAND93-2675. 
Executive Summary and two volumes. Albuquerque, New Mexico: Sandia National 
Laboratories. ACC: NNA.19940112.0123. [100191] 
Zyvoloski, G.; Kwicklis, E.; Eddebbarh, A.A.; Arnold, B.; Faunt, C.; and Robinson, B.A. 2003. 
"The Site-Scale Saturated Zone Flow Model for Yucca Mountain: Calibration of Different 
Conceptual Models and their Impact on Flow Paths." Journal of Contaminant Hydrology, 62-63, 
731-750. [New York, New York]: Elsevier. TIC: 254340. [163341] 
Zyvoloski, G.A.; Robinson, B.A.; Dash, Z.V.; and Trease, L.L. 1997. Summary of the Models 
and Methods for the FEHM 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. Readily available. [156605] 
AP-2.22Q, Rev. 0, ICN 1. Classification Criteria and Maintenance of the Monitored Geologic 
Repository Q-List. Washington, D.C.: U.S. Department of Energy, Office of Civilian 
Radioactive Waste Management. ACC: DOC.20030422.0009. [163021]

MDL-NBS-HS-000021, REV 00 163 July, 2003 
AP-AC.1Q, Rev. 0, ICN 0. Expert Elicitation. Washington, D.C.: U.S. Department of Energy, 
Office of Civilian Radioactive Waste Management. ACC: MOL.19991019.0014. [138711] 
AP-SI.1Q, Rev. 5, ICN 0. Software Management. Washington, D.C.: U.S. Department of 
Energy, Office of Civilian Radioactive Waste Management. ACC: DOC.20030422.0012. 
[163085] 
AP-SIII.10Q, Rev. 1, ICN 2. Models. Washington, D.C.: U.S. Department of Energy, Office of 
Civilian Radioactive Waste Management. ACC: DOC.20030627.0003. [164074] 
9.3 SOFTWARE 
BSC (Bechtel SAIC Company) 2003. Software Code: GoldSim. 7.50.100. PC. 10344- 
7.50.100-00. [161572] 
LANL (Los Alamos National Laboratory) 2001. Software Code: CORPSCON. V5.11.08. 
10547-5.11.08-00. [155082] 
LANL (Los Alamos National Laboratory) 2003. Software Code: FEHM. V2.20. SUN, PC. 
10086-2.20-00. [161725] 
Sandia National Laboratories (SNL) 2003. Software Code: SZ_Convolute. V2.2. PC, Windows 
2000. 10207-2.2-00. [163344] 
Sandia National Laboratories (SNL) 2003. Software Code: SZ_Post. V3.0. Sun, SunO.S. 5.7. 
10915-3.0-00. [163571] 
Sandia National Laboratories (SNL) 2003. Software Code: SZ_Pre. V2.0. Sun, Solaris 7. 
10914-2.0-00. [163281] 
9.4 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
GS010908312332.002. Borehole Data from Water-Level Data Analsis for the Saturated Zone 
Site-Scale Flow and Transport Model. Submittal date: 10/02/2001. [163555] 
GS030108314211.001. Interpretation of the Lithostratigraphy in Deep Boreholes NC-EWDP- 
18P, NC-EWDP-22SA, NC-EWDP-10SA, NC-EWDP-23P, NC-EWDP-19IM1A, and NCEWDP-
19IM2A, Nye County Early Warning Drilling Program, Phase III. Submittal date: 
02/11/2003. [163483] 
LA0002JC831341.001. Depth Intervals and Bulk Densities of Alluviums. Submittal date: 
03/08/2000. [147081]

MDL-NBS-HS-000021, REV 00 164 July, 2003 
LA0302AM831341.001. Saturated Zone Distribution Coefficents (KDS) for U, NP, PU, CS, 
AM, PA, SR, TH, RA, C, TC, AND I. Submittal date: 02/04/2003. [163556] 
LA0302RP831228.001. Type Curve Data for FEHM Macro "SPTR" Based on Sudicky and 
Frind Solution. Submittal date: 02/11/2003. [163557] 
LA0303HV831352.002. Colloid Retardation Factors for the Saturated Zone Fractured 
Volcanics. Submittal date: 03/31/2003. [163558] 
LA0303HV831352.004. Colloid Retardation Factors for the Saturated Zone Alluvium. 
Submittal date: 03/31/2003. [163559] 
LA0303PR831231.002. Estimation of Groundwater Drift Velocity from Tracer Responses in 
Single-Well Tracer Tests at Alluvium Testing Complex. Submittal date: 03/18/2003. [163561] 
LA0306SK831231.001. SZ Site-Scale Transport Model, FEHM Files for Base Case. Submittal 
date: 06/25/2003. [164362] 
LB990801233129.004. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and 
Submodels" (Flow Field #4). Submittal date: 11/29/1999. [117129] 
LB990801233129.009. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and 
Submodels" (Flow Field #9). Submittal date: 11/29/1999. [118717] 
LB990801233129.015. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow Models and 
Submodels" (Flow Field #15). Submittal date: 11/29/1999. [118730] 
MO0003SZFWTEEP.000. Data Resulting from the Saturated Zone Flow and Transport Expert 
Elicitation Project. Submittal date: 03/06/2000. [148744] 
MO0010CPORGLOG.002. Calculated Porosity from Geophysical Logs Data from "Old 40" 
Boreholes. Submittal date: 10/16/2000. [155229] 
MO0105GPLOG19D.000. Geophysical Log Data from Borehole NC EWDP 19D. Submittal 
date: 05/31/2001. [163480] 
MO0105HCONEPOR.000. Hydraulic Conductivity and Effective Porosity for the Basin and 
Range Province, Southwestern United States. Submittal date: 05/02/2001. [155044] 
MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. Submittal date: 09/17/2001. 
[155989] 
SN0004T0501399.002. Correlation of RH (Relative Humidity) Porosity and Bulk Density. 
Submittal date: 04/13/2000. [155046]

MDL-NBS-HS-000021, REV 00 165 July, 2003 
SN0004T0501399.003. Statistical Summary of Porosity Data. Submittal date: 04/13/2000. 
[155045] 
SN0302T0502203.001. Saturated Zone Anisotropy Distribution Near the C-Wells. Submittal 
date: 02/26/2003. [163563] 
SN0306T0504103.005. Revised Groundwater Colloid Mass Concentration Parameters for TSPA 
(Total System Performance Assessment). Submittal date: 06/30/2003. [164132] 
SN0306T0504103.006. Revised Sorption Partition Coefficients (KD Values) for Selected 
Radionuclides Modeled in the TSPA (Total System Performance Assessment). Submittal date: 
06/30/2003. [164131] 
SN9907T0571599.001. Probability Distribution of Flowing Interval Spacing. Submittal date: 
07/15/1999. [122261] 
9.5 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
SN0306T0502103.005. SATURATED ZONE (SZ) 1-D TRANSPORT MODEL. Submittal 
date: 06/05/2003. 
SN0306T0502103.006. DATA SPREADSHEETS TO SUPPORT PARAMETER 
UNCERTAINTY DEVELOPMENT. Submittal date: 06/05/2003. 
SN0306T0502103.007. UPDATED SATURATED ZONE TRANSPORT ABSTRACTION 
MODEL UNCERTAIN INPUTS. Submittal date: 06/12/2003. 
SN0306T0502103.008. UPDATED SATURATED ZONE TRANSPORT ABSTRACTION 
MODEL INPUTS AND RESULTS. Submittal date: 06/12/2003.

MDL-NBS-HS-000021, REV 00 166 July, 2003 
10. ATTACHMENTS 
ATTACHMENT I  Stochastic Parameter Values

MDL-NBS-HS-000021, REV 00 I-1 July, 2003 
ATTACHMENT I 
Table I-1. Stochastic Parameter Values 
DTN: SN0306T0502103.007 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
1 0.70451 0.028309 0.15851 0.11373 1.3862 -3.7026 -10.092 1.5616 6.3364 268.07 259.27 
2 0.61702 0.70184 0.11408 0.081329 0.84234 -3.0161 -10.116 1.1722 4.8505 258.99 113.51 
3 0.35217 0.61633 0.083152 0.20585 1.0234 -3.3666 -10.146 1.0715 4.2112 113.11 290.67 
4 0.43734 0.35304 0.20587 0.19441 0.83422 -3.8921 -10.539 1.2255 7.6552 290.9 159.82 
5 0.3726 0.4368 0.19441 0.16058 0.92304 -4.461 -10.042 1.3846 6.1118 160.14 199.68 
6 0.38137 0.37493 0.16033 0.17169 1.4084 -2.3306 -10.426 1.1451 6.4302 200.28 240.98 
7 0.96095 0.38323 0.17133 0.16309 0.81193 -2.6095 -10.325 1.4043 5.7365 240.86 85.61 
8 0.96721 0.96199 0.1631 0.16459 1.1285 -3.3333 -10.197 1.2161 7.73 86.233 122.88 
9 0.063508 0.96547 0.16442 0.26596 1.3996 -3.1397 -10.612 1.098 4.6382 122.69 82.931 
10 0.39763 0.063782 0.26525 0.26907 1.2126 -3.2812 -10.518 1.176 7.7179 83.165 99.983 
11 0.12641 0.39708 0.26845 0.1011 0.63908 -3.2658 -10.619 1.1747 6.2902 100.11 249.1 
12 0.83363 0.12855 0.10207 0.16643 1.5206 -1.199 -10.572 1.5992 7.5701 248.31 79.438 
13 0.82638 0.83084 0.16658 0.12153 1.3272 -1.15 -10.174 1.2055 6.451 79.842 156.96 
14 0.46725 0.82571 0.12117 0.22766 0.62506 -3.976 -10.626 1.1643 4.9316 156.83 245.64 
15 0.11482 0.46679 0.2272 0.22709 1.6764 -3.2319 -10.431 1.3064 6.8839 244.94 185.29 
16 0.24233 0.11166 0.22688 0.17505 1.0682 -3.8285 -10.185 1.4173 7.3231 183.88 46.974 
17 0.8055 0.24472 0.17513 0.11746 1.2021 -1.8383 -10.366 1.4534 7.8869 47.598 285.48 
18 0.1329 0.80984 0.11813 0.14376 1.0712 -1.8602 -10.758 1.2152 5.1106 284.54 222.27 
19 0.73058 0.13299 0.14387 0.22266 1.4018 -3.0689 -10.059 1.5123 5.8951 223.16 46.513 
20 0.34072 0.73141 0.22261 0.12312 1.3451 -3.856 -10.26 1.5542 8.6697 45.328 329.38 
21 0.048591 0.34315 0.12247 0.21023 1.0043 -3.5674 -10.801 1.405 7.4175 327.85 136.96 
22 0.74837 0.048613 0.21035 0.15875 1.4574 -1.9719 -9.921 1.4846 7.7301 137.24 181.17 
23 0.93881 0.74785 0.15923 0.093691 1.2402 -3.8166 -10.485 1.4062 6.4626 180.92 138.35 
24 0.55458 0.93563 0.09379 0.21283 1.1247 -2.2296 -10.372 1.0732 1.9633 139.62 247.14 
25 0.79283 0.55378 0.21273 0.25453 1.668 -3.3458 -10.476 1.5309 6.3834 246.15 228.25 
26 0.37734 0.79098 0.25543 0.18598 1.816 -4.0395 -10.185 5.9009 7.6101 227.35 115.13

MDL-NBS-HS-000021, REV 00 I-2 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
27 0.67108 0.37594 0.18625 0.2203 0.94555 -2.1743 -10.24 1.4036 7.8466 116.36 264.39 
28 0.65266 0.67222 0.22046 0.16351 1.6175 -1.3137 -10.538 0.84532 6.7485 264.74 194.12 
29 0.62918 0.65188 0.1638 0.20193 1.5918 -2.8203 -10.13 1.4983 10.779 194.18 155.64 
30 0.24883 0.62618 0.20225 0.199 1.3545 -2.032 -10.341 1.1036 2.4415 156.36 325.19 
31 0.71164 0.2459 0.19922 0.19577 0.76344 -3.2677 -10.437 1.2579 6.4552 325.42 362 
32 0.36584 0.7122 0.1961 0.14524 2.4058 -2.4327 -9.9314 1.3744 6.5489 361.97 105.28 
33 0.47113 0.36787 0.14464 0.20748 1.2638 -2.4921 -9.6565 1.3692 6.2446 103.82 313.97 
34 0.58157 0.47388 0.20749 0.16199 1.8275 -2.5698 -10.565 1.03 5.3839 313.5 308.63 
35 0.17154 0.58391 0.16242 0.17587 1.381 -3.5586 -9.9702 1.0949 4.5499 307.59 232.62 
36 0.27276 0.17077 0.17593 0.19016 1.7866 -2.2884 -9.9878 1.1672 6.5466 230.98 72.64 
37 0.16841 0.2727 0.18985 0.13151 1.3153 -3.2946 -10.231 1.3467 5.7734 71.65 395.34 
38 0.21269 0.16757 0.13141 0.14914 1.5424 -3.0598 -10.645 1.0592 4.3751 395.81 200.88 
39 0.60151 0.21358 0.14881 0.13017 1.6877 -2.7243 -9.3455 1.1259 4.6523 201.21 362.94 
40 0.15729 0.60256 0.13036 0.13857 1.4451 -3.7297 -10.322 1.2168 5.863 363.36 239.29 
41 0.3647 0.15605 0.13923 0.19281 1.2456 -3.5069 -9.6366 1.2943 7.3494 238.67 353.32 
42 0.59284 0.36398 0.19225 0.12862 1.5022 -3.7412 -10.208 1.0945 6.6715 353.63 219.29 
43 0.43429 0.59413 0.1289 0.16172 1.0933 -3.6399 -9.7391 1.5736 4.4304 218.86 293.52 
44 0.074964 0.43453 0.1616 0.1909 1.3933 -2.6663 -10.274 1.189 6.7603 293.54 329.87 
45 0.69768 0.072714 0.19154 0.17113 1.7338 -3.7591 -10.037 1.0416 4.24 329.95 260.63 
46 0.53002 0.69555 0.17083 0.10469 0.60159 -3.3102 -9.9122 5.9456 12.998 260.58 195.92 
47 0.066897 0.53497 0.10634 0.20539 1.5563 -2.6836 -10.14 1.2551 6.3144 195.81 278.81 
48 0.81253 0.067039 0.20548 0.18333 1.629 -3.1487 -10.338 1.5648 8.2368 279.26 147.09 
49 0.307 0.81175 0.18364 0.10332 1.1917 -3.954 -10.079 1.1086 5.1387 146.39 242.3 
50 0.42421 0.30885 0.10441 0.2239 1.6554 -2.3446 -10.461 5.8907 12.116 242.61 342.55 
51 0.31471 0.42162 0.22428 0.15377 1.015 -2.8939 -10.193 1.5497 7.6537 342.37 42.645 
52 0.59783 0.31468 0.15362 0.16942 1.0887 -3.9623 -9.8347 1.2477 6.3723 41.049 296.42 
53 0.54881 0.59673 0.16958 0.15458 0.92816 -1.937 -10.881 1.5972 5.3289 296.98 317.67 
54 0.25186 0.54916 0.15499 0.19171 1.3722 -3.4313 -10.022 2.8263 10.605 316.68 177.7 
55 0.64107 0.25325 0.19159 0.18521 0.58809 -3.1758 -9.9578 1.3281 6.9642 177.84 322.55 
56 0.45988 0.64197 0.18541 0.14594 0.70644 -3.4213 -10.38 1.2863 5.5995 322.77 120.09 
57 0.35868 0.45653 0.14567 0.19779 1.1816 -2.6824 -9.9416 1.593 8.3781 119.49 144.75 
58 0.80213 0.35725 0.19771 0.17377 1.8448 -2.8405 -10.526 1.3237 8.2585 144.07 102.59

MDL-NBS-HS-000021, REV 00 I-3 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
59 0.89925 0.80492 0.17397 0.16094 1.8056 -3.5446 -10.465 1.5431 8.3775 102.46 238.09 
60 0.22248 0.89986 0.16077 0.22181 0.8828 -2.5185 -10.569 1.818 7.6319 238.24 40.481 
61 0.77121 0.22433 0.22181 0.24279 1.776 -3.0919 -10.209 4.5641 8.5555 39.125 60.504 
62 0.75746 0.77304 0.24181 0.14055 1.4833 -3.3141 -10.914 1.2771 5.6484 61.745 174.98 
63 0.55579 0.75953 0.14106 0.21688 0.29449 -1.9893 -10.676 1.4246 6.0788 175.27 368.07 
64 0.13508 0.5581 0.2173 0.2146 0.97023 -1.5186 -10.388 1.4437 7.9421 368.85 358.4 
65 0.9875 0.13511 0.21415 0.18662 0.67711 -3.6141 -9.5831 1.3231 7.3588 358.6 93.383 
66 0.47965 0.98618 0.18644 0.12437 1.0221 -2.0912 -9.6872 1.4713 6.3947 93.089 351.55 
67 0.90123 0.47822 0.12407 0.28381 1.3397 -2.146 -10.594 1.2995 4.8544 350.82 273.61 
68 0.57866 0.90303 0.28224 0.17637 1.1865 -2.81 -9.7422 1.3853 7.097 272.91 29.222 
69 0.87669 0.57844 0.17686 0.24362 1.3222 -3.8028 -10.099 1.554 8.2015 29.194 109.73 
70 0.52246 0.87687 0.24338 0.18948 1.4151 -1.0566 -11.127 1.4993 7.9085 110.4 55.672 
71 0.71788 0.52221 0.18946 0.23674 1.8942 -3.0485 -10.55 1.3887 7.2882 54.464 122.53 
72 0.81847 0.71882 0.23781 0.182 1.7624 -1.4862 -10.686 1.0413 4.0931 122.07 225.24 
73 0.63474 0.81922 0.18229 0.20867 0.738 -2.7404 -10.522 1.2817 5.8392 225.84 177.4 
74 0.46117 0.63266 0.20818 0.22519 1.7318 -1.6079 -10.25 1.089 5.563 177.5 220.21 
75 0.68208 0.46283 0.22459 0.19667 1.533 -2.9264 -10.382 1.3449 4.6409 220.36 251.38 
76 0.33346 0.68422 0.19617 0.1746 1.7237 -2.2736 -10.267 3.7206 5.4484 250.42 379.89 
77 0.58661 0.33143 0.17454 0.2033 2.5288 -1.9123 -10.169 1.0843 5.8758 379.91 348.05 
78 0.84781 0.58957 0.20353 0.15752 0.18779 -2.5558 -9.4799 3.5283 8.1698 347.72 65.785 
79 0.055061 0.84838 0.15727 0.1908 1.4319 -3.0857 -9.7859 1.5113 8.3184 65.77 340.28 
80 0.72545 0.059548 0.19074 0.23065 0.65772 -2.3987 -10.66 1.041 6.9709 340.32 288.61 
81 0.78233 0.72652 0.23023 0.09896 1.0081 -3.3729 -9.8592 4.6835 7.3093 288.29 337.65 
82 0.41537 0.78383 0.10033 0.21009 1.5687 -2.7055 -10.051 1.2534 4.2383 338.42 396.46 
83 0.79615 0.4153 0.21009 0.21848 0.1867 -1.7701 -9.868 1.09 4.5096 396.97 24.361 
84 0.26279 0.79769 0.21877 0.169 1.8692 -3.9839 -9.3285 1.2688 6.2532 24.087 256.82 
85 0.32585 0.26149 0.16913 0.22126 1.0848 -2.2475 -11.197 3.1158 8.0548 257.05 51.292 
86 0.21935 0.32771 0.22133 0.14731 0.43697 -2.0638 -10.149 1.2095 6.8038 50.403 118.69 
87 0.57287 0.21868 0.14692 0.15714 1.0417 -3.1822 -10.698 1.0986 5.642 117.57 303.07 
88 0.05408 0.5743 0.15668 0.14015 0.69929 -2.0111 -10.532 1.3984 6.9799 302.88 23.539 
89 0.10576 0.054487 0.13962 0.18832 1.2717 -3.5333 -10.005 1.4976 5.067 22.372 375.01 
90 0.40754 0.10529 0.18845 0.096424 1.6977 -3.3872 -11.258 2.503 8.1054 374.3 142.05

MDL-NBS-HS-000021, REV 00 I-4 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
91 0.91603 0.40782 0.098203 0.11647 0.90599 -3.6232 -9.5364 1.2184 7.3349 143.11 32.802 
92 0.89135 0.91567 0.11686 0.16758 1.7454 -2.7577 -10.47 1.5155 6.3243 33.088 128.36 
93 0.19019 0.89023 0.16751 0.24842 0.46766 -3.9928 -11.072 1.4338 5.532 129.99 59.201 
94 0.87315 0.19372 0.24868 0.24104 1.2729 -3.8725 -10.503 1.3253 8.2211 58.595 204.12 
95 0.66517 0.87134 0.24128 0.13522 1.7668 -3.2063 -10.678 1.2312 6.3196 203.25 333.28 
96 0.024123 0.66764 0.13509 0.2357 0.79926 -1.415 -10.318 1.2901 5.1403 333.2 96.423 
97 0.23899 0.022985 0.23591 0.20122 0.78641 -1.5294 -9.9071 1.4917 10.47 96.617 343.73 
98 0.093079 0.23563 0.20126 0.079449 0.50753 -3.6823 -10.585 1.3754 6.2799 344.24 33.838 
99 0.26953 0.090888 0.078007 0.14284 1.6105 -1.6374 -9.8223 1.7885 12.343 33.832 205.03 
100 0.54079 0.26698 0.14297 0.1121 0.7266 -2.4384 -11.023 1.2352 4.8847 205.87 348.78 
101 0.41165 0.54048 0.11173 0.14771 1.2905 -4.5523 -10.31 1.0886 5.4429 349.62 77.497 
102 0.52854 0.41152 0.14803 0.18493 1.053 -3.5782 -9.7593 5.288 7.4087 77.534 76.842 
103 0.60808 0.52661 0.18474 0.16809 1.8672 -3.9083 -10.633 1.4495 5.0404 76.359 36.081 
104 0.94548 0.60856 0.1683 0.18302 1.8887 -3.5167 -10.633 1.0081 4.9632 36.121 311.98 
105 0.86326 0.94988 0.18294 0.19313 1.9802 -2.8632 -10.973 1.2061 5.8423 312.49 63.968 
106 0.12173 0.86184 0.19307 0.25889 2.2252 -3.196 -9.9776 1.3673 8.3694 64.993 210.78 
107 0.84161 0.12403 0.259 0.23369 0.81543 -2.9144 -10.666 1.0087 4.0211 210.19 132.5 
108 0.70681 0.84374 0.23391 0.12085 1.0518 -2.6365 -10.296 1.4823 8.0432 133.56 371.99 
109 0.83677 0.70737 0.12071 0.22943 1.0756 -1.2562 -10.492 1.2957 7.1784 372.31 378.64 
110 0.99128 0.83905 0.22953 0.20708 1.0619 -1.6871 -9.5526 1.5849 6.2277 377.8 384.4 
111 0.010519 0.99171 0.20724 0.2288 1.1152 -3.8399 -9.5112 1.3726 8.0958 383.78 389.32 
112 0.62269 0.011542 0.22836 0.28924 1.5627 -1.7758 -9.4549 0.47367 2.0554 388.62 81.669 
113 0.084204 0.62223 0.29036 0.067107 1.1593 -2.3046 -9.3949 1.2838 5.0674 81.049 131.2 
114 0.25597 0.083179 0.063538 0.19537 1.7925 -1.8199 -10.623 1.0259 4.8538 131.47 141.54 
115 0.74132 0.25944 0.19539 0.10837 1.8399 -1.0372 -10.499 1.3325 4.3711 140.73 134.5 
116 0.007434 0.74115 0.10822 0.14618 1.3104 -4.793 -10.473 1.326 4.6318 135.74 152.57 
117 0.93236 0.008269 0.14655 0.21192 1.0318 -2.5914 -10.486 1.192 4.8102 151.56 300.09 
118 0.32035 0.93043 0.21235 0.049913 0.25923 -3.925 -10.447 1.5052 8.4928 299.64 166.3 
119 0.030233 0.32271 0.054478 0.25292 1.8314 -3.5417 -10.015 1.2865 6.5942 167.99 355.78 
120 0.28508 0.034057 0.25215 0.15635 1.6384 -2.197 -10.408 1.0441 4.3142 355.96 366.8 
121 0.10144 0.28681 0.15579 0.084439 1.4232 -4.8885 -9.7061 4.0179 8.6042 365.99 216.81 
122 0.48434 0.10353 0.087276 0.15092 1.2272 -1.3375 -9.6162 1.5659 10.632 216.07 125.11

MDL-NBS-HS-000021, REV 00 I-5 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
123 0.82334 0.4826 0.15078 0.11532 1.2217 -3.394 -10.28 1.144 6.8495 126.33 25.85 
124 0.20394 0.82124 0.1155 0.17726 1.8577 -4.3628 -10.513 0.56195 5.2954 25.77 364.38 
125 0.8532 0.20325 0.1773 0.2256 0.64581 -3.4685 -11.163 0.61438 5.5611 364.43 319.08 
126 0.037624 0.85435 0.22552 0.13752 2.2805 -3.8812 -9.6208 1.4824 8.6597 318.59 252.72 
127 0.48593 0.038573 0.1374 0.23209 1.8027 -3.0395 -9.9522 1.1054 4.852 253.06 189.7 
128 0.86876 0.48711 0.2322 0.090398 1.4724 -1.8783 -10.167 1.426 7.4125 189.11 188.25 
129 0.1544 0.86639 0.087853 0.17752 0.8727 -3.6625 -10.349 1.1896 6.6315 189 371.09 
130 0.14816 0.15141 0.17766 0.23528 1.4626 -1.7361 -10.354 1.5565 6.1952 371.34 48.507 
131 0.043598 0.14898 0.2347 0.12704 0.8525 -4.2851 -9.5649 0.57803 6.1647 49.552 391 
132 0.76846 0.043645 0.12788 0.12639 1.9175 -3.0322 -10.707 1.3923 8.5753 392.36 358.05 
133 0.11602 0.76916 0.12658 0.091042 0.77682 -1.663 -9.3758 1.4028 6.1291 357.09 270.33 
134 0.50019 0.11576 0.091188 0.21608 1.5858 -3.7717 -9.697 1.3106 5.1128 268.94 91.21 
135 0.29848 0.50385 0.21619 0.11938 0.66707 -3.782 -10.108 1.5452 7.8604 91.012 266.13 
136 0.92706 0.29908 0.11876 0.1795 0.9665 -4.1659 -10.598 1.2378 6.3067 266.24 87.774 
137 0.94102 0.92914 0.17972 0.15236 1.6015 -2.1023 -10.123 1.2967 4.568 87.49 381.85 
138 0.95563 0.94338 0.1525 0.25203 1.0371 -3.8468 -10.607 1.2594 6.9416 382.11 73.304 
139 0.97152 0.95988 0.25117 0.25751 1.4984 -2.9884 -9.4764 1.3533 7.5599 75.05 305.76 
140 0.16243 0.97467 0.25758 0.26263 1.3352 -3.4489 -10.64 1.318 6.1782 306.58 52.742 
141 0.29141 0.16433 0.26227 0.27269 1.3693 -1.3574 -9.9925 1.009 4.2885 52.555 108.71 
142 0.31613 0.29468 0.27054 0.12983 0.90791 -1.2856 -10.691 1.2243 5.0186 107.51 310.21 
143 0.30444 0.31977 0.12929 0.1517 1.1741 -1.2235 -10.553 1.2052 6.5328 309.31 127.74 
144 0.34719 0.30198 0.15141 0.15513 2.5485 -1.1431 -9.9839 1.4527 4.665 126.78 278.2 
145 0.73918 0.34993 0.15548 0.15306 1.2035 -3.7544 -10.508 1.386 6.9865 278.09 224.01 
146 0.38633 0.73982 0.15327 0.15945 0.94859 -3.4626 -10.086 1.5271 6.2592 223.97 234.71 
147 0.88281 0.38841 0.15936 0.21123 1.7483 -3.4067 -10.258 1.2929 7.0045 235.6 98.655 
148 0.91034 0.88286 0.21103 0.16498 1.5123 -3.4429 -10.217 1.0004 2.7287 98.884 173.85 
149 0.51841 0.91188 0.16505 0.2382 0.12866 -3.3353 -10.578 0.97924 3.0842 172.58 398.45 
150 0.27749 0.51972 0.23803 0.24697 1.4763 -2.2129 -10.391 1.5883 7.36 399.04 182.7 
151 0.018691 0.27629 0.2464 0.18134 1.6242 -3.245 -9.3007 1.4981 6.8565 182.75 106.24 
152 0.90977 0.017058 0.18162 0.14925 0.88989 -1.5786 -10.367 1.4556 7.3442 106.39 346.76 
153 0.78691 0.90918 0.14972 0.071036 1.1644 -1.444 -10.56 1.5135 8.5463 345.34 282.36 
154 0.61273 0.78833 0.073847 0.24478 1.5462 -2.9437 -9.806 1.3871 4.5883 283.74 20.174

MDL-NBS-HS-000021, REV 00 I-6 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
155 0.44835 0.61154 0.24491 0.21959 1.509 -3.4983 -10.066 1.4672 6.1311 20.054 272.36 
156 0.44417 0.44562 0.21926 0.19385 2.3672 -4.6266 -11.292 1.42 7.6511 270.96 316.33 
157 0.92465 0.44049 0.19402 0.17247 1.2376 -1.4517 -10.102 1.4229 7.0916 315.47 94.793 
158 0.076609 0.92395 0.17275 0.17226 1.297 -2.0342 -9.9661 1.0329 4.1036 95.841 169.24 
159 0.97647 0.077995 0.17184 0.25011 1.2888 -2.622 -10.589 1.5898 6.7876 169.73 294.38 
160 0.88672 0.97946 0.24939 0.10731 1.3071 -3.1179 -10.4 1.3553 6.203 294.14 280.49 
161 0.65647 0.88508 0.10708 0.27559 1.3647 -3.1224 -10.027 1.3538 7.3059 281.47 392.49 
162 0.18665 0.65755 0.2747 0.2403 1.4503 -1.3913 -10.072 1.2711 4.7212 392.92 192.19 
163 0.64606 0.18543 0.23956 0.19953 0.86176 -3.9385 -9.369 5.6619 11.544 192.4 212.7 
164 0.17568 0.6463 0.19972 0.13401 1.2833 -1.1169 -10.347 1.0227 5.7699 212.65 209.44 
165 0.95061 0.17555 0.13472 0.19829 1.1026 -1.5522 -10.29 3.1197 12.928 209.18 215.42 
166 0.14335 0.95267 0.19855 0.13239 0.68419 -2.4821 -10.302 1.1126 4.9715 215.41 233.45 
167 0.75389 0.14211 0.13248 0.26065 0.35455 -3.6937 -10.285 1.3633 6.0234 233.3 262.83 
168 0.088815 0.75375 0.26063 0.12567 1.5235 -2.5044 -10.222 1.5655 7.7213 262.21 88.429 
169 0.23232 0.08869 0.12491 0.21379 1.4276 -3.7156 -10.133 1.1445 5.8916 89.341 207.49 
170 0.76434 0.23274 0.21353 0.11061 1.1196 -1.2367 -10.602 1.0316 6.3693 207.28 148.16 
171 0.28202 0.7616 0.11071 0.14232 1.2168 -3.7935 -10.308 1.2806 7.5455 147.76 56.742 
172 0.67838 0.28377 0.1421 0.21493 1.1411 -2.1576 -10.453 1.0248 4.8431 56.111 30.192 
173 0.53511 0.67815 0.2155 0.15048 1.1566 -3.9196 -10.686 1.2576 7.8087 30.992 286.7 
174 0.56885 0.53997 0.15046 0.20288 2.0937 -3.5938 -11.111 5.5411 10.593 286.98 254.82 
175 0.20533 0.5681 0.20264 0.18426 2.1634 -2.1331 -10.054 5.042 12.993 254.19 153.59 
176 0.40471 0.20916 0.18434 0.18769 0.61684 -3.4847 -10.156 1.0129 2.0458 153.92 185.52 
177 0.9995 0.40055 0.18774 0.13838 1.1696 -2.4075 -10.442 1.3699 6.559 186.74 162.09 
178 0.42544 0.99674 0.13813 0.1669 0.74682 -2.8729 -10.359 1.55 6.093 160.92 166.26 
179 0.22637 0.42607 0.16701 0.29202 1.7114 -2.7766 -10.421 1.5916 8.4675 165.99 386.06 
180 0.85993 0.22959 0.29861 0.17001 1.7077 -3.649 -10.414 0.38221 4.25 385.73 387.44 
181 0.69081 0.85616 0.17039 0.14118 1.2552 -3.218 -9.4402 1.3926 6.3219 388.13 42.922 
182 0.000316 0.69391 0.14143 0.23223 0.71843 -1.0082 -9.4219 1.4937 7.6176 44.051 170.83 
183 0.66425 0.000898 0.23224 0.20456 0.98249 -3.165 -10.84 0.8293 1.8184 170.21 68.282 
184 0.77963 0.6644 0.20481 0.02251 1.6687 -3.6051 -10.4 1.1766 4.7156 67.757 336.51 
185 0.19856 0.77701 0.026558 0.20066 0.75819 -1.714 -10.656 1.3618 5.9137 336.43 333.76 
186 0.39325 0.19937 0.2007 0.21764 1.5619 -2.3599 -9.8929 1.2442 6.6568 334.86 197.72

MDL-NBS-HS-000021, REV 00 I-7 July, 2003 
real. # FPLAW FPLAN NVF19 NVF7 FISVO FPVO DCVO KDNPVO KDNPAL KDSRVO KDSRAL 
187 0.72376 0.39066 0.21781 0.13599 1.1067 -4.9164 -9.9021 4.357 10.666 197.9 62.435 
188 0.68892 0.7222 0.13594 0.16567 0.55484 -2.4516 -10.331 1.0521 4.4061 61.878 112.56 
189 0.98274 0.6877 0.1656 0.2091 1.5759 -2.0718 -10.67 3.9188 8.2587 112.62 326.39 
190 0.45275 0.98273 0.20896 0.20396 1.8807 -3.6752 -10.546 1.5064 8.1244 326.54 71.187 
191 0.50526 0.45272 0.20412 0.28052 1.3502 -3.2414 -9.9247 1.237 7.4539 70.071 298.21 
192 0.49598 0.50781 0.27675 0.17357 1.6501 -2.2593 -10.652 1.3048 6.163 298.79 151.05 
193 0.51183 0.49782 0.17314 0.18015 1.1476 -2.3726 -10.017 1.3812 4.1231 150.2 38.786 
194 0.56134 0.51179 0.18047 0.17902 1.4929 -1.0761 -10.45 0.037042 6.0078 38.545 304.18 
195 0.63937 0.56322 0.17911 0.18073 1.469 -3.1087 -10.948 1.3798 5.8151 303.54 376.34 
196 0.18288 0.63794 0.18074 0.18708 1.4386 -2.9756 -9.9997 1.063 4.5618 376.21 230.27 
197 0.49279 0.18439 0.18748 0.19706 0.99788 -3.0038 -9.5125 1.1799 5.6844 229.91 321.71 
198 0.33957 0.49261 0.19742 0.13392 1.5377 -2.9649 -10.239 1.1972 7.7128 321.32 162.65 
199 0.097933 0.33587 0.13394 0.17855 1.1373 -2.7936 -9.9428 1.1266 5.5324 163.61 275.46 
200 0.02951 0.098121 0.17837 0.15841 1.2559 -2.5445 -10.415 0.38035 1.9883 274.65 268.56

MDL-NBS-HS-000021, REV 00 I-8 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
1 5.9431 4.0476 0.8181 1791.7 1.0875 1.0042 0.39801 0.12912 0.82832 0.11435 0.46636 
2 5.4182 4.3547 -0.85495 1889.7 3.5582 1.6714 0.12714 0.83286 0.46792 0.2438 0.11184 
3 5.7796 4.121 -0.1215 1820.9 3.5695 1.1986 0.83439 0.82826 0.11009 0.80568 0.24456 
4 5.7825 4.1487 -0.44224 1984.5 0.90319 1.3675 0.82819 0.4672 0.24114 0.13093 0.80542 
5 6.5266 6.9729 0.39432 1983.7 1.1434 1.5138 0.46584 0.11053 0.80879 0.73468 0.13052 
6 6.5841 7.1394 0.3885 1904.1 0.90338 0.83369 0.11165 0.24447 0.13119 0.34017 0.73259 
7 6.1287 2.9464 -0.03684 1815.2 2.9725 1.0459 0.24061 0.80742 0.73112 0.046301 0.34463 
8 6.2574 4.2057 -0.46085 1855.7 2.9604 0.81838 0.80897 0.13118 0.34463 0.7483 0.04631 
9 5.4494 3.1882 -0.30786 1978.3 1.4071 0.91882 0.13468 0.73388 0.04603 0.93663 0.74671 
10 5.7923 5.8512 0.36448 1823.5 0.90334 1.5367 0.73421 0.34146 0.74618 0.55383 0.93928 
11 6.8214 5.8404 -0.43612 1957.8 0.90373 0.79926 0.34235 0.045831 0.93877 0.79495 0.55274 
12 6.4371 4.4718 0.27522 1878.4 2.8768 1.1894 0.049235 0.74967 0.55011 0.37712 0.79438 
13 5.5876 3.13 -0.19072 1777.8 0.9034 1.5267 0.74852 0.93563 0.79164 0.67425 0.37882 
14 5.9414 3.6295 -0.97733 1961.7 2.5538 1.3075 0.93625 0.55419 0.37553 0.65406 0.67351 
15 6.8651 5.7631 0.29233 2028.3 0.94105 0.77849 0.55335 0.79368 0.67241 0.62614 0.65251 
16 5.4152 3.2064 0.66404 1920 0.90314 1.6522 0.79004 0.37616 0.65068 0.24578 0.62768 
17 6.3998 5.4719 0.059967 1973.9 2.6065 1.4544 0.37912 0.67379 0.62866 0.7112 0.24627 
18 5.8912 3.9963 0.3514 1885.7 3.4344 0.77844 0.67485 0.65038 0.24892 0.3687 0.71087 
19 5.8133 2.8633 -0.14488 1944.9 1.7505 1.8446 0.65415 0.62701 0.711 0.47078 0.36665 
20 5.9168 5.5418 0.20717 1940.3 2.8112 1.0993 0.62895 0.24539 0.36569 0.58084 0.47477 
21 6.4056 6.249 0.18479 1935.4 1.0695 1.288 0.24752 0.71071 0.47397 0.17007 0.5826 
22 6.0838 4.799 0.15118 1856.8 2.2828 1.1135 0.71398 0.36774 0.58472 0.27474 0.1718 
23 6.3714 5.711 -0.30353 1953.7 2.2025 1.5333 0.36813 0.47456 0.17021 0.1663 0.27316 
24 5.9413 4.1293 0.25181 1883.7 2.0793 1.4721 0.47446 0.58489 0.27248 0.21154 0.16614 
25 6.2597 5.251 -0.15875 1904.5 0.90375 1.0179 0.58135 0.17051 0.16512 0.60233 0.21337 
26 13.877 5.1801 -0.03341 1925.9 2.4697 1.5852 0.17104 0.27259 0.21288 0.15556 0.60328 
27 5.5811 5.0737 0.099475 1836.3 1.04 1.3493 0.27161 0.1696 0.60274 0.36263 0.15521 
28 5.4277 3.6421 -0.38882 1862.7 1.4328 1.1809 0.16813 0.2111 0.15655 0.59017 0.36338 
29 6.4587 5.3989 -0.27169 1834.9 1.8884 1.7837 0.21312 0.60029 0.36028 0.43416 0.59491 
30 6.0631 4.1024 -0.39819 1847.3 0.90353 2.3132 0.60039 0.15621 0.59053 0.070562 0.43237

MDL-NBS-HS-000021, REV 00 I-9 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
31 5.9779 4.4969 -0.34483 1930.7 0.90382 0.94597 0.15578 0.36256 0.43289 0.69568 0.072704 
32 6.1335 4.9141 0.11944 1831.2 0.90351 1.7452 0.36078 0.59297 0.074871 0.53396 0.69861 
33 6.0066 3.3664 -0.41112 1882.9 0.90364 1.7258 0.59401 0.43237 0.69566 0.066305 0.53255 
34 5.914 3.7497 -0.16609 1928.7 1.9686 1.4833 0.43426 0.073074 0.53246 0.81035 0.069985 
35 5.7302 3.344 0.10967 1896.5 0.90348 0.77891 0.073323 0.6975 0.067696 0.30531 0.81321 
36 5.7065 3.508 -0.07847 1796.8 1.0186 2.8271 0.6963 0.53488 0.81113 0.42313 0.30702 
37 6.6832 4.9963 -0.76296 1950.8 1.9415 1.3809 0.53406 0.06581 0.30994 0.3125 0.42397 
38 5.417 3.3073 0.23755 1916.7 1.2853 2.3632 0.065321 0.81078 0.4221 0.59713 0.31337 
39 6.585 4.0865 0.037959 1792.3 0.90322 1.5062 0.81429 0.30812 0.31475 0.54755 0.59695 
40 6.1896 4.9427 -0.81314 1978.7 2.3987 2.2149 0.30883 0.42455 0.59518 0.25434 0.54791 
41 5.9651 4.348 0.37313 1870.6 1.6641 1.4434 0.42078 0.31241 0.54998 0.64335 0.25415 
42 5.713 2.9858 -0.23107 1894.9 0.9032 1.6805 0.31042 0.59809 0.25497 0.45955 0.64074 
43 6.6462 5.3518 -0.08994 1872.4 2.8904 1.8892 0.59966 0.549 0.64079 0.35531 0.45927 
44 6.0208 4.7282 -0.2259 1929.2 0.90393 1.5782 0.54701 0.25493 0.45549 0.80303 0.35881 
45 3.906 2.9717 0.11488 1919 1.2471 1.3553 0.25287 0.64012 0.35869 0.89767 0.8011 
46 6.6834 5.7864 0.054703 1857.7 0.90394 1.634 0.64341 0.45504 0.80265 0.22022 0.89575 
47 6.2498 3.8645 -0.29576 1938.4 1.9461 1.1435 0.45681 0.35554 0.89736 0.77279 0.22201 
48 5.894 4.2993 0.16765 1902 1.729 1.5204 0.35767 0.8033 0.22106 0.75653 0.7745 
49 6.3263 3.8948 -0.05232 1881.8 0.90376 2.0395 0.80219 0.8976 0.77391 0.55844 0.75595 
50 6.4312 4.9688 -0.17085 1976.9 2.1536 0.77839 0.89527 0.22021 0.75624 0.13669 0.55693 
51 6.2701 4.7739 0.35802 2009.1 1.3766 1.6906 0.22262 0.77394 0.55501 0.98761 0.13778 
52 5.7903 3.6678 0.4722 1850.2 1.0029 1.7566 0.77311 0.75559 0.136 0.47673 0.98982 
53 5.4627 5.1336 -0.32842 1968.2 2.8598 1.2814 0.75897 0.55733 0.98911 0.90165 0.47795 
54 6.8287 4.4488 0.3249 1965 3.2589 1.7758 0.55928 0.13643 0.47798 0.57992 0.9017 
55 6.3603 4.0579 0.30516 1921.4 0.90367 1.0305 0.13924 0.9852 0.90361 0.87597 0.57623 
56 6.6608 5.7363 0.069194 1824.4 2.7248 1.1388 0.98859 0.47716 0.57516 0.52119 0.8799 
57 16.607 6.1005 -0.43183 2082 2.6468 0.93337 0.47781 0.9021 0.87838 0.71927 0.52202 
58 5.9294 3.5446 0.92526 1905.5 1.7898 1.5033 0.90019 0.57664 0.52429 0.81645 0.71732 
59 6.8208 5.6306 -0.02427 2011 0.90342 0.77833 0.57734 0.87993 0.7155 0.63189 0.8157 
60 6.5861 5.5676 0.47755 1925.5 3.6555 0.77871 0.87726 0.52225 0.81696 0.46085 0.63455 
61 6.7075 4.8121 0.093825 2000.3 1.4533 1.2651 0.52405 0.71818 0.63403 0.6836 0.4645 
62 6.1671 3.2399 0.44786 1914.8 3.2957 2.4448 0.71743 0.81913 0.46208 0.33488 0.68352

MDL-NBS-HS-000021, REV 00 I-10 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
63 6.7063 8.2148 0.027231 1955.4 1.8794 2.2914 0.81684 0.63478 0.68113 0.58819 0.33071 
64 5.9284 4.5135 0.26113 1979.9 3.1858 0.87284 0.63336 0.46033 0.33102 0.84547 0.58869 
65 6.0769 6.1286 0.38063 1936 1.6237 2.1973 0.46483 0.68187 0.58955 0.056247 0.84656 
66 6.8568 4.8948 0.15618 1902.7 2.4911 1.6189 0.68036 0.33279 0.84721 0.72827 0.058062 
67 6.5521 6.0288 -0.04535 1947.4 2.9073 0.77816 0.33359 0.58683 0.055556 0.78499 0.72763 
68 5.8885 4.6899 0.21756 1876.5 2.1063 0.98331 0.5888 0.84941 0.72882 0.41564 0.78044 
69 6.7622 5.4261 -0.19898 1927.3 1.3901 0.77861 0.84696 0.057968 0.78458 0.79874 0.41834 
70 6.6141 5.7935 0.10325 1990.4 2.3218 1.0352 0.059202 0.72741 0.41612 0.26343 0.79713 
71 6.4774 5.1016 0.41512 1786.2 0.91759 1.4684 0.72908 0.783 0.79694 0.32595 0.26112 
72 6.0152 4.4622 -0.90291 1957.5 1.9062 1.2751 0.78309 0.41711 0.26183 0.21814 0.32885 
73 6.6337 5.2846 0.2696 1971.2 3.0586 1.4506 0.41849 0.79753 0.3285 0.57109 0.21954 
74 5.7281 3.9643 0.33449 1893.6 0.90317 1.5424 0.79539 0.26215 0.21556 0.051789 0.57407 
75 5.9141 4.9391 -0.0988 1974.5 2.5336 2.6217 0.26288 0.32672 0.57298 0.10611 0.052027 
76 6.614 5.9195 0.3558 1860.1 2.769 2.1371 0.32568 0.21746 0.053163 0.40591 0.10719 
77 5.583 2.9262 -0.2854 1874.8 1.2181 0.7788 0.21624 0.57483 0.10741 0.91972 0.40777 
78 6.4587 5.4588 -0.20391 1849.7 2.8383 2.0286 0.57311 0.052277 0.40829 0.8908 0.91655 
79 6.7143 5.6723 -0.33597 1924.3 0.90379 1.6683 0.05449 0.10898 0.91926 0.19459 0.89262 
80 6.4207 4.293 0.088795 1785.3 0.90398 1.9847 0.10825 0.4085 0.89123 0.87371 0.19373 
81 13.178 5.7162 -0.95629 1813.8 0.90365 2.8559 0.40932 0.91507 0.19271 0.66865 0.87036 
82 6.2222 3.6944 -0.46886 1891.7 1.847 0.77807 0.91592 0.89045 0.87402 0.022481 0.66851 
83 5.874 3.9482 -0.11054 2018.2 0.90316 1.5616 0.89293 0.19045 0.66901 0.23693 0.024774 
84 5.4575 3.5414 0.57263 2006.8 0.90333 0.77854 0.19004 0.87062 0.023309 0.091047 0.2352 
85 6.6604 4.87 0.47059 1842.7 1.1819 1.0206 0.87302 0.66938 0.2368 0.26906 0.091802 
86 5.6849 2.9113 -0.3659 1998.4 3.3469 1.7082 0.6656 0.024152 0.090667 0.54398 0.26823 
87 5.6681 3.1148 0.44164 1944.2 3.2399 0.77803 0.023333 0.23528 0.26661 0.41455 0.54303 
88 6.0094 4.2502 0.19729 1751.8 0.90358 2.5253 0.23803 0.090919 0.54429 0.52672 0.41381 
89 18.764 6.1699 -1.2709 1853.8 3.1498 1.1287 0.093541 0.26709 0.4112 0.6066 0.52874 
90 6.5229 6.0913 -0.31499 1806.3 2.2535 0.77822 0.26696 0.54419 0.52817 0.94606 0.60614 
91 5.49 3.4321 -0.57236 1861.2 0.90307 1.0671 0.54172 0.41108 0.60997 0.86265 0.94816 
92 14.607 6.0081 -0.27432 1917.9 0.90372 0.77868 0.41491 0.52686 0.94891 0.12263 0.86301 
93 6.5563 5.2247 0.050354 1892.7 0.90328 1.3907 0.52942 0.60533 0.86005 0.84008 0.12295 
94 5.7647 2.2972 -0.10337 1915.2 0.9038 1.9143 0.60947 0.9471 0.12418 0.70779 0.84136

MDL-NBS-HS-000021, REV 00 I-11 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
95 5.7985 3.6118 0.032758 1931.1 1.7069 0.90439 0.94625 0.86346 0.84482 0.83642 0.70974 
96 5.7406 3.0688 0.13087 2035.9 1.2067 2.0823 0.86403 0.12324 0.70673 0.9929 0.83838 
97 6.1417 3.7298 0.73013 1995.7 1.6498 0.77824 0.12021 0.84037 0.83719 0.014448 0.9937 
98 6.0823 4.7642 0.43066 1819 1.9956 1.3968 0.84499 0.70858 0.99258 0.62177 0.010011 
99 6.3706 4.2707 -0.45167 1988.1 3.4882 2.1656 0.70993 0.83907 0.011816 0.080484 0.62177 
100 5.9745 4.6949 0.40649 1952.6 3.1045 0.7812 0.83656 0.99291 0.62029 0.25668 0.084052 
101 6.4906 4.9982 0.24501 1986.7 0.90337 0.77897 0.99369 0.011109 0.084139 0.74363 0.25783 
102 6.53 6.296 0.40263 2096.8 3.03 0.77829 0.012139 0.6206 0.25558 0.008536 0.74421 
103 6.2966 5.9683 0.9646 1736.1 2.4303 1.7389 0.62312 0.083331 0.74082 0.93232 0.008844 
104 5.5766 3.1765 -1.3741 1934.3 2.9977 0.77877 0.082851 0.25726 0.005755 0.32377 0.93333 
105 5.7063 5.8845 0.14663 1800.5 3.6849 1.4182 0.25651 0.74433 0.93264 0.031595 0.32274 
106 6.2582 5.3933 -0.65556 1859.7 0.90304 1.0833 0.74383 0.008921 0.32254 0.28928 0.032629 
107 7.7608 5.8838 -0.29014 1960.3 2.0719 2.503 0.007082 0.93162 0.032139 0.10235 0.28732 
108 10.662 8.4623 0.28677 1711.5 0.90325 2.5914 0.9343 0.32226 0.28774 0.48315 0.10135 
109 5.7953 1.9755 -1.4049 2027.8 0.90377 2.6724 0.32398 0.033875 0.10227 0.82137 0.48128 
110 6.2488 5.0698 0.65206 1874.1 2.5889 2.7358 0.034804 0.28617 0.48419 0.20142 0.82385 
111 5.5802 3.0312 -0.2145 1765.8 0.90302 0.8074 0.28713 0.10452 0.82206 0.85408 0.20133 
112 5.4934 3.6783 -1.1351 1866.8 3.4201 1.0809 0.10321 0.48255 0.20087 0.03713 0.85191 
113 6.4423 5.5068 -0.25443 1811.7 0.90397 1.1169 0.48009 0.82013 0.85325 0.48798 0.038156 
114 5.9016 1.9046 -0.47282 1906.2 0.9031 1.0955 0.82478 0.20143 0.036873 0.86745 0.48608 
115 6.5925 6.2268 -0.02221 1981.5 0.90386 1.1662 0.20399 0.85208 0.48667 0.15011 0.86707 
116 5.5144 3.9339 0.38733 1845.1 0.90331 1.7033 0.85464 0.036304 0.86896 0.14649 0.15383 
117 1.2386 2.4753 -0.35313 1991.5 1.4715 1.2305 0.038431 0.48549 0.15269 0.041893 0.14705 
118 6.0572 3.7894 0.42255 1773.4 2.934 2.2435 0.4888 0.86597 0.1496 0.76799 0.042585 
119 5.5503 3.1009 -1.0969 1907.4 0.90361 2.4104 0.86947 0.1505 0.041331 0.11687 0.76983 
120 6.8224 4.5391 -0.01547 1997.7 3.0755 1.434 0.15471 0.14696 0.76917 0.50225 0.11804 
121 6.7078 5.8264 0.4368 1830.6 0.90311 1.0568 0.1482 0.041927 0.11919 0.29972 0.50172 
122 6.4723 3.4667 -0.41438 1827.8 1.4778 0.77813 0.043749 0.76965 0.50249 0.92993 0.29938 
123 6.1209 5.929 -0.41778 1776.7 3.1256 2.3797 0.76795 0.11768 0.29931 0.94398 0.92995 
124 4.3387 2.6339 -1.0303 1966.5 0.90346 1.7621 0.11763 0.50186 0.92988 0.9591 0.94279 
125 5.8421 4.5436 0.31744 1818.1 0.90345 1.5484 0.50125 0.29969 0.9417 0.9723 0.95904 
126 6.6251 5.9877 -0.45746 1910.2 0.90312 1.3264 0.29829 0.92712 0.95959 0.16336 0.9735

MDL-NBS-HS-000021, REV 00 I-12 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
127 5.4937 3.2852 0.001514 1868.8 2.6949 1.3193 0.92626 0.94495 0.97011 0.29355 0.16075 
128 5.8027 3.2702 -0.24028 2024.4 0.90336 2.4598 0.94317 0.95688 0.16089 0.31924 0.29198 
129 5.9088 2.6876 0.63084 2032.1 1.5522 0.77853 0.95718 0.97024 0.29356 0.30068 0.31688 
130 6.8267 5.6069 0.70954 2044.3 0.9039 2.7802 0.97338 0.16089 0.31924 0.34894 0.30226 
131 5.6516 3.1558 0.77432 2060.7 3.4028 2.2586 0.16471 0.29112 0.30169 0.73742 0.34723 
132 6.1835 4.6179 0.8669 1834 3.4585 1.6053 0.2919 0.31659 0.34685 0.38542 0.73879 
133 6.2919 3.8323 -0.40523 1867.7 3.5324 0.86487 0.31639 0.30034 0.7382 0.8844 0.38707 
134 6.8574 6.22 -0.24736 1873.1 3.5873 1.5948 0.30114 0.34737 0.38911 0.91417 0.88103 
135 6.6929 6.2657 -0.21795 1869.7 0.9035 0.84208 0.34709 0.7389 0.8827 0.51527 0.91491 
136 6.8367 6.5706 -0.23599 1879.7 0.90388 2.6439 0.73959 0.38723 0.91191 0.27739 0.51637 
137 6.3765 7.4878 -0.18222 1959.9 0.90395 0.77896 0.3856 0.88123 0.51821 0.01555 0.27512 
138 5.4213 3.3293 0.28472 1888.1 0.90392 1.721 0.8846 0.91276 0.27884 0.90859 0.015142 
139 6.5404 3.8249 -0.13344 2003.3 0.96295 0.77857 0.91058 0.51807 0.019829 0.78559 0.9075 
140 6.3039 3.9127 0.45875 2015.8 2.5618 0.96496 0.51863 0.27877 0.90669 0.61248 0.78753 
141 5.6224 3.847 0.55231 1913.2 1.1215 1.7325 0.27928 0.018004 0.78506 0.44553 0.6123 
142 6.2112 4.0184 0.022971 1864.3 3.212 1.0603 0.017035 0.90513 0.61484 0.44206 0.44827 
143 6.5305 5.5041 -0.26788 1747.7 3.339 1.6273 0.90617 0.7874 0.44935 0.92037 0.44137 
144 6.6787 4.1826 -1.319 2012.9 1.6067 1.4599 0.78778 0.61244 0.44289 0.077399 0.92211 
145 6.4408 6.0396 0.51974 1971.7 0.90383 1.4942 0.61002 0.44738 0.92177 0.9795 0.075209 
146 13.65 6.1585 0.34072 1931.8 0.90305 0.9128 0.44868 0.44026 0.078919 0.88632 0.9771 
147 6.1936 4.6736 0.13291 1900.1 3.3213 1.2546 0.44447 0.92422 0.97874 0.65608 0.88741 
148 5.7435 3.7619 -0.06401 1898.7 2.7905 2.8905 0.92373 0.077673 0.88803 0.18793 0.65881 
149 5.4669 2.0896 -0.07036 2019.6 2.0286 1.2974 0.076063 0.97623 0.65712 0.646 0.1872 
150 8.9403 6.1315 0.60144 1800.4 1.3319 0.95621 0.977 0.88897 0.18621 0.17963 0.6468 
151 6.4227 5.6864 -0.70644 2065.3 1.3096 2.1114 0.88659 0.65894 0.64638 0.9533 0.17576 
152 6.3057 5.0306 0.88838 2004.3 3.3771 1.6455 0.65842 0.18734 0.17977 0.14185 0.9527 
153 6.478 4.394 0.46244 1941.7 0.90323 0.77801 0.18664 0.64891 0.95287 0.75049 0.14379 
154 5.4622 4.3793 0.1871 1840.8 3.6119 1.6096 0.64507 0.17691 0.14233 0.086316 0.75248 
155 6.5647 6.1992 -0.37093 1939.2 3.2128 1.7536 0.17711 0.95118 0.75482 0.23203 0.087912 
156 5.9147 2.9992 0.17419 1838.4 2.2216 0.88998 0.95059 0.14242 0.086579 0.7641 0.23087 
157 5.7989 7.8565 -0.38192 2039.2 0.90356 1.2436 0.14252 0.75409 0.23232 0.28118 0.76162 
158 6.2505 6.0621 0.75051 1826.1 2.1818 1.6866 0.75153 0.088803 0.76344 0.67984 0.28492

MDL-NBS-HS-000021, REV 00 I-13 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
159 6.8844 5.1999 -0.42699 1963.6 0.90353 1.6433 0.08683 0.2337 0.28051 0.53945 0.67884 
160 5.5314 3.4208 0.29815 1803.9 3.5015 2.797 0.23407 0.76141 0.67786 0.56739 0.53767 
161 6.5527 5.1585 -0.61352 1852.5 0.90344 1.3361 0.76128 0.2824 0.53504 0.20679 0.5676 
162 6.4007 3.3742 -0.3168 1966.2 2.6324 1.4226 0.28348 0.67679 0.56754 0.4036 0.20555 
163 6.8426 6.3283 0.31264 1864.5 0.90326 1.4115 0.6774 0.5359 0.20907 0.99995 0.40382 
164 1.2468 3.2461 -0.26077 1945.8 0.9037 1.4326 0.53853 0.56976 0.40303 0.42927 0.99514 
165 6.6391 5.5608 0.21202 1917.8 2.6793 1.4902 0.56716 0.20581 0.99747 0.22505 0.42972 
166 4.298 3.0393 0.042953 1923.5 0.90386 1.5815 0.20914 0.40267 0.42578 0.85881 0.22675 
167 6.3136 3.5934 0.082558 1846.9 2.304 0.85035 0.40148 0.99633 0.22882 0.69465 0.85692 
168 6.8724 5.5989 -0.3463 1890.8 1.6854 1.4043 0.99946 0.429 0.85968 0.002816 0.69442 
169 6.0327 3.7778 -0.11436 2150 1.8197 1.1554 0.42931 0.22809 0.69398 0.66467 0.004499 
170 6.6137 5.2625 0.9848 1896.2 0.90363 0.77864 0.22617 0.85547 0.000323 0.77513 0.66304 
171 6.133 4.737 -0.08534 1851.6 1.1755 0.77818 0.85851 0.69354 0.66257 0.19757 0.77725 
172 5.5432 4.8472 -0.32558 1992.9 3.6966 1.6616 0.69111 0.003257 0.77945 0.39292 0.19571 
173 5.7763 3.487 0.42615 1949.6 1.2557 1.5596 0.003656 0.66345 0.19765 0.72304 0.3905 
174 9.6773 4.2364 0.23043 1675.6 0.90369 1.1742 0.66204 0.77506 0.39062 0.68608 0.72139 
175 19.99 8.772 -1.4274 1942.6 3.1009 1.3104 0.77547 0.19838 0.72232 0.98368 0.68895 
176 5.5716 4.3221 0.1918 1969.8 2.3748 1.2113 0.19977 0.39453 0.68752 0.45485 0.98231 
177 5.6452 3.5686 0.32826 1844.1 0.903 1.2221 0.39164 0.72283 0.98031 0.50929 0.45473 
178 13.398 5.9529 -0.36243 1888.8 2.2491 2.6986 0.72173 0.68745 0.45427 0.49792 0.50512 
179 6.2551 5.3194 -0.1308 1955.7 2.7377 2.7263 0.68811 0.98268 0.5089 0.51067 0.49559 
180 4.8797 1.7248 0.26453 1948.5 0.90359 0.77843 0.98291 0.45113 0.49716 0.56127 0.51465 
181 6.4204 5.2177 0.22384 2076 1.14 1.249 0.45143 0.50761 0.51411 0.63635 0.56495 
182 13.365 5.6477 0.90461 1900.3 2.4991 0.77886 0.50641 0.4978 0.56414 0.18298 0.63987 
183 5.4669 3.4549 -0.05683 1911.2 2.3608 1.9716 0.49998 0.51184 0.63908 0.49347 0.18035 
184 6.527 4.1951 0.010673 1909.7 3.6328 1.9303 0.51124 0.56314 0.18468 0.33757 0.49318 
185 6.1383 5.4358 -0.00257 1912.2 1.3576 1.3653 0.56096 0.63868 0.49378 0.095147 0.339 
186 6.6416 5.3098 0.015309 1922.2 1.5741 0.77876 0.63832 0.18425 0.33664 0.02893 0.098947 
187 6.891 7.9127 0.072474 1937 1.5171 0.98742 0.18035 0.4943 0.0968 0.70491 0.029299 
188 6.1474 4.4289 0.16452 1839.5 1.5859 1.8086 0.49056 0.33741 0.026781 0.61604 0.70419 
189 6.525 4.637 -0.37947 1909 1.7945 0.77888 0.33874 0.096534 0.70431 0.35289 0.61966 
190 6.2508 4.5943 -0.00717 1877.3 2.1272 1.6963 0.096831 0.029759 0.61591 0.43939 0.35146

MDL-NBS-HS-000021, REV 00 I-14 July, 2003 
real. # KDUVO KDUAL GWSPD BULKDEN 
SITY 
CORAL CORVO SRC4Y SRC4X SRC3X SRC2Y SRC2X 
191 6.0393 4.6492 -0.19088 1809 0.90355 1.1569 0.028917 0.70069 0.35311 0.37338 0.43794 
192 5.9913 4.8274 -0.50508 1763.2 1.5065 0.77832 0.70456 0.6185 0.43943 0.38091 0.37255 
193 5.878 5.1259 -1.2166 1951.2 0.921 1.7169 0.61513 0.35035 0.37237 0.96251 0.38203 
194 2.3362 3.4099 0.23869 1933.3 0.9033 2.5605 0.35362 0.43951 0.38267 0.96816 0.96337 
195 6.1 4.5729 0.13794 1880 0.90309 1.4774 0.43658 0.37213 0.96475 0.063027 0.96716 
196 5.9918 3.9869 -0.176 1897.5 2.4068 1.766 0.37128 0.38098 0.96775 0.39953 0.061097 
197 5.605 3.0866 -0.07449 1884.9 2.0457 1.2188 0.38369 0.964 0.061914 0.1285 0.3971 
198 5.7889 2.3548 -0.15273 1887.1 0.98501 1.6249 0.96476 0.96823 0.39947 0.83442 0.12711 
199 6.0367 5.3679 -0.14182 2047.7 1.3082 1.601 0.96697 0.061409 0.12965 0.82773 0.83158 
200 6.1339 5.0355 0.79534 2055 1.0649 1.5667 0.061482 0.39772 0.83314 0.46639 0.82855

MDL-NBS-HS-000021, REV 00 I-15 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
1 0.83233 0.24005 0.80624 17.732 1.9903 812.85 440.3 87.238 108.87 4.8775 
2 0.82718 0.80526 0.13308 4.6087 1.6863 438.05 704.33 99.833 92.939 5.0531 
3 0.46566 0.13442 0.73247 12.27 1.0289 707.27 688.4 33.356 77.02 4.2620 
4 0.11361 0.73275 0.34383 3.2112 0.54985 688.19 663.39 66.542 109.71 4.5371 
5 0.24003 0.34009 0.049709 7.6813 2.4022 663.62 323.7 77.052 124.51 4.2375 
6 0.80576 0.046205 0.7459 6.9906 2.2194 321.01 742.97 82.59 100.9 4.3941 
7 0.13452 0.74864 0.93901 6.0614 1.7185 741.48 430.16 81.992 112.08 5.1399 
8 0.73186 0.93694 0.55457 2.18 1.8825 429.34 525.79 79.222 94.367 4.2041 
9 0.34145 0.55106 0.79371 9.1734 1.7536 526.19 626.36 91.596 106.1 4.6918 
10 0.047266 0.79274 0.37606 3.1527 1.7716 626.1 256.08 77.994 105.03 5.1004 
11 0.74875 0.37598 0.67186 3.965 3.3158 255.36 346.45 78.102 104.08 4.8134 
12 0.9384 0.67431 0.65349 4.8648 3.4105 344.48 252.75 86.185 89.193 3.8495 
13 0.55426 0.65427 0.62915 1.5987 0.85794 250.6 293.32 95.152 107.76 5.3892 
14 0.79285 0.62833 0.24857 2.3803 1.8079 289.57 644.32 83.888 93.974 4.9578 
15 0.37977 0.24591 0.71151 1.5328 1.1538 644.32 240.83 49.263 97.825 3.8205 
16 0.67304 0.71226 0.36864 1.9111 2.7247 241.27 425.57 88.886 102.21 5.5740 
17 0.65016 0.36852 0.47149 5.1696 2.7109 426.26 632.99 79.081 85.471 4.6028 
18 0.62547 0.47303 0.58007 1.4755 1.9399 631.8 489.65 90.427 90.109 4.8036 
19 0.24894 0.58477 0.17326 3.117 1.099 489.47 166.43 80.258 85.408 4.6142 
20 0.71268 0.17148 0.2719 4.9406 1.4758 166.72 727.65 87.551 87.421 5.1106 
21 0.36671 0.27358 0.16723 3.6422 2.6485 726.02 580.16 56.616 102.9 4.9749 
22 0.47389 0.16561 0.2131 0.74358 1.1613 578.39 161.12 95.787 84.683 4.4990 
23 0.58452 0.21367 0.60303 8.6622 2.4699 159.62 829.77 75.98 93.664 5.2601 
24 0.17185 0.60264 0.15762 4.4577 1.6923 830.57 376.18 78.857 102.68 4.8586 
25 0.27162 0.15986 0.36181 0.70371 0.73272 375.4 481.98 75.926 96.375 4.6846 
26 0.16981 0.36202 0.59096 13.014 2.4972 479.18 381.72 79.314 79.051 5.5658 
27 0.21102 0.59494 0.43437 2.6796 3.1595 381.7 638.55 99.785 107.22 5.6739 
28 0.60015 0.43132 0.070798 3.5794 2.1024 638.67 590.61 75.657 100.17 4.4166 
29 0.15677 0.070876 0.69583 2.6814 2.615 593.85 328.84 89.188 78.996 5.5237 
30 0.36158 0.69708 0.53266 4.9996 1.7618 326.95 678.7 86.55 113.21 5.4983

MDL-NBS-HS-000021, REV 00 I-16 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
31 0.59138 0.53117 0.065333 4.5813 2.3314 677.42 509.58 78.09 91.582 4.9849 
32 0.43049 0.068262 0.81193 2.2104 2.2912 511.98 422.18 75.186 96.013 4.1083 
33 0.074454 0.81122 0.30876 6.6744 2.2459 422.1 820.66 49.841 91.679 5.9685 
34 0.6978 0.3088 0.42281 3.8414 1.4862 822.12 909.44 87.598 102.71 4.8878 
35 0.53021 0.42103 0.3129 3.0765 2.4162 909.46 300.12 97.988 100.7 5.6821 
36 0.068291 0.31034 0.59624 12.605 1.7497 298.61 796.55 77.33 89.246 5.0253 
37 0.81435 0.59788 0.5451 16.073 1.9504 794.22 779.79 83.752 104.64 5.6522 
38 0.30796 0.54611 0.25403 1.9833 2.1609 779.57 599.93 94.378 97.323 4.9442 
39 0.42208 0.25262 0.64219 11.416 1.2938 599.68 224.14 61.75 93.554 5.4314 
40 0.31087 0.64499 0.45689 10.91 1.5451 222.51 987.6 172.18 112.55 5.5843 
41 0.59771 0.45948 0.35958 4.6453 1.2728 987.07 529.6 96.635 119.63 5.2355 
42 0.54692 0.35889 0.80226 1.2839 1.4037 530.28 914.05 77.52 87.977 4.8650 
43 0.2541 0.80481 0.89657 19.479 2.1923 910.33 620.16 157.77 110.89 5.3636 
44 0.64387 0.89955 0.2211 4.0008 1.2504 620.04 891.15 96.594 110 4.6416 
45 0.45648 0.22056 0.77458 16.385 1.7351 891.41 571.89 46.513 101.28 5.0719 
46 0.35594 0.77106 0.75751 4.8125 2.1801 571.12 746.07 85.511 83.562 5.6180 
47 0.8044 0.75705 0.55876 15.444 1.8744 747.9 837.75 88.67 135.96 3.7922 
48 0.89716 0.55861 0.13615 4.3716 0.91376 835.64 667.68 76.295 98.093 5.4487 
49 0.22083 0.1361 0.98634 9.4864 2.3907 670.09 514.51 80.551 120.19 5.5328 
50 0.7728 0.98683 0.4783 13.063 2.0576 514.64 715.01 98.197 102.03 4.7887 
51 0.75745 0.47635 0.90182 6.2683 0.88603 712.87 399.44 70.169 118.01 5.5539 
52 0.5575 0.90124 0.57823 3.9013 2.6678 399.58 628.62 89.094 99.752 4.5138 
53 0.13948 0.57826 0.87579 8.0909 1.6269 627.55 864.64 98.041 107.99 4.6338 
54 0.9886 0.87902 0.52465 2.8593 1.849 864.15 150.75 250.9 113.65 4.4139 
55 0.47636 0.52426 0.71777 4.9025 1.6384 151.12 756.56 92.821 104.29 5.0128 
56 0.90226 0.71853 0.81891 14.232 2.1894 754.26 803.41 98.759 97.509 3.7624 
57 0.57565 0.81586 0.63343 0.60484 2.0898 806.44 474.02 99.074 106.51 3.9613 
58 0.87726 0.63481 0.46333 9.816 1.5057 476.79 818.8 70.063 92.659 4.7692 
59 0.52271 0.46349 0.68074 11.868 2.2752 818.62 336.85 73.661 102.42 5.6955 
60 0.71539 0.68244 0.33489 3.5262 1.9216 336.49 394.56 95.558 115.57 5.6712 
61 0.81858 0.33278 0.58895 12.424 1.7264 394.68 294.57 68.061 78.053 4.3374 
62 0.63424 0.58517 0.84543 2.2896 2.6399 296.99 615.74 81.64 108.66 5.6464

MDL-NBS-HS-000021, REV 00 I-17 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
63 0.46136 0.84982 0.056311 2.8305 2.956 613.08 148.46 94.821 111.49 5.3243 
64 0.68066 0.057841 0.72978 1.9279 1.426 145.92 195.85 63.426 95.797 3.5267 
65 0.33153 0.72969 0.78261 4.7985 2.5599 198.3 467.99 86.455 112.44 4.4555 
66 0.58726 0.78325 0.4167 0.53612 2.5179 465.66 924.72 78.976 89.718 3.9177 
67 0.84941 0.41653 0.79797 1.0404 2.1075 926.22 903.86 84.916 92.376 4.5297 
68 0.058578 0.79803 0.26066 3.4568 1.1735 903.5 273.95 82.841 87.717 4.9694 
69 0.728 0.26347 0.32972 16.911 3.6979 272.15 883.85 38.951 101.83 4.7835 
70 0.78038 0.32548 0.21687 16.014 1.9618 885.32 702.03 37.268 77.264 4.9502 
71 0.41596 0.21798 0.57346 1.7511 2.9809 700.89 121.54 84.703 81.802 5.1614 
72 0.79808 0.57228 0.054074 15.225 2.1481 119.34 314.87 78.102 95.495 5.8209 
73 0.26002 0.052024 0.10657 7.5336 2.8736 311.66 183.97 86.508 121.95 5.6385 
74 0.32626 0.10795 0.40776 0.24534 2.039 183.08 339.8 90.516 119.24 4.0269 
75 0.21674 0.40841 0.91631 2.0967 2.4268 339.18 589.62 53.927 86.459 5.6138 
76 0.57425 0.91592 0.89188 0.92987 2.6786 588.04 473.21 99.006 117.71 5.4099 
77 0.053163 0.89356 0.19002 2.3237 2.2583 471.84 575.22 70.292 105.81 5.6053 
78 0.10825 0.19055 0.87486 4.5209 1.933 572.68 648.88 89.226 73.738 5.9754 
79 0.40749 0.87385 0.66564 3.5023 2.361 646.51 950.64 63.707 88.667 3.3825 
80 0.91533 0.66936 0.024592 4.4069 1.6742 952.86 877.79 14.829 80.824 5.1987 
81 0.89182 0.024802 0.238 5.2885 2.1683 877.91 212.04 75.662 89.887 3.8823 
82 0.19247 0.23768 0.092733 18.024 2.7659 208.9 860.23 97.057 100.63 4.5064 
83 0.8716 0.093798 0.2697 14.834 0.82441 860.11 736.5 77.366 95.705 5.4698 
84 0.66663 0.26782 0.54484 1.1753 2.4578 738.68 855.93 95.89 100.03 3.2578 
85 0.022039 0.54487 0.41286 14.054 2.5864 854.64 993.11 90.006 103.17 5.7672 
86 0.23834 0.41297 0.5255 9.0438 1.8464 994.47 110.54 92.685 126.14 4.6235 
87 0.09303 0.52693 0.60617 13.953 2.6304 110.62 659.13 299.77 116.81 3.6374 
88 0.26994 0.6098 0.94768 19.747 1.5209 658.39 174.16 94.012 82.794 4.5614 
89 0.54397 0.94692 0.8623 0.17871 1.6666 172.55 331.74 94.101 115.37 3.9564 
90 0.41441 0.86116 0.12201 5.8295 1.4188 329.82 767.45 85.307 107.69 4.8941 
91 0.52656 0.12189 0.84487 0.84378 2.1415 766.83 108.83 84.217 115.02 5.5922 
92 0.60929 0.84095 0.70556 2.267 0.76916 108.02 939.97 156.24 139.22 4.3696 
93 0.94947 0.70568 0.83988 10.333 1.062 937.88 389.58 81.663 71.507 5.6284 
94 0.8607 0.83864 0.99131 0.11614 1.8277 388.79 129.98 76.875 103.93 3.6732

MDL-NBS-HS-000021, REV 00 I-18 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
95 0.12496 0.99254 0.012151 17.474 3.0474 127.83 358.17 89.827 80.093 4.8986 
96 0.84424 0.014322 0.6206 2.7787 2.9291 359.12 191.36 97.079 89.546 5.6454 
97 0.70863 0.62212 0.081579 0.34647 1.3502 192.1 534.33 96.311 109.3 4.1823 
98 0.83814 0.081611 0.25537 2.5184 2.8488 534.89 840.2 58.463 68.715 4.1468 
99 0.99153 0.25963 0.74219 1.0399 2.3268 841.52 281.38 92.69 124.07 3.7073 
100 0.01084 0.74266 0.00638 4.0701 0.4986 282.1 868.25 77.692 92.211 5.5092 
101 0.6226 0.008537 0.9333 13.369 1.4611 866.27 135.17 29.459 74.655 3.9941 
102 0.082755 0.93024 0.32214 1.8159 1.0042 131.91 540.77 67.995 90.751 4.9205 
103 0.25772 0.32134 0.031583 14.474 1.5392 539 882.9 15.984 81.538 4.5873 
104 0.74379 0.031874 0.28828 0.39787 2.0766 880.48 236.85 78.325 98.315 5.7497 
105 0.0066 0.28693 0.10244 4.0921 1.833 238.35 232.4 94.807 113.88 5.8007 
106 0.9304 0.10181 0.48385 14.975 2.0524 232.95 136.31 30.253 86.943 5.8716 
107 0.32214 0.48365 0.82219 1.4235 2.2089 139.73 790.5 87.018 116.02 5.9238 
108 0.034931 0.82127 0.20133 1.3614 3.2142 789.56 205.25 15.295 75.807 4.2303 
109 0.28848 0.20343 0.85064 0.47523 2.8115 204.97 554.05 69.971 98.454 4.5744 
110 0.10153 0.85494 0.037852 11.212 1.131 552.51 367.97 85.61 117.35 4.6150 
111 0.48488 0.039425 0.48927 1.1337 2.7541 369.82 936.25 45.83 84.514 4.5945 
112 0.82181 0.48703 0.86816 4.2122 2.4064 935.32 947.4 82.043 84.306 4.6692 
113 0.20309 0.86964 0.15423 2.581 2.735 949.48 963.04 80.577 76.071 5.4624 
114 0.85318 0.15153 0.14775 17.239 3.9162 960.13 975.53 98.014 110.59 4.7348 
115 0.037029 0.14723 0.043615 17.784 0.28545 973.13 244.95 67.66 82.558 5.6580 
116 0.48919 0.044629 0.76977 18.48 2.2311 247.87 362.6 94.324 98.991 5.6920 
117 0.86816 0.76877 0.11639 19.016 0.96482 361.16 385.18 76.984 91.229 4.9390 
118 0.15324 0.11722 0.50208 1.5062 1.5153 386.4 373.33 94.706 123.17 4.5446 
119 0.14901 0.50107 0.29533 2.5563 2.4838 370.58 412.47 90.755 124.87 3.4129 
120 0.042737 0.29727 0.92996 2.7567 0.24038 414.2 765.76 79.187 127.87 5.6875 
121 0.76893 0.92623 0.94325 2.6167 3.1079 763.07 449.47 187.93 130.96 5.5441 
122 0.11682 0.94167 0.9558 2.9723 1.6573 450.84 893.8 80.185 85.118 5.1761 
123 0.50185 0.95667 0.97337 10.141 0.63252 896.39 919.94 75.516 90.898 4.8374 
124 0.29877 0.97469 0.16451 3.2972 1.5766 920.24 564.89 68.053 92.057 4.8294 
125 0.9262 0.16335 0.29046 15.653 1.0562 566.15 347.78 84.548 91.285 5.7118 
126 0.94249 0.29347 0.31994 16.673 1.963 349.81 116.51 77.995 93.119 3.8728

MDL-NBS-HS-000021, REV 00 I-19 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
127 0.95651 0.31629 0.30057 4.3587 2.6953 115.03 915.08 80.543 109.14 5.9370 
128 0.97227 0.30062 0.34665 2.4069 1.3783 917.36 808.56 94.029 94.609 5.6665 
129 0.16375 0.34816 0.73806 0.20749 2.7931 807.17 653.26 47.702 118.5 5.3010 
130 0.2908 0.73514 0.38982 16.487 0.64424 650.78 504.69 95.675 121.56 4.3202 
131 0.31825 0.38902 0.88375 12.122 1.9739 502.29 497.53 79.084 99.609 5.2718 
132 0.30346 0.8811 0.91445 5.5165 2.8316 497.26 928.08 87.425 90.397 4.2901 
133 0.34536 0.91351 0.51775 3.7934 1.2279 932.09 167.74 78.926 71.682 5.8432 
134 0.73979 0.51891 0.27618 3.7533 1.2149 170.49 978.15 53.697 120.69 4.1248 
135 0.38918 0.27944 0.017364 17.149 0.71527 981.81 900.52 29.152 111.8 5.4871 
136 0.88142 0.018064 0.90692 0.80096 2.5438 899.31 692.85 85.375 103.46 3.9044 
137 0.91369 0.90812 0.78832 19.129 1.1016 691.49 268.16 75.06 96.932 4.4487 
138 0.51854 0.78574 0.61055 15.729 2.0081 266.74 684.08 95.652 96.697 5.5024 
139 0.27967 0.61066 0.44885 7.1148 1.6021 682.82 261.21 86.741 122.43 4.5558 
140 0.018437 0.44944 0.44473 1.6814 3.1047 259.8 957.8 52.56 79.558 5.3464 
141 0.90992 0.44492 0.92486 6.8321 3.1925 959.02 228.62 92.132 132.79 4.9658 
142 0.78977 0.92496 0.077725 1.6259 3.2736 228.36 778.38 90.726 118.79 4.9995 
143 0.61162 0.077621 0.97922 18.18 3.4137 776.75 180.78 84.511 105.23 4.3784 
144 0.44672 0.97709 0.88689 1.3552 1.2599 177.45 308.05 79.546 86.269 4.7661 
145 0.44483 0.88694 0.65537 10.812 1.5851 307.83 787.18 26.188 104.91 5.9886 
146 0.92381 0.65965 0.18644 0.89423 1.6389 788.47 355.4 77.964 85.829 4.8111 
147 0.077437 0.18566 0.64725 2.0794 1.6102 354.67 709.36 97.694 127.33 4.4372 
148 0.97688 0.64518 0.17796 11.024 1.7018 710.03 584.97 89.418 83.89 5.6345 
149 0.88764 0.17513 0.95462 2.4793 2.4779 585.05 611.31 87.727 109.74 5.3747 
150 0.65902 0.95013 0.14251 7.9905 1.7862 610.1 285.37 44.46 80.593 3.1110 
151 0.18671 0.14065 0.75367 4.4803 2.8909 285.78 461.67 19.323 88.309 5.3096 
152 0.64903 0.75082 0.085452 4.7229 3.0224 462.78 999.51 90.311 110.43 5.5276 
153 0.17695 0.087076 0.23365 1.8713 2.0351 999.67 483.77 77.454 90.563 4.3465 
154 0.9512 0.23467 0.76487 3.4203 1.5586 484.97 306.89 89.845 106.18 4.7466 
155 0.14091 0.76127 0.2801 19.848 0.38107 306.1 872.4 98.457 100.45 5.4393 
156 0.75336 0.28179 0.67652 3.6112 3.0035 871.12 725.39 91.867 101.58 5.3692 
157 0.08953 0.67582 0.53817 2.0206 2.5998 721.14 103.99 60.614 87.341 5.9484 
158 0.23059 0.53548 0.56945 14.703 2.2116 101.08 695.4 34.592 95.224 4.8526

MDL-NBS-HS-000021, REV 00 I-20 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
159 0.7646 0.56552 0.20822 8.3977 1.8999 698.34 798.89 86.608 148.17 4.9279 
160 0.28497 0.20529 0.40255 0.08363 1.8931 798.55 277.25 179.31 96.195 4.9132 
161 0.67504 0.40101 0.99992 7.3602 3.0661 275.58 455.23 83.162 88.301 4.9346 
162 0.53552 0.99938 0.42575 11.705 0.9365 455.05 748.2 88.263 116.45 4.9929 
163 0.56653 0.42685 0.22858 1.7744 3.5397 751.7 720.14 53.479 106.92 5.2455 
164 0.20863 0.22935 0.85861 3.3344 2.9012 718.67 983.76 95.995 63.959 4.3054 
165 0.40195 0.85843 0.69288 9.6034 2.3059 984.15 509.34 92.983 105.54 4.9098 
166 0.99884 0.69375 0.001538 8.2444 1.3307 505.59 556.96 91.708 111.26 4.6501 
167 0.4295 0.00151 0.66146 19.375 2.2877 556.95 548.66 57.505 86.894 3.9386 
168 0.22599 0.66498 0.77751 3.8245 1.3026 547.43 562.63 88.128 94.915 3.5547 
169 0.8586 0.77867 0.19755 4.2764 3.2398 561.48 608.45 81.325 108.24 5.4048 
170 0.69437 0.1954 0.39244 4.1922 1.1982 608.46 671.99 80.933 106.64 5.1931 
171 0.001231 0.39299 0.72459 4.3053 2.514 671.82 265.99 219.94 134.49 4.6748 
172 0.6606 0.72016 0.68846 4.6899 0.97624 262.5 541.5 94.211 97.076 4.8286 
173 0.77628 0.68789 0.98023 6.4311 1.4467 545.05 402.29 89.533 99.164 4.7081 
174 0.19637 0.98146 0.45478 1.6777 2.5403 403.25 185.89 45.799 98.867 4.7295 
175 0.39311 0.45483 0.50829 4.1271 1.5639 189.74 125.45 95.51 99.409 5.8882 
176 0.72453 0.50536 0.49776 2.8941 2.3457 124.24 734.44 81.464 101.46 5.9004 
177 0.68917 0.49845 0.51009 0.98473 2.0682 731.22 654.92 78.815 104.55 3.8036 
178 0.98396 0.51107 0.56335 0.29817 2.1292 653.57 416.24 91.501 86.075 4.7517 
179 0.45418 0.56394 0.63905 8.9345 1.394 416.08 492.31 83.816 98.647 4.0583 
180 0.50686 0.6384 0.18176 5.6614 1.8196 493.18 435.53 93.055 92.833 5.6042 
181 0.49959 0.18351 0.49236 3.0019 4.0513 437.08 445.56 29.693 81.084 5.5955 
182 0.51036 0.49117 0.33981 3.713 1.862 446.28 964.34 84.386 74.407 4.8724 
183 0.56418 0.33823 0.098419 3.1858 1.4389 965.64 970.23 96.859 107.46 3.9848 
184 0.63522 0.098359 0.029148 3.28 2.8066 970.12 157.45 77.974 103.63 4.4748 
185 0.18001 0.028657 0.7049 18.674 2.3825 155.45 458.25 53.3 93.339 5.5682 
186 0.49328 0.70242 0.61821 18.723 -0.00165 458.27 216.04 85.497 96.562 4.0889 
187 0.33932 0.6174 0.35471 0.66095 2.3105 213.33 848.03 91.901 94.132 5.4564 
188 0.095855 0.35206 0.43994 3.3711 2.5777 848.42 845.9 99.622 94.576 4.6564 
189 0.025006 0.43563 0.37403 1.2357 1.3627 843.72 521.17 94.301 129.18 3.7290 
190 0.70291 0.37478 0.38384 13.799 1.7917 519.67 200.06 94.397 130.24 5.4786

MDL-NBS-HS-000021, REV 00 I-21 July, 2003 
real. # SRC3Y SRC1Y SRC1X HAVO LDISP KDRAVO KDRAAL KD_PU_VO KD_PU_AL KD_PU_C0L 
191 0.61896 0.38398 0.96484 13.577 2.4475 199.43 316.94 83.555 78.41 5.7810 
192 0.35329 0.96202 0.96738 3.9583 2.3695 320.09 827.3 90.094 95.042 4.9796 
193 0.43628 0.9654 0.062055 1.0922 3.5458 826.09 219 71.043 83.247 5.5478 
194 0.37169 0.061335 0.39868 2.1208 1.9109 218.91 760.81 77.053 114.66 4.7098 
195 0.38195 0.39667 0.12538 12.783 2.0123 761.17 408.2 77.048 114.11 5.3385 
196 0.96264 0.12797 0.83326 1.2474 1.9917 406.69 142.25 85.209 97.678 5.2878 
197 0.96574 0.8321 0.82688 9.9052 2.0208 144.67 773.83 25.382 82.048 5.2122 
198 0.063634 0.82798 0.46962 2.9301 2.1217 772.31 943.72 77.31 88.773 4.4856 
199 0.39766 0.46669 0.11218 0.49962 2.2674 943.38 595.47 90.686 113.09 5.4216 
200 0.12612 0.1129 0.24114 10.512 1.3256 596.34 813.08 87.434 83.544 4.6979

MDL-NBS-HS-000021, REV 00 I-22 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
1 6488.6 5700.9 5.6503 4872.9 178.08 3.4892 -4.4407 
2 7769.2 6721 5.8331 3409.9 799.65 2.9211 -4.4107 
3 5702.4 5037 5.9814 6484.7 945 3.0682 -8.7573 
4 6712.4 6161.5 5.0086 7258 653.54 3.3114 -7.4077 
5 5039.6 6078.9 5.4456 5715.2 833.8 2.6497 -8.4926 
6 6166.2 5984.6 4.9920 6664.5 521.65 2.8072 -5.4465 
7 6096 4478.6 5.2380 5017.9 744.24 2.6360 -5.476 
8 5984.4 6343.7 6.0000 6186.1 729.51 2.7197 -7.1382 
9 4483.4 4998.1 4.9762 6100 710.35 3.3486 -8.5426 
10 6347.6 5398.5 5.6375 6006.7 405.6 2.6160 -8.0268 
11 5003.5 5816.1 5.9903 4489.1 773.96 2.9143 -5.6308 
12 5395.8 4080.1 5.7619 6352.7 512.41 3.3299 -8.4685 
13 5804 4586.6 4.7149 4963.6 596.07 2.9856 -6.0663 
14 4084.8 4056 6.3464 5395.2 676.07 2.3959 -7.6293 
15 4591.2 4298.1 5.9175 5837.1 330.43 3.4717 -8.8063 
16 4071.1 5882.9 4.6899 4195.7 431.82 3.2197 -6.018 
17 4312.5 3986.6 6.5623 4585.8 328.73 2.3635 -4.6686 
18 5887.7 4981.3 5.5315 4172.6 371.58 3.5901 -6.7922 
19 3997.5 5842.8 5.7451 4359.4 692.74 2.8522 -5.715 
20 4964.8 5254.5 5.5465 5916.5 318.51 2.9747 -7.4927 
21 5841.3 3352.8 5.9978 4126.1 509.22 2.8589 -6.3092 
22 5249.8 6267.7 5.9360 4951.4 684.76 3.3399 -6.3854 
23 3350.7 5629.4 5.3838 5874.4 563.37 3.2550 -6.4937 
24 6266.9 3265 6.1931 5239 211.99 2.7812 -8.015 
25 5614 6838 5.8089 3793.7 761.1 3.4056 -6.1406 
26 3268.8 4754.3 5.6274 6280.4 639.2 3.0266 -7.5392 
27 6830 5203.4 6.5441 5626 203.9 2.9089 -7.1142 
28 4752.1 4769.3 6.6739 3767.1 847.86 3.5824 -6.6703 
29 5208.6 5863.3 5.2765 6755.6 461.44 3.6609 -8.3015 
30 4760.6 5676.8 6.5011 4739.6 556.39 2.7344 -7.9093

MDL-NBS-HS-000021, REV 00 I-23 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
31 5868 4504.5 6.4728 5197.2 466.35 3.5520 -8.3327 
32 5686.4 6049.8 5.9494 4743.8 688.99 3.5412 -8.1408 
33 4496.5 5340.1 4.9233 5883.1 651.93 3.2668 -6.5819 
34 6054.1 4946 6.9605 5687.4 411.96 2.5760 -8.3777 
35 5335.9 6784.5 5.8382 4503.1 720.52 3.9447 -7.556 
36 4954.1 7395.9 6.6776 6060.6 582.95 3.0918 -6.6373 
37 6768.2 4367.7 5.9759 5335 502.03 3.6629 -7.2777 
38 7399.6 6606.1 6.6522 4938.2 839.43 3.3045 -8.7023 
39 4349 6544.1 5.9085 6713.1 916.61 3.6457 -6.2199 
40 6613.4 5717.4 6.3962 7092.6 383.48 3.2028 -6.8793 
41 6556 3873.3 6.5717 4394.2 818.98 3.4953 -8.7381 
42 5719.5 8732.1 6.1461 6584.6 808.27 3.5966 -5.5862 
43 3858.1 5413.4 5.8195 6537.3 660.06 3.3930 -7.7721 
44 8721.8 7419.7 6.3075 5735 294.01 3.0345 -7.3063 
45 5413.9 5800.7 5.5809 4050.8 991.22 3.4557 -7.745 
46 7437.8 7226.2 5.9859 7456.3 598.1 2.8849 -6.6174 
47 5796.5 5589.3 6.6128 5412.2 919.06 3.3241 -6.8126 
48 7243.6 6357.7 4.6388 7113.4 672.8 3.6195 -7.9985 
49 5589.2 6861.8 6.4183 5814 899.64 2.3345 -6.4285 
50 6364.8 6003.9 6.5159 7016.9 634.71 3.5066 -7.1708 
51 6866 5353.2 5.7348 5591.9 777.9 3.5638 -7.5752 
52 6008.3 6205.2 6.5366 6368.3 852.87 2.9709 -5.6643 
53 5358 4858.7 5.4150 6771.1 712.71 3.5795 -5.0276 
54 6218.9 5834.7 5.5775 6020.5 586.49 2.7970 -8.1064 
55 4843 7046.9 5.2695 5349.7 750.31 2.8776 -5.8657 
56 5831.9 3132.8 5.9717 6230.5 484.63 2.7310 -5.9515 
57 7035.9 6410 4.6104 4835.7 681.99 3.2964 -6.7658 
58 3173.9 6675 4.8343 5843.3 873.87 2.3122 -8.4411 
59 6397.3 5193.9 5.7110 6889.5 194.82 2.4968 -4.1002 
60 6670.5 6733.1 6.6972 3735.9 784.86 2.9609 -7.0941 
61 5191.2 4558.9 6.6712 6400 825.8 3.6766 -4.9691 
62 6755 4836.8 5.1367 6624.1 550.47 3.6582 -6.6998

MDL-NBS-HS-000021, REV 00 I-24 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
63 4559.2 4322.6 6.6454 5174.8 836.11 2.6876 -5.161 
64 4826 5767.5 6.2577 6690.1 421.28 3.6429 -6.9188 
65 4342.6 3093.2 4.3501 4540.6 477.44 3.4355 -6.1259 
66 5774 3650.4 5.3404 4806.1 378.03 2.1519 -5.5367 
67 3112.8 5143.1 4.7901 4379.9 668.9 2.7602 -6.4733 
68 3652.9 7554.3 5.4249 5797.2 186.91 2.4561 -7.1524 
69 5141.2 7336 5.9355 3717.8 260.88 2.8035 -6.2729 
70 7565.7 4199.1 5.7202 3931.1 545.33 3.2382 -7.6777 
71 7361.4 7210.9 5.9101 5128.2 931.75 2.9685 -6.6509 
72 4211.5 6137.8 6.0374 7176.3 911.36 3.2124 -5.3511 
73 7212.3 2536.1 6.8306 7063.8 351.33 3.3517 -8.7724 
74 6144.2 4428.3 6.6335 4262.8 896.71 3.6989 -6.0952 
75 2583 3502.6 4.8833 6998.7 739.45 3.6343 -5.7992 
76 4435.6 4576.3 6.6053 6177.4 142.3 2.5393 -7.3313 
77 3519.2 5666.3 6.3674 1630.1 399.64 3.6162 -5.6828 
78 4580.1 5162 6.5966 4446.5 241.47 3.4880 -7.9519 
79 5656.1 5596.2 6.9741 3863.3 426.23 3.6116 -7.6875 
80 5172.4 5914 4.2386 4561.9 647.46 3.9614 -8.1309 
81 5609.8 7944.5 6.1038 5665.9 550.07 2.0951 -6.7135 
82 5912.4 7132.6 4.7531 5155 634.96 3.3796 -8.7844 
83 7914.7 3773.6 5.4065 5601.3 697.02 2.4256 -8.5657 
84 7132.3 7012.5 6.4456 5928.7 955.7 2.7860 -7.3649 
85 3753.5 6324.4 4.1847 7282.4 885.57 3.5229 -4.8334 
86 6986.5 6980.9 6.7505 6948.9 276.95 2.0594 -5.0489 
87 6306.8 8979.8 5.5658 3996.8 872.71 3.6879 -8.2303 
88 6979.8 2198.1 4.4545 6867.5 769.22 2.8735 -5.1937 
89 9020.7 5962.9 5.4814 6321.5 868.01 2.2234 -6.3262 
90 2223.7 3419.5 4.8231 6843.4 995.38 2.8308 -8.9159 
91 5959.5 4534.1 5.8457 7477.5 122.28 2.4814 -8.049 
92 3435.1 6465.6 6.5752 843.23 707.86 3.1066 -8.6293 
93 4518.4 1938.8 5.1959 5997.2 226.24 3.6012 -7.9308 
94 6479.5 7749.4 6.6201 3826.2 418.09 2.7010 -6.8351

MDL-NBS-HS-000021, REV 00 I-25 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
95 1944.9 4815.2 4.4834 4532.5 794.98 3.6242 -7.3558 
96 7738.3 2757.9 5.8567 6475 116.33 2.2479 -6.8801 
97 4813.7 4650.8 6.6405 806.35 943.93 3.1094 -6.5674 
98 2752.3 3626 4.9596 7234.3 474.28 3.6371 -4.579 
99 4668.5 5430.8 4.9532 4783 156.07 2.6025 -5.2514 
100 3590.2 6886.2 4.5261 2517 445.26 2.5987 -8.5003 
101 5437.2 4246.3 6.4871 4659 253.85 2.2623 -5.3798 
102 6878.3 7050 4.8636 3907.8 602.23 3.5479 -6.1694 
103 4242.2 2836.9 5.8808 5432.1 855.89 2.5293 -5.4229 
104 7071.8 5458.1 5.5038 6785.3 365.43 3.1555 -3.9017 
105 2849 7165.5 6.7372 4317.5 879.29 2.8449 -8.9485 
106 5452 3968.1 6.8082 6918.2 161.11 3.6822 -6.5045 
107 7180.6 3947.5 6.8733 2847.2 607.45 3.6947 -8.6754 
108 3975.9 2963 6.9243 5458 889.84 3.7506 -7.9714 
109 3949.9 6585 4.9802 6969.8 310.82 3.8465 -6.0296 
110 2961.6 3722.4 5.4942 4106.8 306.56 2.6266 -8.9706 
111 6583.9 5508.2 5.5563 4097.8 167.18 2.8365 -4.7113 
112 3744.8 4713.2 5.5211 3160.9 815.33 2.8642 -7.7037 
113 5502.7 7651.4 5.6117 6571.9 271.76 2.8499 -8.8791 
114 4707.5 7827.8 6.4298 3976.7 619.25 2.9020 -7.8504 
115 7668.2 8061.2 5.6812 5508.9 451.04 3.5209 -8.5921 
116 7875.1 8371.1 6.6551 4689.3 937.03 2.9405 -7.0702 
117 8054.6 4033.3 6.6920 7214.6 952.66 3.6481 -5.5235 
118 8382.8 4674.7 5.9025 7266.2 965.4 3.6725 -8.1812 
119 4032.2 4794.8 5.4548 7329.4 975.16 3.1876 -5.3301 
120 4682.7 4727.1 4.3159 7382.2 320.43 2.8162 -8.8483 
121 4789.7 4923.1 6.6857 4150.1 446.62 2.1361 -7.0482 
122 4733.6 6446.1 6.5263 4664.8 470.86 3.6683 -5.226 
123 4918.3 5066.3 6.0719 4768.9 456.71 3.5702 -8.3913 
124 6457.4 7265.2 5.7917 4718.2 493.65 3.3600 -8.4006 
125 5073.8 7501.7 5.7853 4895.3 792.72 2.9976 -8.8265 
126 7269 5566.2 6.7024 6440.7 527.66 2.9937 -5.8902

MDL-NBS-HS-000021, REV 00 I-26 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
127 7503.6 4620.7 4.7329 5055.9 902.78 3.6804 -8.5362 
128 5573.1 2382.2 6.9325 7040 928.67 2.4095 -6.9813 
129 4622.1 7497.1 6.6599 7141.5 629.98 3.8979 -7.8073 
130 2420.4 6694.9 6.2405 5575.8 435.71 3.6530 -4.7451 
131 7457.5 5934.5 5.1173 4611.9 127.29 3.4250 -4.6212 
132 6679.9 5310 6.1987 1210.9 924.13 2.6807 -4.4973 
133 5936.4 5289 5.0374 7129.5 830.59 3.4087 -4.3664 
134 5304.7 7600.3 6.8506 6653.7 698.01 2.6538 -8.3547 
135 5285.5 3394.1 4.9341 5942.9 575.88 3.7269 -7.8364 
136 7609.5 8528.2 6.4669 5294.8 572.62 2.5810 -7.7319 
137 3398.2 7310.8 4.7676 5273.1 934.01 3.5342 -7.7884 
138 8495.8 6104.3 5.3160 7196.6 220.56 2.4374 -7.6139 
139 7329.9 4160.2 6.4786 3800.3 981.25 2.7538 -6.0479 
140 6102.7 6062.9 5.4698 7409.7 907.73 3.5430 -7.4548 
141 4166.5 4117.4 6.2900 7052.7 733.62 2.8222 -5.1313 
142 6062 7991.4 5.9253 6133.5 349.23 3.4512 -4.9116 
143 4131.1 3906.2 5.9633 4248.9 726.94 3.2263 -6.9204 
144 8021.9 6524.3 5.2175 6094.7 336.27 3.2910 -7.891 
145 3903.4 3468.8 5.7076 4211.3 960.78 2.7132 -8.9265 
146 6511.8 4418.7 6.9969 7302.3 300.53 2.9582 -4.9539 
147 3457.3 6579.8 5.7505 4060.9 803.03 3.9972 -5.7348 
148 4404.6 4630.4 5.2945 6516.3 232.94 2.9797 -6.5489 
149 6571.7 6183.3 6.6243 3847.7 394.75 2.7420 -7.2133 
150 4650.1 5637.9 6.3304 4437.2 809.21 3.6309 -7.225 
151 6185.5 5757.9 4.0403 6552.9 439.43 3.4709 -4.7824 
152 5645.3 4276.8 6.2553 4633.2 747.16 2.0382 -8.6861 
153 5748.4 5137.6 6.5065 6203.2 644.24 3.4298 -4.3303 
154 4277.4 9300.6 5.1614 5653.3 668.14 3.5591 -5.0869 
155 5131 5222.6 5.6857 5764.9 369.36 2.6922 -6.3617 
156 9534.9 4376.2 6.3997 4330.4 540.59 2.9465 -8.2544 
157 5223.8 7111.8 6.3160 5103.9 998.61 3.5045 -6.4036 
158 4371.9 6245.4 6.9528 7495.5 559.62 3.4647 -8.2975

MDL-NBS-HS-000021, REV 00 I-27 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
159 7107.4 1511.6 5.8035 5212.8 387.34 3.9291 -4.5372 
160 6262.1 6123.3 5.8876 4412.8 884.11 3.0123 -8.4216 
161 1345 6652.3 5.8745 6936.4 759.54 3.1609 -5.9679 
162 6117.2 4216 5.8954 6265.1 106.16 3.1339 -8.6561 
163 6648.8 5090.8 5.9552 141.74 737.64 3.1759 -8.0717 
164 4235.5 6390.9 6.1584 6148.5 821.88 3.2811 -5.909 
165 5089.3 6227.3 5.0969 6608.2 357.82 3.3966 -7.878 
166 6385.7 8608 5.8603 4287.7 532.58 2.6703 -6.2949 
167 6223.2 5321.4 5.5933 5062.6 781.14 3.1305 -6.8452 
168 8546.8 5534.4 4.8125 6381.6 755.11 2.8881 -6.7339 
169 5319.2 5483.1 4.4143 6249.8 983.03 2.4729 -8.1665 
170 5521.6 5542.5 6.3617 7434.5 580.56 2.1921 -7.3829 
171 5495.8 5731.1 6.0755 5315.5 622.03 3.4794 -3.6765 
172 5549.6 6033.4 5.6232 5524.1 613.79 3.3727 -7.2856 
173 5727.9 4140 5.7782 5490.6 623.75 2.9066 -8.0952 
174 6023.7 5477.9 5.6590 5551.3 664.5 2.9908 -5.2724 
175 4148.4 4872.6 5.6693 5750.9 719.54 2.9265 -6.2288 
176 5479.6 3549.9 6.8814 6054.3 343.37 2.9380 -8.9859 
177 4879.1 2624.6 6.9058 4235.9 608.71 3.8063 -6.3475 
178 3562.2 6292.3 4.6491 5471.9 488.67 3.8289 -5.8284 
179 2691.1 5944.7 5.6981 4848.9 248.32 2.3548 -8.2179 
180 6293.7 4927.5 4.8968 3891 150.62 2.9539 -7.4396 
181 5941.6 5265.2 6.5944 2083 766.1 2.5494 -6.1073 
182 4940.1 5004.8 6.5843 6317.7 701.74 3.6094 -6.2584 
183 5261.6 5043.6 5.8215 5961.4 497.44 3.6051 -4.1654 
184 5020.3 8191.8 4.8495 4914.6 568.89 3.0603 -7.1812 
185 5060.4 8242.6 5.3579 5258.4 517.51 2.5082 -6.9617 
186 8136.4 3206.1 6.5563 4998.6 522.73 2.7668 -7.0139 
187 8289.8 5112.5 4.9119 5032.3 967.88 3.5857 -6.9487 
188 3212.5 3783.9 6.4232 7341.4 972.79 2.5597 -6.7548 
189 5101.7 6943.9 5.6010 7371 199 3.5129 -6.4514 
190 3797.2 6920.3 4.5707 3740.7 535.96 2.8922 -8.267

MDL-NBS-HS-000021, REV 00 I-28 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
191 6929.3 5377.6 6.4533 5083.1 283.4 2.2913 -7.0285 
192 6916.6 3672.1 6.7846 4020 863.42 3.5281 -7.651 
193 5384 4451.3 5.9450 6825.5 861.69 3.6906 -8.615 
194 3694.1 6790.8 6.5366 6810.5 590.15 3.2638 -8.8951 
195 4459 3827.5 5.6646 5375.4 262.72 3.5723 -6.1974 
196 6789.6 6419 6.2765 3949.1 403.04 2.9325 -6.5318 
197 3839.3 4891.3 6.2175 4465.3 844.46 3.4436 -7.5985 
198 6419.4 3017.7 6.1335 6728.3 285.99 3.4185 -7.2599 
199 4889 6501.1 5.3766 4030.4 788.24 3.3858 -7.5095 
200 3037 7780.9 6.3784 6433.3 489.71 2.7745 -7.4663

MDL-NBS-HS-000021, REV 00 I-28 July, 2003 
real. # KD_AM_VO KD_AM_AL KD_AM_COL KD_CS_VO KD_CS_AL KD_CS_COL CONC_COL 
191 6929.3 5377.6 6.4533 5083.1 283.4 2.2913 -7.0285 
192 6916.6 3672.1 6.7846 4020 863.42 3.5281 -7.651 
193 5384 4451.3 5.9450 6825.5 861.69 3.6906 -8.615 
194 3694.1 6790.8 6.5366 6810.5 590.15 3.2638 -8.8951 
195 4459 3827.5 5.6646 5375.4 262.72 3.5723 -6.1974 
196 6789.6 6419 6.2765 3949.1 403.04 2.9325 -6.5318 
197 3839.3 4891.3 6.2175 4465.3 844.46 3.4436 -7.5985 
198 6419.4 3017.7 6.1335 6728.3 285.99 3.4185 -7.2599 
199 4889 6501.1 5.3766 4030.4 788.24 3.3858 -7.5095 
200 3037 7780.9 6.3784 6433.3 489.71 2.7745 -7.4663