Unsaturated Zone Flow Patterns and Analysis Rev 00, ICN 00

MDL-NBS-HS-000012

October 2001

1. PURPOSE 
This Analysis/Model Report (AMR) documents the development of an expected-case model for 
unsaturated zone (UZ) flow and transport that will be described in terms of the 
representativeness of models of the natural system. The expected-case model will provide an 
evaluation of the effectiveness of the natural barriers, assess the impact of conservatism in the 
Total System Performance Assessment (TSPA), and support the development of further models 
and analyses for public confidence building. The present models used in Total System 
Performance Assessment for the Site Recommendation (Civilian Radioactive Waste Management 
System Management and Operating Contractor (CRWMS M&O) 2000 [153246]) underestimate 
the natural-barrier performance because of conservative assumptions and parameters and do not 
adequately address uncertainty and alternative models. The development of an expected case 
model for the UZ natural barrier addresses issues regarding flow-pattern analysis and modeling 
that had previously been treated conservatively. This is in line with the Repository Safety 
Strategy (RSS) philosophy of treating conservatively those aspects of the UZ flow and transport 
system that are not important for achieving regulatory dose (CRWMS M&O 2000 [153246], 
Section 1.1.1). The development of an expected case model for the UZ also provides defense-indepth 
in areas requiring further analysis of uncertainty and alternative models. In general, the 
value of the conservative case is to provide a more easily defensible TSPA for behavior of UZ 
flow and transport processes at Yucca Mountain. This AMR has been prepared in accordance 
with the Technical Work Plan for Unsaturated Zone (UZ) Flow and Transport Process Model 
Report (Bechtel SAIC Company (BSC) 2001 [155051], Section 1.3  Work Package 
4301213UMG). The work scope is to examine the data and current models of flow and transport 
in the Yucca Mountain UZ to identify models and analyses where conservatism may be reduced 
and uncertainty may be better characterized either through new analyses or development of new, 
alternative, models. This AMR supports Site Recommendation (SR) activities by documenting 
analyses and models reported in FY01 Supplemental Science and Performance Analyses, Volume 
1: Scientific Bases and Analyses (BSC 2001 [155950]). However, except for the model results 
reported in Section 6.4.2, this AMR does not support TSPA as documented in either FY01 
Supplemental Science and Performance Analyses, Volume 2: Performance Analyses (BSC 2001 
[154659]) or Total System Performance Assessment for the Site Recommendation (CRWMS 
M&O 2000 [153246]). Furthermore, this AMR represents scoping studies to aid in determining 
whether work beyond the scope of the models and analyses used to support TSPA-SR (CRWMS 
M&O 2000 [153246]) is warranted. If the decision is made to use any of these models and 
analyses for TSPA for License Application, further verification and validation will be required. 
The model results reported in Section 6.4.2 are used for TSPA sensitivity studies as documented 
in FY01 Supplemental Science and Performance Analyses, Volume 2: Performance Analyses 
(BSC 2001 [154659], Section 3.2.2.3). 
The following topics are addressed for development of an expected case: 
(1) Synthesis of geochemical information (Section 6.2) 
(2) Comparison of different transport codes (Section 6.3.1) 
(3) Effects of matrix block discretization on flow and transport (Section 6.3.2)

  
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(4) Effects of drift degradation, including rock fall and rock bolts, on drift seepage (Section 
6.4.1) 
(5) Effects of flow focusing on drift seepage (Section 6.4.2) 
(6) Percolation redistribution in the Paintbrush nonwelded (PTn) unit (Section 6.4.3) 
(7) Effects of episodic flow on drift seepage (Section 6.4.4) 
(8) Flow in the vitric portion of the Calico Hills Formation (Section 6.5.1) 
(9) Fault properties in the Calico Hills (Section 6.5.2) 
(10) Perched water models and lateral diversion (Section 6.5.3) 
(11) Effects of radionuclide release into the rock matrix (Section 6.5.4) 
In order to address topics 4, 5, 7, and 8, new models are developed and validated in this AMR. 
Caveats and Limitations 
The analyses and models documented here are limited in scope as documented in individual 
subsections of Section 6. Extension of the results of these analyses and models beyond the scope 
within which they are performed may lead to erroneous conclusions. For example, many of the 
models documented here are numerical in nature such that the results must be interpreted and 
used only after careful consideration of the conceptual model and model parameters (e.g., time 
step size, mesh discretization, and equivalent hydrologic properties).

  
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2. QUALITY ASSURANCE 
The activities documented in this AMR were evaluated under Administrative Procedure (AP)- 
2.21Q, Quality Determinations and Planning for Scientific, Engineering, and Regulatory 
Compliance Activities, and were determined to be subject to the requirements of the United 
States Department of Energy (U.S. DOE) Office of Civilian Radioactive Waste Management 
(OCRWM) Quality Assurance Requirements and Description (QARD) (DOE 2000 [149540]). 
This evaluation is documented in Technical Work Plan for Unsaturated Zone (UZ) Flow and 
Transport Process Model Report (BSC 2001 [155051], Attachment 1, Work Package 
4301213UMG). Electronic management of information was evaluated in accordance with APSV.
1Q, Control of the Electronic Management of Information, and controlled under YMPLBNL-
QIP-SV.0, Management of YMP-LBNL Electronic Data. This evaluation is documented 
in the Technical Work Plan (TWP) (BSC 2001 [155051], Attachment 2, Work Package 
4301213UMG). 
This AMR reports on natural barriers (the Tiva Canyon Welded, Paintbrush Nonwelded, 
Topopah Springs Welded, and Calico Hills Nonwelded Hydrogeologic Units) that have been 
included in the Q-List (YMP 2000 [149733]) as items important to waste isolation. The AMR 
contributes to the analyses and modeling data used to support performance assessment. The 
conclusions of this AMR do not affect the repository design or permanent items as discussed in 
QAP-2-3, Classification of Permanent Items. 
The modeling activities documented in this AMR were conducted in accordance with the quality 
assurance program of the Yucca Mountain Site Characterization Project (YMP) using OCRWM 
APs and YMP Quality Implementing Procedures (QIPs) for the Lawrence Berkeley National 
Laboratory (LBNL) as identified in the TWP (BSC 2001 [155051], Table 6-1).

  
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3. COMPUTER SOFTWARE AND MODEL USAGE 
The software used in this study is listed in Table 3-1. All qualified software was obtained from 
Software Configuration Management (SCM), in accordance with AP-3.10Q, Analyses and 
Models, Attachment 1, Section 3, and is appropriate for its intended use, and was used only 
within the range of validation in accordance with AP-SI.1Q, Software Management. 
Table 3-1. Computer Software and Routines 
Software Name and Version Software Tracking Number 
(STN) 
DIRS Ref. 
Number 
Platform and Operating 
System (See Notes) 
DCPT V1.0 10078-1.0-00 132448 3 
DCPT V2.0 10078-2.0-00 (unqualified) 154342 3 
EARTHVISION V5.1 10174-5.1-00 152614 4 
GSLIB V1.0MSISIMV1.203 10001-1.0MSISIMV1.203-00 134136 1 
GSLIB V2.0MSISIMV2.0 10098-2.0MSISIMV2.0-00 154340 1 
infil2grid V1.6 10077-1.6-01 134754 1 
iTOUGH2 V4.0 10003-4.0-00 139918 1 and 2 
ITOUGH2 V3.2 10054-3.2-00 154337 1 
ITOUGH2 V3.2_drift 10055-3.2_DRIFT-00 112757 1 
T2R3D V1.4 10006-1.4-00 113942 1 and 2 
TOUGH2 V1.4 10007-1.4-01 146496 1 and 2 
TOUGH2 V1.5 10007-1.5-00 (unqualified) 154322 1 and 2 
Wingridder V1.1 10024-1.1-00 154341 3 
WINGRIDDER V2.0 10024-2.0-00 (unqualified) 154785 3 
AddBound V1.0 10357-1.0-00 152823 1 
AssignRock V1.0 10465-1.0-00 154321 1 
bot_sum.f V1.0 10349-1.0-00 153471 2 
CalBT.for V1.0 10504-1.0-00 154788 3 
CutNiche V1.3 10402-1.3-00 152828 1 
mddf.f V2.0 10456-2.0-00 154347 1 
meshbd.f V1.0 10467-1.0-00 152871 1 
MINCgridv1.f V1.0 10469-1.0-00 154343 2 
mininipresf.f 1.0 10470-1.0-00 152872 1 
minrefine3df.f V1.0 10472-1.0-00 152880 1 
mk_generGL.f V1.0 10476-1.0-00 154349 1 
MoveMesh V1.0 10358-1.0-00 152824 1 
parallelf.java V1.0 10457-1.0-00 154346 3 
Perm2Mesh V1.0 10359-1.0-00 152826 1 
RoutineRick1 V1.1 10474-1.1-00 156137 1 
vf_con.for V1.0 10466-1.0-00 154345 3 
Notes: Platform with Operating System 
1. SUN UltraSparc with Unix OS 
2. DEC-Alpha with Unix OS 
3. PC with MS Windows 
4. SGI with Unix OS 
The use of all codes identified in Table 3-1 is documented in Section 6 and in the supporting 
scientific notebooks identified in Section 6. The unqualified software codes, DCPT V2.0 (LBNL 
2001 [154342]), TOUGH2 V1.5 (LBNL 2001 [154322]) and WINGRIDDER V2.0 (LBNL 2001 
[154785]), were obtained from SCM in accordance with AP-3.10Q, Attachment 1, Section 3. 
These codes have been submitted to SCM to meet the Interim Use of Unqualified Software to 
support Site Recommendation (SR) products in accordance with Section 5.10, AP-SI1.1Q,

  
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Software Management.. For each of these three codes, a Software Activity Plan for use of 
unqualified software, a Software User Request, and a copy of the code have been submitted to 
SCM to meet the Interim Use of Unqualified Software requirements of AP-SI.1Q. 
Tecplot V7.0 and Microsoft Excel 2000 SR-1 were used to plot data generated by simulations 
documented within this AMR and the references specified. Several computations were 
performed using commercial off-the-shelf software and are exempt from AP-SI.1Q. All 
information needed to reproduce the work is included in this AMR and the references specified. 
Results generated using FEHM V2.0 (CRWMS M&O 2000 [141418]) are cited in Sections 6.3.1 
and 7.3.1 and are documented in CRWMS M&O (2000 [134732]). As such, FEHM V2.0 is not 
included in the list of software used. 
The following studies, documented in this AMR, use previously developed and validated 
models: 
1. The analysis of the impact of rock fall on seepage (Section 6.4.1.1) uses models 
documented in Seepage Model for PA Including Drift Collapse (CRWMS M&O 2000 
[153314]; DTN: LB0011SMDCREV1.002 [153570]) and Drift Degradation Analysis 
(CRWMS M&O 2000 [151635]; DTN: MO0109RDDAAMRR.003 [156306]) 
2. The analysis of percolation redistribution in the PTn (Section 6.4.3) uses models 
documented in UZ Flow Models and Submodels (CRWMS M&O 2000 [122797]; 
DTNs: LB991131233129.003 [147119], LB990701233129.002 [125604], 
LB990801233129.022 [156331]) and Calibrated Properties Model (CRWMS M&O 
2000 [144426]; DTN: LB997141233129.001 [104055]). 
3. The model of transient percolation used to evaluate the impact on seepage (Section 
6.4.4) is based, in part, on previously developed and validated models documented in 
UZ Flow Models and Submodels (CRWMS M&O 2000 [122797]) and DTN: 
MO9901MWDGFM31.000 [103769]. (Note that the TDMS now shows DTN: 
MO9901MWDGFM31.000 [103769] to be superseded by DTN: 
MO0012MWDGFM02.002 [153777], however, the new DTN does not include the data 
used for development of this analysis. The comment section on the Technical Data 
Information Form for the more recent DTN also contains the statement, GFM2000 
does not invalidate GFM3.1. Changes to rock layer elevations in the repository area are 
very small in magnitude; rarely as large as 25 feet. Because a variance of 25 feet is 
less than the uncertainty in the depths for stratigraphic layers as reported in Geologic 
Framework Model Analysis Model Report (BSC 2001 [154622], Section 7), this AMR 
maintains the use of the original DTN.) 
4. The model of an unfractured vitric Calico Hills used to evaluate the impact on flow and 
transport (Section 6.5.1) is based, in part, on previously developed and validated 
models documented in Calibrated Properties Model (CRWMS M&O 2000 [144426]) 
and UZ Flow Models and Submodels (CRWMS M&O 2000 [122797]). 
5. The analysis of uncertainty regarding perched water representations (Section 6.5.2) 
uses the model documented in UZ Flow Models and Submodels (CRWMS M&O 2000

  
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[122797]; DTNs: LB990801233129.003 [122757], LB990701233129.001 [106785], 
LB991121233129.001 [147328], LB991121233129.002 [147334]) and the model 
documented in Section 6.5.1 (DTN: LB0103CHVUPROP.001). 
6. The analysis of uncertainty regarding fault properties below the Topopah Spring 
welded hydrogeological unit (Section 6.5.3) uses the model documented in UZ Flow 
Models and Submodels (CRWMS M&O 2000 [122797]; DTNs: LB990701233129.001 
[106785], LB990801233129.003 [122757]). 
7. The analysis of the impact of radionuclide release to the rock matrix (Section 6.5.4) 
uses the model documented in UZ Flow Models and Submodels (CRWMS M&O 2000 
[122797]) which is subsequently modified as documented in Section 6.5.3 (DTN: 
LB0104AMRU0185.009). 
Data developed with these models and analyses and input and output files for the models and 
analyses are submitted and listed under the DTNs listed in Section 8.4.

  
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4. INPUTS 
This section provides documentation for data used as input to this AMR. The Q-status of all 
inputs and a description of the data are shown in the Document Input Reference System (DIRS) 
database. The inputs to the models were obtained from the Technical Data Management System 
(TDMS). Acquired and developed data used to characterize the seepage conditions in the models 
are discussed below. 
4.1 DATA AND PARAMETERS 
Table 4-1. Input Data Used 
Inputs Section 
Used In 
Description of Data Used 
LB0110MESHPROP.001 [156336] 
LB990701233129.001 [106785] 
LB990801233129.003 [122757] 
6.3.1 These UZ model grid and flow simulation data are the 
most appropriate for use as input to the analysis 
presented in Section 6.3.1. 
GS000399991221.002 [147022] 
LB990501233129.001 [106787] 
LB997141233129.001 [104055] 
6.3.2 These fracture geometry, calibrated properties, and 
infiltration data are the most appropriate for use as input 
to the analysis presented in Section 6.3.2. 
LB0010SCMREV01.002 [153393] 
LB0011SMDCREV1.001 [153574] 
LB0011SMDCREV1.002 [153570] 
LB997141233129.001 [104055] 
MO0109RDDAAMRR.003 [156306] 
6.4.1.1 These seepage mode, calibrated properties, and drift 
degradation data are the most appropriate for use as 
input to the analysis presented in Section 6.4.1.1. 
BSC 2001 [155187], Section 
6.5.1.2.2 
BSC 2001 [155187], 
Table 4-10 
CRWMS M&O 2000 [153314], 
Section 6.3 
LB0010SCMREV01.002 [153393] 
6.4.1.2 These rock bolt and model parameter data are the most 
appropriate for use as input to the model presented in 
Section 6.4.1.2. 
LB00090012213U.001 [153141] 
LB0012AIRKTEST.001 [154586] 
LB002181233124.001 [146878] 
LB990901233124.004 [123273] 
LB991121233129.001 [147328] 
6.4.2 These model parameter and air permeability data are 
the most appropriate for use as input to the model 
presented in Section 6.4.2. 
GS000399991221.002 [147022] 
GS950608312272.001 [145617] * 
GS990208312272.001 [146134] 
LA0002JF12213U.002 [156281] 
6.4.3 These UZ model and chloride data are the most 
appropriate for use as input to the analysis presented in 
Section 6.4.3.

  
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Inputs Section 
Used In 
Description of Data Used 
LA9909JF831222.004 [145598] 
LB990701233129.002 [125604] 
LB990801233129.022 [156331] 
LB991131233129.003 [147119] 
LB997141233129.001 [104055] 
CRWMS M&O 2000 [114277], 
Table III-1 
LB991091233129.004 [126111] 
LB997141233129.001 [104055] 
MO9901MWDGFM31.000 [103769] 
6.4.4 These model parameter and geologic model data are 
the most appropriate for use as input to the model 
presented in Section 6.4.4. 
GS990308312242.007 [107185] 
GS990708312242.008 [109822] 
LB990501233129.001 [106787] 
LB991091233129.001 [125868] 
6.5.1 These uncalibrated properties, Calibrated Properties 
Model, and Busted Butte data are the most appropriate 
for use as input to the model presented in Section 6.5.1. 
LB990701233129.001 [106785] 
LB990801233129.003 [122757] 
6.5.2 These three-dimensional, UZ-flow-model data are the 
most appropriate for use as input to the analysis 
presented in Section 6.5.2. 
GS950608312272.001 [145617] * 
GS960308312312.005 [107230] 
GS970208312312.003 [119786] 
GS980508312313.001 [109746] 
GS980708312242.010 [106752] 
GS980808312242.014 [106748] 
GS990208312272.001 [146134] 
LA9909JF831222.004 [145598] 
LB990701233129.001 [106785] 
LB990801233129.003 [122757] 
LB990801233129.004 [117129] 
LB990801233129.019 [144659] 
LB9908T1233129.001 [147115] 
LB991121233129.001 [147328] 
LB991121233129.002 [147334] 
MO0109HYMXPROP.001 [155989] 
6.5.3 These UZ model, perched water, saturation and water 
potential, chloride, and diffusion data are the most 
appropriate for use as input to the analysis presented in 
Section 6.5.3. 
* Chloride abundance data from UE-25 UZ#16 were used from the DTN: GS950608312272.001 [145617]. This 
DTN has been superceded by DTN: GS010708312272.002 [156375]. The chloride abundance data from 
UE-25 UZ#16 have remained unchanged.

  
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4.2 CRITERIA 
This AMR complies with the DOE interim guidance (Dyer 1999 [105655]). Subparts of the 
interim guidance that apply to this analysis or modeling activity are those pertaining to the 
characterization of the Yucca Mountain Site (Subpart B, Section 15). The compilation of 
information regarding geology of the site is in support of the License Application (Subpart B, 
Section 21(c)(1)(ii), and the definition of geologic parameters and the conceptual model used in 
the performance assessment (Subpart E, Section 114(a)). The compilation of information 
regarding hydrology of the site is in support of the License Application (Subpart B, Section 
21(c)(1)(ii)), and the definition of hydrologic parameters and conceptual models used in 
performance assessment (Subpart E, Section 114(a)). The compilation of information regarding 
geochemistry and mineral stability of the site is in support of the License Application (Subpart B, 
Section 21(c)(1)(ii)); and the definition of geochemical parameters and conceptual models used 
in performance assessment (Subpart E, Section 114(a)). 
The Nuclear Regulatory Commission (NRC) Issue Resolution Status Report Key Technical 
Issue: Unsaturated and Saturated Flow under Isothermal Conditions (NRC 1999 [140371], 
subissues 4 and 6) establishes the technical acceptance review criteria that the NRC staff will use 
in their review of DOEs submittals describing deep percolation (Subissue 4) and matrix 
diffusion (Subissue 6). Additionally, the NRC Issue Resolution Status Report Key Technical 
Issue: Radionuclide Transport (NRC 2000 [153313], Subissues 1 and 2) establishes technicalacceptance 
review criteria that the NRC staff will use in their review of DOEs submittals 
describing radionuclide transport through porous rock (Subissue 1) and fractured rock (Subissue 
2) in the UZ of the Yucca Mountain. 
4.3 CODES AND STANDARDS 
No specific formally established standards have been identified as applying to this analysis and 
modeling activity.

  
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5. ASSUMPTIONS 
5.1 ASSUMPTIONS FROM PREVIOUS WORK 
The models and analyses presented in this AMR are generally based on previous work and 
represent refinements to the previous work, or sensitivity studies to assess the impact of 
alternative models and/or parameters. As such, most of the assumptions used in this AMR are 
cited or quoted from other AMRs that document the previous work. Quoted assumptions are 
shown indented and italicized. In addition, new assumptions necessary for this AMR are 
documented below in plain text). 
5.2 ASSUMPTIONS SPECIFIC TO THE SYNTHESIS OF GEOCHEMICAL DATA 
Section 6.2 is a review and synthesis of geochemical data. Much of Section 6.2 is based upon 
Analysis of Geochemical Data for the Unsaturated Zone (BSC 2001 [154874]) which invokes 
several assumptions, generally that water-quality data in the TDMS are sufficiently precise, 
accurate, and representative to support conclusions based on analysis of the data. No 
assumptions specific to this AMR are necessary, as no additional analyses of the data are 
documented in this AMR. 
5.3 ASSUMPTIONS SPECIFIC TO COMPUTATIONAL METHODS FOR 
TRANSPORT 
The assumption documented in Section 5.2, quoted below, of Analysis Comparing Advective- 
Dispersive Transport Solution to Particle Tracking (CRWMS M&O 2000 [141389]) is 
applicable to the comparison of transport computational methods documented in Section 6.3. 
These assumptions do not require verification. 
The transport processes included in this analysis are advection, diffusion and 
dispersion, and equilibrium sorption of solutes. Radioactive decay has been 
ignored to facilitate comparisons between the simulation outputs. It is assumed 
that inclusion of radioactive decay would not significantly affect the comparison 
among the methods. This assumption is justified because radioactive decay is 
mathematically simple and is handled identically by all the simulators. 
5.3.1 Assumptions Specific to Comparison of Transport Codes 
The assumption documented in Section 5.3 of Analysis Comparing Advective-Dispersive 
Transport Solution to Particle Tracking (CRWMS M&O 2000 [141389]) is specifically 
applicable to the analyses documented in Section 6.3.1. It does not require verification. 
Section 5.3 of Analysis Comparing Advective-Dispersive Transport Solution to Particle Tracking 
(CRWMS M&O 2000 [141389]) states: 
All standard numerical flow and transport simulators, including those used here, 
rely upon spatial and temporal discretization, and therefore provide spatially and 
temporal approximations of the natural system Also, the methods tested here

  
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use dual-permeability grids It is assumed that the spatial and temporal 
discretizations, and the appropriate use of dual-permeability grids, do not cause 
significant errors and do not distort the comparisons among the methods. This 
assumption is justified by the process of grid development, in which various 
degrees of grid refinement are tested until further refinement yields little 
improvement. 
5.3.2 Assumptions Specific to Matrix Block Discretization and Its Effects on 
Unsaturated Zone Flow and Transport Simulations 
The UZ flow and transport models use dual permeability grids (Doughty 1999 [135997], pp. 74 
79) with each gridblock not further discretized as in a MINC scheme (Pruess and Narasimhan 
1985 [101707], pp. 1426). The question considered in Section 6.3.2 is whether a MINC scheme 
(which greatly increases the computational effort) would be justified. To decide the question, 
both schemes are compared in a two-dimensional model. The assumption that a two-dimensional 
model is adequate for investigation of the mountain-scale effect of different matrix block 
discretization schemes is specifically applicable to the model documented in Section 6.3.2. 
Rationale: The use of a two-dimensional model does not bias the results as long as all model 
parameters, except the matrix block discretization scheme, remain unchanged between the two 
simulations. No further justification or confirmation is required. 
5.4 ASSUMPTIONS SPECIFIC TO PROCESSES AFFECTING SEEPAGE 
There are no general assumptions that cover all of the investigated seepage-affecting processes. 
Assumptions specific to each process are given below. 
5.4.1 Assumptions Specific to Seepage Enhancement Due to Drift Degradation 
The following assumptions quoted from Section 5 of Seepage Model for PA Including Drift 
Collapse (CRWMS M&O 2000 [153314]) are specifically applicable to the models documented 
in Section 6.4.1. These assumptions require no further justification. (The quote below is 
italicized and indented; notes for clarification are inserted as plain text.) 
5.1 Continuum Approach 
Assumption: It is assumed that the continuum approach is a valid concept to 
calculate percolation flux and drift seepage at Yucca Mountain. 
Rationale: The continuum approach can be considered appropriate for seepage 
studies if it is capable of predicting seepage threshold and seepage percentages 
for a drift in a fractured formation. The appropriateness of using the continuum 
approach to simulate flow through fractured rock was studied by Jackson et al. 
(2000 [141523], pp. 189202) using synthetic and actual field data. They 
concluded that heterogeneous continuum representations of fractured media are 
self-consistent, i.e., appropriately estimated effective continuum parameters are 
able to represent the underlying fracture-network characteristics. Furthermore, 
Finsterle (2000 [151875], pp. 20552066) demonstrated that simulating seepage 
into underground openings excavated from a highly fractured formation could be

  
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performed using a model based on the continuum assumption, provided that the 
model is calibrated against seepage-relevant data (such as data from liquidrelease 
tests). Synthetically generated data from a model that exhibits discrete 
flow and seepage behavior were used to calibrate a simplified fracture continuum 
model. Seepage predictions for low percolation fluxes made with the calibrated 
fracture continuum model were consistent with the synthetically generated data 
from the discrete feature model. 
The continuum approach is considered applicable for seepage studies if applied 
within the framework described in this AMR. Inverse modeling should be used for 
the estimation of process-specific, model-related, and scale-dependent 
parameters, and the same or similar conceptual model should be used for the 
subsequent seepage predictions (i.e., the Seepage Model for PA). Under these 
conditions, this assumption does not require confirmation. 
5.2 Unsaturated flow 
Assumption: Adopting the continuum approach, water flow under unsaturated 
conditions is assumed to be governed by Richards equation (Richards 1931 
[104252], pp. 318333). 
Rationale: Richard's equation states that isothermal flow of water in a porous 
medium occurs under the combined effect of gravitational and capillary forces, 
that flow resistance is a function of saturation, and that, for the purposes of this 
representation, movement of the nonwetting air phase can be neglected. This 
general concept is believed reasonable for unsaturated water flow through both 
porous matrix and fractures and does not require confirmation. 
(Note: The general assumption that the Richards/Darcy approach to modeling flow in porous 
media and fractures is valid is well documented in the scientific literature, e.g., de Marsily (1986 
[100439]), Freeze and Cherry (1979 [101173]), and Domenico and Schwarz (1990 [100569]).) 
5.3 Air Permeabilities 
Assumption: Permeabilities determined from air-injection tests are assumed 
representative of the hydraulic conductivity of the excavation-disturbed zone 
around the opening. 
Rationale: A detailed discussion of this assumption is given in CRWMS M&O 
(2000 [141400], Sections 5.1 and 5.2.1). The assumption holds for the purposes 
of the current application, where postexcavation air-injection tests were 
conducted in a dry fracture network. Air-permeability estimates are used to 
condition the generation of a spatially correlated, random permeability field. 
Potential inaccuracies in this assumption are compensated for by the estimation 
of the van Genuchten 1/. parameter (Luckner et al. 1989 [100590], pp. 2191 
2192). Air-injection tests are a standard method to obtain drift-scale permeability

  
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values (CRWMS M&O 2000 [141400], Section 6.1). The use of these values 
during calibration and prediction of seepage ensures consistency. 
Excavation effects increase the permeabilities around the niches and the Cross 
Drift (Wang and Elsworth 1999 [104366], pp. 751757; CRWMC [sic] M&O 
2000 [141400], Section 6.1.2.2). Since seepage is determined by the formation 
properties within the boundary layer in the immediate vicinity of the opening, it is 
reasonable to use postexcavation air-permeability data for seepage calculations. 
(Note: The assumption is that air-injection tests can be used to determine an intrinsic 
permeability of the flow system that is relevant for the subsequent liquid-release tests and their 
analysis. Whether the relevant flow system is the fracture system only or is some combination of 
the fractures and matrix is immaterial to the assumption. The rationale for the assumption is that 
the permeability of the relevant flow system is associated mainly with the fractures in the 
excavation disturbed zone. The matrix permeability is many orders of magnitude less than that of 
the fractures (CRWMS M&O 2000 [145771], Sections 6.1.1 and 6.2.1). The relevant geologic 
layers, the Tptpmn and Tptpll (see Table 6.5-1) do not have high clay mineral content that could 
swell with the introduction of more water into the system and create a difference between the dry 
intrinsic permeability (air-injection tests) and the wet intrinsic permeability (liquid-release 
tests).) 
This assumption does not require confirmation. 
5.4 Characteristic curves 
Assumption: Relative permeability and capillary pressure are assumed to be 
described as continuous functions of effective liquid saturation, following the 
expressions given by the van Genuchten-Mualem model (Luckner et al. 1989 
[100590], pp. 21912192) as implemented in the iTOUGH2 code (Finsterle 1997 
[104043], p. 224). Capillary strength (represented by the 1/. parameter) and 
permeability are not correlated. 
Rationale: The van Genuchten-Mualem model is the standard model used in the 
suite of UZ flow and transport models; it was chosen here for consistency. 
Furthermore, the applicability of relative permeability and capillary pressure 
functions is consistent with the continuum assumption (see Section 5.1) and is 
appropriate to represent fractures that are rough and/or partially filled with 
porous material. The functional relationship describing the potential correlation 
between permeability and capillary strength is unknown. An increase in 
permeability may be attributed to larger fracture apertures (which would reduce 
capillary strength) or to an increase in fracture density (which would not affect 
capillary strength). The capillary strength parameter 1/. is taken to be constant 
and will be subjected to estimation by inverse modeling. The calibration process 
and the consistent conceptualization in the downstream models (specifically the 
Seepage Model for PA) make this assumption a valid approach. 
This assumption does not require confirmation.

  
  33  
5.5 Matrix Imbibition 
Assumption: The transient effects from matrix imbibition in a fracture-matrix 
system are assumed to be small and do not need to be modeled explicitly in the 
SCM [sic  seepage calibration model] (CRWMS M&O 2000 [sic] [153045]). 
Further, the imbibition and flow into the matrix continuum is not considered in 
the SMPA. 
(Note: CRWMS M&O 2001 [153045] is the correct reference cited above.) 
(Note: SMPA refers to the Seepage Model for Performance Assessment.) 
Rationale: Matrix permeability is low, and the potential for matrix imbibition is 
limited because of relatively low porosity and relatively high liquid saturation. In 
a fracture-matrix system, the transient effects from matrix imbibition are 
restricted to intermediate times, i.e., they are insignificant (1) for a short-term 
liquid-release test with insufficient time for matrix imbibition, and (2) for a longterm 
seepage experiment, when near-steady late-time data are no longer affected 
by matrix imbibition. To match intermediate times during a long-term test, an 
effective porosity is estimated by inverse modeling to account for the storage 
capacity of both the fracture system and the matrix. Porosity estimates are 
irrelevant in the subsequent simulations of seepage under natural flow conditions, 
which are near steady state. 
For SMPA, the imbibition and flow into the matrix continuum is not considered. 
The rationale is that in the current AMR, except for the episodic percolation flux 
case (Sections 6.5 and 6.6.6), we are calculating steady-state flow conditions over 
long time frames. At steady-state, the flow exchange between fracture and matrix 
continua will settle to a small amount with the matrix close to full saturation. The 
flow partitions between the fracture and matrix continua according to their 
effective permeabilities and porosities, and it follows that the matrix with its five 
to six orders-of-magnitude lower permeability would not have significant effects 
on seepage into drift, which would be controlled by the flow in the fracture 
continuum. For the episodic percolation flux case (Sections 6.5 and 6.6.6), the 
matrix continuum provides a damping effect on seepage in the fracture 
continuum, and neglecting it represents a conservative case. 
(Note: Matrix and fracture permeabilities are presented in CRWMS M&O (2000 [144426], 
Section 6.1.4).) 
5.6 Evaporation 
Assumption: The effect of evaporation on the observed seepage rates is 
insignificant, i.e., water removal from the formation, at the drift surface, and from 
the capture system by evaporation and vapor diffusion is assumed to be small. 
Rationale: Under isothermal conditions, potential evaporation at the drift wall or 
in the capture system is small compared to the amount of water being released.

  
  34  
Seepage experiments in the middle nonlithophysal zone of the Topopah Spring 
welded unit were conducted in niches that were closed off by a bulkhead, which 
leads to comparatively high relative humidity and low air circulation. Moreover, 
a humidifier was used in some of the experiments to ensure high relative humidity. 
For these conditions, Ho (1997 [141521], pp. 26652671) and Or and Ghezzehei 
(2000 [144773], pp. 381393) provide a detailed description of evaporation 
mechanisms on the scale of individual water droplets within fractures or 
emerging from fractured formations. The evapo-infiltration thresholds calculated 
by Ho (1997 [141521], p. 2670) are significantly lower than the applied injection 
rates, suggesting a very minor influence of evaporation on measured seepage 
rates in experiments conducted in the niches. 
Evaporation from a large surface of free or nearly free water, however, may be 
significant. As injected water reaches the opening, it spreads along the surface on 
account of capillarity within the rough surface. As a result, water potentially 
seeping into the opening may not only form droplets with a small surface area, 
but may be spread over a large area, providing a large surface for evaporation. 
Depending on the evaporation potential of the air in the opening, the water film 
covering the wall of the opening may evaporate at a rate comparable to the 
injection or seepage rates. 
Moreover, evaporation may be significant during periods of active ventilation 
with high airflows in the drift in combination with low injection rates. Under 
these specific conditions, the evaporation rate may exceed the potential seepage 
rate, preventing the development of liquid droplets that drip into the opening. 
Ventilation effects are evident from the seepage data collected in the Cross Drift 
(see Section 6.3.3.3). To reduce the impact from ventilation effects, calibration of 
the SCM [sic  seepage calibration model] was restricted to seepage rate data 
collected during nighttime and weekends, when ventilation was turned off. 
Currently, no quantitative estimates of evaporation potential under the conditions 
of the seepage experiments are available. The simplified assumption that 
evaporation rates are small compared to the injection rates is non-conservative if 
used for inverse modeling and is therefore an assumption that needs to be verified 
(TBV-4951 [153049]). 
It is important to realize that a non-conservative assumption made in an inverse 
model is a conservative assumption when used for seepage predictions in a 
forward model. Specifically, neglecting evaporation effects by prescribing a 
100% relative-humidity boundary condition in a forward seepage prediction 
model (such as the SMPA) is a conservative assumption. While such a model 
underestimates vapor flow, it yields the maximum liquid-phase influx, which is 
defined here as drift seepage. The underestimation of vapor flow is irrelevant, 
since the assumption of 100% relative humidity already implies that the moisture 
content in the drift environment is as high as possible, maximizing the amount of 
moisture that can condense within the waste-emplacement drift. In a ventilated 
drift, the development of a dry-out zone increases the capillary pressure and local

  
  35  
storage volume and thus reduces the risk of reaching seepage conditions; the 
assumption of 100% relative humidity in the drift is again conservative. The 
assumption is also reasonable for the time when ventilation is stopped and the 
waste-emplacement drift is closed. A repository design that includes ventilation 
yields reduced seepage. 
5.7 Percolation flux range used in this AMR 
Assumption: It is assumed that the range of values for percolation flux used in 
simulations in this AMR is appropriate. 
Rationale: For SMPA calculations, five.values for Qp are used, ranging from 5 to 
500 mm/yr; more specifically Qp = 5, 14.6, 73.2, 213 and 500 mm/yr. The 
justification for the choice of this range is so that the range covers various 
estimates of percolation fluxes. Wu et al. [sic-Wu and Bodvarsson] (1999 
[117161], p. 210) calculated the percolation flux expected at the repository level, 
based on a 3D UZ model of Yucca Mountain. They obtained an average fracture 
flow of 4 to 5 mm/yr at the repository level under present climate conditions. 
Ritcey and Wu (1999 [139174], p. 262) found that under a climate scenario 
simulating the most recent glacial period, the percolation flux ranges from 0 to 
120 mm/yr, with the peak of the probability distribution to be around 20 mm/yr. 
The upper limit of 500 mm/yr is chosen to accommodate potential flow focusing in 
the geologic layers above the drift and to safely bracket an uncertainty range 
more than four times the high flux value of 120 mm/yr. In cases where seepage is 
very low or zero, even larger Qp values are also used to find when seepage might 
occur. 
This assumption does not require confirmation. 
5.4.1.1 Assumptions Specific to Seepage Enhancement Due to Rockfall 
There are no additional assumptions specific to the model documented in Section 6.4.1.1. 
5.4.1.2 Assumptions Specific to Seepage Enhancement Due to Rock Bolts 
The assumption that grout material permeability and capillarity may be loosely correlated is 
specifically applicable to the model documented in Section 6.4.1.2. Rationale: Studies of porous 
media suggest that permeability and capillarity are correlated in porous media (Wang 1992 
[110043]; Leverett 1941 [100588]). Extension of this correlation observed in porous media, to 
fractured rock is considered appropriate if the correlation is defined loosely (Finsterle 2000 
[151875]). Perfect correlation between fracture permeability and capillarity is achieved only if 
the number of fractures remains constant. If the number of fractures increases without the 
average fracture aperture increasing then permeability may increase without capillarity 
increasing. Thus, a loose correlation that allows for some off-correlation behavior to capture this 
uncertainty is assumed here. No further confirmation is required.

  
  36  
The assumption that disconnecting mesh elements near the drift wall adequately represents 
discrete fracture effect for investigation of seepage enhancement due to rock bolts is specifically 
applicable to the model documented in Section 6.4.1.2. Rationale: The major effect of a discrete 
fracture conceptual model for the effect of rock bolts on seepage will be to isolate the last portion 
of the flow path toward the drift wall. Flow in the rock bolt hole that is not diverted into this last 
fracture must enter the drift. Flow in the rock bolt hole prior to the last fracture will, at Yucca 
Mountain, encounter enough fractures that a continuum model will adequately reproduce inflow 
and outflow from the rock bolt hole. It is sufficient to restrict the connections between the rock 
bolt hole and the formation adjacent to the drift wall so that flow in the rock bolt hole that 
bypasses the last fracture is forced into the drift. No further confirmation is required. 
5.4.2 Assumptions Specific to Seepage Enhancement Due to Flow Focusing 
The assumption that a two-dimensional model is adequate for reproduction of flow focusing or 
weeps formation is specifically applicable to the model documented in Section 6.4.2. Rationale: 
In a two-dimensional, heterogeneous-permeability field, such as the ones used for the model 
documented in Section 6.4.2, areas of low permeability (or relative permeability) create barriers 
that divert flow laterally. Flow incident on a barrier will be diverted to one side or the other or be 
split and flow both ways around the barrier. In a three-dimensional model, however, the flow 
incident on a barrier may flow any direction around the barrier. The two-dimensional model, 
because of the more limited flow diversion pathways should predict more flow focusing, i.e., 
flow incident on a barrier in a two-dimensional model will be focused into fewer flow channels 
than that in a three-dimensional model. This assumption creates a conservatism in the model. 
This conservatism may be partially or wholly offset by nonconservatisms due to other 
assumptions. No further confirmation is required. 
The assumption that consideration of only one scale of heterogeneity is adequate for 
reproduction of flow focusing or weeps formation is specifically applicable to the model 
documented in Section 6.4.2. Rationale: The heterogeneous permeability fields used for the 
model of flow focusing are essentially random, using 1 and 3 m correlation lengths. 
Heterogeneity introduced by larger-scale features such as very large fractures or small faults is 
not considered. Note that heterogeneity introduced by larger faults is beyond the scale of this 
model. These large-scale heterogeneities may introduce more flow focusing than the small-scale 
heterogeneity alone. This assumption creates a nonconservatism in the model. This 
nonconservatism may be partially or wholly offset by conservatism due to other assumptions or 
conservatism in the reported result of the model. No further confirmation is required. 
The assumption that use of a single continuum model is adequate for reproduction of flow 
focusing or weeps formation is specifically applicable to the model documented in Section 6.4.2. 
Rationale: Flow in the TSw, particularly the Tptpmn (see Table 6.5-1 for geologic definitions), 
which has very low matrix permeability, is predicted by the UZ Flow model to be dominantly, 
80% or more, in the fracture system (CRWMS M&O 2000 [122797], Table 6-11). Further, under 
steady-state flow, interaction between flow in the matrix and the fractures is limited to areas 
adjacent to layer interfaces. However, for the purposes of modeling of flow focusing, the results 
of Section 6.4.2 show that the focusing distribution is virtually independent of percolation rate, 
and thus the assumption assigning 100% of the flow to the fractures not affect the prediction of a 
flow-focusing distribution. No further confirmation is required.

  
  37  
The assumption that use of mountain-scale flow parameters (other than permeability) is adequate 
for reproduction of flow focusing or weeps formation is specifically applicable to the model 
documented in Section 6.4.2. Rationale: Where the average hydraulic conductivity of the flow 
system is orders-of-magnitude more than the percolation rate, the parameter of importance 
becomes the structural parameters of the heterogeneous hydraulic conductivity (permeability) 
field rather than any other model parameter. So, while the use of Yucca Mountain specific 
parameters is of some importance, scale-specific parameters are not. No further confirmation is 
required. 
5.4.3 Assumptions Specific to Percolation Redistribution and Lateral Flow in the PTn 
The following assumptions, 1 and 59, are quoted from UZ Flow Models and Submodels 
(CRWMS M&O 2000 [122797], pp. 3132) and are specifically applicable to the models 
documented in Section 6.4.3. No further confirmation of the assumptions is required. (The quote 
below is italicized and indented; notes for clarification are inserted as plain text.) 
1. The water table is used as the bottom model boundary which is subject to 
constant water pressure (equal to the atmospherical pressure). Rationale: The 
water table is a surface where the water pressure is a fixed single value. 
Within the numerical models, only one single set of model primary variables 
for solving Richards equations is specified for the bottom boundary and this 
is equivalent to specifying a constant saturation. 
5. The lateral boundaries of the model domain are subject to no-flow boundary 
conditions. Rationale: The boundaries of the northern and southern model 
domain are located so far away from the potential repository area that lateral 
flow effects along these boundaries on flow at the potential repository should 
be small. The eastern boundary is for most parts along the Bow Ridge fault, 
and no lateral flow crossing the fault is reasoned. The western boundary is 
separated from the potential repository by the Solitario Canyon fault, 
therefore this boundary condition effects are expected to be insignificant. 
(Note: Because faults are modeled as high permeability vertical structures, they act much like 
lateral boundaries for flow, so a lateral boundary separated from an area of interest, e.g., the 
potential repository, by a fault will have little influence on the area of interest. Furthermore, a 
lateral boundary that is coincident with a fault will have little influence away from the boundary 
because lateral bounaries like permeable or impermeable faults create barriers to lateral flow 
forcing flow to become vertical, parallel with the fault.) 
6. Perched water occurrence results from permeability barrier effects. 
Rationale: Consistent with the conceptual model that ambient conditions 
reflect long-term, steady-state or transient flow through the unsaturated zone, 
perched water under steady-state flow conditions may only be due to a 
permeability barrier. 
(Note: Perched-water occurrence under long-term, transient flow, or near-steady flow, conditions 
requires a permeability barrier. Under shorter-term transient flow conditions, perched-water

  
  38  
occurrence may be attributable to capillary-barrier effects. This assumption, while a natural 
consequence of assumption 8, quoted below, is given here for completeness.) 
7. Under steady-state flow conditions, moisture flow and tracer transport 
processes can be decoupled. Rationale: Steady-state flow conditions result in 
an unchanging flow field, and as long as the concentrations of tracers and/or 
radionuclides are such that they do not significantly change the properties of 
the fluid, which is the case for simulations documented in this AMR, then the 
flow field does not have to be coupled to transport. 
8. Water flow through the UZ is assumed to occur under steady-state conditions. 
Transient, fast-pathway flow, such has conveyed 36Cl to the ESF horizon, is 
assumed not to contribute significantly to the total flow through the UZ. 
(Note: The rationale for this assumption is provided in CRWMS M&O (2000 [141187], Section 
6.1.2 and 6.1.6).) 
9. The dual-permeability formulation is assumed to be appropriate for 
simulating flow and transport through fractured tuffs. 
(Note: The rationale for this assumption is provided in CRWMS M&O (2000 [141187], Section 
6.4).) 
5.4.4 Assumptions Specific to the Effect of Episodic Percolation on Seepage 
Assumptions 1 and 59, documented in UZ Flow Models and Submodels (CRWMS M&O 2000 
[122797], pp. 3132), are quoted above in Section 5.4.3 and are specifically applicable to the 
model documented in Section 6.4.4. No further confirmation is required. 
The assumption that the infiltration data received under Input Transmittal Number (ITN) 
00316.T are correct is specifically applicable to the model documented in Section 6.4.4. 
Rationale: The upper-bound, glacial-average, infiltration scenario is used to conservatively 
define the highest possible infiltration in order to test whether episodic infiltration incident upon 
the outcrop of the TSw west of Yucca Crest will result in episodic percolation at the repository 
horizon. The negative results of the model using these data justify this assumption. Furthermore, 
comparison of the data received under ITN: 00316.T with other infiltration scenarios shows that 
the upper-bound, glacial-average, infiltration scenario has the highest infiltration and has a 
similar spatial distribution, as expected. No further confirmation is required. 
5.5 ASSUMPTIONS SPECIFIC TO UNSATURATED ZONE FLOW AND 
TRANSPORT BELOW THE REPOSITORY 
Assumptions 1 and 59, documented in UZ Flow Models and Submodels (CRWMS M&O 2000 
[122797], pp. 3132), are quoted in Section 5.4.3 and are specifically applicable to the models 
documented in Section 6.5. No further confirmation is required.

  
  39  
5.5.1 Assumptions Specific to Fracture Flow in the Vitric Calico Hills Formation 
Assumptions documented in Section 5 of Analysis of Hydrologic Properties Data (CRWMS 
M&O 2000 [145771]) and assumptions 1, 7, and 8 documented in Calibrated Properties Model 
(CRWMS M&O 2000 [144426], Section 5) are specifically applicable to the models documented 
in Section 6.5.1. No further confirmation is required. 
Section 5 of Analysis of Hydrologic Properties Data (CRWMS M&O 2000 [145771]) states (the 
quote below is italicized and indented; notes for clarification are inserted in unindented, plain 
text): 
1. The subsurface heterogeneity of the unsaturated zone of Yucca Mountain is 
adequately represented by a number of model layers, each of which is 
assumed to have uniform hydrologic properties. This is based on the following 
considerations. First, the overall behavior of flow and transport processes in 
the unsaturated zone of Yucca Mountain is mainly determined by relatively 
large-scale heterogeneities introduced by stratification of the tuffs. Second, 
the complexity of a heterogeneity model needs to be consistent with the data 
availability. More complicated models generally introduce larger degrees of 
uncertainty in rock property estimations when data are limited. This is 
because more complicated models correspond to larger numbers of variables. 
Third, this layered approach is supported by field observations, such as 
matrix water saturation distributions. For a given geologic unit, measured 
matrix saturation distributions are very similar from different boreholes (Flint 
1998, pp. 24-30, Figures 5-9), indicating that matrix flow behavior and 
effective hydraulic properties should be similar within the unit. A further 
discussion on this assumption is provided in an AMR describing conceptual 
and numerical models for UZ flow and transport. Based on the above 
reasoning, no confirmation is needed for this assumption. 
(Note: CRWMS M&O (2000 [141187] describes the conceptual and numerical model for UZ 
flow and transport.) 
(Note: Flint 1998 [100033]) 
2. Another major assumption is that van Genuchten (1980, pp. 892-898) 
relationships, originally developed for porous media, can be used as 
constitutive relations for the active fracture continuum. Not all connected 
fractures are active in conducting liquid water in the unsaturated zone of 
Yucca Mountain (Liu et al. 1998, pp. 2638-2641). The active fracture 
continuum consists of fractures that actively conduct liquid water. The use of 
van Genuchten relations is based on a conceptual model that flow in fractures 
can be described using porous medium equivalence. A further discussion on 
this conceptual model is provided in an AMR describing conceptual and 
numerical models for UZ flow and transport. No confirmation is needed for 
this assumption.

  
  40  
(Note: CRWMS M&O (2000 [141187]) describes the conceptual and numerical model for UZ 
flow and transport.) 
(Note: van Genuchten 1980 [100610]) 
(Note: Liu et al. 1998 [105729]) 
3. Since a systematic approach for upscaling properties directly from smallscale 
measurements is still lacking for unsaturated fractured rocks, simple 
averaging schemes are assumed to be appropriate in most cases for the 
upscaling purpose in the analyses to be reported in this study. The relation of 
Paleologos et al. (1996, p. 1336), originally developed for porous media, is 
assumed to be appropriate for upscaling matrix permeability when an upper 
limit of 1.5 orders of magnitude is used for the amount of upscaling. 
Hydrologic property data have been determined on scales that are generally 
much smaller than the scales characterizing the subsurface heterogeneity 
(e.g., characteristic sizes for model layers). While considerable progress has 
been made in developing upscaling schemes for porous media, the scaledependent 
behavior of a hydrologic property for fractured rocks can be very 
different from that for porous media. For example, the existence of fractures 
in a fractured rock, which may act as a capillary barrier, can increase 
tortuosity of liquid water in the matrix, and therefore reduce large-scale 
matrix permeability compared with the case without fractures. It is necessary 
to make this assumption to determine the rock properties using small-scale 
measurements. Note that the rock properties to be reported in this report are 
mainly used as initial estimates for use in the inversion process documented in 
an AMR describing calibrated properties model. The upscaling issue is 
further considered in the inversion process which results in the large-scale 
properties by matching the large-scale simulation results with grid blockscale 
observations averaged from small-scale data. Based on the above 
reasoning, no confirmation is needed for this assumption. 
(Note: Paleologos et al. 1996 [105736]) 
4. It is assumed that a van Genuchten fracture m value, estimated from the 
middle nonlithophysal zone of the Topopah Spring welded unit (UZ Model 
layer tsw34), can be used as a representative estimate for all of UZ Model 
layers. This is based on the following considerations. First, for other model 
layers, there are limited data for determining the m values. Second, the m 
value determined in this report is only used as an initial guess for use in the 
inversion process documented in an AMR describing calibrated properties 
model. The inversion process results in more accurate m values for the model 
layers because it adjusts rock properties to make model simulation results 
match the relevant observations. Based on these considerations, no 
confirmation is needed for this assumption. 
(Note: CRWMS M&O (2000 [144426]) describes the calibrated properties model.)

  
  41  
Assumptions 1, 7, and 8 documented in Calibrated Properties Model (CRWMS M&O 2000 
[144426], Section 5) states (the quote below is italicized and indented; notes for clarification are 
inserted in unindented, plain text): 
1. It is assumed that one-dimensional (1-D) vertical flow adequately describes 
the flow patterns around the boreholes used for rock mass (nonfault) property 
calibration 
Inverse modeling involves many forward simulations, and therefore is 
computationally intensive. 1-D, columnar models are used because the time that 
is required for each forward simulation is short (a minute or less). Therefore 
many simulations, thousands in this case, can be accomplished in a reasonable 
(i.e., less than a day) time period. The effect of using 1-D columnar models is that 
all flow is forced to be vertical; there is no lateral flow. From the surface to the 
repository, lateral flow is not expected to be significant because perched water 
has not been found here. Below the repository, in the Calico Hills nonwelded unit 
(CHn) and the Crater Flat undifferentiated unit (CFu), areas of perched water 
exist where lateral flow may be significant. Properties needed to produce perched 
water and varying degrees of lateral flow are not addressed in this AMR but will 
be addressed in a future AMR supporting the Unsaturated Zone Flow and 
Transport PMR. This future AMR will also address the suitability of other CHn 
and CFu properties with respect to flow changes as a result of perched water and 
lateral flow. 
(Note: CRWMS M&O (2000 [122797]) addresses perched water and lateral flow.) 
7. It is assumed that reported saturation values greater than 1.0 are equal to 
1.0 
Measurement error causes calculated saturation values (based on measurements 
of initial, saturated, and dry weight) to be greater than 1.0, but this is not 
physical, if possible saturation is physically constrained to a maximum of 1.0. 
8. Because of data limitations and the way data were interpreted, estimates of 
uncertainty cannot be directly calculated for some of the data. In these cases, 
an appropriate uncertainty is selected (assumed) based on the uncertainties of 
similar data. 
(Note: The assumption is that appropriate uncertainties for one type of data may be estimated 
based solely on the uncertainty of similar data. The uncertainty assumed and the rationale for 
each particular assumption are presented in CRWMS M&O (2000 [144426], Section 6.1.2).) 
The assumption that all flow in the vitric portion of the Calico Hills Formation (CHn(v)) is in the 
matrix such that it may be modeled using a single continuum is specifically applicable to the 
model documented in Section 6.5.1. Rationale: This assumption is supported by unsaturated 
zone flow tests conducted in nonwelded tuffs at Busted Butte and in Exploratory Studies Facility 
(ESF) Alcove 4. The tests at Busted Butte conducted in the upper CHn(v) show flow taking 
place completely in the matrix even though fractures are present, as reported in Unsaturated

  
  42  
Zone and Saturated Zone Transport Properties (U0100) (CRWMS M&O 2001 [154024], 
Section 6.8.9). Tests in ESF Alcove 4 that are conducted in the Paintbrush Tuff nonwelded 
hydrogeologic unit (PTn), which is comprised of nonwelded, vitric tuffs similar to those of the 
CHn(v), also show that flow around a large, through-going fracture is matrix dominated as 
reported in In Situ Field Testing of Processes (CRWMS M&O 2000 [141400], Section 6.7). 
Only when the matrix around the fracture becomes satiated does the fracture begin to flow. Thus, 
a single-continuum, matrix-only model for the CHn(v) is appropriate for all but saturated flow, 
which is neither expected nor predicted in the CHn(v) (CRWMS M&O 2000 [122797], Section 
6.2). No further confirmation is required. 
5.5.2 Assumptions Specific to Fault Characteristics in the CHn and CFu 
The assumption that the limited data specific to the CHn fracture system and analog data, 
documented in Analysis of Hydrologic Properties Data (CRWMS M&O 2000 [145771], 
Sections 6.1 and 6.4.2) sufficiently describe the expected values and distributions for fracture 
permeability and capillarity of the CHn and Crater Flat undifferentiated tuffs (CFu) is 
specifically applicable to the model documented in Section 6.5.2. Rationale: The limited data 
characterizing the CHn fracture system, i.e. one measurement of permeability and 39 fractures 
observed in boreholes (CRWMS M&O 2000 [145771], Tables 5 and 6, respectively), make the 
estimates of fracture permeability and capillarity highly uncertain. This uncertainty is increased 
by the application of these data, which are all from the upper layers of the CHn, to the entirety of 
the CHn and Crater Flat undifferentiated tuffs (CFu). The uncertainty of permeability is treated 
by sensitivity studies with variation of permeability over two orders of magnitude. This is about 
four times the average observed standard deviation of fracture permeability for any one layer 
(CRWMS M&O 2000 [145771], Table 5). The uncertainty of capillarity is treated by variation 
over one order of magnitude. Capillarity, or the van Genuchten . parameter, is proportional to 
the cube root of fracture permeability over fracture frequency (CRWMS M&O 2000 [145771], 
equations 7 and 9), and the uncertainty of fracture frequency is about a factor of two (CRWMS 
M&O 2000 [145771], Table 6). This, combined with the uncertainty of permeability, gives a 
rough estimate of the uncertainty of van Genuchten . parameter as about a quarter an order of 
magnitude, again four times less than the variation used in the sensitivity study. In addition to the 
large ranges around the expected values, an alternative model of an impermeable fault is 
modeled. These ranges as well as the alternative model should sufficiently characterize the 
uncertainty of fault parameters. No further confirmation is required. 
5.5.3 Assumptions Specific to Perched Water Models 
There are no additional assumptions specific to the model documented in Section 5.5.3. 
5.5.4 Assumptions Specific to Radionuclide Release into Matrix Rock 
The assumption that radionuclides released from the emplacement drifts would have to diffuse or 
advect through rock matrix prior to entering the fracture system is specifically applicable to the 
model documented in Section 6.5.4. Rationale: In the absence of substantial and/or long term 
percolation out of the emplacement drift into the fracture system, the most likely immediate 
pathway for radionuclides out of the engineered barrier system (EBS) will be through the matrix. 
This is because, first, the rock matrix forms approximately 99% of the boundary of the

  
  43  
emplacement drift (the other approximately 1% being fractures that are open to the drift) 
(CRWMS M&O 2000 [145771], Sections 6.1 and 6.2); and second, the rock below the drift 
invert will be drier because of a shadow effect (Houseworth et al. 2001 [155876]), will have 
lower (more negative) capillary pressure, and will imbibe water escaping the drift. Radionuclides 
will be forced to diffuse or advect through the rock matrix until encountering a flowing fracture. 
No further confirmation is required.

  
  44  
INTENTIONALLY LEFT BLANK

  
  45  
6. ANALYSIS/MODEL 
6.1 INTRODUCTION 
When analyses and models are used to represent the real world, a certain amount of uncertainty 
is inherent in those analyses and models. This uncertainty is generally due to data limitations. 
That is, because the data are only a sampling of a process or property, or represent a process or 
property at a single, or multiple but discrete, scale(s), there is inherent uncertainty about the 
representation of that process or property by the data. In the analyses and models used for 
unsaturated zone (UZ) flow and transport, uncertainty has been treated in several ways: (1) by 
characterizing the uncertainty in the analysis or model by defining a most likely scenario and 
then by varying key parameters to define a probability distribution about the most likely scenario 
of other, less likely, scenarios, (2) by specifying a process, e.g. seepage enhancement due to rock 
bolts, as low consequence and then treating that process conservatively, and (3) where no data 
exist for a process or property, and thus the uncertainty of that process or property can not be 
characterized, by using data about an analogous process or property to define the scenario. 
In addition to how they treat uncertainty, analyses and models used to represent the real world 
are required to simplify the processes and properties of the real world. Because the real world is 
extremely complex, i.e. processes and properties can be extremely variable in space and time and 
may have different effective characteristics when considered on different scales, analyses and 
models must use simplified descriptions of the processes and properties to efficiently predict 
flow and transport in the UZ. 
In general, uncertainty and simplification have been treated in a conservative manner. 
Conservatism allows performance to be judged with confidence that conditions are not likely to 
be worse. However, it is difficult to predict how treatment of uncertainty and simplification in 
upstream models will eventually affect the results of more complex downstream models. Low 
consequence processes that are conservatively treated in upstream models may cause higher 
consequence impacts to downstream model results. 
In an effort to better understand the consequences of the previous treatment of uncertainty and 
simplification, supplemental studies have been performed, and are presented here for several 
areas of interest. Section 6.2 is a review of the geochemical data available for conceptual model 
development and numerical model calibration and validation. This is a data type that is 
frequently difficult to interpret and is also difficult to use for model calibration and/or validation, 
as it requires a fully developed flow and transport model. Section 6.3 is a review of computation 
methods currently used for transport calculations and an investigation of alternative methods 
specifically to capture transient matrix diffusion behavior, a process that has previously been 
treated in a simplified manner. Section 6.4 is an investigation of several processes affecting 
seepage using more detailed models and/or alternative approaches to those previously used. 
Section 6.5 is an investigation of several processes affecting flow and transport below the 
repository using alternative approaches to those previously used.

  
  46  
Most of the studies documented in this AMR represent analyses that use previously developed 
models to better characterize uncertainty and to ascertain the importance of further investigation 
on a property or process. As such, they do not require validation, specifically: 
. Section 6.2 documents a summary of geochemical data that does not rely on developed 
models and, thus, does not require validation. 
. Section 6.3.1 documents a comparison of different codes. A validation-type exercise for 
the newly developed DCPT V2.0 (LBNL 2001 [154342]) is included for informational 
purposes to demonstrate the fitness of this code, however information about the 
validation of a code is found in the software documentation. 
. Section 6.4.1.1 documents the development of new data through an analysis that uses a 
previously developed and validated model. 
. Sections 6.3.2, 6.4.3, 6.5.2, 6.5.3, 6.5.4, document supplemental uncertainty analyses 
evaluating the effect of alternative parameter combinations using previously developed 
and validated models. 
The development and validation of new models is documented in Sections 6.4.1.2, 6.4.2, 6.4.4, 
and 6.5.1. 
The Scientific Notebooks (SNs) listed in Table 6.1-1 document the input and output files 
presented in DTNs listed in Section 8.4 and provide all details needed to reproduce the modeling 
activities performed in support of the discussions and conclusions in this AMR. 
Table 6.1-1. Scientific Notebooks 
LBNL Scientific Notebook ID YMP M&O Scientific 
Notebook ID 
Page numbers Citation 
YMP-LBNL-CFT-GL-1 SN-LBNL-SCI-033-V1 128129, 145149 Li 2000 [153480] 
YMP-LBNL-CFT-GL-2 SN-LBNL-SCI-189-V1 2267 Bodvarsson 2001 [156334] 
YMP-LBNL-DSM-CFA-1 SN-LBNL-SCI-180-V1 62, 63, 6870 Bodvarsson 2001 [156334] 
YMP-LBNL-GSB-1.1.2 SN-LBNL-SCI-003-V1 8183 Ahlers 2000 [155853] 
YMP-LBNL-GSB-1.6.4 SN-LBNL-SCI-085-V2 2425 Bodvarsson 2001 [156334] 
YMP-LBNL-GSB-LHH-2 SN-LBNL-SCI-098-V1 9094, 129141 Liu 1999 [155675] 
YMP-LBNL-GSB-LP-3 SN-LBNL-SCI-155-V1 142145 Pan 2001 [155954] 
YMP-LBNL-UZ-CFA-1 SN-LBNL-SCI-003-V2 19, 2935 Bodvarsson 2001 [156334] 
YMP-LBNL-UZ-JL-2.0 SN-LBNL-SCI-206-V1 7288 Bodvarsson 2001 [156334] 
YMP-LBNL-YSW-2 SN-LBNL-SCI-120-V1 216254 Wu 2001 [155676] 
YMP-LBNL-YSW-4 SN-LBNL-SCI-200-V1 732 Bodvarsson 2001 [156334] 
YMP-LBNL-YSW-JH-2 SN-LBNL-SCI-143-V1 122123, 152 Hinds 2001 [155955] 
YMP-LBNL-YSW-KEZ-1 SN-LBNL-SCI-197-V1 913, 3948, 85 Zellmer 2001 [155956] 
YMP-LBNL-YSW-KZ-1 SN-LBNL-SCI-202-V1 723 Bodvarsson 2001 [156334]

  
  47  
The importance of the models and analyses documented in this AMR is documented in Table 
6.1-2. The following Sections do not document models or analyses: Section 6.2, Synthesis of 
Geochemical Information, documents available geochemical information; Section 6.3.1, 
Comparison of Transport Codes, documents codes used or available for use to simulate transport 
through the unsaturated zone at Yucca Mountain; Section 6.3.2, Matrix Block Discretization and 
its Effects on Unsaturated Zone Flow and Transport Simulations, documents advantages and 
disadvantages of using alternate matrix block discretization schemes. 
Table 6.1-2 Importance of Model or Analysis 
Model or Analysis (Section) Importance 
Seepage Enhancement due to Rockfall (6.4.1.1) Level 3  Used to confirm conservatism of 
abstraction approach 
The Effect of Rock Bolts on Seepage (6.4.1.2) Level 3  Used to confirm conservatism of 
abstraction approach 
Focusing and Discrete Flow Paths in the TSw (6.4.2) Level 2  Climate, Net Infiltration into the Mountain, 
and Unsaturated Flow 
Percolation Redistribution and Lateral Flow in the 
PTn (6.4.3) 
Level 3  Alternative model for public confidence 
building 
The Effect of Episodic Percolation on Seepage 
(6.4.4) 
Level 3  Used to confirm conservatism of 
abstraction approach 
Fracture Flow in the Vitric Calico Hills Formation 
(6.5.1) 
Level 3  Alternative model for public confidence 
building 
Fault Characteristics (6.5.2) Level 3  Uncertainty analysis for public confidence 
building 
Perched Water Models (6.5.3) Level 3  Alternative model for public confidence 
building 
Radionuclide Release into Matrix Rock (6.5.4) Level 3  Alternative model for public confidence 
building

  
  48  
6.2 SYNTHESIS OF GEOCHEMICAL INFORMATION 
Geochemical information offers unique insights over large scales, both spatially and temporally, 
into the flow and transport processes in the UZ of Yucca Mountain. Different types of fluid 
samples analyzed in Yucca Mountain studies include precipitation, surface waters, pore waters, 
gases from the unsaturated zone, and perched water. Fluid geochemical parameters of 
importance to site characterization and repository evaluations include major, minor, and trace 
species, ages of fracture minerals, stable isotopes (hydrogen, carbon, oxygen), cosmogenic and 
atmospheric radionuclides (tritium, carbon-14, chlorine-36), radiogenic isotopes (isotopes of 
strontium, uranium, and uranium decay products), oxidation/reduction potentials, pH, 
redox-sensitive elements, and others (BSC 2001 [154874], Section 6.2). Data on stable isotopes, 
cosmogenic and atmospheric radionuclides, and radiogenic isotopes are used primarily for sitecharacterization 
purposes to develop and calibrate models for the hydrologic flow system. The 
major constituent and trace-element concentration data are used in both site characterization and 
radionuclide transport issues. 
Geochemical and isotopic data have been used to constrain, calibrate, and validate the UZ Flow 
and Transport Model (FTM). For example, geochemical modeling of pore-water concentrations 
of chloride, sulfate, and chlorine-36 (CRWMS M&O 2000 [122797], Section 6.4) and calcite 
deposition in fractures and cavities (CRWMS M&O 2000 [122797], Section 6.5) has been used 
to constrain hydrological parameters such as infiltration/percolation flux. 
This subsection presents a synthesis of available geochemical information at Yucca Mountain to 
support the continuous development of conceptual models for the FTM. Uncertainty issues 
regarding geochemical data and the limitations of the modeling approach are discussed in 
appropriate subsections. The synthesis is intended to present the data clearly and concisely in 
order to facilitate its further use in the development of conceptual and numerical models for flow 
distribution, perched water, and transport mechanisms in the UZ of Yucca Mountain and to 
reduce uncertainty in those areas. A discussion about matrix diffusion is also presented, based on 
the various lines of geochemical evidence. 
6.2.1 Synthesis of Available Geochemical Data 
Figure 6.2-1 illustrates a summary of the available geochemical and isotopic information related 
to UZ flow and transport, with brief discussions on each item presented below in this section. 
6.2.1.1 Summary of Findings: Geochemical Composition of Pore Waters in the 
Different Hydrogeologic Units and in Perched Water 
This subsection is based largely on the discussion in Analysis of Geochemical Data for the 
Unsaturated Zone (BSC 2001 [154874], Section 6.5.3). Pore-water samples were extracted by 
tri-axial compression or by centrifugation from unsaturated core samples recovered from drydrilled 
boreholes. Pore waters extracted from the PTn are calcium-chloride or calcium-sulfatetype 
waters. Data for TSw pore waters are sparse because of the difficulty of extracting sufficient 
sample for analysis from densely welded core. In general, the TSw pore waters have equal 
quantities of Na and Ca. The dominant anion is bicarbonate, with a much smaller proportion of

  
  49  
sulfate than typical PTn waters. In terms of relative proportions of anions, the chemical 
composition of TSw waters is intermediate between those of the PTn and CHn. 
Perched 
Water 
Fracture 
Flow 
Net Infiltration 
Redistribution 
Vitric 
Zeolitic Matrix Flow 
CFu 
CHn 
Solitario 
Canyon Fault 
Cross Section West of Ghost Dance Fault 
Yucca 
Mountain 
Sundance 
Fault 
TSw
PTn 
TCw 
Increase in 87Sr/86Sr ratio in 
PTn pore water suggests 
enhanced water-rock interaction. 
Vertical trends in ion concentrations 
(e.g., Cl-,SO42-, and Na+) suggest 
at least some component of lateral 
flow within the nonwelded units. 
14C activities in PTn and CHn pore 
waters suggest that their apparent 
ages range from modern to 5,200 
years. 
14C data indicates that average 
travel times through the UZ are on 
the order of 5,000 to 10,000 years. 
Chloride concentrations in pore water support 
low infiltration (avg. ~6 mm/yr) with small deep 
infiltration (0.6-3.3 mm/yr). 
High 234U/238U ratios in shallow saturated zone 
indicate low flux and suggest a relatively isolated 
body of water underlies Yucca Mountain. 
Shift in dominance from divalent to monovalent 
cations with increasing depth reflects ion-change 
reactions with zeolites/clay in the CHn. 
Dating of fracture coatings 
(calcite/opal) shows slow, steady 
growth (1-5 mm/Myr) over last 10 Myr. 
Calculated seepage flux ~2 mm/yr. 
Bomb-pulse 36Cl and 3H indicate 
faults/fracture zones can serve as 
fast flow pathways. However, bulk of 
water moves much more slowly 
through the matrix. 
Perched water analysis has yielded 
dates ranging from 3,500-11,000 
years (14C data) and from 2,000 to 
12,000 years (36Cl/Cl data). 
Lack of bomb-pulse tracers (3H, 
36Cl, 14C) in perched water 
indicates no more than a small 
component of fast-flow water. 
Busted Butte tests show that vitric 
CHn exhibits strong capillary forces 
and matrix-dominated flow and 
tracer transport. 
Figure 6.2-1. Geochemical and Isotopic Information Related to UZ Flow and Transport

  
  50  
Pore waters extracted from the CHn unit are sodium carbonate-bicarbonate-type waters. Sodium 
concentration increases with increasing depth within the CHn. This shift in dominance from 
divalent to monovalent cations primarily reflects ion-exchange reactions with zeolites in the CHn 
unit (Figure 6.2-1). The zeolites preferentially take up calcium and magnesium while releasing 
sodium to the water (BSC 2001 [154874], Figures 1416). Such ion-exchange processes (that 
lead to sorption and retardation) are also expected to operate on any cationic radionuclides (e.g., 
cesium and strontium) released from the potential repository into aqueous solutions that migrate 
into the zeolitic CHn. Deviations from vertical trends in ion concentrations (chloride, sulfate, 
sodium) suggest at least some component of lateral flow within the nonwelded units (BSC 2001 
[154874]). 
The pore-water strontium (Sr) data obtained from borehole USW SD-7 show that the ratio of 
87Sr/86Sr increases with depth from ground surface to the repository horizon. This increase is 
steeper within the nonwelded units of the PTn and is flatter in the underlying TSw (BSC 2001 
[154874], Figure 38). The increase in pore-water 87Sr/86Sr indicates that water infiltrating into or 
percolating through nonwelded PTn tuff reacts readily and acquires a strontium isotope signature 
that reflects interaction with this unit (Figure 6.2-1). Water infiltrating into welded tuff (TCw or 
TSw) tends to retain the strontium isotope composition of the overlying soil or PTn. 
The existence of perched water bodies beneath Yucca Mountain is of interest because of 
potential implications for flow and transport in the UZ. Perched-water compositions are 
generally distinct from the compositions of unsaturated pore waters, although they are very 
similar to saturated-zone water compositions, suggesting that these waters are subject to similar 
water-rock interactions (e.g., mineral/rock dissolution and ion exchange) (BSC 2001 [154874], 
Section 6.5.3.2). 
Chloride concentration data for pore waters from the TCw, PTn, TSw, and CHn hydrogeologic 
units were compared against data for precipitation, surface waters, perched waters, and saturated 
zone (SZ) waters to elucidate general trends (BSC 2001 [154874], Section 6.5.3.1). The smaller 
concentration of chloride, which behaves as a conservative groundwater tracer, in perched water 
implies that pore waters and perched waters have distinctly different histories of geochemical 
evolution, undergoing different degrees of evaporation and/or water-rock interaction. There are 
differing interpretations to explain the difference between chloride concentrations in perched and 
pore waters (CRWMS M&O 2000 [151940], Section 3.8.2). One explanation is that the perched 
water was derived from fracture water that is more dilute than that traveling through the matrix. 
Another explanation is that the perched water was derived from areas of higher infiltration (and 
lower chloride) that are found generally to the north of the potential repository area. A third 
explanation is that the perched water only forms during relatively short periods (thousands of 
years) of high infiltration associated with wetter glacial cycles. These hypotheses for the origin 
of perched water are not mutually exclusive. 
The data available on pore-water and perched-water chemistry are limited in several ways (BSC 
2001 [154874], Section 6.5.4). First, complete pore-water analyses are available mainly for those 
horizons in Yucca Mountain that contain nonwelded tuffs with relatively high porosities. Very 
few complete pore-water analyses are available for well-indurated, low-porosity rocks (for 
example, welded tuffs in the repository horizon). Second, pore-water and perched-water analyses 
are only available for samples from a limited number of boreholes. Third, the procedure for

  
  51  
extraction of water from the pores may have an impact on the water chemistry. Despite these 
restrictions, the major ion chemistry of the pore waters is sufficiently consistent and the controls 
on this chemistry are sufficiently well understood that bounds can be placed on the likely range 
of variations to be expected. An important parameter in estimation of these bounds is the net 
infiltration rate over the regulatory period. 
Apparent infiltration rates were estimated by the chloride mass balance method, using chloride 
concentrations for pore-water samples (BSC 2001 [154874], Section 7.4). The infiltration rates 
in the PTn were generally higher than the rates estimated for alluvium (which is less than 0.5 
mm/yr), presumably caused by lateral flow and mixing within the PTn unit. PTn samples beneath 
deep alluvium had infiltration rates between 0.6 and 3.3 mm/yr. The overall average infiltration 
rate for pore-water samples collected along the Main Drift and Cross Drift (30 samples) is about 
6 mm/yr (Figure 6.2-1). 
6.2.1.2 Summary of Findings: Ages of Pore Waters in the Different Hydrogeologic Units 
and in Perched Water 
The best-developed isotopic method for dating groundwater is that using 14C (BSC 2001 
[154874], Section 6.6.4.1). In general, 14C activities in pore waters from both the PTn and CHn 
yield apparent ages ranging from modern to 5,200 years (Figure 6.2-1). Apparent ages are based 
on the assumption (see Section 5.2, assumption a) that the initial 14C activity is 100 pmc 
(Percent Modern Carbon) and that the carbon isotopic composition of the sample has not been 
significantly altered by any geochemical processes so that changes relative to the initial 
atmospheric 14C activity are solely the result of radioactive decay. The data do not show any 
trend with stratigraphic depth in the UZ. In fact, larger 14C activities are interspersed among 
smaller 14C activities in a vertical profile. These profile inversions are consistent with a 
conceptual model in which fracture flow and perhaps lateral flow occur in some of the units. 
Radiocarbon ages for PTn pore-water samples span a narrower range than for CHn pore waters, 
as expected if the CHn unit were fed by fracture flow mixing to variable extents with slower 
matrix flow (BSC 2001 [154874], Section 7.2). 
Questions regarding corrections to the radiocarbon ages remain to be resolved. The extent of 
contamination of pore-water samples with drilling air has not been quantified; such 
contamination would shift the isotopic signature to apparently younger ages. Pore-water and 
perched-water 14C activities can also be diluted by the dissolution of older carbon in the 
carbonate minerals, which would result in anomalously old apparent ages. Reaction with or 
incorporation of gas-phase CO2 from deep in the unsaturated zone can also result in an 
anomalous apparent age (BSC 2001 [154874], Section 7.2). 
The 14C values for perched water indicate an apparent age of 3,500 to 11,000 years (BSC 2001 
[154874], Section 6.9.3). The 36Cl analyses of perched water indicate its ages ranging from 2,000 
to 12,000 years for the different perched-water bodies sampled, which is in general agreement 
with 14C-based ages (BSC 2001 [154874], Section 6.6.3.6). 
The fact that perched water samples appear to be up to 11,000 years old, based on 14C and 36Cl 
ages, supports the explanation that the perched water was derived from an earlier period(s) of 
increased infiltration rates (Section 6.2.1.1). Major ion concentrations and uranium isotope data

  
  52  
suggest that these water bodies were formed by water flowing through fractures in the UZ rather 
than through the matrix. These waters do not appear to have equilibrated with water in the matrix 
of units in which the perched-water bodies are found. This supports a distinct origin (e.g., 
fracture flow) for these waters and a very slow exchange between fracture and matrix reservoirs 
(BSC 2001 [154874], Section 7.5). 
6.2.1.3 Summary of Findings: Chlorine-36 and Tritium 
Chlorine-36 analyses exist for several hundred rock samples from surface-based boreholes and 
the ESF (BSC 2001 [154874], Section 7.2). Bomb-pulse concentrations are present in the PTn at 
several locations and in the vicinity of some fault zones in the ESF, which indicates that water 
has flowed to at least the depth of the ESF in less than 50 years. This water presumably flowed 
along pathways that included fractures and/or faults (Figure 6.2-1). To account for the data, there 
must also be flow pathways such as fractures and/or faults through the PTn. It is difficult to 
quantify how much of the total percolation flux results from fracture flow. The available 
hydrochemical data, in toto, suggest the proportion is small, which implies that most of the water 
in the UZ moves through the matrix (BSC 2001 [154874], Section 7.3). 
The analytical uncertainty for tritium analysis is 4 tritium unit (TU) based on counting statistics. 
All values above 25 TU are considered to lie outside the range of the population of background 
samples (BSC 2001 [154874], Sections 6.2.6 and 6.6.2.2). The limitation of this approach is that 
background in this case includes postbomb waters that have decayed to prebomb tritium levels. 
Detectable levels of tritium (> 25 tritium units) have been observed in the Bow Ridge Fault Zone 
in ESF Alcove 2 and in about 6% of the pore waters extracted from core samples from 11 
surface-based boreholes. These detections occur within the TCw, PTn and TSw, and also in 
some samples from the CHn, as deep as the Prow Pass member of the CFu (BSC 2001 [154874], 
Section 6.6.2.3). No bomb-pulse tritium was detected in TSw samples from the drillhole 
transecting the Ghost Dance fault in the Northern Ghost Dance Fault Access Drift (Alcove 6), 
despite the fact that elevated levels of 36Cl were detected in Alcove 6. Tritium data for some of 
the UZ boreholes show several inversions in which samples with larger tritium concentrations 
occur below samples with background values in a vertical profile. Such inversion is strong 
evidence for the occurrence of fracture and lateral flow at Yucca Mountain (BSC 2001 [154874], 
Section 7.2). No postbomb water is detectable in the perched water by any of the three bombpulse 
isotope signals (3H, 14C and 36Cl) (BSC 2001 [154874], Section 7.2). 
To provide additional confirmation about the fast-flow water, work is currently underway to 
evaluate more thoroughly the distribution of 36Cl/Cl across two structural zones within the ESF 
(Drill Hole Wash Fault and Sundance Fault) that exhibited bomb-pulse signatures in previous 
studies. The work uses a suite of bomb-pulse indicators including 36Cl/Cl, 3H, 99Tc, and 129I 
(BSC 2001 [154874], Section 6.10.3.10). 
6.2.1.4 Summary of Findings: Uranium Isotopes 
Uranium isotopic ratios have been used to address the prevalence and frequency of fracture flow 
through the UZ at Yucca Mountain and the issue of local recharge to the water table. Substantial 
differences in 234U/238U activity ratios between pore water and fracture water (from 234U/238U in

  
  53  
fracture minerals as well as perched water) imply that there may be minimal liquid exchange 
between these two types of flow pathways (BSC 2001 [154874], Section 6.6.7). 
Groundwater from the SZ beneath Yucca Mountain has elevated 234U/238U activity ratios 
(between 6 and 8.5) compared to water from wells in adjacent areas to the south (between 1.5 
and 4 (BSC 2001 [154874], Figure 42)). Groundwater obtained from Paleozoic carbonate rocks 
at depth beneath Yucca Mountain (UE-25 p#1) has a much smaller 234U/238U ratio of 2.32, which 
is typical of the regional carbonate aquifer and is indicative of the stratification of shallow and 
deep aquifers at the site (Figure 6.2-1). The anomalous uranium isotopic compositions of shallow 
SZ water beneath Yucca Mountain are similar to the 234U/238U compositions measured for deep 
UZ minerals and perched-water bodies within the welded TSw. This similarity supports the 
concept of recharge through the thick UZ at Yucca Mountain, and that much of the local 
recharge derives from flow through fracture pathways in the deep UZ rather than from 
percolation through the matrix column (BSC 2001 [154874], Section 6.6.7). 
6.2.1.5 Summary of Findings: Fracture-Lining Minerals 
Deposits of calcite and opal lining fractures and cavities in the ESF contain spatial and temporal 
information on past migration of water through the UZ at Yucca Mountain. These mineral 
coatings provide a record of past water percolation through the connected fracture network in 
areas where solutions exceed chemical saturation with respect to various mineral phases. 
Observations of (1) mineral textures, (2) the fact that less than 10% of all fractures and open 
spaces contain coatings of calcite and opal, and (3) the restriction of minerals to fracture 
footwalls and cavity floors are all consistent with deposition from thin films of descending 
fracture water at locations where solutions lose carbon dioxide and water vapor (BSC 2001 
[154874], Sections 6.10.3 and 7.6). 
Calcite is abundant in the calcic soils at Yucca Mountain, leading to rapid saturation of 
infiltrating water with respect to calcite. The volcanic rocks are calcium-poor, so infiltrating 
water is essentially the only source of Ca available to form the calcite in the UZ. Therefore, the 
calcite that has formed in a cavity can be related directly to an amount of water required to 
transport that amount of Ca into the cavity. The calculated amount of water would be a minimum 
estimate of the amount of water that actually seeped into the cavity, unless the water evaporated 
completely within the cavity. The total seepage flux for the whole UZ, based on measurements 
of total calcite abundance in the ESF, indicates a flux of about 2 mm/yr, which is within an order 
of magnitude of the estimated long-term infiltration flux at the surface (BSC 2001 [154874], 
Section 6.10.3.5). 
Geochronological data indicate that calcite and opal grow at extremely slow and relatively 
uniform rates for millions of years. Radiocarbon, uranium-thorium, and uranium-lead ages for 
outer (youngest) mineral surfaces range from less than 10,000 to about 1.5 million years. 
Uranium-lead ages for interior (older) layers of opal and chalcedony range from 0.5 to 10 million 
years and result in calculated long-term average deposition rates of about 1 to 5 mm/million 
years. These rates are consistent with estimates based on uranium-thorium ages for subsamples 
deposited over the last half-million years (BSC 2001 [154874], Section 7.6).

  
  54  
Stable isotope compositions (.
13C and .
18O) of calcite deposited over the last several million 
years span a wide range of values, indicating deposition from water originating from both pluvial 
and interpluvial precipitation. This is consistent with climate fluctuations documented 
throughout the region. However, uniform mineral growth rates imply that fracture flow in the 
deep UZ at Yucca Mountain did not vary substantially despite these climate variations. In 
addition, 230Th/U ages do not show clustering that can be correlated with cycles of pluvialinterpluvial 
climate over the last 200,000 years. Initial 234U/238U ratios calculated for opal and 
calcite deposited within the potential repository horizon also imply that deep UZ fracture flow at 
Yucca Mountain was low in volume or infrequent. 
A combination of hydrogeologic factors has resulted in the long-term hydrologic stability of the 
fracture-flow system at the level of the potential repository horizon (BSC 2001 [154874], Section 
7.6). These factors include (1) increased runoff and surface drainage in response to additional 
precipitation, (2) downslope diversion along the colluvium-bedrock interface, (3) increased 
vegetation during wetter climates (leading to greater rates of evapotranspiration), and (4) the 
presence of nonwelded tuffs with large matrix permeabilities in the PTn overlying the fractured, 
densely welded tuffs. 
6.2.1.6 Summary of Findings: Busted Butte Studies 
The Busted Butte test facility is located 8 km southeast of the potential Yucca Mountain 
repository area and was chosen as a test location, based on its readily accessible exposure of the 
TSw and vitric CHn (CRWMS M&O 2001 [154024], Sections 6.8.1.1 and 6.8.1.2). 
Tracer tests in the Busted Butte indicate that strong capillary forces in the rock matrix of the 
vitric CHn are likely to modulate fracture flow from overlying units, thereby damping pulses of 
infiltrating water. The vitric CHn behaves as a porous medium, which will provide a large degree 
of contact between potential radionuclides and the rock matrix, and hence prolong their travel 
time through this unit (Figure 6.2-1). 
The Phase-1B experiment of the Busted Butte tests showed that, even when injection occurs 
immediately adjacent to a fracture, water appears to be imbibed quickly into the surrounding 
matrix. Under the injection rate of 10 mL/hr, the transport times for the nonsorbing tracers were 
observed to be on the order of 30 days over a distance of about 28 cm, whereas pure fracture 
flow would have resulted in travel times of minutes to hours at this flow rate. For a sorbing tracer 
like lithium, the low and late breakthrough indicates that sorption significantly delayed its 
migration (CRWMS M&O 2001 [154024], Section 6.8.9). 
6.2.2 Summary of Findings: Matrix Diffusion 
6.2.2.1 Geochemical Evidence Related to Matrix Diffusion 
It is well accepted that matrix diffusion can be a very important mechanism for the removal of 
solute/radionuclides from advective transport in the fractures in the saturated system (Freeze and 
Cherry 1979 [101173], pp. 408413; Neretnieks 1993 [123099]). This mechanism is especially 
important for the sorbing radionuclides because matrix diffusion increases the chances for the 
radionuclide to contact with the matrix sorbent, which consequently leads to their sorption.

  
  55  
Matrix diffusion will occur wherever there is a solute concentration gradient between fracture 
and matrix water; this is also true for back-diffusion, in which solute is transferred from matrix 
to fracture in response to concentration gradient. The importance of matrix diffusion in the UZ, 
however, has not been fully determined. Relevant lines of geochemical evidence presented in 
BSC 2001 [154874] have been reviewed with respect to their implications for matrix diffusion 
and solute transport. It appears that the evidence does not directly support the significant 
contribution of matrix diffusion in the UZ. On the other hand, the geochemical evidence does not 
refute the occurrence of matrix diffusion. Basically, this is related to the constraints of 
geochemical studies, as discussed below: 
. The sampling and analysis protocol for geochemical studies might be one of the major 
reasons for the lack of direct evidence of matrix diffusion. As the pore water is 
extracted from the rock samples, it homogenizes the diffusion concentration profiles, 
while the measurable chemical/isotopic tracer concentration might be only in the 
centimeter range from the fracture-matrix interface (see the discussion of Section 
6.5.2.1). 
. Very few pore-water analyses have been performed on the densely welded samples, 
because the low porosity (and hence low storage of water) does not yield sufficient 
sample size for analysis. It happens that, in the densely welded tuff, fractures exist in 
large numbers and significantly affect flow and transport because of the large 
permeability contrast between fractures and matrix. 
. Fracture water percolating through the UZ has not been sampled at Yucca Mountain 
(BSC 2001 [154874], Section 6.10.3.3), and this makes it difficult to obtain the direct 
and convincing evidence required to interpret matrix diffusion from the geochemical 
studies. Specific measurements of the concentration profile in the matrix from the 
flowing fractures are required to investigate matrix diffusion in the unsaturated 
fractured rocks. 
. The chemical/isotopic tracer source term is very difficult to constrain in the 
geochemical studies that use natural tracers. Well-defined tracer tests are necessary 
(Section 6.2.3). 
. Mass transfer between the fractures and rock matrix can occur by imbibition, because 
of the capillary pressure gradient (from fractures to the matrix) as well as matrix 
diffusion in response to the concentration gradient (in both directions between the 
fractures and matrix). Matrix imbibition, if it occurs, will mask and overwhelm the 
contribution of matrix diffusion. 
There are no available reports about the direct geochemical measurements of matrix pore water 
and adjacent fracture water at Yucca Mountain. The only related data were presented by 
Thordarson (1965 [106585], pp. 7580), who reported a marked difference in the salinity (i.e., 
dissolved solids) of the matrix pore and fracture water in zeolitized bedded tuff in Rainier Mesa 
and its vicinity at the Nevada Test Site. The specific conductance of the matrix pore water is 25 
to 35 times (with the corresponding salinity roughly 18 to 30 times) greater than that of water 
perched in fractures. Note that these are average values, instead of discrete comparisons between

  
  56  
matrix water and that in the adjacent flowing fracture. The difference, which indicates limited 
interaction between fracture and matrix water, was explained to be related to differences in the 
residence time of the matrix pore water and fracture water, or to relatively saline matrix pore 
water at the time of its introduction into the tuff (Thordarson 1965 [106585], pp. 7580). 
Nevertheless, the current approach to matrix diffusion (CRWMS M&O 2000 [141389]) is 
supported by the analyses of flow and transport tests in Alcove 1 (CRWMS M&O 2000 
[122797], Section 6.8.1). Alcove 1 is located near the North Portal of the ESF in the upper 
lithophysal zone of the TCw. The tests involved water application at the ground surface and 
seepage observation in Alcove 1 approximately 30 m below. At a second stage of the tests, a 
conservative tracer, bromide, was introduced into the infiltrating water. Hydrological properties 
calibrated to earlier seepage data were used in the tracer simulation. The simulated breakthrough 
curve closely matches the tracer concentration data and suggests the importance of matrix 
diffusion in delaying tracer transport. 
6.2.2.2 Approach to Representing Tortuosity Factor in Matrix Diffusion Evaluation 
The effective diffusion coefficient (De), which is the product of D0, tortuosity factor (., . < 1) 
and water content (i.e., porosity . and water saturation Sw), is used to account for rock geometry 
and saturation effects on matrix diffusion. The . value describes the tortuous nature of pore 
networks, including dead-end pores and steric hindrance (in extremely narrow pores). In most 
cases, only the porosity of geological media can be easily determined while the . values are 
unknown. This is also true for the YMP, because there are very limited experimental data on the 
. distribution in the various Yucca Mountain geologic units. Only the diffusion in a few saturated 
devitrified tuffs has been experimentally conducted. 
Since aqueous diffusion is analogous to electrical conductivity in porous media, a relationship 
similar to Archies law (Archie 1942 [154430]) (i.e., an empirical correlation describing 
electrical conductivity in porous rocks) should be able to predict . based solely on ., as shown 
below (Grathwohl 2000 [141512], pp. 2835, Eq. 2-33). (Note that Grathwohls symbol . for 
porosity is replaced by . and . as defined is 1/.f as used by Grathwohl): 
. = . m-1 (Eq. 1) 
where m denotes the empirical Archies law exponent. The concentration gradient that gives rise 
to the diffusive flux in this case is analogous to the electrical field. Grathwohl (2000 [141512], 
pp. 2835) has compiled the observed m values in the literature. The m value varies between 1.8 
and 2.0 in consolidated materials, and is 1.3 in unconsolidated sand. For a typical . value of 0.4 
for sandy materials, . will be 0.76 for the m value of 1.3, which is consistent with reported . 
values in sandy materials (e.g., Hu and Brusseau 1994 [122837]). In diffusion experiments with 
sedimentary rocks, values of m are observed to be close to 2 (i.e., . = .). Generally, in materials 
of low porosity (e.g., < 0.2), larger values of m (. 2) are found (Grathwohl 2000 [141512], pp. 
2835). 
The approach of using the porosity value to approximate tortuosity was confirmed 
experimentally with the tested Yucca Mountain tuff samples under saturated conditions. From

  
  57  
3H2O diffusion experiments in six devitrified tuff samples, a . estimate of 0.0806  0.035 was 
obtained for the tuff with the measured average porosity being 0.0767  0.019 (Hu and Brusseau 
1995 [122846]; CRWMS M&O 2000 [144331], Section 6.1.2.4); with the m value close to 2. 
This approach is expected to be applicable for the saturated system or where water saturation is 
high (e.g., tuff matrix in the welded units). 
Less information exists on the effect of water content on effective diffusion coefficient in the 
tuff. Conca and Wright (1990 [101582]) determined De values for K+ ions for a variety of water 
contents and grain sizes on angular gravels. For volumetric water contents ranging from 0.5% to 
6%, the De ranged from 10-14 m2/s to 10-11 m2/s (i.e., the dependence was much stronger than 
what could be expected from a linear relationship between De and water content). At low 
moisture contents, many of the pores can be separated by thin films of liquid on the surfaces of 
the particles that surround empty pores, through which diffusion is evidently very slow. Rowell 
et al. (1967 [154646]) found that very little movement of chloride in a sandy loam soil occurred 
at moisture contents lower than 0.075. The tortuosity factor was 1 . 10-6, 1.8 . 10-4, and 
9.9 . 10-3 at moisture contents of 0.013, 0.034, and 0.067, respectively. At higher moisture 
contents, the impedance factor increased in an almost linear relationship to the moisture content. 
The effects of water content, as well as the contribution of surface and internal waters to 
diffusion in porous tuff, deserve more attention. Diffusion models, which relate the effective 
diffusion coefficient to water content, porosity, and other parameters (such as suggested by 
Millington and Quirk (1961 [139143]) and Olesen et al. (1996 [155700])) can be employed in 
modeling diffusion in unsaturated media. 
6.2.2.3 Testing to Reduce Uncertainty in Matrix Diffusion 
The following tests should help to further evaluate matrix diffusion related to the conceptual 
models for the UZ Flow and Transport Model. 
1. Field testing of matrix diffusion and transport: tests planned in YMP 2001 [155724] 
are specifically designed to validate a matrix diffusion conceptual model, wherein 
liquid tracers will be introduced into the enhanced characterization of repository block 
(ECRB) Alcove 8 and monitored 20 m below in Niche 3 in the ESF. The tests are to 
demonstrate the importance of matrix diffusion by using multiple nonsorbing tracers 
with different diffusivities. If matrix diffusion is important, it will be critical to 
accurately determine the fracture-matrix interface area that largely determines the 
degree of matrix diffusion. This area has been roughly estimated from fracture 
mapping data and has never been confirmed from the flow and transport data. Tracertest 
results from Alcove 8/Niche 3 tests will estimate the fracture-matrix interface area 
under both saturated and unsaturated conditions. 
2. Laboratory testing of matrix diffusion and transport: tracer tests are to be performed in 
a tuff block of 0.11.0 cubic meter in size to complement the larger-scale 
Alcove 8/Niche 3 field tests. The fracture network in the block will be characterized 
by mapping and flow testing (both gas and liquid). An appropriate background water 
(e.g., J-13 water) with and without a series of nonreactive tracers, each with different 
diffusivities, will be introduced to the top of the block to investigate matrix diffusion 
during seepage in the unsaturated, fractured system. Rates of water addition and

  
  58  
collection, tracer concentration, and other parameters will be monitored. Rock samples 
perpendicular to fractures will be collected, and tracer penetration into the matrix from 
fractures will be examined to provide a direct measure of matrix diffusion. Using 
models to analyze the data, the fracture-matrix interface area will also be evaluated. 
3. Fracture water percolating through the UZ has not been sampled at Yucca Mountain. 
Fracture water is likely to have compositions similar to or even more chemically 
evolved than runoff samples, considering the interactions that take place during 
infiltration through calcite- and opal-rich soils and possible silicate/water interaction 
that occurs within the nonwelded tuffs of the PTn. To fully evaluate and interpret 
geochemical and isotopic information in the context of UZ flow and transport (e.g., 
matrix diffusion), fracture water needs to be collected and its chemical composition 
analyzed. Protocols need to be developed to collect reliable fracture water samples. 
6.2.3 Conclusions and Recommendations 
This subsection presents a synthesis of available geochemical information at Yucca Mountain to 
support the conceptual models used by the UZ Flow and Transport Model. The following 
conclusions can be drawn from this section: 
1. Vertical trends of ion concentrations (chloride, sulfate, sodium) in the different 
hydrogeologic units suggest at least some component of lateral flow within the 
nonwelded units. The increase in pore-water 87Sr/86Sr in the PTn tuff suggests enhanced 
water-rock interaction. The shift in dominance from divalent to monovalent cations 
reflects the ion-exchange reactions with zeolites in the CHn unit. Busted Butte tests 
show that vitric CHn exhibits strong capillary forces and matrix-dominated flow and 
tracer transport. Chloride concentrations in pore water suggest low infiltration (avg. ~6 
mm/yr) with even lower percolation at depth (0.6.3.3 mm/yr). 
2. Carbon-14 activities in PTn and CHn pore waters suggest that their apparent ages range 
from modern to 5,200 years. The general trends of 14C data indicate that average travel 
times through the UZ are on the order of 5,000 to 10,000 years. Perched water analysis 
has yielded dates ranging from 3,500 to 11,000 years (from 14C data) and from 2,000 to 
12,000 years (from 36Cl/Cl data). 
3. Bomb-pulse 36Cl and 3H indicate that faults/fracture zones can serve as fast flow 
pathways. However, most of the water moves much more slowly through the matrix. 
Lack of bomb-pulse tracers in perched water suggests no more than a small component 
of fast-flow water. 
4. Because of the constraints of the geochemical studies, available geochemical evidence 
does not directly support or disprove the significance of matrix diffusion in the UZ. 
Tests are suggested to evaluate matrix diffusion conceptual models for the UZ Flow 
and Transport Model.

  
  59  
6.3 COMPARISON OF TRANSPORT-COMPUTATION METHODS 
Modeling transport processes, especially in dual-permeability media, can be very complex. 
Conservative simplification of the transport processes is used in order to increase computational 
efficiency. For the UZ at Yucca Mountain this has generally meant neglecting the complex 
interaction of early time matrix diffusion and flow between fractures and matrix, or completely 
neglecting early time matrix diffusion altogether. In Section 6.3.1, codes previously used for 
transport modeling and a newly developed code are evaluated with respect to predicting transport 
at Yucca Mountain. In Section 6.3.2, flow and transport predicted by two matrix discretization 
schemes are evaluated with particular attention paid to early time diffusion. 
6.3.1 Comparison of Transport Codes 
Modeling 3-D chemical transport in unsaturated, heterogeneous, fractured porous media such as 
the UZ of Yucca Mountain is a challenging task in terms of both scientific basis and computing 
resources. The current models used in transport calculations are developed using the software 
codes T2R3D V1.4 (LBNL 1999 [113942]), FEHM Particle Tracker V2.0 (used in TSPA-SR, 
CRWMS M&O 2000 [153246]), and DCPT V1.0 (LBNL 1999 [132448]) (used in Analysis 
Comparing Advective-Dispersive Transport Solution to Particle Tracking, CRWMS M&O 2000 
[141389]). T2R3D V1.4 (LBNL 1999 [113942]) is based on the integral finite-difference method 
of solving advection-dispersion equations (LBNL 1999 [113942]). FEHM Particle Tracker V2.0 
uses the node-based particle-tracking method (CRWMS M&O 2000 [141418]) while DCPT 
V1.0 (LBNL 1999 [132448]) uses the random-walk-particle-tracking method (LBNL 1999 
[132448]). The models developed using these three codes are based on the same dualpermeability 
grid with the steady-state flow field calculated using TOUGH2 V1.4 (LBNL 2000 
[146496]). 
The dual-permeability grid consists of two overlapped meshes that represent the fracture and the 
matrix continua, respectively, in a dual-continuum approach. The dual-continuum approach 
conceptualizes the flow and transport in fractured porous media as two spatially overlapping and 
interactive subprocesses (Figure 6.3-1). Global flow and transport can take place in both the 
fracture and the matrix continua, while mass transfer between the fractures and the matrix occurs 
locally in every grid cell. The major advantage of the dual-continuum model is its ability to 
capture the macro features of the flow and transport in the fractured porous rock with minimum 
computational resources. In the following subsections, each of these three codes and modeling 
approaches are described; inherent characteristics of each are presented.

  
  60  
Fractured Rock 
Fracture/Matrix Interaction 
Flow & Transport in Fracture Flow & Transport in Matrix 
Figure 6.3-1. Schematic of the Dual-Continuum Model 
6.3.1.1 Current Modeling Codes 
6.3.1.1.1 T2R3D V1.4 
T2R3D V1.4 (LBNL 1999 [113942]) uses an integral finite-difference method to solve the 
advection-dispersion equations based on the dual-continuum grid. It treats the fracture-matrix 
interaction as an additional connection between the fracture grid node and the matrix grid node. 
The local mass transport between the fractures and the matrix is calculated using a 
finite-difference approximation, whereas both the interface area and the nodal distance are 
calculated based on the geometrical features of the fracture system (LBNL 1999 [113942]). It is 
capable of incorporating the anisotropy of the dispersion tensor. The primary dependent variable 
is the mass fraction, expressed on grid nodes. After tracers, representing radionuclides, released 
into the fracture continuum, the concentration gradient at the fracture-matrix interface is sharper 
near the front boundary of the tracer plume than further away from the front. But the finitedifference 
approximation of the concentration gradient at the fracture-matrix interface [used in 
T2R3D V1.4 (LBNL 1999 [113942])] does not make this distinction and uses instead a fixed 
node distance, and the average concentration in the matrix block, to calculate the diffusive flux at 
the fracture-matrix interface. Such average values account for the average behavior of the 
fracture-matrix mass exchange, but the small-scale features of the concentration gradient are 
missed. This discretization error could lead T2R3D V1.4 (LBNL 1999 [113942]) to significantly 
underestimate diffusive flux at early time, which results in overestimation of breakthrough at the 
water table for cases with small molecular diffusion coefficients and large fracture spacing. 
T2R3D V1.4 (LBNL 1999 [113942]) avoids this problem by making use of a Multiple 
Interactive Continua (MINC) or similar grid, which further splits the matrix gridblock into 
multiple nested sub-blocks. Using a more detailed grid would result in decreased efficiency of 
the simulations, and may not be acceptable for large-scale and multiple-realization transport

  
  61  
calculations used in the PA calculations of the Yucca Mountain UZ. In addition, the question of 
how to connect submatrix blocks of the MINC grid in the global matrix water flow field remains 
a difficult problem. Another disadvantage of T2R3D V1.4 (LBNL 1999 [113942]) is that it may 
suffer numerical dispersion and mixing, especially for cases with a coarser grid such as those 
likely to be used in the TSPA calculation. 
6.3.1.1.2 FEHM V2.0 
FEHM V2.0 uses the residence time/transfer function (RTTF) approach for tracking particles 
that calculates the probability of the residence time for a particle in a cell, as well as the 
probability of which adjacent cell the particle will enter if it leaves the current cell (CRWMS 
M&O 2000 [141418]). This approach is based upon analogies between the cumulative 
probability distribution function of the residence time and relative concentration as a function of 
time for a cell with a given flow path length (to account for diffusion/dispersion). In FEHM 
V2.0, particles can move between nodes only via advection. The residence time of a particle in a 
cell is calculated in two stages. It is first calculated as the ratio of the fluid mass in the cell to the 
sum of the outlet mass flow rates from the cell. Then it is used as a scaling factor to calculate a 
new residence time from a dimensionless residence time, to account for the diffusion/dispersion 
processes between nodes in the same continuum. The dimensionless residence time is 
determined randomly based on the cumulative probability distribution function of the residence 
time equivalent to a 1-D analytical solution of the advection-dispersion equation for the cell 
(with a step input function). A similar approach is used to determine the modified residence time 
that accounts for the effects of the fracture-matrix diffusion process for the particles in the 
fracture continuum. 
The cumulative probability distribution function is based on an analytical solution for a dualporosity 
system (i.e., where there is no water flow through the matrix or the fracture-matrix 
interface). The reason for this two-stage approach in FEHM V2.0 is to provide a more rapid 
calculation method that also avoids the discretization errors associated with large matrix grid 
cells. Note that the residence time from the first modification stage (accounting for the 
diffusion/dispersion in the same continuum) is a random value, but will be used to characterize 
the fracture-matrix transport system (i.e., the ratio of travel length along a fracture over the porewater 
velocity in the fracture) in the second modification stage (accounting for diffusion between 
fracture and matrix). This implies that different fracture-matrix transport systems can exist for 
particles entering the same cell. 
How the introduction of randomness into the fracture-matrix transport system affects the overall 
simulation of the transport is not theoretically clear. However, numerical experiments show that 
this effect may lead FEHM V2.0 to underestimate the increase in residence time due to diffusion 
into the matrix of particles traveling in the fractures (CRWMS M&O 2000 [134732], Section 
6.2.5). For the particles in the matrix continuum, the fracture-matrix diffusion process is 
neglected in FEHM V2.0. In principle, the fracture-matrix diffusion process should increase the 
residence time for the particles traveling in the fracture continuum and decrease the residence 
time for the particles traveling in the matrix continuum, when the pore-water velocity in the 
fracture continuum is higher than that in the matrix continuum. (Velocities in the fractures are 
typically larger than those in the matrix by several orders of magnitude.) As a result, FEHM 
V2.0 can either underestimate or overestimate the breakthrough of nuclides to the water table,

  
  62  
depending on particular scenarios. Numerical experiments confirm this observation as shown in 
Particle Tracking Model and Abstraction of Transport Processes (CRWMS M&O 2000, 
[141418], Section 7) and FY01 Supplemental Science and Performance Analysis, Volume 1: 
Scientific Basis and Analysis (BSC 2001 [155950]). Furthermore, although FEHM V2.0 avoids 
the 1-D numerical dispersion by incorporating a 1-D analytical solution, it is not free from 
numerical mixing caused by multiple dimensional discretization and particle residence times. 
6.3.1.1.3 DCPT V1.0 
DCPT V1.0 (LBNL 1999 [132448]) simulates the transport of a plume by tracking the random 
walk of particles in a continuous 3-D space. However, the velocity field and other parameters are 
expressed on the grid nodes (grid cell-wise constant). A full dispersion tensor is incorporated. 
Particles travel either in the fractures or in the matrix. In DCPT V1.0 (LBNL 1999 [132448]), the 
mass exchange between the fractures and the matrix is simulated as a random-switch process 
between two continua controlled by the particle-transfer probabilities. This model is based upon 
analogies between the particle-transfer probabilities (either from fracture to matrix or vice versa) 
and the mass flux through the fracture-matrix interface with respect to the mass amount in each 
continuum. The approach is similar to the residence time/transfer function (RTTF) method used 
in the particle-tracking algorithm of FEHM V2.0. The difference is that DCPT V1.0 (LBNL 
1999 [132448]) calculates the probability of a particle leaving the current continuum after a 
given duration, while FEHM V2.0 calculates the probability of how much time a particle will 
spend in a given cell. Although the continuum-switching of each particle is statistically 
independent of other particles, the calculation of the particle-transfer probabilities needs 
parameters describing the fracture-matrix system based on an approximation of the concentration 
gradient at the fracture-matrix interface. 
In this regard, the concentration gradient at the interface will decrease as the particles diffuse 
farther into the matrix with time. DCPT V1.0 (LBNL 1999 [132448]) does not consider this 
dynamic feature, and uses the same approximation of the concentration gradient at the interface 
as that in T2R3D V1.4 (LBNL 1999 [113942]) to derive the solution of the particle-transfer 
probability. Thus, it has the same problem with dual-permeability grids as T2R3D V1.4 (LBNL 
1999 [113942]). The transport calculation results found for these codes agree with each other 
(CRWMS M&O 2000 [141389]). However, DCPT V1.0 (LBNL 1999 [132448]) is free of 
numerical dispersion and mixing because the particles move in a continuing space. On the other 
hand, the pore water velocity is not available at every point except for some simple cases where 
an analytical solution of velocity is available. For the UZ of the Yucca Mountain, the velocity 
fields are calculated using TOUGH2 V1.4 (LBNL 2000 [146496]) on a discretized space 
(numerical grid). The exact velocity is unknown and has to be estimated from the flux on the 
interfaces between gridblocks. In multidimensional, heterogeneous, fractured porous media, 
accurate estimation of the velocity field from the fluxes on the interfaces remains a difficult 
problem for random-walk particle-tracking methods such as DCPT V1.0 (LBNL 1999 [132448]). 
6.3.1.1.4 Methodological Uncertainties 
Despite progress in understanding and modeling transport in fractured porous media, and the 
advances in computer resources in the past few decades, simulating transport of a tracer in 
heterogeneous fractured porous media is still a challenge. One of main difficulties is how to

  
  63  
simulate the mass transfer between fractures and matrix, two subdomains often having very 
different velocities. A discrete-fracture-network model, which describes the detailed spatial 
structure of a fracture-matrix transport system, is not feasible for the real-world problems such as 
those in the UZ of Yucca Mountain, because of the high requirements in both computer 
resources and field-measured data (parameters). Therefore, a dual-continuum approach is used in 
current models to numerically simulate the UZ transport system. However, discretization errors 
may be a significant problem when mass transfer between fractures and the matrix is mainly 
controlled by a slow diffusion process into a large matrix block (i.e., large fracture spacing, small 
fracture-matrix interface, and small diffusion coefficient), especially at early times (for example 
as shown in Figure 6.3-5). 
The net effect is underestimation of the mass transfer flux into the matrix at early times, which 
usually makes the model (i.e., T2R3D V1.4 (LBNL 1999 [113942]), DCPT V1.0 (LBNL 1999 
[132448])) a conservative predictor in the repository performance evaluation. FEHM V2.0 tends 
to avoid this discretization problem by using an analytical solution for a dual-porosity transport 
system. However, its implementation biases the calculation of the residence time because it 
excludes the diffusion process for the particles that entered the matrix via advection and ignores 
the differences in concentration gradients between early and later times. It may also introduce 
other uncertainties related to extending the 1-D analytical solutions for a dual-permeability 
system in which global water flow exists in both continua. The analytical solution on which it is 
based applies to a dual-porosity system where there is no flow through the matrix or the fracturematrix 
interface. As a result, it can be either a conservative or an optimistic predictor in the 
repository performance evaluation, depending on particular scenarios. 
The challenge is how to model the mass transfer between the fractures and the matrix within the 
framework of the dual-continuum approach, without missing the small-scale features of the 
diffusion front between the fractures and the matrix. 
6.3.1.2 Improved Modeling Approach: DCPT V2.0 
As discussed above, the dual-continuum model is a practical approach for simulation of the UZ 
transport, but it may be over-conservative. The reason is because the finite-difference 
approximation used to calculate mass transfer between fractures and the matrix may be subject to 
significant discretization errors for the cases with a larger matrix block. Recently, Pan and 
Bodvarsson (2001 [155875]) proposed a more accurate model for the fracture-matrix mass 
transfer within the framework of the dual-continuum random walk particle method (RWPM) by 
introducing the concept of active range to calculate particle transfer probability. Active range is 
defined as a function of particle age (the time since the particle first entered the domain) to 
capture the slower process of propagation (diffusion) of a disturbance in the fracture in the 
matrix without adding any additional sub-blocks for the matrix (as the MINC approach does). 
The following section describes the details of the model and its underlying theory. 
6.3.1.2.1 Description of DCPT V2.0 
The fracture-matrix mass transfer is simulated by tracking the particles transferred in either 
direction between the fractures and the matrix. This transfer is governed by the particle transfer 
probability. Equivalent to the finite-difference approximation for calculation of the mass transfer

  
  64  
rate between the fractures and the matrix, the particle transfer probability from Continuum 1 to 
Continuum 2 can be determined as (Pan and Bodvarsson 2001 [155875], Equation 5a or 5b and 
A7after substitution of equivalent symbols): 
)] / exp( [1 c 
out 
12 
12 
12 T t 
F F 
F P . . . 
. 
. (Eq. 1) 
where F12 is a parameter that describes the combined strengths of the water flow and the 
diffusion process through the interface between two continua. It is defined as follows (Q12 = 
qfmA12) (Pan and Bodvarsson 2001 [155875], Equation 6a or 6b): 
12 
12 12 
12 12 ) 0 , max( 
S 
A D Q F . . (Eq. 2) 
where the effective dispersion coefficient at the fracture-matrix interface is D12 = Dfm.m, the 
fracture-matrix interface area is A12, the characteristic distance of the fracture-matrix system is 
S12, and .m is volumetric water content in the matrix. Fout is a parameter that is the sum of the 
total water outflow from the cell to adjacent cells and the strength of the dispersion process 
through their interfaces through Continuum 1 (Pan and Bodvarsson 2001 [155875], Equation 6b 
or 6e). The strength of the dispersion process can be calculated like the second term of Equation 
2, but for each interface with the adjacent cells in the same continuum instead of the fracturematrix 
interface. Tc is the characteristic time of Continuum 1 and is defined as a function of the 
water body volume in the cell (V0), the retardation factor. (R) based on .d and defined in 
Equation 2 of Pan and Bodvarsson (2001 [155875]), F12, and Fout (of Continuum 1) (Pan and 
Bodvarsson 2001 [155875], Equation 6c or 6f): 
out 12 
0 
F F 
R V 
Tc 
. 
. (Eq. 3) 
Equation 1 shows that the particle transfer probability is a function of the time step .t, but not t 
itself. In other words, the particle transfer process is assumed to be a stationary random process 
(i.e., the probability density function is independent of time). This is because the concentration 
gradient at the fracture-matrix interface can be represented as the difference of the average 
concentrations in the fractures and the matrix divided by the node spacing (a fixed characteristic 
distance). In terms of particle walking, this is equivalent to assuming that the particles in a given 
pulse will have the same range to walk within the matrix over time. However, this is not a proper 
assumption at early times, when a plume has just entered the domain. Physically, a pulse in the 
fracture only has limited influence in the matrix at early times; significant time will be needed 
for the pulse to have its full range of influence, especially for cases with larger fracture spacing. 
As depicted in Figure 6.3-2 (lower part), the probability density function of the particle becomes 
wider and flatter with increasing time (t3 > t2 and t2 > t1). To catch this dynamic feature, the 
particle transfer probability defined in Equation 1 with Equation 2 and Equation 3 has to be 
modified by introducing a new concept: the active range. The active range is defined for each 
pulse such that the probability of finding a particle of the pulse outside of the range is practically 
zero; that is, all particles are confined to this spatial range over a time step. This leads to the 
replacement of the characteristic distance S12 and the water body volume V0 in Equations 2 and 3

  
  65  
with the effective distance S12(t) and the effective volume V0(t), both of which are related to the 
active range. For parallel fracture systems, they can be defined as: 
B
t B S t S ) ( ) ( 12 12 
. 
. (Eq. 4) 
and 
B
t B V t V ) ( ) ( 0 0 
. 
. (Eq. 5) 
where B*(t) is the active range within the matrix at time t. B is defined such that 2B is the fracture 
spacing. The effective volume for the fractures is assumed to be constant because the fracture 
aperture is usually so small that the active range can quickly reach its full capacity. 
2B 
2b 
Porous Matrix Porous Matrix Porous Matrix 
Fractures 
s 
C 
t1 
t2 
t3 
Figure 6.3-2. Schematic of the Propagation of a Pulse in Fracture-Matrix System with Time 
To get a scheme for estimating the active range B*(t), consider the transport in a system of 
parallel-plate fractures separated by porous rock (Figure 6.3-2). By the superposition principle, 
only the one-dimensional governing equation (in fracture-matrix dimension) is needed to derive 
the active range (temporarily ignoring advection): 
. . . .
.
. 
. .
.
. 
.
. 
.
. 
. 
.
. 
s 
C D 
s 
C R 
t 12 (Eq. 6) 
where s is the distance into the matrix. With sources (and ignoring the fracture aperture 2b 
because b is much smaller than B) (Pan and Bodvarsson 2001 [155875], Equation 7):

  
  66  
) 2 ( 0) , ( s B i s M s C . . . (Eq. 7) 
where .(s - 2iB) is a Dirac delta function whose value is zero everywhere except for an infinite 
value at point zero, which makes initial concentrations nonzero at the fractures only. The term Ms 
is a scaling factor that makes the concentration, C, in the final solution become a dimensionless 
variable within a range between 0 and 1. The i is the index of the fracture (from 0 to infinite). 
The solution to Equation 6, subject to Equation 7 follows the example of Bear (1988 [101379], 
Equation 10.6.10) for a single source (Pan and Bodvarsson 2001 [155875], Equation 8). For s . 0 
and using symmetry: 
.
.
. 
. 
. . 
0 i 12 
2 
1/2 
12 
s ) 
/ 4 
) 2 ( exp( 
) / (4 
2 
) , ( 
R t D 
B i s 
R t D
M t s C 
. 
(Eq. 8) 
For very small time, only the first term in the series need be considered (Pan and Bodvarsson 
2001 [155875], Equation 9): 
) 
/ 4 
exp( 
) / (4 
2 
) , ( 
12
2 
1/2 
12 
s 
R t D
s 
R t D
M t s C . . 
. 
(Eq. 9) 
The concentration in Equation 9 can be interpreted as the probability of finding a particle 
(initially at s = 0) at location s and time t. Therefore, the probability a particle will be located in 
the active range [0, B*] is found by integrating Equation 9 with respect to s from 0 to B* (Pan 
and Bodvarsson 2001 [155875], Equation 10): 
) 
4 
( erf ) (0 
12 R / t D
B B s P 
. 
. . . . (Eq. 10) 
Equation 10 implies that B* should be proportional to the square root of t. By definition, a B* 
should be selected such that P(0 	 s 	 B*) is close to 1. An adequate active range for short time 
can be expressed as (Pan and Bodvarsson 2001 [155875], Equation 11): 
. . B R t D t B , / 4 4 min ) ( 12 . 
. (Eq. 11) 
The corresponding P(0 	 s 	 B*) is close to 1 and B is half of the fracture spacing, which is the 
maximum active range by definition. 
For a longer time, B* approaches B, and the other terms in Equation 8 cannot be ignored. There is 
no simple solution like Equation 9 for that case. However, because the purpose is to get a proper 
B*(t), can be taken as the relative effects of the other terms in Equation 8 on the active range are 
equal to their relative contributions to concentration. In other words, the active range can be 
modified as follows (Pan and Bodvarsson 2001 [155875], Equation 12): 
. . B t W R t D t B ), ( / 4 4 min ) ( 12 . 
. (Eq. 12)

  
  67  
The weighting function W(t) is obtained as the ratio of the two-term solution over the one-term 
solution as defined in Equation 8 at a given B*, and can be approximated as (Pan and Bodvarsson 
2001 [155875], Equation 13): 
. . 
R t D 
B B B 
t W 
/ 
1 
1 1 ) ( 
12 
. 
. 
. 
. . (Eq. 13) 
The reason for taking only two terms in calculating the weighting function is because further 
terms are insignificant for typical values of B. 
A similar approach can be used to incorporate the effects of fracture-matrix water flow on the 
active range. In a dual continuum model, the total water flow rate through the interface is known 
at s = 0) and at s = B (where Q is zero). One can take a linear interpolation and get the final 
scheme for the active range as (Pan and Bodvarsson 2001 [155875], Equation 14): 
. .
.
. 
. .
.
. 
. .
.
. 
. .
.
. 
. . 
. 
. B 
B 
B 
A 
t Q t W R t D t B - 1 ) ( / 4 4 min ) ( 
12 
12 
12 (Eq. 14) 
Note that the time, t, used in the above equations is for a single pulse. Multiple initial values of 
time (i.e., t = 0) have to be defined for cases with multiple pulses. In other words, for the same 
pair of fracture and matrix cells at the same simulation time, the particle transfer probability may 
be different for different individual particles depending upon which pulse they originated in. The 
implementation in DCPT V2.0 (LBNL 2001 [154342]) tracks the age of each particle, which is 
defined as the time elapsed since the particle was released into the domain. Thus, the particle 
transfer probability is a function of the age of the particle. 
The above derivation of the active range is valid only for particles initially released in the 
fractures. The active ranges for particles released into the matrix would be different, and depend 
on how far from the interface they are initially located, which is not known in practice. It is 
assumed that all particles initially released into the matrix are uniformly distributed within the 
matrix, and thus the active range will always be B. A parameter called initial status is assigned 
to each particle to distinguished which continuum it is released into initially (at tp=0) where tp is 
the age of the particle. 
6.3.1.2.2 Verification with Analytical Solutions (Parallel Fractures) 
An analytical solution for solute transport in fractured porous media with parallel fractures 
(Figure 6.3-3) was derived by Sudicky and Frind (1982 [105043]) with solute transport between 
fractures and matrix occurring through matrix diffusion in the horizontal direction only, and 
ignoring the matrix advection and diffusion in the vertical direction. In this dual-porosity model, 
water enters and leaves only via the fracture. Table 6.3-1 shows the relevant parameters for the 
test cases 1 and 2 with fracture spacing 1 m and 10 m, respectively. The values used, Table 
6.3-1, are representative of typical values used for Yucca Mountain Modeling (see assumptions 
listed in Section 5.3). The analytical solution is obtained using parallelf.java V1.0 (LBNL 2001 
[154346]).

  
  68  
This work is further documented in Pan (2001 [155954], pp.142145). The grid used for the 
DCPT simulations is generated using WINGRIDDER V2.0 (LBNL 2001 [154785]). 
Table 6.3-1. Transport Parameters for a Parallel Fracture System 
Parameter Value 
Molecular diffusion coefficient 2.5.10-11 m2 /s 
Fracture spacing 1.0 m (Case 1) or 10.0 m (Case 2) 
Retardation factor 30 
Velocity in fracture 1.1574.10-5 m/s (1.0 m/d) 
Grid spacing 0.5 m 
Matrix volume per cell 0.25 m3 (Case 1) or 25.0 m3 (Case 2) 
Fracture volume per cell 0.5.10-5 m3 
Fracture-matrix interface area 0.5 m2 
Domain length (vertical) 36.75 m 
DTN: LB0104AMRU0185.014 
In Figures 6.3-4 through 6.3-6, results are shown in the form of breakthrough curves at the 
bottom of the model. These calculations are for a step increase in concentration at the top of the 
model, and the breakthrough curves are normalized concentration C/Co. Figure 6.3-4 shows that 
for Case 1 (1 m fracture spacing) both DCPT V1.0 (LBNL 1999 [132448]) and DCPT V2.0 
(LBNL 2001 [154342]) give breakthrough curves that agree well with the analytical solution 
(Note: CalBT.for V1.0 (LBNL 2001 [154788]) is a required preprocessor for DCPT V1.0 (LBNL 
1999 [132448])). However for fracture spacing =10 m (Case 2, Figure 6.3-5), DCPT V1.0 
(LBNL 1999 [132448]) overestimates the breakthrough at early times. The breakthrough curve 
reaches approximately 60% as early as 0.1 year (the earliest arrival, not shown in the figure). At 
much later times, however, DCPT V1.0 (LBNL 1999 [132448]) agrees well with the analytical 
solution. This phenomenon clearly indicates that the finite-difference approximation is accurate 
only for later times; the degree of the problem depends on the fracture spacing. DCPT V2.0 
(LBNL 2001 [154342]) agrees nearly perfectly with the analytical solution in both cases because 
it catches the dynamic feature of the fracture-matrix mass transfer process. Additionally, the 
fracture spacing should have little effect at early times for this case, according to Equations 13 
and 14. Figure 6.3-6 depicts the analytical solutions for Case 1 and Case 2 and shows that the 
early time breakthrough curve (until 5,000 years) is independent of the fracture spacing.

  
  69  
matrix matrix 
fracture 
fracture 
fracture 
diffusion 
Water flow 
Figure 6.3-3. Schematic of a Parallel Fracture System without Water Flow between the Fractures and 
the Matrix 
102 103 104 105 
TIME (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
C/C0 
Analytical 
DCPT V2.0 
DCPT V1.0 
Fracture Spacing = 1 m 
DTN: LB0104AMRU0185.001 
Figure 6.3-4. The Predicted Breakthrough by DCPT V1.0 (LBNL 1999 [132448]) and DCPT V2.0 
(LBNL 2001 [154342]) and the Analytical Solution for the Case with 1 m Fracture Spacing

  
  70  
102 103 104 105 106 
TIME (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
C/C0 
Analytical 
DCPT V2.0 
DCPT V1.0 
Fracture Spacing = 10 m 
DTN: LB0104AMRU0185.001 
Figure 6.3-5. The Predicted Breakthrough by DCPT V1.0 (LBNL 1999 [132448]) and DCPT V2.0 
(LBNL 2001 [154342]) and the Analytical Solution for the Case with 10 m Fracture 
Spacing 
102 103 104 105 106 
TIME (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
C/C0 
F-Spacing = 1m 
F-Spacing = 10 m 
DTN: LB0104AMRU0185.001 
Figure 6.3-6. The Effect of Fracture Spacing on the Breakthrough as Function of Time (analytical 
solution)

  
  71  
6.3.1.2.3 Results: UZ transport 
The case of TSPA UZ transport with the present-day mean infiltration map and Perched Water 
Table Model #1 is used to assess the impact of the different models of the fracture-matrix mass 
transfer. The grid for the transport simulations is created using DTN: LB0110MESHPROP.001 
[156336] and Wingridder V1.1 (LBNL 2001 [154341]). Input files for DCPT are created using 
DNTs: LB990801233129.003 [122757]; LB9907012333129.001 [106785] and TOUGH2 V1.4 
(LBNL 2000 [146496]). Figure 6.3-7 shows the cumulative breakthrough curves of two 
radionuclides at the water table predicted by the current model (DCPT V1.0 (LBNL 1999 
[132448])) and the more-refined model (DCPT V2.0 (LBNL 2001 [154342])), respectively. The 
current model predicts faster early breakthrough compared to the more refined model for both 
radionuclides, especially for the conservative radionuclide. 
100 101 102 103 104 105 106 107 
TIME (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Cumulative Mass (m/m0) 
NP--DCPT1 
TC--DCPT1 
NP--DCPT2 
TC--DCPT2 
TSPA99 (present daymean infiltration) 
DTN: LB0104AMRU0185.001 
Figure 6.3-7. The Predicted Cumulative Breakthrough Curves for Base Case of the UZ Transport 
System by DCPT V1.0 (LBNL 1999 [132448]) and DCPT V2.0 (LBNL 2001 [154342]), for 
Sorbing (Np) and Non-sorbing (Tc) Tracers 
6.3.1.3 Conclusions 
Well-controlled experiments related to transport in unsaturated, fractured porous rock will be 
necessary to verify the numerical model and to deepen our understanding of the fracture-matrix 
mass transfer process. No analytical solution has ever been developed in the literature for 
transport in unsaturated fractured porous media with global water flow occurring in both 
continua, no such experiments have been performed either. An example of a well-controlled 
experiment could be a lab experiment of tracer with a large-enough block (1 m3) of fractured 
rock. This experiment is important for building an accurate numerical model because many 
aspects of the fracture-matrix interaction process are still unknown. Many numerical experiments

  
  72  
show that the fracture-matrix mass transfer is a critical process that controls how fast 
radionuclides migrate to the water table. 
Development of numerical models for flow and transport with higher spatial resolution is another 
necessary task in reducing the prediction uncertainty. The current numerical models use rather 
coarse grids (vertically up to 60 m and laterally up to 200 m) because of limitations on 
computational resources. T2R3D and FEHM may suffer multidimensional numerical mixing 
caused by the coarser grids, while DCPT may suffer inaccurate interpolation of the pore velocity 
field. Furthermore, a coarse grid is expected to allow TOUGH2 to underestimate the capillary 
effects in the case where the critical layers are thin, which will lead to very different flow fields 
and transport pathways for nuclides. In such a complex and heterogeneous media as the UZ, the 
effects on radionuclide travel time could be very large. Calculation of detailed flow fields within 
the UZ needs parallelization of TOUGH2. Considerable effort is also required to develop particle 
trackers that can simulate transport with large grids very efficiently. 
6.3.2 Matrix Block Discretization and its Effects on Unsaturated Zone Flow and 
Transport Simulations 
Because fractures and the matrix have very different hydraulic properties, flow and transport 
between them significantly affect the overall flow and transport behavior in the UZ. 
Consequently, the accuracy for calculating flow and transport between them, largely determined 
by the matrix block discretization schemes, is a critical issue for simulating overall flow and 
transport processes and for assessing the performance of the potential repository. As discussed in 
the AMR Conceptual and Numerical Models for UZ Flow and Transport (CRWMS M&O 2000 
[141187], Section 6.4), a dual-permeability model (DKM) has been used in the UZ Flow and 
Transport Model as the baseline approach for the matrix block discretization. This was based on 
considerations regarding flow and transport behavior in the UZ, scale of the problem, data 
availability, and computational feasibility (CRWMS M&O 2000 [141187], Section 6.4.2). 
In the DKM, the matrix is treated as a single continuum (as will be discussed in this section). 
Therefore, capillary pressure and concentration gradients between fractures and the matrix are 
presented using a single-matrix-node approximation that cannot accurately describe the steep 
fronts near fracture-matrix interfaces. This issue is especially important for modeling matrix 
diffusion and radionuclide transport in the UZ. The objectives of this study are as follows: 
. Evaluate the DKM for modeling UZ flow and transport by comparing simulation 
results obtained with the DKM with a more accurate matrix block discretization 
scheme. 
. Make recommendations of possible actions for improving the currently used matrix 
discretization schemes, based on the simulation results. 
6.3.2.1 Matrix Block Discretization 
In the continuum approach, each gridblock within a given model domain generally includes a 
fracture block and a matrix block. Depending on the matrix block discretization scheme used for 
a numerical simulation, the matrix block can either be treated as a single matrix gridblock or

  
  73  
further subdivide into a number of matrix gridblocks. Several matrix-block discretization 
schemes within the context of the continuum approach are available in the literature for modeling 
flow and transport in unsaturated fractured rock (Doughty 1999 [135997], pp. 7479). Typical 
schemes include the effective-continuum model (ECM) (Pruess et al. 1990 [100819]), the dualporosity 
model (Warren and Root 1963 [100611]), the DKM, and the multiple interacting 
continua (MINC) model (Pruess and Narasimhan 1985 [101707]). These schemes are illustrated 
in Figure 6.3-8 for a one-dimensional column of gridblocks. 
In the ECM (Figure 6.3-8(a)), liquid saturation is partitioned into the matrix and fracture in 
accordance with the principle of thermodynamic equilibrium, which requires that capillary 
pressure in the matrix and fracture components of a gridblock be equal. This is equivalent to 
assuming that flow and transport between fractures and the matrix occurs instantaneously. In 
other words, both fractures and the matrix are combined as a single continuum in a numerical 
simulation. 
In the dual-porosity model (Figure 6.3-8 (b)), each gridblock includes a fracture gridblock and a 
matrix gridblock. Unlike the ECM, the fracture and matrix gridblocks need not be in 
thermodynamic equilibrium. Therefore, in this approach, flow and transport occurs between 
fractures and the matrix, but is ignored between matrix gridblocks. The DKM is the same as the 
dual-porosity model, except that global flow and transport between matrix blocks is allowed 
(Figure 6.3-8 (c)). 
The schemes mentioned above can give rise to poor solutions for transient flow and transport in 
unsaturated fractured rocks because of the thermodynamic equilibrium assumption (in the ECM) 
and the use of one matrix gridblock (in the other two schemes) (Doughty 1999 [135997], pp.74 
79). These schemes cannot accurately consider the highly transient flow and transport between 
fractures and the matrix. To overcome this problem, Pruess and Narasimham (1985 [101707]) 
proposed the multiple interacting continua (MINC) model (Figure 6.3-8 (d)), which is similar to 
the DKM except that the matrix is further subdivided into several continua, depending on the 
distances to the fracture-matrix interface. Specifically, all fractures will be lumped into a fracture 
continuum (as in the dual-porosity model and the DKM), all matrix material within a certain 
distance from the fractures will be lumped into matrix continuum #1, matrix material at larger 
distance becomes matrix continuum #2, and so on. In other words, the matrix block is subdivided 
into a number of matrix gridblocks. The MINC can more accurately resolve sharp gradients near 
the fracture-matrix interface and is therefore more suitable for modeling transient flow and 
transport.

  
  74  
M22
M21 
M23 
M12 
M11 
M13 
M32
M31 
M33 
M42
M41 
M43
M52
M51 
M53 
F1 M1 
F2 M2 
F3 M3 
F4 M4 
F5 M5 
F1 M1 
F2 M2 
F3 M3 
F4 M4 
F5 M5 
F1 
F2 
F3 
F4 
F5 
F1 
F2 
F3 
F4 
F5 
(a) (b) (c) (d) 
Figure 6.3-8. Schematic Diagram of a One-dimensional Column of Gridblock, Modeled as (a) ECM, (b) 
Dual-porosity, (c) Dual-permeability, and (d) MINC with Three Matrix Continua 
(Gridblocks) 
Although the MINC is more accurate than the other schemes, it needs much more computational 
effort because more matrix gridblocks are involved for a given fracture block. Therefore, the 
DKM has been used as the baseline approach in the UZ flow and transport models. To evaluate 
the accuracy of the DKM in modeling flow and transport in UZ, simulation results obtained from 
the DKM are compared with those obtained from a MINC model (Figure 6.3-9). In this MINC 
model, a fracture network is conceptualized as two perpendicular sets of vertical fractures, and 
the matrix is divided into five matrix continua (gridblocks), as shown in Figure 6.3-9. Ratios of 
the distances (from interfaces between the matrix continua to the fracture-matrix interface) to the 
corresponding fracture spacing are 0.004, 0.032, 0.108 and 0.256, respectively. Very fine 
discretization is used near the fracture-matrix interface. All the matrix continua are globally 
connected in the vertical direction. In the horizontal directions, only the first matrix continuum is 
globally connected while the connection parameters (e.g., node distance and interface area) are 
the same as those in the DKM for the same fracture configuration.

  
  75  
Matrix Continua 
Vertical Fractures
1 2 
3 
4 
5 
NOTE: Not to scale 
Figure 6.3-9. Matrix Discretization for the MINC Scheme Used in this Study 
6.3.2.2 Numerical Simulations 
Because a simulation with the MINC approach is computationally intensive, a site-scale, twodimensional 
(2-D) cross section was employed for all the simulations in this study (Figures 6.3- 
10 and 6.3-11). The cross section was selected because the vitric Calico Hills Formation is not 
present in this location, such that matrix diffusion was expected to be a significant mechanism 
for radionuclide transport between fractures and the matrix below the potential repository. In the 
vitric Calico Hills formation (characterized by porous medium flow), diffusion from fractures to 
matrix is no expected to be significant. Simulation results are compared for the two matrix block 
discretization schemes (the DKM and the MINC). The initial and boundary conditions for flow 
and transport, together with rock properties, remain the same in all the simulations. The DKM 
and MINC grids were generated using a subroutine MINCgridv1.f V1.0 (LBNL 2001 [154343]) 
from an ECM grid (DTN: LB0110AMRU0185.015) generated with WINGRIDDER V2.0 
(LBNL 2001 [154785]). The analysis is documented in the related scientific notebook (Liu 1999 
[155675], pp. 129141).

  
  76  
239000 
238000 
237000 
236000 
235000 
234000 
233000 
232000 
231000 
230000 
229000
168000 170000 172000 174000 
a 
A A' 
Easting in meters 
Northing in meters 
Figure 6.3-10. Plan View of the UZ Model Domain Showing the Location of East-West Cross Section 
A-A' Used in Numerical Simulations

  
  77  
Figure 6.3-11. Two-dimensional Numerical Grids for the East West Cross Section A-A' 
The top model boundary for the 2-D vertical cross-sectional model domain coincides with the 
bedrock surface of the mountain. Surface net infiltration is applied to the top boundary using a 
source term for flow and transport simulations. The present-day infiltration map (DTN: 
GS000399991221.002 [147022]), the fracture geometry (DTN: LB990501233129.001 
[106787]), and the calibrated, base-case, UZ property set (DTN: LB997141233129.001 
[104055]) were used in this study. The infiltration map is interpolated onto the top boundary 
using Infil2grid V1.6 (LBNL 1999 [134754]). The bottom boundary is located at the water table. 
Zero flow flux in the horizontal direction is applied at the left and right boundaries. The steady 
state flow fields were simulated with the EOS9 module of TOUGH2 V1.4 (LBNL 2000 
[146496]), which solves Richards equation. Transport runs were carried out by the T2R3D code 
V1.4 (LBNL 1999 [113942]). 
In the tracer transport simulations, a conservative (nonadsorbing) component is transported from 
the potential repository to the water table under steady-state flow conditions. As initial condition, 
all tracer mass is in water in the fracture continuum in the potential repository. The simulation 
results for tracer transport are represented by the cumulative mass of tracer arriving at the water 
table over time, normalized by the total initial mass introduced at the potential repository. For the 
cross section under consideration, the potential repository is located between Nevada east 
coordinates 170152.36 m and 171304.17 m. The elevation of the potential repository ranges from 
1050.6 m to 1055.8 m. Hydrodynamic dispersion does not have a significant effect on solute 
transport through the unsaturated fracture-matrix system, as discussed in an AMR UZ Flow 
Models and Submodels (CRWMS M&O 2000 [122797], Section 6.8.1) and is therefore ignored 
herein. Two molecular diffusion coefficients, 0 and 3.2 . 10-11 m2/s, were used in the simulations 
for all model layers. The latter is consistent with the matrix molecular diffusion coefficients for 
Tc reported in the AMR Unsaturated Zone and Saturated Zone Transport Properties (U0100) 
(CRWMS M&O 2001 [154024], Table 16).

  
  78  
6.3.2.3 Results and Discussions 
Figures 6.3-12 and 6.3-13 show comparisons between simulated results obtained with the DKM 
(solid line) and the MINC (circles), respectively, for the two vertical columns (a14 and a23) from 
the 2-D cross section. These two columns intercept the potential repository horizon. The 
simulated matrix saturations are in good agreement for the two schemes of matrix block 
discretization, indicating that, under steady-state flow conditions, the whole matrix block can be 
treated as a single continuum, as used in the DKM. This is further supported by the observation 
that with the MINC, all five matrix continua have almost the identical water saturations and 
potentials (Figure 6.3-14). In other words, all five matrix continua are hydraulically in 
equilibrium, consistent with the assumption used in the DKM. This is not surprising considering 
that the matrix has small van Genuchten alpha (or very strong capillarity) and flow between 
different matrix continua is purely determined by the capillary forces. Note that the gravity term 
is not involved in a horizontal connection between matrix continua (Figure 6.3-9). 
0 0.2 0.4 0.6 0.8 1 
Saturation 
700 
800 
900 
1000 
1100 
1200 
1300 
1400 
1500 
Elevation (m) 
TCw 
PTn 
TSw 
CHn 
CFu 
10-6 10-5 10-4 10-3 10-2 10-1 100 101 
Fracture flux (mm/yr) 
700 
800 
900 
1000 
1100 
1200 
1300 
1400 
1500 
Elevation (m) 
TCw 
PTn 
TSw 
CHn 
CFu 
DTN: LB0104AMRU0185.002 
NOTE: The column is located at point (170250 m, 235087 m) in Cross section A-A. 
Figure 6.3-12. Comparisons Between Simulation Results Obtained Using the DKM (solid line) and the 
MINC (circles) for a Vertical Column a14

  
  79  
0 0.2 0.4 0.6 0.8 1 
Matrix saturation 
800 
900 
1000 
1100 
1200 
1300 
1400 
Elevation (m) 
TCw 
PTn 
TSw 
CHn 
10-6 10-5 10-4 10-3 10-2 10-1 100 
Fracture flux (mm/yr) 
800 
900 
1000 
1100 
1200 
1300 
1400 
Elevation (m) 
TCw 
PTn 
TSw 
CHn 
DTN: LB0104AMRU0185.002 
NOTE: The column is located at point (171150 m, 235087 m) in Cross section A-A. 
Figure 6.3-13. Comparisons Between Simulation Results Obtained Using the DKM (Solid Line) and the 
MINC (circles) for a Vertical Column a23 
0 1 2 3 4 
Distance from the fracture/matrix interface (m) 
0
1
2
3
4
5 
- Capillary pressure (1.E5 Pa) 
Fracture 
Matrix Continuum 
#1 #2 #3 #4 #5
DTN: LB0104AMRU0185.002 
Figure 6.3-14. Capillary Pressure Distribution within a Matrix Block at Elevation of 
923 m for Column s14

  
  80  
Figures 6.3-12 and 6.3-13 also show comparisons between simulated distributions of water flux 
in fractures for the two vertical columns. While a fairly good agreement is achieved between the 
DKM and the MINC, fracture flux (liquid flux in the fractures) in the PTn is estimated by the 
DKM to be higher. This is likely to be because a steep capillary-pressure gradient exists near the 
fracture-matrix interface, although capillary-pressure is nearly uniform within a matrix block 
(e.g., Figure 6.3-14). In a conventional DKM, the connection distance between nodes 
corresponding to the fracture and matrix gridblocks is determined based on the method of 
Warren and Root (1963 [100611]). For a fracture network given in Figure 6.3-9, this connection 
distance is calculated as the fracture spacing divided by a factor of 8 (Warren and Root 1963 
[100611]; Pruess 1983 [100605], Table 1). This is considerably larger than the connection 
distance between the fracture gridblock and the matrix gridblock corresponding to matrix 
continuum #1 in the MINC scheme (Figures 6.3-9 and 6.3-14). Because calculated flux decreases 
as the connection distance increases, the DKM may underestimate the flux from fractures to the 
matrix and therefore overestimate the fracture flux. 
The above discussion is also consistent with the finding presented in the Unsaturated Zone Flow 
and Transport Model Process Model Report (CRWMS M&O 2000 [151940], Figure 3.6-9). The 
current site-scale UZ model based on the DKM might overestimate fracture flow in the vitric 
part of the CHn. (In the cross section shown in Figure 6.3-11, there is no vitric part in the CHn.) 
The PTn and the vitric part of the CHn have similar rock hydraulic properties. The current UZ 
model predicts about 20% of liquid water occurring in fractures within this vitric part (CRWMS 
M&O 2000 [151940], Figure 3.6-9). However, tracer tests from the Busted Butte site clearly 
indicated that unsaturated flow occurs only in the matrix in the vitric part of the CHn (see 
Section 6.5.1). 
While very similar fracture flux distributions in the TSw are obtained using the two schemes for 
matrix block discretization, fracture fluxes are higher in the CHn and CFu for the DKM 
estimates (Figures 6.3-12 and 6.3-13). Compared with the TSw, these units have relatively small 
fracture permeabilities and large effective fracture-matrix interface areas indicated by the small 
values of active fracture parameter 
 (DTN: LB997141233129.001 [104055]). A combination of 
these factors and the fine discretization of the matrix block results in a larger flux from fractures 
to the matrix and consequently smaller fracture fluxes for the MINC scheme than those for the 
DKM. The differences in fracture flux are not a result of lateral flow in the relevant units, 
because very close total water fluxes (including contributions from both the matrix and fractures) 
are obtained at the water table (for each of the two columns) for both the DKM and the MINC.

  
  81  
100 101 102 103 104 105 106 
Time (year) 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Normalized tracer cumulative flux 
DKM 
MINC 
(a) 
100 101 102 103 104 105 106 
Time (year) 
0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
Normalized tracer cumulative flux 
DKM 
MINC
(b) 
DTN: LB0104AMRU0185.002 
Figure 6.3-15. Normalized Tracer Cumulative Flux at Water Table as a Function of Time for Molecular 
Diffusion Coefficient (a) Dm = 0 and (b) Dm = 3.2 x 10-11 m2/s 
Figure 6.3-15 shows simulated tracer transport results with and without diffusion (molecular 
diffusion coefficients Dm = 0 and 3.2 x 10-11 m2/s). The use of Dm = 0 allows for investigation of 
effects of pure advection. In this case (Figure 6.3-15a), both schemes correspond to very similar 
breakthrough times (less than 10 years), but different values for the tracer cumulative flux. This 
results from the differences in fracture fluxes in the CHn and CFu units, as discussed above. For 
the DKM, the majority of tracer mass is transported through fractures by advection from the 
potential repository (within TSw) to the water table, as implied by the relative uniform fracture 
flux distributions within the TSw unit and the below (Figures 6.3-12 and 6.3-13). On the other 
hand, only a relatively small portion of the tracer mass is transported through the fractures to the 
water table for the MINC scheme. 
Comparisons between simulated transport results for the two molecular diffusion coefficients 
further confirms the importance of the matrix diffusion indicated by the Alcove 1 test and 
modeling study that is discussed in the AMR UZ Flow Models and Submodels (CRWMS M&O 
2000 [122797], Section 6.8.1). For each scheme of the matrix-block discretization, significantly 
different breakthrough curves are simulated for the two different molecular diffusion 
coefficients. The comparisons also suggest the necessity to accurately consider the solute 
concentration gradient near the fracture-matrix interface. For example, similar breakthrough 
times are simulated for both matrix-block discretization schemes for Dm = 0, but significantly 
different breakthrough times are observed for Dm = 3.2 x 10-11 m2/s. This is mainly a result of 
using different discretization schemes. (Matrix diffusion is estimated by the DKM to be smaller 
at early time than it is with the MINC.) Because the MINC is expected to provide more accurate 
results, it is likely that the DKM may underestimate the breakthrough time for radionuclide 
transport from the potential repository to the water table.

  
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6.3.2.4 Conclusions and Recommendations 
The MINC simulation results show that under steady-state flow conditions, all the matrix 
continua within a given gridblock have almost the identical water saturations and potentials, 
indicating that the matrix can be treated as a single continuum. In other words, the dualpermeability 
concept is valid for modeling steady-state flow processes in the unsaturated zone of 
Yucca Mountain. 
Comparisons between simulation results indicate that the current dual-permeability approach 
may overestimate fracture fluxes in some units, resulting from a too-large connection distance 
used between the fracture and matrix gridblocks. This is consistent with the noted discrepancy 
between the previously simulated fracture fluxes in the vitric Calico Hill formation and those 
implied from the tracer test results at the Busted Butte site. It is recommended to use a reduced 
connection distance in generating DKM grids for future flow simulations. The determination of 
this reduced distance needs further investigation. 
Simulation results demonstrate the significance of matrix diffusion and accurate representation 
of concentration gradient near fracture-matrix interfaces on the overall radionuclide transport 
processes in the unsaturated zone of Yucca Mountain. Because the DKM underestimates matrix 
diffusion at the early time, it is very likely that this model provides conservative estimates of the 
breakthrough time for radionuclide transport from the potential repository to the water table. This 
issue can be resolved in future site-scale flow and transport simulation using one of the following 
three approaches: 
1. Directly use MINC for both flow and transport in the site-scale UZ model. This is the 
most reliable approach, but it is computationally intensive. 
2. Take advantage of the finding that the DKM is valid for modeling steady-state flow 
processes as long as the reduced connection distance is used. In this case, flow fields 
are simulated with the DKM and then mapped into a MINC grid. The transport is 
simulated for the MINC grid using computationally efficient T2R3D V1.4 (LBNL 1999 
[113942]) which only solves the solute transport equation. 
3. Improve the current particle trackers such that they could handle the sharp 
concentration gradient for a DKM grid and the corresponding flow fields. A detailed 
discussion of the current particle trackers and their capabilities is given in Section 6.3.1. 
6.4 PROCESSES AFFECTING SEEPAGE 
Many factors influence the amount of water that may seep into emplacement drifts. Beyond the 
primary factors of the average incident percolation flux, the hydrologic characteristics of the 
rock, and the size and general shape of the drifts, several other factors may also affect the 
amount of seepage. Seepage enhancement due to some of these other factors has been treated 
quite conservatively, while for others, no seepage enhancement has been applied. In Section 
6.4.1, seepage enhancement due to small-scale changes in drift geometry from rock fall (i.e., drift 
degradation) and rock bolts is considered, and new seepage enhancement distributions are 
proposed based on more detailed analyses as well as new properties. Sections 6.4.2, 6.4.3, and 
6.4.4 consider the effect of the detailed nature of percolation at the repository horizon. In Section

  
  83  
6.4.2, characterization of flow focusing on a scale intermediate between those of the mountain 
and drift-scale models previously used is documented, and new seepage enhancement 
distributions due to flow focusing are proposed. In Section 6.4.3, a comparison of the calibration 
of alternate model parameters against geochemical data and the resultant predictions of 
percolation distribution at repository horizon are documented. In Section 6.4.4, investigation of 
the extent of episodic percolation at the repository horizon due to infiltration directly on TSw 
outcrop west of Yucca Crest is documented, and the previously used seepage enhancement factor 
is confirmed. Except for the model used to investigate flow focusing (Section 6.4.2), the models 
and analyses presented in Section 6.4 are scoping investigations using more detailed or 
alternative approaches and are not intended for direct use in TSPA. They do, however, provide 
confirmation of the approach and conservatism used in TSPA-SR (CRWMS M&O 2000 
[153246]). 
6.4.1 Seepage Enhancement due to Drift Degradation 
Drift degradation may enhance seepage because of small-scale changes to the drift wall 
geometry. Investigations of seepage enhancement because of drift degradation at Yucca 
Mountain, which incorporate the latest calibrated properties and are more detailed than previous 
investigations, are presented here. Two issues with respect to drift degradation are addressed: 1) 
in Section 6.4.1.1, the effect of changes to drift wall shape due to rockfall in the Tptpmn and 
Tptpll are addressed, 2) in Section 6.4.1.2, the effect of changes to the drift wall shape and 
properties due to degradation of rock bolts used as ground support in Tptpmn is addressed. 
6.4.1.1 Seepage Enhancement due to Rockfall 
The objectives of this section are to calculate seepage values for different values of percolation 
flux down to the drift, to discuss the effect on seepage due to excavation-induced rockfall from 
drift ceiling in the Topopah Spring middle nonlithophysal (Tptpmn) unit and the Topopah Spring 
lower lithophysal (Tptpll) unit. 
The model used in this section follows that presented in Seepage Model for PA Including Drift 
Collapse (CRWMS M&O 2000 [153314], Sections 5 and 6) and the methodology is also 
described in Birkholzer et al. (1999 [105170], pp. 358362). The physical framework and 
mathematical construct of this model is identical to that of seepage calibration model (CRWMS 
M&O 2001 [153045], Sections 5 and 6), with the only difference being the manipulation of the 
output data to obtain seepage results. 
6.4.1.1.1 Seepage Model 
The conceptual model is a heterogeneous permeability field (DTN: LB0011SMDCREV1.001 
[153574]) for the fracture continuum generated with parameters discussed below, using the 
SISIM module of the GSLIB package (Specifically, GSLIB V2.0MSISIMV2.0 (LBNL 1999 
[154340])). The model follows that of the seepage calibration model (CRWMS M&O 2001 
[153045], Section 6) and is also described in Birkholzer et al. (1999 [105170], pp. 358362), 
which provides the scientific and technical background for this section. The 3D field is 19.22 m 
vertical, 15.25 m wide normal to drift axis, and 10.065 m along the drift axis. With the drift of 
5.5 m diameter, an overlying thickness of 8.845 m, an underlying thickness of 4.875 m, and the

  
  84  
distance to either side boundary of 4.875 m, the vertical cross-sectional dimensions were chosen 
to be wide enough to capture the main flow feature [i.e. flow diversion around the drift (Philip et 
al. 1989 [105743], p. 21, Figure 1)]. The distance along the drift axis is 10.065 m. The side 
boundary conditions are no-flow, the lower boundary condition is gravity drainage, and the 
upper boundary surface is simulated by an extra grid cell with constant percolation flux 
connected to all the grid cells in the first row. Flow is thus free to move into these cells according 
to local property parameters of these cells. Regarding the no-flow boundary condition on the two 
planes at the end of the waste package normal to the drift axis: for a homogeneous, constantproperty 
medium, these planes are symmetry planes between successive waste packages, and a 
no-flow boundary condition is justified. For a heterogeneous system, the issue is the length of the 
flow domain versus the spatial correlation length .. In the simulations below, . = 0.305 m so that 
the length of the domain is about 33 correlation lengths and the effect of the no-flow boundary 
should not have a significant effect on the flow results. The fracture continuum permeability kFC 
and the standard deviation of ln kFC will be given in the Section 6.4.1.1.2. 
The mesh consists of over 100,000 grid cells. The grid cell dimension of 0.305 m . 0.305 m . 
0.305 m is chosen to be the same as in degraded emplacement drift profiles (CRWMS M&O 
(2000 [151635]; DTN: MO0109RDDAAMRR.003 [156306]). 
The spatial correlation length . is chosen to be equal to the grid size of 0.305 m. This choice 
implies an uncorrelated spatial distribution of permeability values. This is consistent with 
CRWMS M&O (2001 [153045], Section 6.3.2.1) where . is 0.2 m, which is smaller than our 
grid size for the case of the lower lithophysal zone. The AMR, Seepage Calibration Model and 
Seepage Testing Data (CRWMS M&O 2001 [153045], Section 6.4.2.1, Figure 9), presents 
semi-variograms indicating an uncorrelated permeability structure for the middle nonlithophysal 
zone. 
At the drift wall, the nodal distance between the drift surface and the grid cell representing the 
drift is set to be very small, so that the boundary condition can be applied directly at the drift 
wall. The length of the last vertical connection between the drift wall and the neighboring 
gridblocks representing the formation is set equal to 0.05 m. This is done to make our model 
consistent with the seepage calibration model (CRWMS M&O 2001 [153045], Sections 6.3.2.2 
and 6.4.2.2), whose parameter values are used in the current calculations. The choice of this 0.05 
m vertical connection to the drift wall implies a direct gravity-controlled vertical flow, with no 
horizontal diversion within this 0.05 m distance. (This is sometimes called a needle or 
discrete surface fracture effect.) Because of this 0.05 m vertical gravity flow at the drift wall, a 
capillary pressure higher (i.e., less negative) than -490 Pa at the grid cells in the formation next 
to the drift wall will allow seepage into the drift: the -490 Pa is insufficient to balance the 
hydrostatic pressure that develops along the 0.05 m vertical connection. For 1/. values of 870 
Pa, seepage occurs when saturation in the grid cell next to the drift wall exceeds 90%. 
Flow calculation was performed using ITOUGH2 V3.2_drift (LBNL 1999 [112757]). A number 
of routines were also used for preprocessing of inputs for ITOUGH2 V3.2_drift (LBNL 1999 
[112757]). Specifically, iTOUGH2 V3.2_drift (LBNL 1999 [112757]) input files are generated 
and reformatted using the routines mddf.f V2.0 (LBNL 2001 [154347]), meshbd.f V1.0 (LBNL 
2001 [152871]), mininipresf.f 1.0 (LBNL 2001 [152872]), minrefine3df.f V1.0 (LBNL 2000

  
  85  
[152880]), and mk_generGL.f V1.0 (LBNL 2001 [154349]). Their use is described and 
documented in Li (2000 [153480], pp. 128129, 145149). 
6.4.1.1.2 Input Data 
The first parameter set, Set A, is the set of calibrated mean parameters for the middle 
nonlithophysal zone documented in Seepage Model for PA Including Drift Collapse (CRWMS 
M&O 2000 [153314]): 
kFC = 1.38 . 10-12m2 DTN: LB0010SCMREV01.002 [153393] 
1/. = 589 Pa DTN: LB0010SCMREV01.002 [153393] 
n = 2.55 DTN: LB997141233129.001 [104055] 
. = 1.93 DTN: LB0010SCMREV01.002 [153393] 
Here .=1.93 is used for both sets as a more conservative value (i.e., the greatest value for 3 
niches). 
The second parameter set, Set B, is chosen to be the set of mean calibrated parameters for the 
lower lithophysal unit documented in Seepage Model for PA Including Drift Collapse (CRWMS 
M&O 2000 [153314]): 
kFC = 1.86 . 10-11 m2 DTN: LB0010SCMREV01.002 [153393] 
1/. = 871 Pa DTN: LB0010SCMREV01.002 [153393] 
n = 2.57 DTN: LB997141233129.001 [104055] 
. = 1.93 DTN: LB0010SCMREV01.002 [153393] 
An additional parameter Set B. is defined: 
kFC = 1.86 . 10-11 m2 DTN: LB0010SCMREV01.002 [153393] 
1/. = 537 Pa DTN: LB0010SCMREV01.002 [153393] 
n = 2.57 DTN: LB997141233129.001 [104055] 
. = 1.93 DTN: LB0010SCMREV01.002 [153393] 
This parameter set B. is same as Set B, except the 1/. is reduced to account for the effects of the 
lithophysal cavities on seepage. As discussed in Seepage Calibration Model and Seepage Testing 
Data (CRWMS M&O 2001 [153045], Section 6.3.3.3), since SMPA does not include lithophysal 
cavities explicitly, it is necessary to represent this effect by a reduced 1/. value. One calibration 
case was run with and without lithophysal cavities in the model. The reduction of the log(1/.) 
value caused by the presence of lithophysal cavities is found to be 0.21 (CRWMS M&O 2001 
[153045], Section 6.3.3.3), suggesting a value of log(1/.) of 2.73, which translates to the 1/. 
value of 537 Pa. 
Based on the information presented in Drift Degradation Analysis (CRWMS M&O 2000 
[151635]), alternative drift rockfall modes are evaluated, and four scenarios are identified for 
seepage model studies.

  
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All the cases are computed for 3-D heterogeneous unsaturated systems. Because some cases 
involve more than one run, altogether more than 40 runs were made. 
Detailed discussions of fracture continuum permeability kFC, standard deviation of ln kFC, spatial 
correlation length, ., of kFC, and percolation flux are given in CRWMS M&O (2000 [141400], 
Sections 5.1 and 5.2.1). 
For our calculations, four
values for Qp are used, ranging from 14.6 to 500 mm/yr; more 
specifically Qp = 14.6, 73.2, 213 and 500 mm/yr. For the seepage model in Tptpll, where 
seepage is zero for Qp = 500 mm/yr, even larger Qp values (1000, 1500, 2000, and 2500 mm/yr) 
are used to find when seepage might occur. 
6.4.1.1.3 Impact of Rockfall on Seepage 
Drift degradation may occur in three ways: loosening of rock blocks and hence wider fracture 
aperture (fracture dilation), rock-fall from the ceiling of the drift and extended rock failure in the 
drift roof. 
In Seepage Model for PA Including Drift Collapse (CRWMS M&O 2000 [153314]), four drift 
degradation submodels were designed to evaluate the impact of drift degradation on seepage: 
fracture dilation, 1.0 m3 rockfall from the drift crown, 1.0 m3 rockfall from the spring line, and 
extended rock failure reaching 3 m depth. Table 6.4-1 presents the calculated seepage 
percentages for parameter Set A for three realizations (R1, R2 and R3) with drift degradation 
modes and compares them with the no-degradation case. Only the Qp = 500 mm/yr cases are 
shown. The results show that the effect of a single rockfall is not significant for seepage because 
of the increased likelihood of the creation of topographic lows. A deeper rock failure in the drift 
roof increases seepage. Calculations were also made with parameter Set B with the results of 
zero seepage for all cases, with or without drift degradation. 
Table 6.4-1. Seepage Percentage (%) for Alternative Drift Degradation Scenarios, for 
Qp = 500 mm/yr and Parameter Set A 
Seepage Percentage 
Condition R1 R2 R3 
No-degradation case 7.1 7.1 13 
1 m rock fall from crown of drift 7.2 7.3 12 
1 m rock fall from springline of drift 7.1 7.1 13 
3 m rock failure in drift roof 9.0 11 15 
DTN: LB0011SMDCREV1.002 [153570] 
Previous studies show that extended rock failure causes the largest impact on seepage. To make a 
more quantitative evaluation, instead of the schematic rock failure profile used earlier, detailed 
degraded-drift profiles calculated using a discrete-region key-block analysis (CRWMS M&O 
2000 [151635]; DTN: MO0109RDDAAMRR.003 [156306]) were used. The key-block analysis 
provides the following detailed 3-D profiles, using 0.305 m (1 foot) grid size.

  
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For Topopah Spring middle nonlithophysal unit (Tptpmn): 
(1) Worst degradation (largest rockfall volume) drift profile 
(2) Profile at 75th percentile 
(3) No degradation (91.9% of stochastically-generated cases). 
For Topopah Springs lower lithophysal unit (Tptpll): 
(1) Worst degradation (largest rockfall volume) drift profile 
(2) Profile at 75th percentile 
(3) No degradation (99.6% of stochastically-generated cases) 
For the Tptpmn, 91.9 percent of the drift length exhibits no drift degradation. Of the 8.1 percent 
that does exhibit degradation, the 75th percentile means that 75 percent of the 8.1 percent has a 
rockfall volume less than that shown in the 75th percentile drift profile. Similarly for Tptpll, 0.4 
percent (100 percent to 99.6 percent) of the drift length exhibits drift degradation, with the 75th 
percentile profile indicating that 75 percent of 0.4 percent of the drift length has a rockfall 
volume that is less than that shown. 
A typical example of the detailed degraded drift profile is shown in Figure 6.4-1 for the worst 
degradation case in the Tptpmn unit. 
Degraded emplacement drift profiles are generated for four cases: Tptpmn worst-case profile, 
Tptpmn 75 percentile profile, Tptpll worst-case profile, and Tptpll 75 percentile profile 
(CRWMS M&O 2000 [151635]; DTN: MO0109RDDAAMRR.003 [156306]).

  
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DTN: MO0109RDDAAMRR.003 [156306] 
Figure 6.4-1. Emplacement Drift Profile for the Tptpmn Unit, Worst Case

  
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DTN: MO0109RDDAAMRR.003 [156306] 
Figure 6.4-2. Emplacement Drift Profile for the Tptpmn Unit, 75 Percentile Case 
DTN: MO0109RDDAAMRR.003 [156306] 
Figure 6.4-3. Emplacement Drift Profile for the Tptpll Unit, Worst Case

  
  90  
DTN: MO0109RDDAAMRR.003 [156306] 
Figure 6.4-4. Emplacement Drift Profile for the Tptpll Unit, 75 Percentile Case 
Based on these discussions, four seepage models were designed to evaluate the impact of 
rockfall on seepage, and it is calculated for four alternative scenarios. 
6.4.1.1.4 Results 
Seepage percentage is defined as the ratio of liquid that seeped into the drift to the total liquid 
arriving on a cross-sectional area corresponding to the footprint of the drift. (Note that this term 
is defined differently in the seepage calibration model (CRWMS M&O 2001 [153045], Section 
6.1.2), where it is defined in reference to the total water released in the liquid release tests). All 
results and the input/output files for the model computation are submitted to TDMS under DTNs 
LB0104AMRU0185.011 and LB0104AMRU0185.003, respectively. The SN supporting this 
work is Bodvarsson (2001 [156334], YMP-LBNL-CFT-GL-2, pp. 2267). 
Table 6.4-2 presents seepage percentages for three realizations for parameter Set A (Section 
6.4.1.1.2) and four percolation rates.

  
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Table 6.4-2. Seepage Percentage (%) for Alternative Drift Degradation Scenarios, for parameter Set A 
Qp (mm/yr) 14.6 73.2 213.4 500 
R1 0.0 0.0 0.46 5.69 
R2 0.0 0.0 0.82 11.04 
R3 0.0 0.0 0.15 10.71 
Base Case 
Average 0.0 0.0 0.48 9.15 
R1 0.0 0.0 0.48 8.97 
R2 0.0 0.0 0.86 13.99 
R3 0.0 0.0 0.34 12.58 
Worst Case 
Average 0.0 0.0 0.56 11.85 
R1 0.0 0.0 2.87 1.63 
R2 0.0 0.0 3.39 17.53 
R3 0.0 0.0 2.36 16.50 
75 % Case 
Average 0.0 0.0 2.87 14.89 
DTN: LB0104AMRU0185.011 
0 100 200 300 400 500 
Percolation-flux(mm/y) 
0
5 
10 
15 
20 
Seepage-rate(%) 
Tptpmn Unit, worst case 
Tptpmn Unit, 75 percentile case 
Tptpmn Unit, base case
DTN: LB0104AMRU0185.011 
Figure 6.4-5. Seepage Percentage as a Function of Percolation Flux QP for the Two Degradation 
Scenarios for Parameter Set A, Realization 1

  
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0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
15 
Y 
Sliq 
0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-6. Saturation Distribution around a Drift for the Worst Case in the Tptpmn with 
Parameter Set A, Realization 1 
0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
15 
Y 
Sliq 
0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-7. Saturation Distribution around a Drift for the 75 Percentile Case in the Tptpmn with 
Parameter Set A, Realization 1

  
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0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
15 
Y 
Sliq 
0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-8. Saturation Distribution around a Drift for No-Degradation Case in the Tptpmn with 
Parameter Set A, Realization 1 
The results in Table 6.4-2 show that the effect of rockfall on seepage into drift for the Tptpmn 
unit (parameter Set A). A series of percolation flux values were used up to 500 mm/yr to explore 
the effect of drift degradation on seepage threshold. Figure 6.4-5 shows the calculated seepage 
percentage as a function of percolation flux Qp, Realization 1. It is seen in this figure that the 
effect of drift degradation for the scenarios decreases with decreasing Qp, so that its impact on 
seepage threshold is relatively small. This can perhaps be explained by the fact that, under 
vertical percolation flux, the seepage threshold depends significantly on the horizontal cross 
section (footprint) of the drift, so that, if the cross-sectional area does not change very much, the 
seepage threshold also will not change very much. 
The results of Realization 1 also indicate that seepage enhancement ranges from 05 percentage 
points for Qp up to 500 mm/yr due to drift degradation for the worst case and 75 percentile case. 
The enhancement does not seem to be dependent on whether it is worst case (i.e., largest 
rockfall) or 75 percentile. The shape of the cavity in the ceiling may be more important than the 
volume. Confirming calculations were performed by using a homogeneous medium and it shows 
that more seepage obtained for the 75 percentile case. 
Figures 6.4-6, 6.4-7, and 6.4-8 illustrate the saturation profile around the drift for two 
degradation scenarios and the no-degradation case in the Tptpmn unit with parameter Set A, 
Realization 1. The figures clearly show the degradation effect on the seepage into the drift. 
Table 6.4-3 presents the seepage percentages of three realizations for parameter Set B. 
representing the lower lithophysal unit with drift degradation modes, worst degradation case and

  
  94  
degradation at 75 percentile, and compares them with the no-degradation case. Here, because of 
the low seepage, values of Qp up to 2500 mm/yr were needed. 
Table 6.4-3. Seepage Percentage (%) for Alternative Drift Degradation Scenarios, for 
Parameter Set B. 
Qp (mm/yr) 500 1000 1500 2000 2500 
R1 0.0 0.0 0.33 0.55 0.83 
R2 0.0 0.0 0.50 1.05 2.09 
R3 0.0 0.0 0.0012 1.03 2.86 
Base Case 
Average 0.0 0.0 0.28 0.88 1.93 
R1 0.0 0.2 0.65 1.42 2.41 
R2 0.0 0.0 1.50 3.04 4.56 
R3 0.0 0.0 0.11 1.94 4.25 
Worst Case 
Average 0.0 0.07 0.75 2.13 3.74 
R1 0.0 0.0 0.33 0.59 1.24 
R2 0.0 0.0 0.50 1.06 2.32 
R3 0.0 0.0 0.33 1.36 3.10 
75 % Case 
Average 0.0 0.0 0.39 1.00 2.22 
DTN: LB0104AMRU0185.011 
0 500 1000 1500 2000 2500 
Percolation-flux(mm/y) 
0
1
2
3
4
5 
Seepage-rate(%) 
Tptpll Unit, worst case 
Tptpll Unit, 75 percentile case 
Tptpll Unit, base case 
DTN: LB0104AMRU0185.011 
Figure 6.4-9. Seepage Percentage as a Function of Percolation Flux QP for the Two Degradation 
Scenarios for Parameter Set B., Realization 1

  
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0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
15 
Y 
Sliq 
0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-10. Saturation Distribution around a Drift for the Worst Case in the Tptpll with 
Parameter Set B., Realization 1 
0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
15 
Y 
Sliq 
0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-11. Saturation Distribution around a Drift for the 75 Percentile Case in the Tptpll with 
Parameter Set B., Realization 1

  
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0
5
10 
15 
20
Z 
0 
2 
4 
6 
8 
10 
X 
0 
5 
10 
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0.95 
0.8 
0.6 
0.5 
0.4 
0.2 
0.05 
DTN: LB0104AMRU0185.011 
Figure 6.4-12. Saturation Distribution around a Drift for No-Degradation Case in the Tptpll with 
Parameter Set B., Realization 1 
The results in Table 6.4-2 show the effect of rockfall on seepage into drift in the Tptpll unit. 
Figure 6.4-9 shows the calculated seepage percentage as a function of percolation flux Qp, 
Realization 1. The results indicate that the seepage threshold is not significantly affected by drift 
degradation, up to two percentage points. Figures 6.4-10, 6.4-11, and 6.4-12 illustrate the 
saturation profile around the drift for two degradation scenarios and the no-degradation case in 
the Tptpll unit with parameter Set B., Realization 1. 
Figures 6.4-13 and 6.4-14 show the spread of the drift seepage in the Tptpmn and Tptpll units 
from the three realizations. For the base case, the 75th percentile case, and the worst case, with 
the percolation flux value of 500 mm/yr, the seepage spread is between 5 and 7 percentage points 
in the Tptpmn and around 2 percentage points in the Tptpll unit.

  
  97  
0 100 200 300 400 500 
Percolation-flux(mm/y) 
0
5 
10 
15 
20 
Seepage-rate(%) 
Tptpmn,worst case:mean 
Tptpmn,worst case: top spread 
Tptpmn,worst case: bottom spread 
Tptpmn,75% case:mean 
Tptpmn,75% case: top spread 
Tptpmn,75% case: bottom spread 
Tptpmn,base case:mean 
Tptpmn,base case: top spread 
Tptpmn,base case:mean 
DTN: LB0104AMRU0185.011 
Figure 6.4-13. Seepage Spread from Three Realizations in the Tptpmn Unit 
0 500 1000 1500 2000 2500 
Percolation-flux(mm/y) 
0
1
2
3
4
5 
Seepage-rate(%) 
Tptpll,worst case:mean 
Tptpll,worst case: top spread 
Tptpll,worst case: bottom spread 
Tptpll,75% case:mean 
Tptpll,75% case: top spread 
Tptpll,75% case: bottom spread 
Tptpll,base case:mean 
Tptpll,base case: top spread 
Tptpll,base case: bottom spread 
DTN: LB0104AMRU0185.011 
Figure 6.4-14. Seepage Spread from Three Realizations in the Tptpll Unit 
Calculations were also made with parameter Set B that resulted in zero seepage for all cases with 
the percolation flux up to 2500 mm/yr, with or without drift degradation.

  
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6.4.1.1.5 Conclusions 
Four scenarios of detailed degraded drift profiles, calculated using a discrete region key-block 
analysis (CRWMS M&O 2000 [151635]; DTN: MO0109RDDAAMRR.003 [156306]), were 
selected for conducting seepage calculations. The model has been refined over previous studies 
(CRWMS M&O 2000 [153314]) both by use of 3-D key-block analysis (replacing prior 
schematic 2-D rock-failure profiling), and by incorporation of a revised set of calibrated mean 
parameters for the Tptpll unit. 
Results in this section are based on seepage calibration model results and a review of available in 
situ field results appropriate to the Tptpmn lithostratigraphic unit and one set of data for the 
Tptpll unit. As more data from these units (where the potential repository resides) are obtained in 
field measurements, parameter values (with their uncertainties and probability weightings) 
should be developed and then seepage predictions from tables in this AMR can be used in PA to 
obtain the best estimates (with uncertainty ranges) for Yucca Mountain. 
Uncertainty associated with geostatistics is evaluated through calculations using three 
realizations for each case. Results are shown in Tables 6.4.1.1-2 and 6.4.1.13. The spread of 
results from the three realizations gives an indication of geostatistical variation. 
In summary, this section demonstrates that the impact of drift degradation and flow-field 
heterogeneity can be evaluated. Generally, for both the Tptpmn and Tptpll units, simulated 
seepage enhancement because of drift degradation is calculated, with larger effects for larger 
percolation flux values. Seepage enhancement resulting from rockfall is between 0 and 5 
percentage points in all three realizations for the Tptpmn unit, and less than 2 percentage points 
for the Tptpll unit. The enhancement does not seem to be dependent on whether it is worst case 
(i.e., largest rockfall) or 75 percentile. The shape of the drift cavity may be more important to 
drift seepage than the volume of rockfall. These scoping calculations confirm that the approach 
used for seepage enhancement due to drift degradation in TSPA-SR (CRWMS M&O 2000 
[153246]) is conservative. 
6.4.1.2 The Effect of Rock Bolts on Seepage 
Using grouted rock bolts is one proposed method of ground support for the emplacement drifts in 
the Tptpmn. Rock bolts are lengths of steel that are grouted into a borehole normal to the drift 
wall. They accomplish two purposes: (1) binding the mass of rock above the drift to prevent 
large rockfalls, and (2) providing an anchoring point for a steel mesh, which is placed against the 
drift wall to prevent raveling (small rock falls). 
Rock bolts present a concern with respect to seepage because they may provide a direct flow 
conduit to the drift wall, and if so, they will increase the likelihood that a flowing fracture will be 
intersected and that flow will be diverted to the drift wall to become seepage. This simple model 
of the effect of rock bolts on seepage is illustrated in Figure 6.4-15. Flow along Path A, which 
may be considered a flowing fracture, is diverted around the drift, while flow along Path B 
intersects the rock bolt, which provides a direct conduit to the drift wall.

  
  99  
A B 
Figure 6.4-15. Simple Model Schematic of Rock Bolt Impact on Seepage 
6.4.1.2.1 Rock Bolt Model 
A more complete model of the effect of rock bolts will consider several other factors, including: 
. The properties of degraded grout and/or rock bolt material, including the case in which 
the rock bolt and grout are completely removed from the hole such that the rock-bolt 
hole is itself a capillary barrier 
. The dimensions of the rock bolt and grout 
. Uncertainty in the hydraulic properties of the formation 
. A range of percolation rates 
. The possibility for lateral diversion away from the rock bolt at or near the drift wall 
. Rock bolt density and orientation(s). 
Figure 6.4-16 shows a sketch of the conceptual model for rock bolt interaction with percolation, 
which may enhance seepage. Flow along a fracture may encounter a rock-bolt hole and either be 
diverted around the hole or enter the hole. How much enters the hole and how much is diverted 
around it depends on the dimensions of the hole, the angle of the fracture with respect to the 
hole, the rate of flow, channeling of flow in the fracture, the hydraulic properties of the grout (if 
any), filling the hole, and the local saturation of the grout. Flow that enters the hole will not 
necessarily result in seepage. The head (or reduction in capillary pressure) at the collar of the 
hole (i.e. where the hole intersects the drift wall) may not be sufficient to induce seepage,

  
  100  
especially if there are pathways for the water to flow back into the formation and be diverted 
around the drift. Similarly, if seepage would already be occurring without the presence of rock 
bolts, sufficient diversion capacity may exist such that the rock bolts will not increase seepage. 
rock-bolt hole 
inclined fracture 
drift wall 
seepage? 
fractured rock 
NOTE: Possible paths of percolating water are shown by arrows. 
Figure 6.4-16. Conceptual Model Schematic of Rock Bolt Impact on Seepage 
Previous treatment of rock bolts as a seepage enhancing factor, documented in the AMR Seepage 
Model for PA Including Drift Collapse (CRWMS M&O 2000 [153314], Section 6.7), considered 
only an extremely simplified model for rock bolts in order to study their effect on seepage. The 
rock bolts were modeled as needles extending from the drift wall (the last grid node before the 
drift wall) vertically downward into the drift, unlike a bolt hole, which extends upward away 
from the drift. Because the needle is a single connection, no opportunity occurs for lateral flow 
away from the needle near the drift wall. The size and properties of this node were unmodified 
with respect to the surrounding grid. This is in contrast to an actual rock-bolt hole, which would 
have a significantly smaller horizontal cross section and, depending on the properties of the 
material in the hole (or lack thereof), might create a permeability or capillary barrier and divert 
flow. These simplifications are likely to significantly impact the results. Seepage enhancement 
was found to stabilize for a needle length of 0.150.25 m. The seepage enhancement for one 
needle was found to be 3%. 
The proposed use of ground support is documented in the AMR Ground Control for 
Emplacement Drifts for SR (BSC 2001 [155187]). The proposed rock bolt and grout dimensions 
are 3 meters long (BSC 2001 [155187], Section 6.5.1.2.2), with a rock bolt diameter of 0.0254 m 
(1 inch) and a grout annulus thickness of 0.00635 m ( inch) (BSC 2001 [155187], Table 4-10). 
The rock bolts are proposed to be emplaced with a lateral spacing of 1.5 m (BSC 2001 [155187], 
Section 6.5.1.2.2). The properties and expected longevity of the rock bolt and grout system is

  
  101  
documented in (BSC 2001 [155667], Section 6.4.3.1). The design permeability of the newly 
emplaced grout is less than 10-19 m2 (10-12 m/s) (BSC 2001 [155667], Section 6.4), and its 
expected life at that permeability is 300 years (BSC 2001 [155667], Section 6.4) 
A refined model that includes a range of properties for the grout and the formation, as well as a 
range of percolation rates, has been prepared. Figure 6.4-17 shows a sketch of the model. The 
model uses a two-dimensional, radially symmetric grid with a vertical symmetry axis generated 
using the software iTOUGH2 V4.0 (LBNL 1999 [139918]). Grid size is 10 cm, with finer 
discretization, down to 0.1 mm, at the interface between the grout and the surrounding rock. 
Because this is a radially symmetric grid, the drift opening, created using the routines MoveMesh 
V1.0 (LBNL 2000 [152824]) and CutNiche V1.3 (LBNL 2000 [152828]), is spherical instead of 
cylindrical. Knight et al. (1989 [154293], p. 37) find that seepage exclusion from a cylindrical 
cavity is similar to that of a spherical cavity of twice the radius. This is explained by relating the 
seepage exclusion potential of an opening to the total curvature of the boundary of the opening. 
For a cylindrical cavity, the curvature is infinite along the axis of the cylinder and finite 
perpendicular to the axis. For a spherical cavity, the curvature is finite and equal in any direction. 
Thus, the equivalent radius of the spherical drift in the model is twice that of the design drift 
radius. 
1m 
3m 
5.5m 
2m 5.5m 
NOTE: The shaded areas represent the upper boundary where percolation is uniformly 
applied and the lower boundary where a gravity drainage condition is applied. 
Figure 6.4-17. Numerical Grid Dimensions 
As a base case, seepage into the opening without any rock bolts is modeled. Percolation rates of 
5, 14.6, 73.2, 213, and 500 mm/yr are applied uniformly to the upper model boundary as used in 
the AMR Seepage Model for PA Including Drift Collapse (CRWMS M&O 2000 [153314], 
Section 6.3.7). Parameter Set A from the same AMR (DTN: LB0010SCMREV01.002 [153393]) 
and the alternative 1/. values of 400 and 200 Pa (CRWMS M&O 2000 [153314], Sections 6.3

  
  102  
and 6.3.4) are used for the formation. A constant zero capillary pressure is specified at the drift 
wall boundary, a gravity drainage condition at the lower boundary (assigned in the grid using the 
routine AddBound V1.0 (LBNL 2000 [152823])), and a no-flow condition on the lateral 
boundary, all of which are consistent with the current models of seepage at Yucca Mountain 
(CRWMS M&O 2001 [153045], Section 6.3.2.4; CRWMS M&O 2000 [153314], Section 6.3). 
To investigate the impact of a rock bolt on seepage, only the case of a rock-bolt hole vertically 
upward from the crown of the drift is modeled. This case is sufficient to investigate whether 
there is any impact on seepage due to the presence of the rock-bolt hole. Three slightly different 
grids are prepared to explore diversion capacity away from the rock-bolt hole. Case 1 allows 
flow between the rock-bolt hole and the surrounding rock along the entire length of the bolt hole. 
Case 2 prevents flow between the bolt hole and the surrounding rock for 10 cm above the crown 
of the drift. Case 3 restricts flow between the bolt hole and the surrounding rock for 50 cm above 
the crown of the drift. Cases 2 and 3 represent scenarios where the first feature capable of 
carrying flow away from the bolt hole is found 10 cm or 50 cm, respectively, into the hole. A 
0.0254 m (1 inch) radius bolt hole with a 0.0127 m ( inch) radius rock bolt and a 0.0127 m 
( inch) grout annular thickness is modeled. These features are added to the grid using the 
routine AssignRock V1.0 (LBNL 2001 [154321]). The modeled grout annular thickness is twice 
as great as the design value (BSC 2001 [155187], Table 4-10); this results in a conservative 
model, because the modeled bolt hole has less potential as a capillary barrier to exclude in-flow, 
a larger surface area to intercept flow, and allow a greater opportunity to conduct flow to the drift 
wall. 
Because the greatest impact of the rock bolts on seepage may come many thousands of years in 
the future after cool down and rewetting of the repository horizon and during wetter future 
climates, the grout is not likely to retain its design hydraulic properties. It may even completely 
disintegrate, leaving an open hole. So a range of properties for the grout is used. Figure 6.4-18 
shows the parameter combinations evaluated. In the lower left combination, permeability equals 
10-18 m2 and 1/. equals 107 Pa, corresponds to the design (or a slightly degraded) grout, while in 
the upper right combination, permeability equals 10-10 m2 and 1/. equals 10 Pa, essentially 
corresponds to an open bolt hole. 
The details of the model and sensitivity study setup are found in Bodvarsson (2001 [156334], 
YMP-LBNL-DSM-CFA-1, pp. 62, 63, and 6870). The sensitivity study uses the software 
TOUGH2 V1.5 (LBNL 2001 [154322]) to simulate unsaturated flow.

  
  103  
1.0 
2.5 
4.0 
5.5 
7.0 
-18 -16 -14 -12 -10 
log(k [m 2 ]) 
log(1/ a [Pa]) 
Figure 6.4-18. Grout Parameter Combinations 
6.4.1.2.2 Results of Rock Bolt Model 
No seepage enhancement is predicted for any combination of the percolation rate, formation 
parameter, grout parameter, and numerical grid simulations. This result is very different from the 
previous needle calculation, where 3% seepage enhancement was shown for one rockbolt 
(CRWMS M&O 2000 [153314], Section 6.7). This result is understandable, especially 
considering two key points about the previous simulation: 
1. The area onto which flow may be incident, if the lateral surfaces are considered, is 1.25 
m2 in the previous model as opposed to 0.24 m2 in the current model, a ratio of 5 to 1. 
If only the horizontal surfaces are considered, the ratio increases to more than 100 to 1. 
2. The parameters from the seepage calibration model, on which the seepage model for 
performance assessment is based, are predicated on the use of 5 cm connection 
distances between the drift wall and the first node adjacent to the drift wall (CRWMS 
M&O 2001 [153045], Sections 1, 6.3, 6.4.2.2). The previous calculation observed the 
seepage enhancement to be significant only when that connection was 3 to 5 times the 
recommended length, restricting the lateral flow away from the rock bolt. 
6.4.1.2.3 Validation of Rock Bolt Model 
Validation of the model for the intended use, i.e., evaluation of the seepage enhancement 
potential of rock bolts, can be judged by two criteria: 1) does the base case model using a 
spherical opening and a homogeneous permeability field provide comparable results to models 
previously used and validated for seepage calculations, and 2) do observations from Yucca 
Mountain contradict the results of the model.

  
  104  
A comparison of the seepage percentage predicted by this model with that predicted by the 
seepage model for performance assessment (SMPA) (CRWMS M&O 2000 [153314], Section 
6.6.1), is shown in Figure 6.4-19. The SMPA uses a model with a cylindrical opening and a 
heterogeneous permeability field. For the formation parameters used, the two models perform 
similarly. There is more difference in the seepage percentage between the different formation 
parameters than there is between the models. Further, since the result of concern is seepage 
enhancement caused by rock bolts rather than seepage percentage, the use of a consistent model 
(i.e., one using a spherical opening and a homogeneous permeability field) for both the base-case 
simulations and the rock-bolt simulations is the important issue. The impact on seepage 
enhancement of using the spherical opening model with a homogeneous permeability field is 
considered a second-order effect. Thus, the model meets the first criterion listed above for 
validation. 
0 
20 
40 
60 
80 
100 
0 100 200 300 400 500 
Percolation (mm/yr) 
Seepage Percentage 
RBM, 1/a=589 Pa 
RBM, 1/a=400 Pa 
RBM, 1/a=200 Pa 
SMPA, 1/a=589 Pa 
SMPA, 1/a=400 Pa 
SMPA, 1/a=200 Pa 
DTN: LB0104AMRU0185.004 
SOURCE: (CRWMS M&O 2000 [153314], Section 6.6.1) 
NOTE: For the SMPA cases with 1/. equal to 400 and 200 Pa, the permeability is 0.9.10-12 m2 
rather than 1.4.10-12 m2. No seepage is predicted for SMPA with 1/. = 589 Pa. 
Figure 6.4-19. Seepage percentage predicted by base case rock bolt model (RBM) 
compared to that for the seepage model for performance assessment 
(SMPA). 
The model prediction of no seepage enhancement due to rock bolts appears to be counter to 
anecdotal evidence of occasional dripping at rock bolts in the ESF and associated tunnels (Note 
that there are no qualified data on seepage associated with rock bolts that could be used to 
directly validate this model). Several factors associated with the rock bolts in the ESF and 
adjacent tunnels suggest that the processes causing this dripping will not enhance seepage of 
background percolation. First, the type of rock bolt used in the ESF and associated tunnels is not

  
  105  
the same as will be used in the emplacement drifts. In the current tunnels, hollow steel swellex 
bolts are used. These bolts are expanded against the sides of the hole using water pressure (the 
end of the bolt is capped), which may leave behind water inside the bolt (which is available to 
drip out). Second, temperature, humidity, and pressure variations in the tunnels could lead to 
condensation inside the swellex bolts that would lead to dripping. Note that this water is not 
water from the formation but from the tunnel atmosphere because the bolt is impermeable. Third, 
water that has been used both in the mining of these tunnels and for drilling of the bolt holes may 
also be condensing and creating saturated conditions on the outside of the bolts, because the bolts 
are better thermal conductors than the surrounding rock. Thus, the model meets the second 
criterion listed above for validation. 
The model results are not abstracted for TSPA-SR (BSC 2001 [155950], Section 4.3.3.6). Rather 
they are scoping calculations that provide confirmation of the conservatism of the models used 
and directly relied upon in TSPA-SR (CRWMS M&O 2000 [153246]; BSC 2001 [154659], 
Section 3.2.2.5). Because it meets the two criteria listed above, the model is valid for its intended 
use. 
6.4.1.2.4 Alternative Rock Bolt Models 
Alternative models for the investigation of seepage enhancement due to rock bolts include: 
. Continuum models employing multiple realizations of heterogeneous permeability 
fieldsThe discussion in Section 6.4.1.2.3 suggests that a model of this type is 
unlikely to save significantly different results 
. Discrete fracture models (Section 6.4.2)The key element of the discrete fracture 
model, i.e., discrete features for flow into or out of the bolt hole, is adequately captured 
by the two current models in which the bolt hole is disconnected from the formation 
near the drift wall. 
. Models that include inclined rock-bolt holesThe use of a vertical rock bolt rather 
than an inclined one minimizes the area onto which percolation is incident. However, 
the current simulations show that, for certain grout parameter combinations, flow enters 
even a vertical bolt hole from the sides, enhancing percolation through the grout with 
respect to the percolation around the bolt. The key to the lack of seepage enhancement 
is that the potential for sufficient lateral diversion at or near the drift wall exists, so that 
the flow in the bolt hole may be diverted away from the hole. For an inclined hole, 
there will exist even more diversion potential because the height of any disconnected 
length of the hole will be less and the diversion potential along the angled portion of the 
drift wall is much greater than at the crown of the drift. Thus, it is unlikely that a model 
including inclined rock bolts will give significantly different results. 
6.4.1.2.5 Conclusions for Rock Bolt Models 
The conclusion of this investigation of the potential for seepage enhancement caused by rock 
bolts is that there is no significant enhancement of seepage. These scoping calculations confirm

  
  106  
that the approach used for seepage enhancement due to drift degradation in TSPA-SR (CRWMS 
M&O 2000 [153246]) is conservative. 
6.4.2 Focusing and Discrete Flow Paths in the TSw 
The objective of this section is to investigate flow focusing and discrete paths that may occur 
through unsaturated fractures within the TSw unit. We developed a discrete fracture model that 
honors fracture data from these units, using a stochastic representation of fracture permeabilities. 
The model was then used to study flow allocation mechanisms and patterns and to assess the 
frequency and flux distributions of major water-bearing flow paths and transport pathways from 
the bottom of the PTn unit to the repository horizon. 
6.4.2.1 Preferential Flow Phenomena 
Field evidence at Yucca Mountain (for example, elevated levels of 36Cl originating from 
atmospheric nuclear tests conducted in the 1950s and 1960s) found at several locations in the 
ESF (Fabryka-Martin et al. 1996 [144839], Section 9), suggests that preferential flow pathways 
may exist in the unsaturated rocks of Yucca Mountain. The focusing flow along these 
preferential paths or well-connected fracture networks may play an important role in controlling 
patterns of percolation through highly fractured tuffs, such as the TSw unit, and have a direct 
impact on seepage into drifts. 
The mechanisms that control unsaturated flow and transport in fractured rocks may be very sitespecific 
and are practically unknown. On the other hand, such detailed knowledge is necessary to 
accurately predict the degree of preferential flow and transport. In practice, accurate description 
of flow-focusing processes in unsaturated fractures is essential for accurate prediction of water 
seepage into emplacement drifts of the potential nuclear waste repository. The modeling studies 
on seepage into drifts showed that the amount of water that bypasses or breaks thorough a 
capillary barrier of an emplacement drift wall depends not only on the capillarity and 
permeability of the surrounding fracture system, but also on the heterogeneity of the water flux 
and flow paths (CRWMS M&O 2001 [153045], Section 6.5.2). 
Several conceptual models have been proposed for handling water flow through the thick, 
fractured UZ at Yucca Mountainfrom continuous fracture flow, such as indicated by the results 
of the dual-permeability model described in UZ Flow Models and Submodels (CRWMS M&O 
2000 [122797]), to sparse discrete flow through a very small portion of the fracture network 
(Pruess et al. 1999 [117112]). Modeling approaches used in characterizing general fracture flow 
include (1) the continuum model (e.g., ECM and dual-permeability (Wu et al. 1999 [117161])) 
and (2) the discrete-fracture model (CRWMS M&O 2001 [153045], Section 6.5.1). 
6.4.2.2 Modeling Approach and Model Description 
The modeling studies of this section are based on a 2-D, vertical cross-sectional model that has 
the upper boundary at the bottom of the PTn and the lower boundary at the repository horizon. 
This cross section has a width of 100 m and is 150 m in vertical extent (Figure 6.4-20). The 
dimension of the model was considered adequate in the horizontal direction because the 
correlation length for variability in fracture permeability and spacing is on the order of 1 m. The 
150 m vertical extent of the model corresponds to an average distance from the interface between

  
  107  
the PTn and TSw units to the repository horizon over the repository area. The bottom of the PTn 
was chosen as the upper boundary because this unit is believed to behave as a porous medium, 
with limited fracture flow. Both uniform and nonuniform percolation flux boundary conditions 
are prescribed at this upper boundary. The two side boundaries are treated as no-flux boundaries, 
whereas the bottom boundary allows for gravitational drainage out of the model. 
Only the fracture continuum is modeled in this study because the matrix system is believed to 
play a limited role in carrying water. The matrix is also not expected to have a major impact on 
the development of preferential flow paths or weeps within the model boundaries because of its 
orders-of-magnitude lower permeability than fractures (CRWMS M&O 2000 [144426], Table 
13). The properties of the fracture system are based on those from the Calibrated Properties 
Model (CRWMS M&O 2000 [144426]). Five different hydrogeologic layers (TSw31 to TSw35) 
within the 2-D model, are represented by different fracture properties (DTN: 
LB991121233129.001 [147328]). 
Fracture permeability is prescribed stochastically, based on measured air-permeability data. 
Spherical semivariogram models (Deutsch and Journel 1992 [100567], p. 23) are used to 
represent the empirical log-permeability semivariograms. Details on the methodology of 
generating stochastic fracture permeability are discussed in the AMR Seepage Calibration Model 
and Seepage Testing Data (CRWMS M&O 2001 [153045], Section 6.4.2.1), which concludes 
that the fracture permeability near the potential repository is essentially random, without a 
noticeable or significant spatial correlation. 
The fracture permeability distribution (defined using DTNs: LB990901233124.004 [123273], 
LB002181233124.001 [146878], LB0012AIRKTEST.001 [154586], LB00090012213U.001 
[153141]) is generated by multiplying the mean fracture permeability of each hydrogeologic unit 
by randomly generated multipliers. The SISIM module of the GSLIB package (Specifically, 
GSLIB V1.0MSISIMV1.203 (LBNL 1999 [134136])) is used to generate the two-dimensional, 
spatially correlated permeability field multipliers for gridblocks of 0.25 m . 0.5 m, using a 
sequential-indicator simulator (Deutsch and Journal 1992 [100567], p. 151). The random 
permeability field takes into account the measured post-excavation air-permeability data. The 
resulting permeability fields are inserted into the 2-D numerical mesh for each permeability field 
realization using Perm2Mesh V1.0 (LBNL 2000 [152826]). 
The cumulative distribution functions used for permeability field generation are documented in 
scientific notebooks (Bodvarsson 2001 [156334], YMP-LBNL-GSB-1.6.4, pp. 2425; YMPLBNL-
YSW-4, pp. 2527). 
Figure 6.4-20 shows examples of the prescribed fracture permeability distributions over the 
model domain, using correlation lengths of 1 m and 3 m, respectively. The figure shows that 
fracture permeability varies nearly four orders of magnitude, between approximately 3 . 10-13 m2 
and 3 . 10-9 m2. Each distribution has contrasting fracture permeability patterns, with upper 
regions (in TSw31, TSw32, and TSw33 units) having relatively high permeabilities extending 
110 m vertically and the region just above the repository horizon boundary (in TSw34 unit) 
having lower permeability. The permeability structure (Figure 6.4-20 (a)) reflects the 1 m 
correlation length, which results in patches of high and low permeabilities extending over the 
correlation length in each direction. Figure 6.4-20 (b) shows a similar permeability structure

  
  108  
using a 3 m correlation length. Both permeability structures and the resulting simulation results 
are presented in this report. All other fracture properties besides fracture permeability are taken 
as constant over each hydrogeologic unit within the entire model domain (Table 6.4-4, DTN: 
LB991121233129.001 [147328]). 
The work described here is further documented in Bodvarsson (2001 [156334], YMP-LBNLYSW-
KZ-1, pp. 723, YMP-LBNL-YSW-4, pp. 2832). 
(a) 
(b) 
DTN: LB0104AMRU0185.005 
Figure 6.4-20. Spatially Correlated Fracture Permeability Fields [log (k(m2))] Used in the Model 
Studies; (a) 1 m Correlation Length; (b) 3 m Correlation Length

  
  109  
Table 6.4-4. Fracture Properties Used in the Model Studies 
Permeability van Genuchten 
parameters 
Porosity Residual 
saturation 
Model Layer 
kF 
(m2) 
.F 
(1/Pa) 
mF 
(-) 
.F 
(-) 
Srf 
(-) 
Tsw31 3.21E-11 2.49E-4 0.566 5.5E-3 0.01 
Tsw32 3.56E-11 1.27E-3 0.608 9.5E-3 0.01 
Tsw33 3.86E-11 1.46E-3 0.608 6.6E-3 0.01 
Tsw34 1.70E-11 5.16E-4 0.608 1.0E-2 0.01 
Tsw35 4.51E-11 7.39E-4 0.611 1.2E-2 0.01 
DTN: LB991121233129.001 [147328] 
6.4.2.3 Model Results and Analyses 
All the flow model results discussed below correspond to steady-state flow simulation results. 
Among these study cases, the realization (Realization #1) of fracture permeabilities with a 
correlation length of 1 m is considered as the base-case scenario. The upper boundary for the 
base-case modeling scenario is prescribed with uniform percolation flux of 5 mm/year for 
allocating flow to different fractures. 
Model Results with 1 m Correlation Length: Figure 6.4-21 shows the distribution of simulated 
liquid mass flux magnitude within the 2-D domain with the base-case scenario. The figure shows 
clearly that a number of vertically high-flux, discrete flow paths develop for this flow scenario. 
In addition, Figure 6.4-21 indicates that about five to ten major pathways (or weeps) are present 
in the upper layer (above the elevation of 110 m). Considerably more pathways are present in 
the lower layer. 
Figure 6.4-22 shows the vertical liquid mass flux at two different elevations. The first horizontal 
profile is for the depth of 25 m (Figure 6.4-22 (a)) and the second one at the bottom of the model 
domain (Figure 6.4-22 (b); at 150 m depth). At both elevations, the figure shows a significant 
variability in flux, with values ranging from practically 0 mm per year to almost 30 mm/year. 
The results shown in Figure 6.4-22 (a) and (b) indicate the development of some 50 weeps over 
the 100 m wide model domain, which average to about one major water pathway every 2 m. 
There appears to be little difference between the flow patterns in (a) and (b), suggesting that the 
water flow paths and their characteristics developed within tens of meters from the top of the 
model remain similar in statistics for the remaining 100 m vertical extent of the model. This 
similarity is clearly illustrated by Figure 6.4-23, which exhibits the normalized flux (with respect 
to mean infiltration rate on the top) on the horizontal axis and the flux frequency distribution on 
the vertical axis. The frequencies are generated by grouping the vertical flux results along an 
elevation, counting the total found in each group, and then calculating the percent contribution 
relative to the total horizontal distance (or area) in each category. Figure 6.4-23 compares 
statistical results at four different depths of the model: 25, 50, 100, and 150 m (bottom of the 
model). The figure shows very similar flux frequency distribution at all these elevations.

  
  110  
DTN: LB0104AMRU0185.005 
Figure 6.4-21. Distribution of Flux Magnitude within the 2-D Model Domain, Simulated Using the 
Base-Case Scenario with 1 m Correlation Length, Indicating Forming Several High-Flux 
Flow Paths (Realization #1)

  
  111  
(a) 
Infiltration= 5mm/year, at 25m 
Base case, correlation length=1m, realization #1 
0
2
4
6
8 
10 
12 
14 
16 
18 
20 
0 20 40 60 80 100 
X (m) 
Liquid Flux (mm/year) 
(b) 
Infiltration= 5mm/year, at bottom 
Base case, correlation length=1m, realization #1 
0
5 
10 
15 
20 
25 
30 
0 20 40 60 80 100 
X (m) 
Liquid Flux (mm/year) 
DTN: LB0104AMRU0185.005 
Figure 6.4-22. Distribution of Vertical Fluxes within the 2-D Model Domain, Simulated Using the Base- 
Case Scenario with 1 m Correlation Length, (a) at a Depth of 25 m; (b) at the Bottom

  
  112  
Infiltration=5mm/year 
Base case, correlation length=1m, realization #1 
0
2
4
6
8 
10 
12 
14 
16 
18
0 1 2 3 4 5 6 7 
Normalized flux 
Frequency (%)
Bottom 
25m 
50m 
100m 
DTN: LB0104AMRU0185.012 
Figure 6.4-23. Comparison of Frequency Distribution of Simulated Fluxes at Different Elevations 
within the 2-D Model Domain, Simulated Using the Base-Case Scenario with 1 m 
Correlation Length 
Several sensitivity analyses were performed using the base-case model. In particular, the flux 
values of the top boundary condition were varied from 1 to 500 mm per year. Figure 6.4-24 
shows again the normalized flux plotted against the flux frequency for five distinct infiltration 
cases: 1, 5, 25, 100, and 500 mm/year. With percolation normalized to infiltration rates on the 
top, as shown in Figure 6.4-24, the flux frequency and distribution for all cases are statistically 
similar. The majority of normalized fluxes are in the range from zero to two, while the remaining 
high fluxes have low frequencies. The maximum flux that occurs in the system is generally about 
five to six times more than the prescribed infiltration rates at the upper boundary. This flowfocusing 
factor is considerably lower than what is currently assumed in the Total System 
Performance Assessment (TSPA) models, which assume flow focusing up to about 50 times the 
local percolation flux.

  
  113  
Base case, correlation length=1m, realization #1 
at bottom 
0
2
4
6
8 
10 
12 
14 
16 
18 
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 
Normalized Flux 
Frequency (%) 
1mm/yr 
5mm/yr 
25mm/yr 
100mm/yr 
500mm/yr 
DTN: LB0104AMRU0185.012 
Figure 6.4-24. Frequency Distribution of Simulated Fluxes at Different Infiltration Rates within the 2-D 
Model Domain, Simulated Using the Base-Case Scenario with 1 m Correlation Length 
A second realization (Realization #2) of fracture permeability, generated using a different 
random number (but otherwise using the same fracture properties and model domain with the 
same correlation length of 1 m), was also considered. The permeability distribution is found to 
be similar to that shown in Figure 6.4-20(a) and the resulting normalized flux versus frequency 
plot is shown in Figure 6.4-25. For this realization, three percolation fluxes were applied at the 
upper boundary at 1, 25, and 500 mm per year. The statistical results obtained are very similar to 
that shown in the first realization, as seen in the comparing of Figures 6.4-24 and 6.4-25. It 
therefore appears that the results shown in these figures can and should be used in future 
abstractions of flow focusing at the repository horizon.

  
  114  
Base case, correlation length=1m, realization #2 
at bottom 
0
2
4
6
8 
10 
12 
14 
16 
18 
20 
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 
Normalized Flux 
Frequency (%)
1mm/yr 
25mm/yr 
500mm/yr 
DTN: LB0104AMRU0185.012 
Figure 6.4-25. Frequency Distribution of Simulated Fluxes at Different Infiltration Rates within the 2-D 
Model Domain, Simulated Using Realization #2 with 1 m Correlation Length 
Model Results with 3 m Correlation Length: Simulations performed using a 3 m correlation 
length for the permeability field in the fracture network are presented below. Figure 6.4-20(b) 
shows the permeability spatial distribution with this realization. As expected, the patches or 
regions of high and low permeability are relatively larger, on the order of five to ten meters. The 
value range for fracture permeabilities is the same as other cases, from about 100 mD to over 100 
D. 
Figure 6.4-26 shows the distribution of simulated liquid flux across the 2-D domain with the 
5 mm/year infiltration described on the top. Compared with the flow patterns on Figure 6.4-21 
for the 1 m correlation length case, Figure 6.4-26 shows that fewer but wider discrete, high-flux 
flow paths (or weeps) are predicted with the 3 m correlation length scenario. Larger areas with 
similar high or low permeabilities (Figure 6.4-20(b)) result in larger higher and lower flow 
zones. 
Figure 6.4-27 show vertical liquid fluxes at elevations of -25 m and -150 m (bottom), 
respectively. The figure shows that there are many more extended regions of low and high liquid 
flux for this case in comparison to the 1 m correlation length case (Figure 6.4-22). The extended 
regions of high or low flux cover on the order of tens of meters rather than just a few meters (as 
in the previous case). In addition, a comparison of Figures 6.4-27(a) and (b) shows different 
patterns at the two elevations. This indicates that the large correlation length (3 m) requires a 
longer vertical distance to reach the statistically similar flux distributions. 
Figure 6.4-28 shows the normalized flux verses flux frequency distribution for the 3 m 
correlation length case under different infiltration rates at the upper boundary. Comparison of

  
  115  
Figures 6.4-24 and 6.4-28 indicates a rather similar behavior in spite of the large difference in 
correlation lengths. A more systematic shift occurs in the peak frequencies as a function of 
percolation flux for the 3 m correlation length case in this set of simulations. 
DTN: LB0104AMRU0185.005 
Figure 6.4-26. Distribution of Flux Magnitude within the 2-D Model Domain, Simulated Using with 3 m 
Correlation Length Case, Indicating Forming Large High- and Low Flux Flow Paths

  
  116  
(a) 
Infiltration= 5mm/year, at 25m, correlation length=3m 
0
5 
10 
15 
20 
25 
30 
35 
0 20 40 60 80 100 
X (m) 
Liquid Flux (mm/year) 
(b) 
Infiltration= 5mm/year, at bottom, correlation length=3m 
0
5 
10 
15 
20 
25 
30 
35 
0 20 40 60 80 100 
X (m) 
Liquid Flux (mm/year) 
DTN: LB0104AMRU0185.005 
Figure 6.4-27. Distribution of Vertical Fluxes within the 2-D Model Domain, Simulated with the 3-m 
Correlation Length, (a) at a Depth of 25 m and (b) at the Bottom

  
  117  
At bottom, correlation length=3m 
0
2
4
6
8 
10 
12 
14 
16 
18 
20 
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 
Normalized Flux 
Frequency (%) 
1mm/yr 
5mm/yr 
25mm/yr 
100mm/yr 
500mm/yr 
DTN: LB0104AMRU0185.012 
Figure 6.4-28. Frequency Distribution of Simulated Fluxes at Different Infiltration Rates within the 2-D 
Model Domain, Simulated with 1 m Correlation Length 
Results with Nonuniform Infiltration: A sensitivity study on the effect of a nonuniform 
infiltration boundary condition at the upper boundary (at the bottom of the PTn), is given here. 
The case considered is that of water flux being injected at one point (pulse of 0.25 m wide) every 
5 m along the top boundary. The total amount of injected mass flux is the same as that of the 5 m 
uniformly distributed infiltration. Thus, there are 20 discrete sources at the top of the model over 
the 100 m width of the model domain. Figure 6.4-29 shows the normalized flux versus frequency 
for this case at different elevations. Comparison of Figure 6.4-29 with Figure 6.4-23 shows that 
the results using uniform and nonuniform infiltration on the top boundary are very similar. This 
sensitivity analysis thus indicates that the flow patterns using a nonuniform infiltration flux 
behaves as if there were a uniform flux condition at the upper boundary.

  
  118  
Normalized flux distribution at different depth 
correlation length=1m, pulse infiltration 
0
2
4
6
8 
10 
12 
14 
16 
18
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 
Normalized Flux 
Frequency (%) 
bottom 
100m 
50m 
25m 
DTN: LB0104AMRU0185.012 
Figure 6.4-29. Frequency Distribution of Simulated Fluxes at Different Elevations with 5 m Pulse 
Different Infiltration, Simulated with 1 m Correlation Length 
Results with Tracer Transport: Tracer transport analyses with the 2-D model may provide 
additional insight into flow focusing and discrete paths. Here we discuss some of the transport 
modeling using the base-case flow model, i.e., uniform top infiltration flux and 1 m correlation 
length for fracture permeability. A conservative tracer (nonsorbing) with a molecular diffusion 
coefficient of Dm = 3.2 .
10-11 m2/s (for technetium) constant concentration condition is 
prescribed for the top model boundary. Under steady-state flow conditions, the tracer starts to 
transport into the model domain from the top by advection and diffusion as time starts. Figure 
6.4-30 shows the concentration contours in the model domains after one year of tracer release 
from the top boundary. Note that this time period (1 year) is considered short because all matrix 
blocks are omitted in these simulations, so that retardation due to matrix diffusion and sorption 
are implicitly neglected. Evaluation of the results in Figure 6.4-30 displays clearly that there 
exist several faster/fingering channels at this time, indicating very nonuniform, complex 
transport pathways. However, if compared with the high-flow paths of Figure 6.4-21, Figure 
6.4-30 indicates that the faster transport pathways generally follow the faster flow pathways. 
Therefore, concentration distributions within the model domain serve as indicators of preferential 
flow. 
Generalized Results for Seepage Abstraction: As Figure 6.4-24 demonstrates, the results of 
the analyses can be used to estimate the flow focusing factor for the seepage abstraction. The 
normalized flux distributions are similar, and it is reasonable to define a single distribution that 
applies to all expected percolation rates. A regression curve with confidence bands, summarizing 
the results of all the simulations, is shown in Figure 6.4-31.

  
  119  
DTN: LB0104AMRU0185.005 
Figure 6.4-30. Simulated Distribution of Tracer Concentration at One Year of Simulation Time within 
the Model Domain, Identifying Preferential Flow Pathways 
Bottom flux distribution (with 95% confidence range ) 
y = -0.3137x4 + 5.4998x3 - 35.66x2 + 102.3x - 11.434 
0 
20 
40 
60 
80 
100
0 1 2 3 4 5 
Normalized Flux 
Accumulative Frequency (%) DTN: LB0104AMRU0185.012 
NOTE: Results averaged over all simulations. Regression: y =-0.3137x4 + 5.4998x3 + 35.66x2 + 102.3x  11. 
Range is given as the 95-percent confidence interval. 
Figure 6.4-31. Distribution and Range of Cumulative Flux as a Function of Percolation Flux for the 
Bottom of the Model Domain

  
  120  
6.4.2.4 Validation and Alternative Models 
The intended use of the model for focusing and discrete flow paths in the TSw is to provide an 
estimate of the flow-focusing factor for seepage calculations. There are no sufficiently detailed 
data specific to focused flow and discrete flow paths in the TSw that can be used to validate this 
model. Validation of the model for the intended purpose is addressed through the criterion of 
comparison to analog studies and data. Analogous studies and data presented by Faybishenko et 
al. (2001 [156009]; 2000 [156010]) and Pruess et al. (1999 [117112]), which are published in the 
open literature, address the problems of modeling focused and discrete fracture flow using 
heterogeneous models similar to the one used here including modeling actual flow and transport 
experiments in fractured rock. This increases the confidence that the model used here is 
appropriate to address the problem at hand. A conservative approach is recommended here, i.e., 
applying a flow focusing distribution determined for the sub-meter scale to a drift-scale (multimeter-
scale) problem. More detailed models and/or alternative models (discussed below) are not 
likely to overcome this conservatism. Because the validation criterion is met, the model is valid 
for its intended use. However, the model results are not directly relied upon for TSPA-SR 
(CRWMS M&O 2000 [153246]). Rather, they are used for sensitivity studies (BSC 2001 
[154659], Section 3.2.2.3) and provide confirmation of the conservatism of the models used and 
directly relied upon in TSPA-SR (CRWMS M&O 2000 [153246]). 
Alternative approaches to the problem of modeling flow and transport in fractured media other 
than the high-resolution, heterogeneous continuum model used here are discussed in detail in 
Pruess et al. (1999 [117112]). Briefly, the alternative approaches include: 
. macro-scale continuum models, which were the method previously used and are what 
are being improved upon in this study 
. transfer functions and transit time distributions 
. the weeps model 
. chaos and fractal structures 
. fracture network models 
. percolation theory 
All of these methods, except the fracture network models, attempt to use effective parameters 
and empirically observed phenomena to characterize in a simplified manner that is non 
deterministic (i.e., can produce probabilistic predictions but not specifics of where and when 
flow focusing will occur). The fracture network model, on the other hand, requires an immense 
amount of data and computational power that is generally infeasible, especially for a model of 
the scale described here. 
6.4.2.5 Summary and Conclusions 
A series of numerical studies have been conducted to evaluate flow focusing through fractures 
from the bottom of the PTn to the potential repository horizon. The studies were carried out 
using a 100 m wide and 150 m deep 2-D flow domain and covered the upper five different 
hydrogeologic units of the TSw at Yucca Mountain. Mean fracture parameters used in the 
simulations were those developed in the Calibrated Properties Model AMR (CRWMS M&O 
2000 [144426]) as described in Section 6.4.2.2. The heterogeneous fracture permeability

  
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distributions were generated using a stochastic approach. The studies considered various 
percolation fluxes, correlation lengths, and uniform and nonuniform percolation-flux boundary 
conditions. The results obtained provide a quantitative analysis of flow focusing and discrete 
path formation. All simulation results indicate that the flow-focusing factor is about an order of 
magnitude smaller than the conservative value used for TSPA-SR (CRWMS M&O 2000 
[153246]) calculations. The frequency distributions of normalized flux are insensitive to 
magnitudes and spatial distributions of infiltration fluxes on the upper boundary, and to spatial 
correlation structures of the permeability fields within the UZ domains. The results of this model 
are used to support sensitivity studies for TSPA-SR (BSC 2001 [154659], Section 3.2.2.3). 
6.4.3 Percolation Redistribution and Lateral Flow in the PTn 
6.4.3.1 Introduction 
The UZ system of Yucca Mountain has been the subject of intensive geological, hydrologic, and 
subsurface engineering studies. Main issues are the flow and transport pathways, and most 
importantly, the percolation flux through the system. The percolation distribution affects the 
waste-canister performance as well as solute travel times to the accessible environment. The 
long-term performance of the repository is determined by the timing of subsurface fluid 
percolation. Percolation distribution strongly depends on the infiltration rates and their spatial 
and temporal distributions. The conceptual model of net-infiltration spatial distribution 
(Simulation of Net Infiltration for Modern and Potential Future Climates, USGS 2001 [154674]) 
describes the effects of precipitation, runoff, evapotranspiration, and redistribution of water in 
the shallow UZ. The present-day mean infiltration rate over the potential repository footprint has 
been estimated to range from one millimeter per year to as high as hundreds of millimeters per 
year (USGS 2001 [154674], Table 6-10). Past climate changes have been used to estimate the 
possible range in infiltration rates in the future. 
Geochemical data provide additional information to analyze the UZ system. Distribution of 
chemical constituents in both liquid and solid phases of the UZ system depends on many factors, 
such as hydrological and geochemical processes of surface precipitation, evapotranspiration, the 
fracture-matrix interactions of flow and transport, large-scale mixing via lateral transport, and 
history of climate changes and recharge. Naturally occurring and anthropogenic environment 
tracers provide a valuable interpretive resource of evaluating flow and transport processes over 
time and space scales. By synthesizing geochemical and geologic data, the model results provide 
insight into the validity of alternative hydrologic parameter sets, flow and transport processes, 
and the conceptual models. 
The stratigraphic structure of the unsaturated zone of Yucca Mountain is comprised of 
alternating layers of welded and nonwelded volcanic tuffs that are tilted, uplifted, fractured, and 
faulted. Characterization of these units and their subunits has advanced as more information from 
field data become available (CRWMS M&O 2000 [144426]). The first major hydrologic unit 
below the surface is the Tiva Canyon welded tuff (TCw). The saturated matrix permeability of 
the TCw is relatively low, but the high degree of fracturing leads to a much higher bulk 
permeability. Below the TCw is the Paintbrush nonwelded tuff (PTn). The PTn matrix 
permeability is generally several orders of magnitude greater than that of the TCw, but PTn 
fracturing is substantially less, which results in a significantly lower bulk permeability. The

  
  122  
Topopah Spring welded tuff (TSw), below the PTn, is the horizon of the potential repository and 
much thicker than the TCw and PTn together. Matrix permeabilities in the TSw are low, but the 
bulk permeability is substantially greater resulting from a high degree of fracturing. Finally, 
between the TSw and the water table are the Calico Hills (CHn), Prow Pass, and Bullfrog 
nonwelded tuffs. 
Below the zone of evapotranspiration, water can percolate through the UZ through a variety of 
pathways. Fracture flow is initiated in the upper welded tuff unit (TCw), and a transition from 
fracture-dominated flow to matrix-dominated flow occurs when the flow enters the PTn. In 
general, matrix flow in the PTn is expected to damp out seasonal climate variability. The 
questions concerning the conceptual models are: (1) what hydrogeologic features control isolated 
fast pathways through the PTn and (2) to what extent can the PTn damp extreme episodic 
infiltration pulses and to provide a uniform flux at the potential repository horizon. 
In this study, chloride served as an interpretive natural tracer and measured pore-water chloride 
concentration data were used in conjunction with geologic interpretation and 3-D chemical 
transport simulations, to estimate lower and upper bounds on infiltration rates into the UZ 
system. Model results of chloride distributions matched the observed data better when the 
calibrated infiltration rates were used. Effects of PTn lateral flows on percolation and chloride 
redistribution were studied by 3-D simulations with increased horizontal permeability (i.e., 
anisotropy). The combined results from these scoping studies furnish alternative interpretations 
for matching the UZ model to chloride data. The relevant simulations runs are documented in the 
Scientific Notebook (Bodvarsson 2001 [156334], YMP-LBNL-UZ-JL-2.0, pp. 7288). 
6.4.3.2 Available Data 
Measurements of pore-water chloride concentrations offer a unique spatially distributed data set 
for assessing unsaturated zone flow and transport processes and testing the conceptual models. 
The data available and applied were from samples collected at boreholes (USW NRG-6, USW 
NRG-7A, USW SD-6, USW SD-7, USW SD-9, USW SD-12, USW UZ-14, and UE-25 UZ#16), 
the ECRB tunnel, the Exploratory Studies Facility (ESF) tunnel, including South Ramp, North 
Ramp, and Main Drift (Data Sources: DTN: GS950608312272.001 [145617], 
DTN: GS990208312272.001 [146134], DTN: LA9909JF831222.004 [145598], 
DTN: LA0002JF12213U.002 [156281]). The detailed description of these data was given in 
several reports (Yang et al. 1998 [101441], Table 4, pp. 1213; CRWMS M&O 1998 [104878], 
Sections 2 and 3). The water infiltration flux in the base-case study was from the present-day 
mean infiltration map (Figure 6.4-32). Combining the mean annual precipitation of about170 
mm/year with a present day chloride surface flux of 106 mg/m2 year yields a mean chloride 
concentration of about 0.62 mg/L (Sonnenthal and Bodvarsson 1999 [117127], p. 113). Chloride 
surface flux was obtained by applying the mean chloride concentration to precipitated water. 
6.4.3.3 Modeling Approaches 
The UZ consists of a series of welded and unwelded volcanic tuff layers with different 
hydrogeologic characteristics, including fracture density. The welded units are generally heavily 
fractured, with fracture flow considered the dominant mode of air and water movements. The 
unwelded units, however, have higher porosity and fewer fractures, and matrix flow is

  
  123  
prominent. A dual-permeability transient model is necessary to investigate fluid flow and 
chemical transport phenomena and represent the large spatial and temporal chemical variations 
(CRWMS M&O 2000 [141187]). 
The system is modeled as two-phase isothermal flow conditions for water and air. The major 
chemical transport process taken into account were molecular diffusion. A three-dimensional 
dual-permeability model and the T2R3D V1.4 (LBNL 1999 [113942]) of the TOUGH2 code 
V1.4 (LBNL 2000 [146496]) were employed for the simulations. Simulation grids as well as 
basic hydrologic properties of rock matrix and fractures are the same as those used in the 3-D UZ 
nonperched water model described in CRWMS M&O (2000 [122797]), and are available under 
DTNs: LB991131233129.003 [147119]; LB990701233129.002 [125604]; LB997141233129.001 
[104055]; LB990801233129.022 [156331]). Boundary conditions for chemical components were 
treated similarly to those for flow simulations, with mass fluxes described at the top boundary 
and no-flow and water table conditions at the lateral and bottom boundaries, respectively. The 
dispersivities for both fracture and matrix continua in the simulation were set to zero (Sonnenthal 
and Bodvarsson 1999 [117127], p. 129). Diffusion coefficients used were those for chemical ions 
at 25oC and infinite dilution in water (Lasaga 1998 [117091], p. 315, Table 4.1). 
6.4.3.4 Model Calibration and Analyses 
The complexity of the spatial and temporal patterns of infiltration make it difficult to correlate 
measurements taken at depths of a few hundred meters with observable surface features. 
Calibration was done by dividing the surface-infiltration area into nine regions (Figure 6.4-33) 
according to the availability and range of Cl data, the range of present-day mean infiltration data, 
and the hydrogeologic and hydrostructural features. The Cl field data were first assigned to the 
corresponding simulation cells based on the pore-water sample locations. The cell-water 
infiltration flux was then computed using the Cl net-infiltration flux and the assigned Cl 
concentration data at the cell. For cells where Cl data were unavailable, the net-infiltration flux 
was interpolated based on the already calculated infiltration flux in nearby cells in the same 
region and the cell surface area. The map of calibrated infiltration is shown in Figure 6.4-33. 
Averaged present-day mean net-infiltration was applied to regions where regional Cl data is 
unavailable (Regions I, II, and VIII). The overall and regional net-infiltration rates of the two 
infiltration schemes are compared in Table 6.4-5.

  
  124  
Table 6.4-5. Infiltration Data by Region 
Region Area Infiltration Volume by Calibration Infiltration Rate by Calibration 
Before After Before After 
km2 % m3/yr % m3/yr % mm/yr mm/yr 
I 9.9 25.5 104435 58.9 104436 54.2 10.57 10.57 
II 5.3 13.8 12317 6.9 12317 6.4 2.31 2.31 
III 3.7 9.6 26266 14.8 20194 10.6 7.10 5.46 
IV 3.6 9.4 8819 5.0 16267 8.4 2.43 4.48 
V 4.6 11.9 12510 7.1 17534 9.1 2.71 3.80 
VI 2.2 5.6 2479 1.4 5447 2.8 1.14 2.51 
VII 1.8 4.6 3345 1.9 3345 1.7 1.88 1.88 
VIII 3.0 7.7 2156 1.2 2156 1.1 0.73 0.73 
IX 4.7 12.0 4996 2.8 11022 5.7 1.07 2.36 
Overall 38.7 100.0 177323 100.0 192718 100.0 4.58 4.98 
DTN: LB0104AMRU0185.006 
Three-dimensional flow and Cl transport simulations were conducted using the present-day mean 
infiltration (Figure 6.4-32) and the calibrated present-day mean infiltration (Figure 6.4-33) to 
assess the two infiltration schemes. Figures 6.4-34 through 6.4-36 show the comparisons of 
model results of steady-state Cl concentrations with measured pore-water Cl concentration data 
along the stations in the ESF, ECRB, and borehole UE-25 UZ#16, respectively. Compared to the 
data, the model results using the present-day mean infiltration are higher at the North Ramp (0 
2,000 m), South Ramp (6,4008,000 m), northeast ECRB (left side of the figure), and borehole 
UE-25 UZ#16; and lower at southwest ECRB (right side of the figure). To examine the cause of 
these differences, we plotted the infiltration rates along the ECRB in Figures 6.4-37. As can be 
seen, higher model results at northeast ECRB correspond to very low infiltration rates, while 
extreme higher infiltration rates lead to lower model results at southwest ECRB. In Figure 6.4- 
38, with logarithmic scale, we plotted the distribution of Cl concentration in infiltrated water 
along the ECRB. The Cl infiltration concentrations vary significantly compared to the rather 
smooth concentration data at the same location. This inconsistency is not expected for a system 
dominated by vertical flow. Figure 6.4-39 shows the percolation fluxes at the ECRB station, 
using the present-day mean infiltration rates and the calibrated present-day mean infiltration 
rates. With the calibrated present-day mean infiltration rates, the percolation flux along the 
ECRB station is smoother than that by the present-day mean infiltration rates. 
Model results at the same locations using the calibrated infiltration are closer to the Cl field data 
compared to those using present-day mean infiltration. Absolute differences between model 
results and measured field Cl data were calculated and shown in Figures 6.4-40. The differences 
by calibrated infiltration are in several smaller than those by present-day mean infiltration.

  
  125  
230000 
231000 
232000 
233000 
234000 
235000 
236000 
237000 
238000 
239000 
Northing [m] 
168000 169000 170000 171000 172000 173000 
Easting [m] 
(mm/yr) 
0
1
2
3
4
5
6
7
8
9 
10 
120 
I 
II III 
IV 
V 
VI 
VII 
VIII IX 
DTN: LB990801233129.022 [156331] 
Figure 6.4-32. Present-day Mean Infiltration

  
  126  
230000 
231000 
232000 
233000 
234000 
235000 
236000 
237000 
238000 
239000 
Northing [m] 
168000 169000 170000 171000 172000 173000 
Easting [m] 
0
1
2
3
4
5
6
7
8
9 
10 
120 
I 
II III 
IV 
V 
VI 
VII 
VIII IX 
(mm/yr) 
DTN: LB0104AMRU0185.006 
Figure 6.4-33. Calibrated Present-day Mean Infiltration

  
  127  
0 
50 
100 
150 
200 
250 
0 1000 2000 3000 4000 5000 6000 7000 8000 
ESF Station [m] 
Cl Concentration [mg/L] 
Field data 
Present-day mean 
infiltration 
Calibrated present-day 
mean infiltration 
Source DTNs for Field Data: LA0002JF12213U.002 [156281] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-34. ESF Cl Model Results by Present-day and Calibrated Present-day Mean Infiltration 
0 
20 
40 
60 
0 500 1000 1500 2000 2500 
ECRB Station [m] 
Cl Concentration [mg/L] 
Field Data 
Present-day mean infiltration 
Calibrated present-day mean infiltration 
Source DTNs for Field Data: LA9909JF831222.004 [145598] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-35. ECRB Cl Model Results by Present-day and Calibrated Present-day Mean Infiltration

  
  128  
UE-25 UZ#16 
700 
800 
900 
1000 
1100 
1200 
0 100 200 300 400 500 
Cl Concentration [mg/L] 
Elevation (m) 
Field data 
Present-day mean infiltration 
Calibrated present-day mean 
infiltration
PTn 
TSw 
CH 
TCw 
Source DTNs for Field Data: GS950608312272.001 [145617] 
GS990208312272.001 [146134] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-36. Borehole UE-25 UZ#16 Model Results by Present-day and Calibrated Present-day Mean 
Infiltration 
0 
20 
40 
60 
0 500 1000 1500 2000 2500 
ECRB Station [m] Cl Concentration [mg/L] 
0
20 
40 
60 
Water Infiltration [mm/yr] 
Cl field data 
Cl model results 
Present-day mean infiltration 
Source DTNs for Field Data: LA9909JF831222.004 [145598] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-37. ECRB Present-day Mean Infiltration

  
  129  
1 
10 
100 
1000 
0 500 1000 1500 2000 2500 
ECRB Station [m] 
Cl Infiltration [mg/L] 
Field data 
Present-day mean infiltration 
Calibrated present-day mean infiltration 
Source DTNs for Field Data: LA9909JF831222.004 [145598] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-38. ECRB Cl Infiltration Concentration by Present-day and Calibrated Present-day Mean 
Infiltration 
0
5 
10 
15 
20 
0 500 1000 1500 2000 2500 
ECRB Station [m] 
Percolation flux [mm/yr] 
Present-day mean infiltration 
Calibrated present-day mean infiltration 
Dash line: Infiltration 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-39. ECRB Percolation Flux by Present-day and Calibrated Present-day Mean Infiltration

  
  130  
0 
50 
100 
150 
0 20 40 60 80 100 
Field Data [mg/L] 
Absolute Differences (mg/L) 
Calibrated present-day mean 
infiltration 
Present-day mean infiltration 
Source DTNs for Field Data: 
GS950608312272.001 [145617]; GS990208312272.001 [146134]; 
LA9909JF831222.004 [145598]; LA0002JF12213U.002 [156281] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-40. Differences Between Cl Model Results and Cl Data 
6.4.3.5 PTn Lateral Flow Effects 
A transition from fracture-dominated flow to matrix-dominated flow occurs when fluids flow 
from TCw into PTn. PTn layers have variable porosity and permeability. The transition to matrix 
flow in PTn is expected to damp out the variability in infiltration flux and produce a more 
uniform Cl distribution. Flow through this unit was believed to be primarily vertical, with some 
lateral flow occurring because of its layered structure and associated heterogeneities (Wu et al. 
1999 [117161]). To study the effect of PTn lateral flow on the degree of damping and Cl 
distribution, 3-D simulations were run with increased PTn horizontal permeability, which gave 
ratios of horizontal permeability to vertical permeability of 10:1 and 100:1, respectively. Figures 
6.4-41 through 6.4-43 show the model results of Cl concentrations at ESF and ECRB, and 
borehole UE-25 UZ#16. The degrees of damping effects vary in different locations. They were 
observed at North Ramp, south Main Drift, and northeast ECRB. As horizontal permeability 
increased, the simulated Cl concentrations in borehole UE-25 UZ#16 below PTn units are 
decreased and are closer to the measured Cl data from pore water samples. Decreased Cl 
concentrations were also observed at boreholes USW NRG-6, USW NRG-7A, USW SD-7, USW 
SD-12, and UE-25 UZ#4 as PTn permeability altered. Little change was found, however, at 
boreholes USW SD-9 and USW UZ-14. Figure 6.4-44 gives the simulated percolation flux at the 
ECRB. A smoother and smaller percolation flux than that of the base case is observed as the PTn 
horizontal permeability is increased.

  
  131  
0 
50 
100 
150 
200 
250 
0 1000 2000 3000 4000 5000 6000 7000 8000 
ESF Station [m] 
Cl Concentration [mg/L] 
Field data 
kh/kv=1 
kh/kv=10 
kh/kv=100 
Source DTNs for Field Data: LA0002JF12213U.002 [156281] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-41. ESF Cl Model Results by Increased PTn Horizontal Permeability 
0 
20 
40 
60 
0 500 1000 1500 2000 2500 
ECRB Station [m] 
Cl Concentration [mg/L] 
Field Data 
kh/kv=1 
kh/kv=10 
kh/kv=100 
Present-day mean 
infiltration 
Source DTNs for Field Data: LA9909JF831222.004 [145598] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-42. ECRB Cl Model Results by Increased PTn Horizontal Permeability

  
  132  
UE-25 UZ#16 
700 
800 
900 
1000 
1100 
1200 
0 100 200 300 400 500 
Cl Concentration [mg/L] 
Elevation (m) 
Field data 
kh/kv=1 
kh/kv=10 
kh/kv=100 
PTn 
TSw 
CH 
TCw 
Source DTNs for Field Data: GS950608312272.001 [145617] 
GS990208312272.001 [146134] 
Source DTN for Simulations: LB0104AMRU0185.006 
Figure 6.4-43. Borehole UE-25 UZ#16 Cl Model Results by Increased PTn Horizontal Permeability 
0
5 
10 
15 
20 
0 500 1000 1500 2000 2500 
ECRB Station [m] 
Percolation flux [mm/yr] 
kh/kv=1 
kh/kv=10 
kh/kv=100 
Infiltration
DTN: LB0104AMRU0185.006 
Figure 6.4-44. ECRB Percolation Flux by Increased PTn Horizontal Permeability

  
  133  
6.4.3.6 Conclusions 
Percolation flux affects both waste-canister performance and solute travel times to the accessible 
environment. Percolation distribution strongly depends on infiltration rates and their spatial and 
temporal distributions. The present-day mean infiltration in the Yucca Mountain flow and 
transport models was calibrated, and percolation distribution analyzed, using pore-water Cl 
concentration data. The surface-infiltration area was divided into regions according to the 
availability and range of Cl data, the range of present-day mean infiltration data, and 
hydrostructural and hydrogeologic features. Infiltration rates in each region were calculated 
based on the pore-water Cl concentration data and Cl infiltration flux. Results of the threedimensional 
simulation using the calibrated infiltration map match the Cl data better than when 
using an uncalibrated infiltration map. 
PTn lateral flow effects on percolation and Cl distribution were studied by 3-D simulation with 
increased horizontal permeability. The degree of the effects varied by locations. As expected, a 
more uniform Cl distribution under PTn was observed in most places when lateral-flow effects 
increased. Further calibration can be done by adjusting layer heterogeneity and anisotropic 
permeability in different regions, based on the hydrostructural features, percolation fluxes, and 
distribution of geochemical data. 
This scoping study suggests that several approaches may be used to obtain UZ model results 
consistent with chloride data. 
6.4.4 The Effect of Episodic Percolation on Seepage 
Episodic percolation has been shown to enhance seepage. The AMR Seepage Model for PA 
Including Drift Collapse (CRWMS M&O 2000 [153314], Section 6.6.6) considers an example of 
episodic flow. Each years worth of infiltration is concentrated into two months of percolation at 
the repository level, and there is no percolation the other ten months. This model shows that for 
this limited case, the expected peak seepage percentage for episodic flow is the same as that for 
continuous percolation at the same rate. 
The AMR Abstraction of Drift Seepage (CRWMS M&O 2001 [154291], Section 5) neglects the 
effects of episodic flow on seepage because it is generally believed that the PTn effectively 
damps out most, if not all, episodic flow from the TCw. However, portions of the western margin 
of the proposed repository are near the western escarpment of Yucca Crest above Solitario 
Canyon and the PTn and TSw outcrop in several places along that escarpment. At these 
locations, the TSw is exposed to episodic infiltration with very little to none of the moderating 
influence of the PTn. If this episodic infiltration is diverted laterally to the east, it may intersect 
emplacement drifts, with the possibility of enhancing seepage. 
6.4.4.1 Episodic Percolation Model 
To investigate the potential for lateral flow of transient percolation, a model that includes the 
details of the PTn and TSw outcrops on the western escarpment of Yucca Crest and a transient 
infiltration boundary condition is used.

  
  134  
A simple, two-dimensional, rectilinear model is generated with lateral grid size of 10 meters and 
maximum vertical grid size of 10 meters. Where layers are thinner than 10 m, the grid size is 
equal to the layer thickness. Layer thicknesses are constant and are defined by data from 
borehole USW SD-6 (CRWMS M&O 2000 [114277], Attachment III, Table III-1). The dip of 
the layers is defined by average layer dip between boreholes USW SD-6 and USW SD-12, which 
is 7 below horizontal to the southeastward. 
A single continuum fracture-only model is used to simplify calculations and to provide a 
conservative approach to determining whether the potential for transient percolation exists. 
Representation of the matrix in the model would provide more storage and thus more damping 
capacity for both vertical and lateral transient flow. The software iTOUGH2 V4.0 (LBNL 1999 
[139918]) is used to generate the grid. The routine AssignRock V1.0 (LBNL 2001 [154321]) is 
used to assign material properties, including TSw fault properties to the columns next to the noflow 
lateral boundaries. The routine AddBound V1.0 (LBNL 2000 [152823]) is used to add a 
gravity-drainage boundary condition to the lower boundary of the model. 
The cross-sectional alignment is defined by SD-6 and SD-12 so that the cross section crosses the 
western escarpment of Yucca Crest where the Tptrv, Tptrn, and Tptpul outcrop and the proposed 
repository footprint comes closest to these outcrops. The bedrock surface, extracted from 
GFM3.1 (DTN: MO9901MWDGFM31.000 [103769]) using EarthVision V5.1 (Dynamic 
Graphics 1998 [152614]), is used to manually clip the surface of the rectilinear grid. A schematic 
of the resulting grid is shown in Figure 6.4-45. Grid generation details are found in Bodvarsson 
(2001 [156334], YMP-LBNL-UZ-CFA-1, pp. 19, 2935) and Hinds (2001 [155955], p. 152). 
TCw 
TSw 
PTn 
Figure 6.4-45. Schematic of Numerical Grid 
The upper-bound glacial-average infiltration map (ITN: 00316.T) is used to define the 
infiltration condition at the upper boundary. Steady-state infiltration rates are calculated for each 
upper-boundary node, using routine RoutineRick1 V1.1 (LBNL 2001 [156137]). Transient 
infiltration rates are calculated by assuming that infiltration happens only 1 week per year. 
Transient infiltration is applied only to the upper boundary nodes where the TSw outcrops, so

  
  135  
that possible transient-infiltration effects from other areas do not mask or complicate the 
interpretation of possible transient percolation below and/or just to the east of the TSw outcrop. 
These calculations are documented in Bodvarsson (2001 [156334], YMP-LBNL-UZ-CFA-1, pp. 
19, 2935) and Hinds (2001 [155955], pp. 122123). 
Fracture properties are from the AMR Calibrated Properties Model (CRWMS M&O 2000 
[144426], Section 6; DTN: LB997141233129.001 [104055]; DTN: LB991091233129.004 
[126111]). 
The model is first used to simulate steady-state conditions, using a steady-state infiltration 
boundary condition everywhere on the upper boundary. Then 100 years of transient infiltration is 
simulated using the steady-state conditions as initial conditions. All the simulations are 
performed with the software TOUGH2 V1.5 (LBNL 2001 [154322]). These simulations are 
documented in Bodvarsson (2001 [156334], YMP-LBNL-UZ-CFA-1, pp. 19, 2935). 
6.4.4.2 Results of Episodic Percolation Model 
The results are contained in DTN: LB0104AMRU0185.007. These results indicate that transient 
percolation is damped out by the time it reaches the interface between the Tptpul and Tptpmn, 
and that lateral diversion of transient percolation is not at all significant. These results are not 
unexpected because: 
. Gravity drainage is expected to dominate a system with such high permeabilities, from 
10 . 10-12 to 100 . 10-12 m2. 
. The capillarity and storage of the fracture system damp out the transient infiltration 
rapidly. Even where the bedrock surface is only 40 meters above the interface between 
the Tptpul and Tptpmn, the transient percolation is effectively damped out. 
6.4.4.3 Validation of Episodic Percolation Model 
Validation of this model against observations is not possible because no data exist on large-scale 
fracture flow in the TSw. However, validation for intended use can be achieved by using the 
criterion that a negative result is predicted using a conservative model. The conservatism built 
into this model (i.e., using a fracture-only model, using the upper-bound glacial-average 
infiltration map, and putting all the infiltration into a short, transient pulse) build confidence in 
the model finding of no episodic percolation at the western margin of the repository and meet the 
criterion for validation listed above. The model is valid for its intended purpose, i.e., as 
confirmation of the abstraction approach for TSPA-SR that does not include episodic percolation 
as a seepage enhancing factor (CRWMS M&O 2001 [154291], Section 6.4.4; BSC 2001 
[154659], Section 3.2.2.4). 
6.5 PROCESSES AFFECTING UNSATURATED ZONE FLOW AND TRANSPORT 
BELOW THE REPOSITORY 
Flow and transport through the UZ below the repository is important because these are the 
processes by which radionuclides may be carried to the water table. However, the sparsity of 
data from below the repository horizon, particularly in the CHn and CFu, makes discrimination

  
  136  
between alternative models difficult. In some cases, it also makes parameter estimation highly 
uncertain. In this section, scoping of alternative models is used to document whether the choice 
of model impacts transport simulations significantly. As an alternative to the previously used 
conceptual model that fractures and fracture flow are continuous through the vitric CHn, the 
conceptual model that the fractures and fracture flow through the vitric CHn is discontinuous, 
and thus flow is carried wholly through the matrix, is used and is presented in Section 6.5.1. Also 
presented in this section is the calibration of vitric CHn hydrologic properties for the UZ Flow 
and Transport Model based on this alternative conceptual model. In Section 6.5.2, uncertainty in 
perched water models and resulting percolation and tracer breakthrough patterns at the water 
table are addressed by investigating impact of different perching zone permeabilities and 
configurations. In Section 6.5.3, uncertainty in fault parameters for the CHn and CFu are 
investigated by a study of the sensitivity of transport results to variations of fault parameters. In 
Section 6.5.4, the impact of releasing radionuclides directly to the matrix continuum below the 
waste emplacement drift, rather than to the fracture continuum, is studied. None of the results of 
studies documented in this section are used for TSPA. 
6.5.1 Fracture Flow in the Vitric Calico Hills Formation 
Relatively unaltered (vitric), nonwelded tuff exists beneath the potential repository horizon 
within the Calico Hills Formation, as indicated in Figure 6.5-1. Flow and transport behavior 
within this unit may have important effects on the overall performance of the potential 
repository. This section presents a modeling study of flow and transport processes within the 
vitric tuff, based on a new conceptual model and additional rock property data from the Busted 
Butte test site. Effects of the conceptual model and property changes on simulated flow and 
transport processes (from the potential repository to the water table) will also be discussed. Note 
that fracture flow and matrix flow herein refer to water flow occurring in fractures and in the 
rock matrix, respectively. 
6.5.1.1 Conceptual Models 
Two conceptual models can be used for describing flow and transport in the vitric Calico Hills 
Formation, as indicated in Figure 6.5-1. One conceptual model, (a), hypothesizes that flow 
occurs both in fractures and in the rock matrix, while the other, (b), hypothesizes no fracture 
flow under unsaturated conditions. The current flow and transport models of the UZ are based on 
the first conceptual model and predict about 20% of liquid water flow occurring in fractures 
within this unit, as discussed in Unsaturated Zone Flow and Transport Model Process Model 
Report (CRWMS M&O 2000 [151940], Figure 3.6-9). However, the Unsaturated Zone 
Transport Test (UZTT) at Busted Butte strongly supports the second conceptual model, (b).

  
  137  
NOTE: Conceptual model (a) hypothesizes that flow occurs both in fractures and in the rock matrix, while model (b) 
hypothesizes no fracture flow under unsaturated conditions. 
Figure 6.5-1. A North-South Cross Section of Yucca Mountain Showing Two Conceptual Models for 
Water Flow in the Vitric Calico Hills 
Busted Butte is located approximately 8 kilometers southeast of the potential repository area at 
Yucca Mountain (Figure 6.5-2). The underground test facility at Busted Butte exposes portions 
of the Topopah Spring Tuff (Tpt) and the Calico Hills Formation (Tac) lithostratigraphic units, 
which represent a distal extension of the rocks located directly beneath the potential repository. 
As discussed in the AMR Unsaturated Zone and Saturated Zone Transport Properties (U0100) 
(CRWMS M&O 2001 [154024], Section 6.8), tracer transport testing at Busted Butte has 
focused on three specific lithostratigraphic units at the contact between Topopah Spring welded 
unit and Calico Hill nonwelded unit: the moderately welded (Tptpv2) and non- to partially 
welded (Tptpv1) vitric tuffs at the base of the Topopah Spring Tuff, and the largely unaltered 
(vitric) upper portion of the Calico Hills Formation.

  
  138  
Source: modified from CRWMS M&O 2000 [151940], Figure 2.2-12(c) 
Figure 6.5-2. Busted Butte Test Site and Observed Tracer Plume from the Phase 1A Test 
In Phase 1A testing at the Busted Butte site, the tracer was injected from a point. The observed 
tracer plume from this testing clearly indicates that flow and transport occurs only in the matrix 
within the vitric Calico Hills Formation (Figure 6.5-2). During Phase 1B testing in which liquid 
was injected immediately adjacent to a fracture, water imbibed quickly into the surrounding 
matrix, as discussed in the AMR Unsaturated Zone and Saturated Zone Transport Properties 
(U0100) (CRWMS M&O 2001 [154024], Section 6.8.9). This is also consistent with observed 
relatively high matrix permeabilities and matrix porosities, and small fracture densities compared 
to welded units (CRWMS M&O 2000 [145771], Tables 6 and 7), which are expected to 
essentially prevent flow and transport processes from occurring in fractures because of the large 
storage and strong capillary force within the matrix. These arguments strongly support the 
validity of conceptual model (b), in which flow and transport occurs only in the matrix. This 
conceptual model is considered more realistic and is used in this study. Use of conceptual model 
(a) (where some flow occurs in fractures of the vitric Calico Hills Formation) might 
underestimate the water and radionuclide travel times through the vitric Calico Hills Formation.

  
  139  
6.5.1.2 Determination of Rock Properties 
Conceptual model (b), in which flow and transport occur only in the matrix, is incorporated into 
the site-scale model by removing the fracture continuum from model layers corresponding to the 
vitric portions of the Calico Hills Formation. Rock properties have been updated to be consistent 
with this conceptual model change and to incorporate new rock-property data from the Busted 
Butte site. The determination of updated rock properties is documented in the Scientific 
Notebook (Liu 1999 [155675], pp. 9094). 
Determination of rock properties consists of two steps. First, small-scale rock property data are 
analyzed to develop average hydrological properties for the UZ model layers. Because of scale 
issues and uncertainties in property-estimation methods, properties developed from this step may 
not be reliable for use in the flow and transport models of the UZ. Therefore, the second step is 
to refine hydrological properties for the UZ model layers based on model calibration, which is a 
procedure to adjust hydrological properties such that simulated results are consistent with field 
observations, including matrix water saturation and potential data. The estimated properties from 
the first step are used in model calibration as prior information and initial guesses to constrain 
the property values that are to be determined. While detailed descriptions of methodologies used 
in these two steps are given in two AMRs, Analysis of Hydrologic Properties Data (CRWMS 
M&O 2000 [145771]) and Calibrated Properties Model (CRWMS M&O 2000 [144426]), a brief 
introduction to these methodologies is provided here. 
6.5.1.2.1 Available Data 
Since the fracture continuum is removed from only the vitric portion of the Calico Hills 
Formation, only properties corresponding to this unit are updated while other properties remain 
the same as those in the base case mountain-scale property set reported in AMR Calibrated 
Properties Model (CRWMS M&O 2000 [144426], Table 13). Relations between the 
lithostratigraphy of the Geologic Framework Model (GFM3.1) and the UZ model layers are 
given in Table 6.5-1 (CRWMS M&O 2000 [114277], Table 10).

  
  140  
Table 6.5-1. GFM3.1 Lithostratigraphy, UZ Model Layer, and Hydrogeologic Unit Correlation (CRWMS 
M&O 2000 [114277], Table 10) 
Major Unit GFM3.1* Lithostratigraphic 
Nomenclature 
Fiscal (FY) 99 
UZ Model Layer 
Hydrogeologic Unit 
Tiva Canyon welded (TCw) Tiva_Rainier tcw11 CCR, CUC 
Tpcp tcw12 CUL, CW 
TpcLD 
Tpcpv3 tcw13 CMW 
Tpcpv2 
Paintbrush Tuff nonwelded Tpcpv1 ptn21 CNW 
(PTn) Tpbt4 ptn22 BT4 
Tpy (Yucca) 
ptn23 TPY 
ptn24 BT3 
Tpbt3 
Tpp (Pah) ptn25 TPP 
Tpbt2 ptn26 BT2 
Tptrv3 
Tptrv2 
Topopah Spring welded (TSw) Tptrv1 tsw31 TC 
Tptrn 
tsw32 TR 
Tptrl, Tptf tsw33 TUL 
Tptpul 
Tptpmn tsw34 TMN 
Tptpll tsw35 TLL 
Tptpln tsw36 TM2 (upper 2/3 of 
Tptpln) 
tsw37 TM1 (lower 1/3 of 
Tptpln) 
Tptpv3 tsw38 PV3 
Tptpv2 tsw39 PV2

  
  141  
Calico Hills nonwelded (CHn) Tptpv1 ch1 (vit, zeo) BT1 or 
BT1a (altered) 
Tpbt1 
Tac (Calico) ch2 (vit, zeo) CHV (vitric) 
or CHZ (zeolitic) 
ch3 (vit, zeo) 
ch4 (vit, zeo) 
ch5 (vit, zeo) 
Tacbt (Calicobt) ch6 BT 
Tcpuv (Prowuv) pp4 PP4 (zeolitic) 
Tcpuc (Prowuc) pp3 PP3 (devitrified) 
Tcpm (Prowmd) pp2 PP2 (devitrified) 
Tcplc (Prowlc) 
Tcplv (Prowlv) pp1 PP1 (zeolitic) 
Tcpbt (Prowbt) 
Tcbuv (Bullfroguv) 
Crater Flat undifferentiated Tcbuc (Bullfroguc) bf3 BF3 (welded) 
(CFu) Tcbm (Bullfrogmd) 
Tcblc (Bullfroglc) 
Tcblv (Bullfroglv) bf2 BF2 (nonwelded) 
Tcbbt (Bullfrogbt) 
Tctuv (Tramuv) 
Tctuc (Tramuc) tr3 Not Available 
Tctm (Trammd) 
Tctlc (Tramlc) 
Tctlv (Tramlv) tr2 Not Available 
Tctbt (Trambt) 
NOTE: * GFM3.1 refers to the Geologic Framework Model Version 3.1. 
Core measurements from surface-based boreholes and from the Busted Butte site include matrix 
saturated hydraulic conductivity, matrix porosity, matrix relative unsaturated hydraulic 
conductivity as a function of saturation, and capillary pressure as a function of saturation. The 
averaged properties determined based on core measurements from surface-based boreholes 
were reported in the AMR Analysis of Hydrologic Properties Data (CRWMS M&O 2000 
[145771], Section 6.2) (DTN: LB990501233129.001 [106787]). These properties need to be 
updated, however, to incorporate core measurements from Busted Butte (DTNs: 
GS990308312242.007 [107185] and GS990708312242.008 [109822]) made available after the 
analysis of hydrologic properties was completed. In this case, both data from Busted Butte and 
surface-based boreholes are used for updating rock properties for the relevant model layers.

  
  142  
Correlation between location of a core sample from Busted Butte and the appropriate UZ model 
layer is determined from geological information of the core sample (CRWMS M&O 2000 
[154123]). 
The Busted Butte underground facility provides access to the lower Topopah Spring Tuff 
(crystal-poor, vitric subzones, Tptpv2 and Tptpv1) and the upper Calico Hills Formation (Tac). 
This lithostratigraphic sequence is marked by a downward gradation from moderately welded 
tuffs (upper Tptv2) to nonwelded tuffs (Tptpv1 and Tac). Samples from the lower part of layer 
Tptpv2, layer Tptpv1, and the upper part of layer Tac have been collected and analyzed to 
determine matrix hydrologic characteristics. Average matrix permeabilities of Busted Butte 
samples from the lower Topopah Spring Tuff and upper Calico Hills Formation are higher than 
those from surface-based boreholes near or within the potential repository area at Yucca 
Mountain. This may result from a possible difference in degree of alteration, but it more likely 
reflects a biasing of the samples collected from the surface-based drilling toward those that are 
less friable (those with a greater degree of welding or increased clay or zeolite content). Matrix 
permeability data from Busted Butte are also available for the Tptpv2 lithostratigraphic unit, 
corresponding to UZ model layer tsw39. However, these data are significantly different from 
those collected from surface-based boreholes. For example, the average matrix permeability 
from the Busted Butte site is about three orders of magnitude higher than that determined using 
core measurements from surface-based boreholes. Even the smallest matrix porosity for this 
layer observed at Busted Butte (0.28) is larger than the average porosity obtained from surfacebased 
boreholes (0.17) (DTN: LB990501233129.001 [106787]), suggesting almost no overlap 
between observed porosity values from these two sources. This apparent discrepancy may reflect 
vertical differences in sampling locations within the Tptpv2 lithostratigraphic unit, which is 
characterized by a welding transition. Core samples from surface-based, vertical boreholes may 
have been biased to the upper, more welded part of the Topopah Spring-Calico Hills transition 
(which has lower porosity), while samples from Busted Butte were taken near the base of this 
transition, where it exhibits a lesser degree of welding (therefore, higher porosity). Further 
investigation may be needed to determine if the Busted Butte data are representative of the vitric 
Topopah Spring-Calico Hills welding transition below the potential repository. In this study, 
these data for Tptpv2 were not used. 
Although unsaturated matrix relative permeability (unsaturated hydraulic conductivity) data are 
available, they are not used in this study, because the water potential versus saturation 
relationship enables successful prediction of the relative permeability relationship based on van 
Genuchtens (1980 [100610], pp. 892893) model (Flint et al. 1999 [107377], pp. 297298). 
Note that van Genuchten (1980 [100610], pp. 892893) relations are used in this study for 
describing unsaturated flow in the matrix. 
In addition to hydrological property data, observed matrix saturation and in-situ water potential 
data, infiltration rates and developed numerical grids are used for model calibration. These data 
have been incorporated into model input files for the Calibrated Properties Model (CPM) (DTN: 
LB991091233129.001 [125868]) that is used in this study. A detailed discussion of these data in 
terms of their use for model calibration can be found in the AMR Calibrated Properties Model 
(CRWMS M&O 2000 [144426], Section 4).

  
  143  
6.5.1.2.2 Analysis of Hydrological Properties Data 
Small-scale rock property data need to be analyzed to develop average hydrological properties 
for UZ model layers, as previously discussed. Matrix permeability is considered to be a lognormally 
distributed quantity (CRWMS M&O 2000 [145771], Section 6.2.1). Therefore the 
geometric mean is used to represent the average permeability of a model layer. Measured data 
are presented in terms of saturated hydraulic conductivity (m/s) and the need to be converted to 
permeability (m2) (CRWMS M&O 2000 [145771], Section 6.2.1). For a given model layer, the 
geometric mean can be very different from the effective matrix permeability used to represent 
large-scale water flow and solute transport due to scale effects (Paleologos et al. 1996 [105736], 
Figure 4, p. 1337). While many upscaling schemes are available in the literature, a scheme for 
highly heterogeneous porous media is described by the following expression (Paleologos et al. 
1996 [105736], p. 1336, Equation 26): 
)] 
2
1 ( exp[ 2 
) ln( D k k k g e . . . (Eq. 6.5.1.1) 
where ke is the large-scale effective permeability, kg is the geometric mean of small (core) scale 
permeability, .ln(k)
2 is the variance of the natural log transformed permeability, and D is a 
function of spatial dimensional (e.g. 2-D and 3-D) and the correlation scale of ln(k). For a 3-D 
isotropic problem, D = 1/6 when the characteristic size of a flow domain under consideration (a 
model layer for example) is much larger than the correlation length (Paleologos et al. 1996 
[105736], p. 1336). For a site-scale model layer, these conditions are approximately satisfied. In 
this case, Equation 6.5.1.1 can be rewritten as: 
2 
) log( 38 . 0 ) log( ) log( k g e k k . . . (Eq. 6.5.1.2) 
where .log(k)
2 is the variance of the log transformed permeability. 
Matrix porosity is considered a normally distributed quantity, so the arithmetic mean of core 
measurements is used to determine the porosity for a model layer. These core measurements 
were obtained after drying samples in a 105oC oven for at least 48 hours to obtain a standard dry 
weight (Flint 1998 [100033], p. 17). 
Matrix van Genuchten parameters are satiated saturation (Ss), residual saturation (Sr), . and m. 
Satiated saturation is assumed to be one (there is no residual gas saturation). Residual saturation 
is determined from relative-humidity (RH) porosity and total porosity. With satiated and residual 
saturations fixed, . and m are obtained for a model layer by fitting combined water-potential and 
saturation data for all samples located within the model layer, and their uncertainties (standard 
error) are calculated as diagonal terms of the covariance matrix associated with the fitting 
procedure. Because the data used to estimate . and m are from laboratory desaturation 
experiments, the estimate of . represents a low bound of the average wetting and drying 
behavior. Therefore, the estimated . values need to be corrected by forcing the water potential 
curve through saturation and in situ water potential data representing field conditions. A detailed 
description of the procedures to estimate matrix van Genuchten parameters can be found in the 
AMR Analysis of Hydrologic Properties Data (CRWMS M&O 2000 [145771], Section 6.2.3).

  
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Table 6.5-2 shows estimated matrix properties for the vitric Calico Hills Formation layers. Note 
that for the case without considering Busted Butte data, the property values are directly from 
DTN: LB990501233129.001 [106787]. For the case considering the Busted Butte data, detailed 
calculations for estimating the properties are documented in the Scientific Notebooks (Ahlers 
2000 [155853], pp. 8183; and Liu 1999 [155675], pp. 9094). 
Table 6.5-2. Uncalibrated Matrix Hydrological Properties for Model Layers Corresponding to the Vitric 
Calico Hills Formation 
UZ 
Model 
Layer 
Permeability (m2) Porosity 
(-) 
Van Genuchten Parameters 
k SElog(k) . . (Pa-1) m (-) SEm
a Sr Ss 
Parameter set without considering the Busted Butte data 
(DTNs: LB990501233129.001 [106787]) 
ch1v 2.6E-14 0.269 0.273 2.91E-5 0.337 0.035 0.03 1 
ch(2-5)v 8.9E-14 0.335 0.345 7.20E-5 0.220 0.057 0.07 1 
New parameter set considering the Busted Butte data 
ch1v 2.30E-13 0.201 0.327 9.08E-5 0.240 0.011 0.04 1 
ch(2-5)v 1.19E-12 0.247 0.348 1.73E-4 0.178 0.010 0.06 1 
a SE refers to the standard error and is related to standard deviation (.) by SE = ./N0.5, where N is number of 
samples. 
DTN: LB0103CHVUPROP.001 
6.5.1.2.3 Calibrated Hydrological Properties 
One-dimensional data inversion is carried out for a number of vertical columns corresponding to 
boreholes UE-25 NRG#5, USW NRG-6, USW NRG-7a, USW SD-7, USW SD-9, USW SD-12, 
UE-25 UZ#4, USW UZ-14, UE-25 UZ#16 and USW WT-24 (CRWMS M&O 2000 [144426], 
Section 6.1.1). Matrix saturation and/or in situ water potential data are available for these 
boreholes. The vitric Calico Hills Formation occurs only in columns corresponding to boreholes 
USW SD-6, USW SD-7, and USW SD-12. Therefore, the fracture continuum was removed from 
these columns for UZ model layers ch1v and ch(2-5)v. One-dimensional data inversion (based 
on inverse modeling) was used because inverse modeling involves many forward runs, and it is 
not computationally feasible to use 3-D site-scale model directly. 
The EOS9 module (Richards equation) of iTOUGH2 V3.2 (LBNL 1999 [154337]) is used for 
model calibration. For this study, only the base-case infiltration scenario is considered. 
Uncalibrated hydrological property values for matrix permeability and van Genuchten 
parameters excluding residual and satiation saturations (Table 6.5-2) are used as prior 
information and initial parameter guesses during inverse modeling. The optimized (calibrated) 
parameter values are obtained when the objective function reaches the minimum, as determined 
automatically by the ITOUGH2 code.

  
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Table 6.5-3 gives the calibrated hydrological properties for UZ model layers ch1v and ch(2-5)v. 
As previously indicated, property values for other UZ model layers remain the same as those in 
the base-case parameter set (CRWMS M&O 2000 [144426], Table 13). As an example, Figure 
6.5-3 shows the match between the simulation results achieved with the calibrated parameter set 
(incorporating the Busted Butte data) and the observed matrix saturation data for USW SD-7. 
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 
Matrix saturation 
700 
800 
900 
1000 
1100 
1200 
1300 
1400 
Elevation (m) 
TCw 
PTn 
TSw 
CHn 
Prow Pass 
USW SD-7 
DTNs: LB991091233129.001 (observations) [125868] 
LB0103CHVUPROP.002 (simulations) 
Figure 6.5-3. Match Between the Simulation Results (solid curve) Achieved with the Calibrated 
Parameter Set (incorporating the Busted Butte data) and the Observed Matrix Saturation 
Data for USW SD-7 
Comparison between the calibrated and uncalibrated property values (Tables 6.5-2 and 6.5-3) 
indicates that calibrated matrix permeability values are consistently larger than uncalibrated 
ones. This may result from the scale-dependent behavior of matrix permeability, although this 
behavior is approximately considered when determining uncalibrated permeability values 
(Equation 6.5.1.1). The calibrated matrix . and m values are consistently smaller and larger, 
respectively, than the uncalibrated ones. This suggests that a systematic bias may exist in our 
procedure to determine the uncalibrated values for these parameters, which is removed by using 
the model calibration. Note that the above discussion cannot be extended to other model layers 
characterized by the dual-continuum. Also, a reliable upscaling procedure, directly based on 
small-scale measurements and without using model calibration, is not available at this stage 
(Looney and Falta 2000 [153458]). Therefore, the two-step procedure mentioned above provides 
a practical and reliable approach to estimating large-scale unsaturated flow and transport 
parameters (Looney and Falta 2000 [153458], pp. 685690).

  
  146  
Table 6.5-3. Calibrated Matrix Hydrological Properties for Model Layers Corresponding to the Vitric 
Calico Hills Formation 
UZ Model Layer Permeability (m2) . (Pa-1) m 
Parameter set without considering Busted Butte data 
ch1v 1.50E-13 2.46E-5 0.374 
ch(2-5)v 2.58E-13 3.87E-5 0.270 
Parameter set considering Busted Butte data 
ch1v 2.95E-12 5.57E-5 0.291 
ch(2-5)v 1.42E-12 4.41E-5 0.254 
DTN: LB0103CHVUPROP.001 
6.5.1.3 Site-Scale Modeling Results 
This section presents and analyzes 3-D modeling results for site-scale flow and transport, using 
the UZ 3-D TSPA grid, present-day and mean infiltration scenario, and the modified vitric 
conceptual model parameters, as discussed in the previous section. The simulations are also 
based on perched water Conceptual Model #1 (see Section 6.5.3 for details), and the results are 
compared to those without considering the vitric zone model modification (conceptual model (a) 
in Figure 6.5-1). The details on numerical modeling procedures are the same as those in the 
AMR UZ Flow Models and Submodels (CRWMS M&O 2000 [122797]). The relevant 
simulations runs are documented in the Scientific Notebook (Wu 2001 [155676], pp. 216254) 
Two sets of 3-D flow and transport simulations are carried out, using the new parameters for the 
Calico Hills Formation vitric zones, estimated in the previous sections, with and without 
incorporating the Busted Butte data. The two sets of flow simulation results have been checked 
against the field observed data of matrix liquid saturations, water potentials (when available), 
and perched water elevationswith reasonable agreements. Flow and transport simulations use 
TOUGH2 V1.4 (LBNL 2000 [146496]) and T2R3D V1.4 (LBNL 1999 [113942]) 
6.5.1.3.1 Comparison of Percolation Fluxes at Water Table 
Figures 6.5-4  6.5-6 show the simulated percolation fluxes at the water table using the two 
simulation results as well as the original flow field without the vitric-zone properties 
modification (CRWMS M&O 2000 [122797], Section 6.6). By comparing these with the 
percolation fluxes at the water table for the two vitric-zone conceptual models and three 
parameter sets, we find the following: 
. As expected, model results using the original conceptual model indicate faster vertical 
flow through vitric zones than model results based on the newer conceptual model, 
which assumes no fracture flow in the vitric Calico Hills. The vitric area is limited in 
extent to the southern part of the model domain below the potential repository horizon 
(as discussed in Unsaturated Zone Flow and Transport Model Process Model Report 
(CRWMS M&O 2000 [151940], Section 3.2.4)). In areas of the model domain where 
vitric tuffs have been altered to zeolites, the calibrated percolation flux at the water

  
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table is the same for both conceptual models because the model parameters are 
unchanged in these areas. 
. Simulations based on the new conceptual model (i.e., no vitric fracture flow), with and 
without incorporation of the Busted Butte data, show similar flow patterns at the water 
table. This indicates that inclusion of Busted Butte data has an insignificant effect on 
model results. 
Source: CRWMS M&O 2000 [122797], Figure 6-45, based on DTN: LB990801233129.003 [122757] 
Figure 6.5-4. Simulated Percolation Fluxes at the Water Table Under Present-day, Mean Infiltration 
Using the Results of the Base-Case Conceptual Model (a)

  
  148  
DTN: LB0104AMRU0185.013 
Figure 6.5-5. Simulated Percolation Fluxes at the Water Table Under Present-day, Mean Infiltration, for 
Conceptual Model (b) and the New Vitric Properties Without Incorporation of the Busted 
Butte Data

  
  149  
DTN: LB0104AMRU0185.013 
Figure 6.5-6. Simulated Percolation Fluxes at the Water Table Under Present Day, Mean Infiltration, 
for Conceptual Model (b) and the New Vitric Properties With Incorporation of the Busted 
Butte Data 
6.5.1.3.2 Comparison of Tracer Transport Times 
For each of the three flow simulations, one transport run was made for a conservative tracer. 
Tracer migration times since release from the potential repository to the water table estimated 
from these transport simulations are compared in Figure 6.5-7. In this figure, the fractional mass 
breakthrough curve for the conservative tracer is defined as the cumulative mass of the tracer 
arrived at the water table over the entire bottom model boundary at the time, normalized by the 
total initial mass at the potential repository. 
Figure 6.5-7 shows that the new conceptual model slightly increases transport times. Without 
fracture effects (i.e., conceptual model (b) rather than (a), see Section 6.5.1.1), the vertical flow 
through the vitric zones is reduced, and as a result, the early breakthrough (20% or less) time for 
a conservative tracer is a little longer. Similar to flow results, the transport simulations with and 
without incorporating the Busted Butte data give the same transport times.

  
  150  
100 101 102 103 104 105 106 
Time since Releasing (years) 
0.2 
0.4 
0.6 
0.8
1 
Fractional Breakthrough atWater Table 
Conceptual Model (a) 
Conceptual Model (b), 
No BB Data 
Conceptual Model (b), 
BB Data 
DTNs: LB990801233129.003 [122757] Conceptual Model (a) (file Pach1_tr1.out) 
LB0104AMRU0185.009 Conceptual Model (b), No BB Data (file Expm1_tr1.out) 
LB0104AMRU0185.013 Conceptual Model (b), BB Data (file ebb_t1.out) 
NOTE: In this figure, BB refers to Busted Butte. 
Figure 6.5-7. Comparison of Simulated Cumulative Breakthrough Curves of Conservative 
Tracer Mass Arriving at the Water Table Since Release from the Potential 
Repository, using the Different Vitric-Zone Conceptual Models 
6.5.1.4 Model Validation and Alternative Models 
Validation of the data inversion for model parameter estimation can be addressed by evaluating 
four criteria given by CRWMS M&O (2000 [144426], Section 6.4): 
1. Calibration within experimental data sets. 
2. Comparison of predictions using the calibrated property sets and the UZ 
Flow and Transport Model to data not used in the calibration process. 
3. Review of model calibration parameters for reasonableness, or 
consistency in explanation of all relevant data

  
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4. Technical review through publication in the open literature. 
Criteria 1, 3, and 4 are considered partially met by the same rationale given in CRWMS M&O 
(2000 [144426] Section 6.4). It is not possible to evaluate criterion 2 with respect to this model 
because there are no data relevant to mountain-scale processes that allow discrimination between 
a vitric CHn model with or without fractures. However, the evidence presented above in Section 
6.5.1.1 and shown in Figure 6.5-2 does suggest that at the meter scale, flow is completely matrix 
dominated. Note that for the Calibrated Properties model, the intended use is the broad goal of 
providing estimated model parameters for the UZ Flow and Transport model and other models. 
For this model, the intended use is the much more limited goal of providing model parameters 
for presenting an alternative model for flow through the vitric CHn. Moreover, this alternative 
model is not used for TSPA-SR (CRWMS M&O 2000 [153246]), but does provide confirmation 
of the conservatism of the models used and directly relied upon in TSPA-SR. Based on this 
limited goal, the above criteria are applied less rigorously, and based on the evidence above, this 
model is valid for its intended use. 
An alternative to the two conceptual models presented in Section 6.5.1.1 is that fractures exist in 
the non-welded layers (PTn, vitric and zeolitic CHn, and non-welded portions of the CFu) at 
multiple scales but only form continuous flow paths capable of supporting unsaturated flow at 
larger scales. In this model, small-scale fractures would not support large-scale, continuous flow 
through the non-welded layers because of insufficient fracture length and density. Though it 
would be possible for the small-scale fractures to contribute some secondary permeability to the 
non-welded layers. The larger-scale fracturing, generally due to tectonics, would provide 
continuous flow paths through the non-welded layers, but would support liquid flow only under 
large transient percolation conditions or saturated conditions. This model would be consistent 
with the bomb-pulse 36Cl and 3H data from the TSw (see Section 6.2.1.3) and the pneumatic data 
from the TSw (CRWMS M&O 2000 [144426], Section 6.1.2) which both suggest larger 
permeability through the PTn than can be accounted for by the matrix alone. Through analogous 
treatment of all non-welded layers, this model would allow the much more substantial data with 
respect to the PTn to be applied to the non-welded layers below the TSw while still being 
consistent with the vitric CHn specific data indicating completely matrix dominated flow. 
However, analogous treatment of all non-welded layers should not be considered a substitute for 
collection of data that would allow development of a more robust model (or discrimination 
between the proposed models) for flow and transport in the non-welded vitric and zeolitic layers 
below the TSw. 
6.5.1.5 Conclusions and Recommendations 
This section presents the incorporation of newly available data on the vitric CHn into the UZ 
Flow and Transport Model. The data, from the Busted Butte test site, suggest higher matrix 
permeability and lower matrix capillarity than the previously used data indicate. Further, tests at 
Busted Butte suggest that unsaturated flow and transport in the vitric CHn is completely matrix 
dominated. A new conceptual model in which fractures are not present in the vitric CHn is used, 
and new model parameters for these layers are estimated based prior information about the layer 
properties updated with the Busted Butte data. Mountain-scale, three-dimensional simulations 
using this updated model show lower percolation fluxes at the water table directly under the 
vitric portion of the CHn and longer initial-breakthrough times for contaminants from the

  
  152  
repository horizon at the water table. Direct validation of this model of the vitric CHn (with no 
fractures) is not possible because there are no relevant data against which to compare model 
predictions. However, the use of calibration, review of the estimated parameters for 
reasonableness, and technical review of the calibration approach through open literature as well 
as consistency with the Busted Butte test results make the model valid for its intended use of 
presenting an alternative model for flow and transport through the vitric CHn. At this time, 
further development of alternative models is not warranted. Rather, more data on flow and 
transport through the layers between the bottom of the TSw and the water table is needed in 
order to discriminate between alternative models and allow development of a single robust 
model. 
6.5.2 Fault Characteristics 
6.5.2.1 Introduction 
Yucca Mountain is a structural complex of Tertiary volcanic rock. Faults at Yucca Mountain 
were categorized by Day et al. (1996 [102757]) into three types: (1) north-striking block 
bounding faults such as the Solitario Canyon and Bow Ridge faults, (2) northwest-striking faults 
such as Drill Hole Wash, Sever Wash, and Pagany Wash faults, and (3) intrablock faults. Blockbounding 
faults are key structural features that dip steeply to the west and have large cumulative 
displacements. Intrablock faults tend to be shorter and more discontinuous than block-bounding 
faults, and, with the exception of the Ghost Dance fault, generally have minor displacements. 
Displacement along northwest-striking faults varies from small to moderate. Figure 6.5-8 shows 
the location of the major faults and boreholes at Yucca Mountain. 
Major faults may play a large role in shaping the ambient hydrogeologic system. The hydrologic 
properties within and near fault zones are expected to be different than in areas without faulting. 
In brittle, densely welded tuffs, fracture intensities may be high within and adjacent to major 
faults. Increase in fracture aperture associate with faulting can result in increased permeability 
and decreased capillarity. However, mineral precipitation along flow pathways or development 
of fault gouge may effectively reduce fault zone permeability. Nonwelded intervals are less 
likely to develop intensely fractured zones associated with faulting because of their more ductile 
properties. 
The main area of the potential repository is located in a relatively undeformed section bounded 
by long, north-trending, normal faults. That faults may provide a direct path from the repository 
horizon, through the Calico Hills, (CHn), the Crater Flat, (CFu), Prow Pass, Bullfrog and Tram 
nonwelded tuffs, to the water table is particularly significant to the problem of waste isolation, 
because radionuclides released from the potential repository could bypass altered, zeolitic layers 
within the CHn where sorption could occur. Consequently, dissolved radionuclides could enter 
the saturated zone where hydrologically significant faults and the water table intersect. 
Very few direct measurements of fault properties have been made. The relative lack of data with 
respect to faults makes prediction of their effects on the ambient system and on future potential 
repository performance challenging. There are no fault data, other than the prior information, for 
the lower fault layer, CHn/CFu. Sensitivity studies with respect to CHn and CFu fault properties

  
  153  
could help to investigate the effects of hydrogeologic parameters on transport between the 
potential repository and the water table and reduce uncertainty in these parameters. 
Sensitivity studies were conducted for this study using the 3-D site-scale flow and transport 
model. The results indicate that cumulative transport fluxes at the water table are not sensitive to 
variations in fracture permeability and capillary pressure parameters used to describe the CHn 
and CFu faults. Among major faults, transport fluxes mainly go through Drill Hole Wash, 
Sundance, and Ghost Dance faults from the potential repository to the water table. 
239000 
238000 
237000 
236000 
235000 
234000 
233000 
232000 
231000 
230000 
229000 
168000 170000 172000 174000 
a 
SOURCE: CRWMS M&O 2000 [114277] 
Figure 6.5-8. Location of the Major Faults and Boreholes at Yucca Mountain 
6.5.2.2 Conceptual Model 
Fluid flow in faults has been described using various conceptual models based on several factors, 
including the type of rock, the proximity of a region of the fault zone to the surface and/or the 
water table, and the degree of offset along the fault. 
Because there are no fault data for units below TSw, they are taken as analogous to those of PTn. 
In some respects, the rocks below the TSw will behave like the PTn in the fault zone. The more 
plastic character of the rocks will reduce the intensity of fracturing in comparison to the densely

  
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welded rocks. Gouge formation is also expected to be important for mountain-scale flow in these 
nonwelded units. However, in some places, most notably east of the Solitario Canyon Fault, the 
Bullfrog and Tram units are above the water table. These units are more welded and therefore, 
where they are faulted, they are expected to behave more like the TCw and TSw with very 
intense fracturing. All of the units below the TSw are near the present water table and are 
therefore likely to have undergone hydrothermal alteration in the past under higher water table 
conditions. Hydrothermal alteration will serve to reduce the permeability of the fault zone. The 
reduced permeability of fault zones below the TSw will aid the formation of perched water at the 
base of the TSw where structural traps are formed by fault offset. The fault zones are likely to be 
more permeable than the surrounding altered rock, and thus will still form the main drain from 
perched water zones. 
Characterization of the hydrogeologic setting at Yucca Mountain is complicated by the presence 
of numerous faults. Other than geologic-mapping studies, limited data have been collected to 
characterize faults at Yucca Mountain. Types of data available include pneumatic pressure 
monitoring, air-injection and tracer-testing data, core sample measurements of water potential 
and saturation, in situ measurements of water potential, fracture characteristics and temperature 
and geochemical data. An east-west vertical cross section model through borehole USW UZ-7a 
was used to calibrate parameters for the faults (CRWMS M&O 2000 [144426], Section 6). Data 
from USW UZ-7a are the most comprehensive with respect to faults. Saturation, water potential, 
and pneumatic pressure data are available within the Ghost Dance fault zone from the surface to 
the upper layers of the TSw. Because data are limited, it is best to characterize one fault (Ghost 
Dance fault) as completely as possible and apply these properties to all other faults. 
Heterogeneity in faults is considered a function of major hydrogeologic units. The limited data 
were separated into four layers (TCw, PTn, TSw, and CHn/CFu) to reduce the number of 
calibration parameters. Data for inversion are only available for the first three layers. Fracture 
permeability for the CHn unit is based on only one measurement in the CHn (CRWMS M&O 
2000 [145771], Table 5). Fracture permeability for the TCw and TSw fault layers is given by the 
crosshole air-injection tests. Permeability for the PTn and CHn/CFu fault layers is calculated by 
scaling the weighted average bulk-rock fracture permeability. Equivalent fracture permeability is 
calculated for all four fault layers using the weighted harmonic mean of permeabilities for the 
corresponding non-fault model layers. The average ratio of the measured permeability to the 
calculated equivalent permeability for layers TCw and TSw is calculated. This factor multiplies 
the calculated equivalent permeability of the PTn and CHn/CFu layers to scale them up. Fracture 
porosity is determined by scaling the weighted arithmetic mean of bulk rock fracture porosity. 
The scaling factor is the ratio of fault fracture aperture to mean bulk rock fracture aperture. The 
fracture-to-matrix connection area for the faults is approximated as the weighted arithmetic mean 
of bulk rock fracture to matrix connection area. The process is explained in Analysis of 
Hydrologic Properties Data (CRWMS M&O 2000 [145771]). Calibrated data sets are used in 
the base case of this study. 
6.5.2.3 Model Setup and Sensitivity Studies 
Fluid flow in faults has been simulated using many different conceptualizations including a 
fractured medium, a seepage face, a single- or double-porosity medium, and a dual-permeability 
medium.

  
  155  
Sensitivity studies were conducted in this work to consider the impact of varying (i.e., increasing 
and decreasing) CHn and CFu fault fracture permeability and van Genuchten curve-fitting . 
parameter on transport fluxes from the potential repository to the water table. 
A three-dimensional dual-permeability model, T2R3D V1.4 (LBNL 1999 [113942]), and 
TOUGH2 V1.4 (LBNL 2000 [146496]) were employed for the sensitivity studies described 
herein. Simulation grids, basic hydrologic properties of rock matrix, and fractures are the same 
as those used in the 3-D UZ perched water model (DTN: LB990801233129.003 [122757], DTN: 
LB990701233129.001 [106785]). The T2R3D module simulates transport of radionuclides in 3- 
D multiphase subsurface systems. A conservative liquid tracer applied at the potential repository 
is observed using bot_sum.f V1.0 (LBNL 2000 [153471]) to study the effect of fault parameters 
on tracer flow in a steady-state flow field. The dual-permeability formulation was used for all 
simulations to describe fracture and matrix continua within and outside of the fault zones. 
For each sensitivity run, fault properties were changed throughout the CHn and CFu layers. The 
base-case values of fracture permeability and van Genuchten curve-fitting parameter . for 
matrix and fracture are 0.36 . 10-12 m2, 0.979 . 10-6 Pa-1, and 0.23 . 10-2 Pa-1, respectively. For 
the sensitivity studies, permeability is increased and decreased by two orders of magnitude, and 
. is increased and decreased by one order of magnitude. This range is appropriate considering 
the limited available data. 
The top model boundary represents the ground surface of the mountain or, where present, the 
bottom of the alluvium. The bottom boundary of the model represents the water table, which is a 
relatively flat, stable surface. Lateral boundaries are treated as no-flow boundaries. The spatial 
distribution of net infiltration along the top ground surface boundary was described in UZ Flow 
Models and Submodels (CRWMS M&O 2000 [122797]; DTN: LB990801233129.003 
[122757]). 
6.5.2.4 Results 
Sensitivity-study results can be evaluated considering both the distribution of instantaneous and 
cumulative tracer fluxes at the water table. Figure 6.5-9 shows the changes in the total 
cumulative tracer fluxes at the water table to the base case as a result of increasing and 
decreasing fracture permeability and van Genuchten parameter .. There are basically no 
differences in these curves in terms of both breakthrough times and amount of tracer fluxes, 
indicating that the model is not sensitive to the order-of-magnitude changes in these flow 
parameters. The results of an impermeable-fault case are also shown in this figure, and again 
with little difference compared to other cases. Table 6.5-4 lists the percentages of cumulative 
tracer fluxes going through each major fault relative to the total cumulative tracer flux at the 
water table at a simulation time of 1 million years. For all scenarios, the total tracer flux through 
faults is approximately 20%, with the Drill Hole Wash fault containing the majority of that flux 
(about 15%). The Sundance and Ghost Dance faults account for most of the remaining 5% of the 
total flux, while the other modeled faults do not significantly participate in tracer transport. 
Except for the high capillarity (low .) case, which results in a 34% increase in total flux, there 
are no notable differences among the different simulation scenarios. Figures 6.5-10 through 6.5- 
12 show the distributions of cumulative tracer fluxes along the three faults with the higher 
percentages. The results are consistent with those given in the table. For Sundance and Ghost

  
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Dance faults, the case with higher capillary pressure gives a slightly higher cumulative tracer 
flux, but this difference was not observed in Drill Hole Wash fault. Figure 6.5-13 show the 
cumulative tracer fluxes along an east-west cross section that crosses the faults of Solitario 
Canyon, Splay, Ghost Dance (west), Ghost Dance, Dune Wash, and Imbricate and goes through 
borehole USW UZ-7a. Higher tracer fluxes can be observed around fault zones.

  
  157  
Table 6.5-4. Cumulative Tracer Fluxes Reaching Water Table through Major Faults after One Million 
Years as a Percentage of Total Flux 
Faults Base Case High 
Permeability 
Low 
Permeability 
High 
Capillary 
Pressure 
(low .. 
Low 
Capillary 
Pressure 
(high .. 
Impermeable 
Case 
Drill Hole Wash 15.05 15.20 14.86 16.26 14.78 0.00 
Sundance 2.18 2.23 2.09 2.80 2.11 0.00 
Ghost Dance 1.63 1.68 1.55 2.80 1.54 0.00 
Ghost Dance West 1.06 1.15 0.79 1.67 1.00 0.00 
Solitario Canyon 0.08 0.08 0.07 0.09 0.07 0.00 
Splay 0.01 0.01 0.01 0.01 0.01 0.00 
Dune Wash, Dune west, 
Dune X 
0.00 0.00 0.00 0.00 0.00 0.00 
Imbricate 0.00 0.00 0.00 0.00 0.00 0.00 
Pagany Wash 0.00 0.00 0.00 0.00 0.00 0.00 
Sever Wash 0.00 0.00 0.00 0.00 0.00 0.00 
Solitario Canyon West 0.00 0.00 0.00 0.00 0.00 0.00 
Solj Fat 0.00 0.00 0.00 0.00 0.00 0.00 
Total 20.0 20.4 19.4 23.6 19.5 0.00 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 
Time [years] 
Water table cumulative tracer flux (fraction) 
base case 
high permeability 
low permeability 
high capillary pressure 
low capillary pressure 
impermeable case 
DTN: LB0104AMRU0185.008 
Figure 6.5-9. Cumulative Tracer Fluxes at the Water Table

  
  158  
0
2
4
6
8 
170000 170500 171000 171500 172000 172500 173000 
Along Drill Hole Wash Fault (Easting, m) 
Cumulative tracer flux (%) 
base case 
high permeability 
low permeability 
high capillary pressure 
low capillary pressure 
impermeable case 
DTN: LB0104AMRU0185.013 
Figure 6.5-10. Cumulative Tracer Fluxes along the Drill Hole Wash Fault 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
171000 171050 171100 171150 171200 171250 171300 
Along Sundance Fault (Easting, m) 
Cumulative tracer flux (%) 
base case 
high permeability 
low permeability 
high capillary pressure 
low capillary pressure 
impermeable case 
DTN: LB0104AMRU0185.013 
Figure 6.5-11. Cumulative Tracer Fluxes along the Sundance Fault

  
  159  
0.0 
0.2 
0.4 
0.6 
230000 231000 232000 233000 234000 
Along Ghost Dance Fault (Northing, m) 
Cumulative tracer flux (%) 
base case 
high permeability 
low permeability 
high capillary pressure 
low capillary pressure 
impermeable case 
DTN: LB0104AMRU0185.013 
Figure 6.5-12. Cumulative Tracer Fluxes along the Ghost Dance Fault 
0.0 
0.2 
0.4 
0.6 
0.8 
1.0 
169000 169500 170000 170500 171000 171500 172000 172500 173000 
EW cross section ( through borehole UZ-7a, Easting, m ) 
Cumulative tracer flux (%) 
base case 
high permeability 
low permeability 
high capillary pressure 
low capillary pressure 
impermeable case 
DTN: LB0104AMRU0185.013 
Figure 6.5-13. Cumulative Tracer Fluxes along EW Cross Section (through borehole USW UZ-7a)

  
  160  
6.5.2.5 Summary and Conclusions 
The role of major faults in the vicinity of the potential repository area in flow and transport 
processes within the UZ is uncertain, given the absence of information about fault hydrological 
properties below the Topopah Spring Tuff. Sensitivity of modeled flow and transport behavior to 
changes in certain key hydrological parameters assigned to major faults below the potential 
repository horizon has therefore been evaluated. Results of this study indicate that changes in 
fracture permeability within the fault zones (increased and decreased by two orders of 
magnitude) and van Genuchten parameters . for both fractures and matrix within fault zones 
(increased and decreased by one order of magnitude) have little impact on tracer transport from 
the potential repository horizon to the water table. Of the total cumulative tracer fluxes through 
the water table, about 15% go through the Drill Hole Wash fault, followed by Sundance and 
Ghost Dance faults, which combined contribute about 5%. The total tracer fluxes through faults 
are about 20%, and the case with higher capillary pressure gives about 3% higher tracer fluxes. 
It is therefore concluded that, with the current infiltration rate and conceptualization of fault 
zones and perched water, flow and transport between the potential repository horizon and the 
water table are not sensitive to these fault-zone parameters. The analysis conducted here used 
only one infiltration scenario, with the flow-through perched-water model. To explore all the 
uncertainties in the CHn/CFu flow and transport behavior, further studies need to be performed 
considering the combined factors of fractured or unfractured vitric CHn, permeable or 
impermeable faults, and flow-through or lateral-flow perched-water model. What may be more 
important is the percolation flux occurring within major fault zones, which is affected by 
infiltration rates and potential flow focusing within faults. 
6.5.3 Perched Water Models 
The objectives of this section are: (1) to summarize the available data for perched water; (2) to 
review the current perched water conceptual models and the related issues affecting potential 
repository performance; (3) to evaluate effects of different perched water conceptual models on 
flow and transport processes; and (4) to discuss several more likely scenarios of perched water 
models. 
6.5.3.1 Available Data 
Perched water has been encountered in a number of boreholes at Yucca Mountain, including 
boreholes USW UZ-14, USW SD-7, USW SD-9, USW SD-12, USW NRG-7a, USW G-2, and 
USW WT-24 (see Figure 6.5-14 for the borehole locations). These perched water observations 
were made during borehole drilling (Rautman and Engstrom 1996 [101008], p.8; Rautman and 
Engstrom 1996 [100642], p.8; Rousseau et al. 1999 [102097], pp. 170183; and DTN: 
GS980508312313.001 [109746]). The most recent perched water data were collected found from 
borehole USW WT-24 (DTN: GS980508312313.001 [109746]). The observed perched water 
data in boreholes at Yucca Mountain have been used for developing the UZ Flow Model 
(CRWMS M&O 2000 [122797]). 
Several field hydraulic pumping tests on perched water were conducted at the site. Boreholes 
tested include USW UZ-14 (DTN: GS960308312312.005 [107230]) and USW G-2 (DTN:

  
  161  
GS970208312312.003 [119786]). Some of these tests were successful and have been used to 
estimate perched water bodies and local rock permeabilities (Wu et al. 1999 [117167], pp. 178 
180). 
In addition to the observation of perched water at boreholes, a wide range of chemical and isotopic 
data was obtained from the perched water and matrix pore waters of the UZ. These data include 
tritium (3H), Carbon-14 (14C), chloride (Cl-) concentration, delta Carbon-13 (.
13C), and other 
geochemical and isotopic compositions of pore water samples (Yang et al. 1996 [100194], pp. 34 
39, Table 7, Figure 20; Rousseau et al. 1999 [102097], Table 4.2.4-1). 
6.5.3.2 Current Perched Water Models 
Since the mid-1980s, the U.S. Department of Energy has pursued a program of site-characterization 
studies designed to characterize the geological, hydrological, and geothermal conditions in the UZ 
and SZ of Yucca Mountain. During these field investigations, several perched water zones have 
been encountered (Rautman and Engstrom 1996 [101008], p.8; Rautman and Engstrom 1996 
[100642], p.8; Rousseau et al. 1999 [102097], pp. 170183; and DTN: GS980508312313.001 
[109746]). The presence of perched water bodies within Yucca Mountain may have important 
implications for flow paths and transport times of water and radionuclides through the UZ and 
therefore could have a possible impact on the performance of the potential repository. 
Perched water may accumulate where adjacent formation units have disparate hydraulic 
conductivities, such as when water migrating downward through a more permeable tuff reaches a 
much-less-permeable rock through which flow paths are limited. It may occur in a permeable layer 
overlaying a relatively impermeable layer or in a well-connected fractured unit overlaying a locally 
unfractured or poorly globally connected fractured unit. Perched water may also form along a 
dipping, low-permeability layer that is adjacent to a fault that acts as a capillary barrier to retard 
down-dip water flow. 
In general, the presence of perched water indicates that vertical percolation flux locally exceeds the 
saturated hydraulic conductivity of the perching layers. It also suggests that flow paths may not be 
completely vertical through the CHn to the water table. Instead, the water may be partially diverted 
laterally to a fault zone or other high-permeability channel that may serve to focus flow downward 
to the water table. A concern is that perched water zones may divert water around low-permeability 
zeolitic layers of a CHn formation unit underlying the potential repository horizon. Bypassing of 
these units, which have substantial capacity to retard radionuclide transport, could have an impact 
on the capability of the geologic system to retard radionuclide releases to the water table. 
In terms of groundwater flow paths, travel times, and radionuclide transport from the potential 
repository level, perched water zones and the CHn, which separates the potential repository horizon 
from the SZ, may play an important role. The predominantly nonwelded CHn, consisting mainly of 
high-porosity vitric tuffs and low-permeability zeolites, creates complex, heterogeneous flow paths 
within this unit. In addition, the existence of perched water bodies within the CHn further 
complicates assessment of the flow patterns and transport processes in the unit. 
The current perched water conceptual models are based on the UZ Flow Model (CRWMS M&O 
2000 [122797]), which is in turn built on the numerical model grids (CRWMS M&O 2000

  
  162  
[114277]) and Calibrated Properties Model (CRWMS M&O 2000 [144426]). In the UZ Flow 
Model, the UZ of Yucca Mountain is represented using two numerical discrete grids (3-D UZ 
Calibration and TSPA grids) for investigating flow and transport processes using a numerical 
modeling approach. The model domain and the associated 3-D grid are shown in Figure 6.5-14. 
Vertically, the model extends from the ground surface to the water table. Within the UZ Flow 
Model, the CHn is represented with fourteen 3-D model layers in general, based on lithostratigraphy 
and available hydrogeologic properties, as discussed in (CRWMS M&O 2000 [114277]). 
The genesis of perched water at Yucca Mountain is much debated among Yucca Mountain Project 
scientists, and several conceptual models have been discussed (e.g., Wu et al. 1999 [117167], pp. 
163164). At Yucca Mountain, occurrence of perched water is found to be associated with lowpermeability 
zeolites in the CHn or the densely welded basal vitrophyre of the TSw. The current 
conceptual model of the UZ Flow Model relies on a permeability-barrier concept for perched water 
occurrence. Related modeling studies (Wu et al. 1999 [117167] and CRWMS M&O 2000 [122797], 
Sections 6.2 and 6.6) concluded that this conceptual water-perching model is able to match the 
observation data of perched water at the site. The perched water conceptual model of the UZ Flow 
Model consists of two permeability-barrier scenarios. One (Conceptual Model #1) uses reduced 
fracture permeabilities within zeolitic layers (beneath the basal vitrophyre) as well as within the 
basal vitrophyre of the TSw unit and is called the permeability-barrier model. The other scenario 
(Conceptual Model #2) (called the unfractured zeolite model) presumes that the occurrence of 
perched water at Yucca Mountain results mainly from the lack of globally connected fractures 
within zeolitic units and that a water-perching mechanism is controlled by the low-permeability 
zeolitic matrix only (i.e., the effects of fractures in zeolites are ignored). 
In the UZ Flow Model and submodels, the perched water occurrence is assumed to follow these two 
conceptual models (the permeability-barrier and unfractured zeolite models). In addition to the two 
conceptual models, a third alternative scenario considered in the UZ Flow Model is a nonperching 
model, which provides an extreme case using the 1-D calibrated properties. This model ignores 
perched zones and their effects, and provides maximum and rapid vertical flow through all the 
layers in the CHn.

  
  163  
Source: CRWMS M&O 2000 [122797], Figure 6-2 
DTN: LB990701233129.001 [106785] 
Figure 6.5-14. Plan View of the 3-D UZ TSPA Model Grid, Showing the Model Domain, Faults 
Incorporated, and Borehole Locations 
While several mechanisms may be responsible for the occurrence of perched water in the formation 
below the potential repository, the main concern with respect to PA is the impact of perched water 
on radionuclide transport from the potential repository to the water table. Evaluation of perched 
water effects on radionuclide transport depends, among other factors, on perched water conceptual 
models. Modeling studies in UZ Flow Models and Submodels (CRWMS M&O 2000 [122797]) 
indicate that for sorbing (reactive) radionuclides, the current perched water conceptual model is very 
conservative. This is because the current model predicts significant lateral flow over or within the 
zeolitic units of the CHn, which therefore reduces the amount of water flowing through the zeolites. 
As a result, the potential of highly sorbing or retardation effects of these zeolitic rocks is not 
sufficiently utilized, and a large mount of bypassing water, carrying radionuclides, goes through 
lower-sorbing vitric zones, faults, and/or high-permeability fractures. 
For nonsorbing (conservative) radionuclides, without the benefit of adsorption on rocks, the major 
factor to determine transport times under steady-state percolation condition is matrix diffusion 
and/or liquid dilution for a pulse release of radionuclides from the potential repository neither of

  
  164  
which are related to the perched water conceptual models. In this case, transport times of 
conservative radionuclides are determined by several competing factors, which also depend on how 
much water flows through vertically and how much is diverted laterally. On the one hand, a large 
amount of water rapidly flowing through fractures in the underlying zeolites will leave little time for 
matrix diffusion and liquid dilution. This would result in very short radionuclide breakthrough times 
at the water table (conservative model results). However, the modeling studies indicate that this is a 
very unlikely scenario because the observed perched water occurrence cannot be matched by this 
model. On the other hand, if a large amount of water is significantly diverted laterally, the resulting 
groundwater travel distance or travel times along these diverted flow paths will be longer, compared 
to paths with rapidly vertical flow. However, intensive lateral diversion over perched water zones 
and significantly focused flow over small areas of faults or fractured channels will decrease the 
amount of water seeping through perched bodies and low-permeability zeolites. This will 
significantly reduce contact between flowing water (carrying radionuclides) and rock matrix blocks 
and will result in a minimum benefit of matrix diffusion and liquid dilution for retarding the 
radionuclide migration. Therefore, even with the longer lateral travel distance, less vertical flow 
through reduces interaction with low permeability zeolites and as a result may lead to shorter overall 
transport time. 
6.5.3.3 Alternative Perched Water Conceptual Models 
Conceptual models involving perched water occurrence in the UZ below the potential repository 
horizon are of particular interest in assessing nature-system performance of the potential repository. 
Waste isolation strategies at the potential repository depend in part on sorption within the 
zeolitically altered CHn and on groundwater travel times between the potential repository horizon 
and the water table. 
There are several alternative conceptual models regarding the formation of perched water bodies. 
One of them is called the fault-controlled perching model. This conceptual model was proposed 
by USGS scientists to explain the thick perched body present in USW UZ-1 and USW UZ-14 of 
the North Ramp (Rousseau et al. 1999 [102097], pp. 170183). In this hypothesis, the water 
perching in this area may result from the presence of a northeast trending fault that forms a 
barrier to lateral water flow. In the UZ, faults may play an important role in forming localized 
perched water bodies and were considered as a possible perching mechanism (Montazer and 
Wilson 1984 [100161], Figure 14, p. 45) for Yucca Mountain. However, lack of detailed 
characterization studies of faults and, in particular, limited knowledge of fracture and matrix 
properties within and near faults make it very difficult to test this conceptual model using the 3- 
D site-scale model. 
Three possible conceptual explanations for water perching are illustrated in Figures 6.5-15, 6.5-16, 
and 6.5-17, for the northern part of the UZ model domain. The geological information along the 
cross section is closely based on the current geological framework model. Figure 6.5-15 presents a 
very simplified scenario for the non-water perching model. This model assumes that fractures in the 
basal vitrophyre and in the CHn are so extensive that no large or significant perched bodies can 
form and perched water effects can be ignored. Another extreme case, shown in Figure 6.5-16, is 
that extensive, continuous perched water zones exist, leading to significant, large-scale lateral flow 
and a small percentage of vertical flow through. Figure 6.5-17 presents a water-perching scenario

  
  165  
between the two extremes, with discontinuous but quite large perched bodies and moderate lateral 
flow, mainly within the perched zones. 
Figure 6.5-15. Schematic of Non-Water Perching Model in the Northern Part of the UZ Flow Model 
Domain with Extensive Globally Connected Fractures, Ignoring Perched Water Effects 
with Little Lateral Diversion

  
  166  
Figure 6.5-16. Schematic of Permeability-Barrier Model (Conceptual Model #1) in the Northern Part of 
the UZ Flow Model Domain with Additional Conceptual Model Element of Few Globally 
Connected Fractures. This Model Results in Large, Continuous Perched Water Bodies, 
Limited Vertical Flow under the Perched Water Bodies, and Extensive Lateral Flow to 
Faults

  
  167  
Figure 6.5-17. Schematic of Permeability-Barrier Model (Conceptual Model #1) in the Northern Part of 
the UZ Flow Model Domain with Additional Conceptual Model Element of Some 
Globally Connected Fractures. This Results in Discontinuous Perched Water Bodies, 
Limited Vertical Flow only Directly under Perched Bodies, Limited Lateral Flow to 
Faults and Areas between Perched Water Bodies. 
The identification of controlling mechanisms for perched water occurrence at Yucca Mountain is 
complicated by the lack of field data, as well as by large uncertainties about the exact locations 
of many of the key geological formations and the past infiltration history. The conceptual models 
for water perching, as discussed above, need to be further investigated before a better 
understanding can be obtained of the perched water conditions at Yucca Mountain. 
6.5.3.3.1 Results and Analyses 
This section analyzes and compares modeling results of six 3-D simulations of flow and transport, 
respectively, using the UZ 3-D TSPA grid and present-day, mean infiltration scenario. The 
simulations are based on perched water Conceptual Models #1 and #2, with modifications to the 
vitric zone conceptual models and fracture properties in the zeolites associated with perched water 
bodies. The details on the numerical method, modeling approach, boundary, and initial condition 
specifications are the same as those in UZ Flow Models and Submodels (CRWMS M&O 2000 
[122797]).

  
  168  
The simulation scenarios of flow and transport, which use TOUGH2 V1.4 (LBNL 2000 [146496]) 
and T2R3D V1.4 (LBNL 1999 [113942]), are listed in Table 6.5-5. This table summarizes the 
simulation cases, associated conceptual models/grids, and parameter sets. As shown in Table 6.5-5, 
two (pa_pchm1 and pa_pchm2) of the six flow scenarios are directly taken from the work on the UZ 
Flow Model (CRWMS M&O 2000 [122797]). The three new simulations (exp_m1, exp_m2 and 
exp_m3) implement the new estimated parameters, which ignore fracture-flow effects within vitric 
zones, as discussed in Section 6.5.1. Fracture parameters for the grid are modified using vf_con.for 
V1.0 (LBNL 2001 [154345]). In addition, fracture permeabilities are increased by a factor 10 and 
100, respectively, for potentially water perching zeolites to investigate effects of large vertical flow 
through perched water bodies. 
Table 6.5-5. Six Flow and Transport Simulation Scenarios: INPUT Files, Conceptual Models/Grids, 
with Present-Day, Mean Infiltration Rate 
Designation/ 
Flow 
Simulation 
Designation/ 
Transport 
Simulation 
Perched Water Conceptual 
Model/Numerical grid 
Description/ 
Parameter DTN 
pa_pchm1 
DTN: 
LB990801233 
129.003 
[122757] 
pam1_tr1 
pam1_tr2 
DTN: 
LB9908T12331 
29.001 [147115] 
#1 
permeability-barrier model/ 
3d2kpa_pc1.mesh 
DTN: LB990701233129.001 
[106785] 
Taken from the AMR on UZ Flow Models 
and Submodels (CRWMS M&O 2000 
[122797]) 
(DTN: LB991121233129.001 [147328]) 
exp_m1 expm1_tr1 
expm1_tr2 
#1 
permeability-barrier model/ 
3d2knvf_pc1.mesh 
DTN: LB0104AMRU0185.009 
New simulation, modifying parameter set 
(DTN: LB991121233129.001 [147328]) 
with unfractured CHn vitric unit 
(DTN: LB0103CHVUPROP.001) 
exp_m2 expm2_tr1 
expm2_tr2 
#1 
permeability-barrier model/ 
3d2knvf-pc1.mesh 
DTN: LB0104AMRU0185.009 
New simulation, modifying parameter set 
(DTN: LB991121233129.001 [147328]) 
with unfractured CHn vitric unit 
(DTN: LB0103CHVUPROP.001) and 
increasing fracture permeabilities in 
potentially perched zeolites by a factor of 
10 
exp_m3 expm3_tr1 
expm3_tr2 
#1 
permeability-barrier model/ 
3d2knvf_pc1.mesh 
DTN: LB0104AMRU0185.009 
New simulation, modifying parameter set 
(DTN: LB991121233129.001 [147328]) 
with unfractured CHn vitric unit 
(DTN: LB0103CHVUPROP.001) and 
increasing fracture permeabilities in 
potentially perched zeolites by a factor of 
100 
pa_pchm2 
DTN: 
LB990801233 
129.004 
[117129] 
pchm2_tr1 
pchm2_tr2 
DTN: 
LB9908T12331 
29.001 [147115] 
#2 
unfractured zeolitic model/ 
3d2kpa_pc2.mesh 
DTN: LB990701233129.001 
[106785] 
Taken from the AMR on UZ Flow Models 
and Submodels (CRWMS M&O 2000 
[122797]) 
(DTN: LB991121233129.002 [147334]) 
exp_pch2 expch2_tr1 
expch2_tr2 
#2 
unfractured zeolitic model/ 
3d2knvf_pc2.mesh 
DTN: LB0104AMRU0185.009 
New simulation, modifying parameter set 
(DTNs: LB991121233129.002 [147334]; 
with unfractured CHn vitric unit 
(DTN: LB0103CHVUPROP.001)

  
  169  
In Table 6.5-5, *_tr1 represents transport simulations for conservative/nonsorbing 
tracer/radionuclide and *_tr2 for reactive/sorbing tracer transport. Transport properties for nonsorbing 
and sorbing tracers correspond to those of technetium (99Tc) and neptunium (237Np) 
(CRWMS M&O 2000 [122797]), when not explained. 
Examination of Flow Model Results: The two flow and transport scenarios of Table 6.5-5, 
corresponding to flow scenarios pa_pchm1 and pa_pchm2, were developed in the AMR UZ 
Flow Models and Submodels (CRWMS M&O 2000 [122797]), and the results have already been 
checked. For the rest of the four flow fields, we have compared the model results with the field 
observed data of matrix liquid saturation and water potentials (when available) (DTNs: 
MO0109HYMXPROP.001 [155989], GS980808312242.014 [106748], GS980708312242.010 
[106752]), and perched water elevations (see DTNs given in Section 6.5.3.1), and reasonable 
agreement is observed (Wu 2001 [155676], pp. 216254; Bodvarsson 2001 [156334], YMP-LBNLYSW-
4, pp. 720; Zellmer 2001 [155956], pp. 913, 3948, 85). 
Comparisons with Measured Chloride Data: Geochemical data provide additional information 
to analyze the UZ flow process and history. Here pore-water chloride chemical concentration 
data are used to examine the perched water model and resultant flow fields. Distribution of 
chemical constituents in both liquid and solid phases of the UZ system depends on many factors, 
such as hydrological and geochemical processes of surface precipitation, evapotranspiration, the 
fracture-matrix interactions of flow and transport, large-scale mixing via lateral transport, and the 
history of climate changes and surface recharge. 
The results of three-dimensional chemical transport simulations using the steady-state flow field, 
exp_m2, have been compared with measured pore-water chloride concentration data in this 
study. (The data available and applied are from samples collected from boreholes (USW NRG-6, 
USW NRG-7a, USW SD-6, USW SD-7, USW SD-9, USW SD-12, USW UZ-14, and UE-25 
UZ#16); the ECRB tunnel; and the Exploratory Studies Facilities tunnel, including South Ramp, 
North Ramp, and Main Drift (Data Sources: DTN: GS950608312272.001 [145617], 
DTN: GS990208312272.001 [146134], DTN: LA9909JF831222.004 [145598], 
DTN: LA0002JF12213U.002 [156281]).) Detailed descriptions of these data are given in reports 
by Yang et al. (1998 [101441]) and Fabryka-Martin et al. (1997 [100145]). Chloride surface flux 
is obtained by applying a mean chloride concentration to precipitated water. Combining the 
mean annual precipitation of about 170 mm/year (Flint et al. 1996 [100147]) with a present-day 
chloride surface flux of 106 mg/m2/year (Flint et al. 1996 [100147]) yields a mean chloride 
concentration of about 0.62 mg/L (Fabryka-Martin et al. 1997 [100144]; Sonnenthal and 
Bodvarsson 1999 [117127]). The system is assumed to be under two-phase isothermal flow 
conditions for water and air. Major chemical transport processes taken into account are advection 
and molecular diffusion. 
Model and basic hydrologic properties of rock matrix and fractures are the same as those used in 
the flow model. Boundary conditions for chemical components of chloride are treated similarly 
to those for flow simulations, with mass fluxes described at the top boundary and no-flow and 
water table conditions at the lateral and bottom boundaries, respectively. Diffusion coefficients 
used were those for chemical ions at 25oC and infinite dilution in water (Lasaga 1998 [117091]).

  
  170  
Simulated chloride concentrations from the 3-D transport model are compared with measured 
chloride concentrations at boreholes USW SD-7, USW SD-9, USW SD-12, USW UZ-14, and 
UE-25 UZ#16 as well as along the ECRB and ESF tunnels. The model results are found in 
reasonable agreement with the field (Bodvarsson 2001 [156334], YMP-LBNL-YSW-4, pp. 13 
17). 
Percolation Fluxes at the Potential Repository and the Water Table: Percolation fluxes at the 
potential repository horizon, simulated using the present-day, mean infiltration map, are almost the 
same for the six flow fields. This is because the only difference between the six models is in the 
flow properties and conceptualization for the CHn and the bottom portion of the TSw, which has 
little effect on the upstream flow condition in an upper elevation (at the potential repository 
horizon). One example of percolation fluxes at the potential repository level is shown in Figure 6.5- 
18, indicating a very nonuniform distribution (with high percolation fluxes) located mainly at the 
northern part, over the potential repository area along the mountain ridge, and the Solitario Canyon 
Fault in the middle-to-south portion of the model domain. 
DTN: LB0104AMRU0185.009 
Figure 6.5-18. Simulated Percolation Fluxes at the Potential Repository Horizon under Present-Day, 
Mean Infiltration Using the Results of Simulation exp_m1

  
  171  
A comparison of the simulated percolation fluxes at the water table with the six simulations 
(Figures 6.5-19 to 6.5-24) for the perched water, vitric, and zeolitic fracture conceptual models, 
reveals the following: 
. Conceptual Model #1 predicts the least flow-through or maximum bypassing over 
perched water zones or zeolites in the northern part of the model domain. In the area 
directly below the potential repository or vitric zones in the southern part of the model 
domain, this model results in a large vertical flow-through (Figure 6.5-19). 
. Conceptual Model #1 with unfractured vitric zone modification shows the least vertical 
flow-through in the southern part of the model domain, the vitric zones below the 
potential repository (Figures 6.5-20). 
. Conceptual Model #1, with reduced fracture permeability in potential water perching 
zeolites, as well as unfractured vitric zone modification, predicts significantly more 
vertical flow-through in the northern part of the model domain and less lateral diversion 
(Figures 6.5-21 and 6.5-22) than the original scenario. 
. Conceptual Model #2, with (Figures 6.5-23) or without (Figure 6.5-24) unfractured 
vitric zone modification, predicts similar vertical flow patterns through the CHn below 
the potential repository, but significantly less vertical flow-through in the northern part 
of the model domain, compared with Conceptual Model #1.

  
  172  
DTN: LB990801233129.003 [122757] 
Figure 6.5-19. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation pa_pchm1, Conceptual Model #1

  
  173  
DTN: LB0104AMRU0185.009 
Figure 6.5-20. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation exp_m1, Conceptual Model #1 with Unfractured Vitric 
Zones

  
  174  
DTN: LB0104AMRU0185.009 
Figure 6.5-21. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation exp_m1, Conceptual Model #1 with Unfractured Vitric 
Zones and Reduction of a Factor 10 for Fracture Permeability in Potential Water 
Perching Zeolites

  
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DTN: LB0104AMRU0185.009 
Figure 6.5-22. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation exp_m1, Conceptual Model #1 with Unfractured Vitric 
Zones and Reduction of a Factor 100 for Fracture Permeability in Potential Water 
Perching Zeolites

  
  176  
DTN: LB0104AMRU0185.009 
Figure 6.5-23. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation pa-pchm2, Conceptual Model #2

  
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DTN: LB0104AMRU0185.009 
Figure 6.5-24. Simulated Percolation Fluxes at the Water Table under Present-Day, Mean Infiltration 
Using the Results of Simulation exp_pch2, Conceptual Model #2 with Unfractured 
Vitric Zones 
Flow Through versus Bypassing in Perched Water Zones: The percentage of water flowing 
through or bypassing perched water bodies below the potential repository may have an impact on 
groundwater flow paths and travel times. This can, in turn, affect the amount of radionuclides that 
can sorb on to sorptive materials or diffuse into low-permeability rock matrixes. As a result, the 
percentage of the percolation flux through highly sorptive rock matrix over the total percolation 
fluxes will have a direct impact on performance of the potential repository. The percentage of flowthrough 
or bypassing of perched bodies can be further analyzed using the 3-D model results. Figure 
6.5-25 shows vertical flow distributions at locations near USW UZ-14 from the six model results. 
The location of USW UZ-14 is shown in Figure 6.5-14, which is located in the north of the potential 
repository. 
Figure 6.5-25 shows that at the location near USW UZ-14, vertical fluxes through the perched water 
or zeolitic zones vary significantly with conceptual models. The simulations with non-water 
perching and high fracture permeability (by a factor of 100) predict the highest vertical 
flow-through. As fracture permeability in zeolites decreases, vertical flow decreases and indicates

  
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more lateral diversion. The original Conceptual Model #1 gives very low vertical flow and 
Conceptual Model #2, or unfractured zeolitic zone model, predicts the lowest vertical flux at this 
location. 
Liquid Flux (mm/yr) 
Elevation (m) 
0.0 2.0 4.0 6.0 8.0 10.0 
700 
800 
900 
1000 
1100 
1200 
1300 
exp-m1 
exp-m2 
exp-m3 
pa-pchm1 
non-perching 
exp-pch2 
UZ-14 
NOTE: See Table 6.5-5 for key to legend 
DTN: LB0104AMRU0185.009, except for pa-pchm1 DTN: LB990801233129.003 [122757] 
and non-perching DTN: LB990801233129.019 [144659] 
Figure 6.5-25. Comparisons Between Simulated Vertical Percolation Fluxes at the Location of USW 
UZ-14 Using Different Perched Water, CHn Vitric and Zeolitic Fracture Permeabilities 
Effects on Tracer Transport Times: For each flow simulation, as listed in Table 6.5-5, two 
transport runs (in general) were carried out for conservative and reactive tracer transport, 
respectively. Tracer or radionuclide migration times since its release from the potential repository to 
the water table can be analyzed using a cumulative or fractional-mass curve. Figures 6.5-26 and 6.5- 
27 present the fractional-mass breakthrough curves for conservative and reactive tracers (i.e., 
nonsorbing and sorbing), respectively, using perched water Conceptual Model #1. Figure 6.5-28 
shows the results for perched water Conceptual Model #2. In these figures, fractional mass 
breakthrough is defined as the cumulative mass of tracer or radionuclide arriving at the water table 
over the entire bottom of the model boundary at the time, normalized by the total initial mass at the 
potential repository.

  
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Figure 6.5-26 shows that different CHn vitric and zeolitic fracture properties with perched water 
Conceptual Model #1 have a large impact only for early breakthrough (30% or less) of a 
conservative tracer (nonsorbing) tracer or radionuclide. For reactive tracer transport, effects of 
different perched CHn conceptual models under study seem insignificant (Figure 6.5-27). Under 
perched water Conceptual Model #2, Figure 6.5-28 shows that excluding fractures from the vitric 
CHn units has little impact on the early breakthrough times of both sorbing (up to 10,000 years) and 
nonsorbing (up to 1,000 years) tracer transport. Notable effects can be seen in the later times for 
both tracers, with the unfractured vitric model giving shorter travel times in both cases. 
100 101 102 103 104 105 106 
Time since Releasing (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Fractional Breakthrough atWater Table
pam1-tr1 
expm1-tr1 
expm2-tr1 
expm3-tr1 
NOTE: See Table 6.5-5 for key to legend 
DTN: LB0104AMRU0185.009, except for pam1-tr1 DTN: LB9908T1233129.001 [147115] 
Figure 6.5-26. Simulated Cumulative Breakthrough Curves of Conservative Tracer/Radionuclide 
Mass Arriving at the Water Table, Using Different CHn Vitric and Zeolitic Fracture 
Permeabilities with Perched Water Conceptual Model #1

  
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102 103 104 105 106 
Time since Releasing (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Fractional Breakthrough atWater Table
pam1-tr2 
expm1-tr2 
expm2-tr2 
expm3-tr2 
NOTE: See Table 6.5-5 for key to legend 
DTN: LB0104AMRU0185.009, except for pam1-tr2 DTN: LB9908T1233129.001 [147115] 
Figure 6.5-27. Simulated Cumulative Breakthrough Curves of Reactive Tracer/Radionuclide Mass 
Arriving at the Water Table, Using Different CHn Vitric and Zeolitic Fracture 
Permeabilities with Perched Water Conceptual Model #1

  
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Time since Releasing (years) 
Fractional Breakthrough at Water Table 
100 101 102 103 104 105 106 0 
0.1 
0.2 
0.3 
0.4 
0.5 
0.6 
0.7 
0.8 
0.9
1 
expch2-t1 
expch2-t2 
pchm2-tr1 
pchm2-tr2 
NOTE: See Table 6.5-5 for key to legend 
DTN: LB0104AMRU0185.009, except for pchm2-tr1 and pchm2-tr2 DTN: LB9908T1233129.001 
[147115] 
Figure 6.5-28. Simulated Cumulative Breakthrough Curves of Conservative and Reactive 
Tracer/Radionuclide Mass Arriving at the Water Table, Using Different CHn Vitric 
Models with Perched Water Conceptual Model #2 
For transport of a nonsorbing tracer, Figure 6.5-26 indicates that the original Conceptual Model #1 
(pa_pchm1), which considers fracture effects in vitric zones, results in shortest early travel times 
due to the large lateral flow over perched water zones. By ignoring fracture flow in vitric zones, 
breakthrough (exp_m1) improves a little bit during early times. If more flow through the zeolites or 
an increase in contacts is allowed in order to increase vertical flowing water and matrix blocks for 
enhancing matrix diffusion and liquid dilution effects, the simulation results (exp_m2 and exp_m3) 
show a further improvement (slightly longer early travel times). 
For transport of a sorbing tracer, Figure 6.5-27 displays very similar breakthrough behavior for the 
four flow fields with different CHn vitric and perched water conceptualizations of Conceptual 
Model #1, until 10,000 years after release from the potential repository. After that, breakthrough 
curves show some differences (by a factor of 2), with the more flow-through models (exp_m2 or 
exp_m3) predicting longest travel times.

  
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6.5.3.3.2 Likely Scenarios 
The existence of perched water bodies in the UZ of Yucca Mountain, as observed in the field 
investigations, should be considered in UZ flow modeling studies as well as in TSPA analyses. 
Different perched water conceptual models, as discussed in the previous section, may have 
significant impact on flow paths and lateral diversion in the CHn. In terms of affecting 
tracer/radionuclide transport, however, perched water conceptual models are found to have a 
large impact only for early breakthrough times of a conservative or nonsorbing tracer with 
Conceptual Model #1. These results should be taken into account when discussing the most 
likely scenario of perched water conceptual models. 
Conceptual Model #1 (permeability-barrier model) in the UZ Flow Model (CRWMS M&O 2000 
[122797]) could match observed perched water data, as well as moisture data. However, at the 
base of this model (without modification in fracture permeability in potential perching zeolites) 
are low-permeability layers of fracture and matrix in zeolitic zones, which are continuous on a 
1,000 m scale without being intersected by vertical high permeability. This may not be very 
realistic, given the highly fractured nature of the tuffs of the basal vitrophyre as well in the CHn. 
At the site, extensive lateral flow along perched water and zeolitic zones, as predicted by this 
model, may not occur. 
A more likely model of water perching is considered here to be the case of simulation scenarios 
exp_m2 or exp_m3, with schematic shown in Figure 6.5-17. Even though these two simulations 
are also based on perched water Conceptual Model #1 or the permeability-barrier concept, they 
allow for more vertical flow because of an increase in fracture permeability or connectivity 
crossing the potential water-perching zeolites. This addresses the fact that large-scale fractures 
and faults may cross certain portions of basal vitrophyre and/or zeolitic zones, and should be 
considered in conceptual models. In addition, these modified permeability-barrier conceptual 
models can also match the field observation data reasonably well, which supports the argument 
that they are the more likely scenarios. 
Under ambient moisture conditions of the unsaturated zone of the mountain, recent radionuclide 
transport modeling studies (CRWMS M&O 2000 [122797]) identify that the two most important 
parameters impacting radionuclide transport are percolation fluxes and sorbing effects. In 
addition, matrix diffusion has also been found to have significant effects on nonsorbing tracer 
transport (CRWMS M&O 2000 [144331]). Therefore, a reliable transport model should 
incorporate the most representative matrix diffusion coefficients. Figure 6.5-29 presents a 
comparison of transport simulation results using two different matrix diffusion coefficients with 
the original and modified permeability-barrier conceptual models.

  
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100 101 102 103 104 105 106 
Time since Releasing (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Fractional Breakthrough at Water Table 
pam1-tr1, Dm=3.2x10-11 m2/s 
expm1-tr1, Dm=3.2x10-1
1 m2/s 
expm1-tr1, Dm=1.6x10-10 m2/s 
expm2-tr1, Dm=1.6x10-10 m2/s 
expm3-tr1, Dm=1.6x10-10 m2/s 
expch2-tr1, Dm=3.2x10-11 m2/s
DTN: LB0104AMRU0185.009 
Figure 6.5-29. Comparison of Simulated Cumulative Breakthrough Curves of Conservative 
Tracer/Radionuclide Mass Arriving at the Water Table, Since Releasing from the 
Potential Repository, Using the Different Matrix Diffusion Coefficients and Perched 
Water Conceptual Models 
In Figure 6.5-29, the first two simulations (pam1_tr1 and expm1_tr1) uses a molecular diffusion 
coefficient of Dm = 3.2 .
10-11 (m2/s) for technetium. This value may not be very representative 
(in general) for a common nonsorbing tracer or radionuclide to diffuse in water phase. A value of 
Dm = 1.6 .
10-10 (m2/s) is within a range of tritiated water diffusion coefficient (Dm = 2.236 .
10- 
9, m2/s) (Mills 1973 [133392]), multiplied by a tortuosity of matrix porosity, as estimated in the 
AMR on ambient transport (CRWMS M&O 2000 [144331]). This modified effective molecular 
diffusion coefficient is also equivalent to the molecular coefficient measured for tritium (3H) 
transport (DTN: LA000000000034.001 [148602]; BSC 2001 [154874]). Using this modified, 
more representative matrix diffusion coefficient, the last three simulations, using the same flow 
fields, show much longer travel times in cumulative breakthrough curves for non-sorbing tracer 
transport. The reduction in fractional breakthrough is more significant during early times up to 
60% breakthrough. Note that there is little difference in the transport results among those three 
simulations whether the fracture permeability is increased by a factor of 10 or 100. Among the 
three transport simulations (exp_m1, exp_m2 and exp_m3) with unfractured vitric CHn zone

  
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modifications, exp_m2 is considered in this study to be the most likely case for explaining 
perched water occurrence. 
6.5.3.3.3 Testing to Reduce Uncertainty 
Testing to discriminate between alternative different perched water conceptual models is 
currently difficult and costly. One economical way is to make use of the existing boreholes in 
which perched water is observed to conduct further tests. A disadvantage is that this may 
measure only the disturbed conditions of perched water. Nevertheless, multiborehole interference 
tests, such as air-permeability, tracer or pumping tests (conducted using the existing boreholes in 
the northern part of the model domain by measuring pressure responses at different 
layers/elevation of the CHn), may provide critical information regarding global connections of 
fractures/faults. Another potential testing program could be conducted to extend a tunnel from 
the ESF to the lower CHn in the northern part of the potential repository, near borehole USW 
UZ-14. Through this extension direct measurements of perched water under in situ conditions and 
of fracture connection data could be made. 
6.5.4 Consideration of Radionuclide Release into Matrix Rock 
This subsection presents a modeling assessment of effects of radionuclide release from drifts into 
the rock matrix on UZ transport. The objective of this study is to evaluate potential repository 
performance under the rock matrix release scenario, rather than fractures, with the present-day, 
mean infiltration rate using the expected flow and perched water models. 
6.5.4.1 Model Description 
Most analyses of UZ radionuclide transport consider that radionuclides be released directly into 
fractures below repository drifts (CRWMS M&O 2000 [122797]; CRWMS M&O 2000 
[144331]). These release-to-fracture mechanisms assume that radionuclides, when leaking from 
canisters, would be carried mainly by dripping water, which would flow into high-permeability 
fractures below the drifts. Another reason for using this type of releasing is that such handling of 
radionuclide release results in more conservative estimates (i.e., shorter transport times) for 
TSPA calculations. There may be other radionuclide leak mechanisms from drifts, such as 
releasing to matrix tuffs, that need to be considered. The argument supporting this release-tomatrix 
scenario assumes that rock blocks directly below drifts may be very dry (with much 
lower liquid saturation than surrounding rocks) because capillary effects along drift tunnel walls 
may divert or bypass significant amounts of percolating water from the area below drifts. 
Therefore, once dropping water, carrying radionuclides within drifts, falls on the rock, it will be 
immediately sucked into matrix rocks by the strong capillary forces of the dry matrix. 
This modeling study of radionuclide release directly to the matrix, and its effects on repository 
performance is based on the UZ Flow Model (CRWMS M&O 2000 [122797]) for unsaturated 
flow fields. Specifically, the current model is built on the more likely flow scenarios, as 
discussed in Section 6.5.3, in which fractures within the vitric portion of the CHn units are 
excluded. The flow fields used in transport modeling are exp_m1 and exp_m2 (see Table 6.5-5), 
i.e., using the UZ 3-D TSPA grid and Conceptual Model #1 with modifications to fracture 
properties of the vitric zones and zeolites associated with perched water bodies (DTN:

  
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LB0104AMRU0185.009). Radionuclides are handled as conservative (nonsorbing) or reactive 
(sorbing) tracers released from repository matrix blocks, with uniform initial concentrations, and 
transported by advection and diffusion processes, under ambient percolation, at the present-day 
infiltration rate. Transport is simulated using T2R3D V1.4 (LBNL 1999 [113942]). Studies are 
further documented in Bodvarsson (2001 [156334], YMP-LBNL-YSW-4, pp. 2124). 
6.5.4.2 Results and Analyses 
The 3-D transport modeling results are in part summarized in Figure 6.5-30. For transport of a 
nonsorbing or conservative tracer, Figure 6.5-30 compares breakthrough curves for radionuclides 
at the water table, released from repository matrix blocks (M-Release) and fracture blocks (FRelease), 
using two flow fields and different molecular diffusion coefficients. Figure 6.5-30 
shows that for low molecular diffusion (Dm=3.2 . 10-11 m2/s), significantly longer (one order of 
magnitude) transport times are obtained when radionuclides are released to (or from) matrix 
blocks rather than fractures. However, for higher values of diffusion coefficients (i.e., Dm=1.6 . 
10-10 m2/s) increase in transport times by matrix release is relatively small, but travel times still 
increase by a factor of 2. This indicates that the main transport mechanism for radionuclides 
from the repository within the TSw unit is the advection by fracture flow. As matrix diffusion 
coefficients increase, more radionuclides diffuse from matrix into flowing water in fractures, 
resulting in more rapid downwards migration. 
In addition, Figure 6.5-30 shows very small differences made by the two flow fields, exp_m1 
and exp_m2, on release-to-matrix transport results. In either case, radionuclide transport times 
increase by the matrix release mechanism rather than fracture release. Additional modeling 
studies with sorbing tracer (237Np) show little difference in UZ transport times between matrix 
and fracture radionuclide release, because the retardation or sorbing effect is a more dominant 
factor in this case.

  
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100 101 102 103 104 105 106 
Time since Releasing (years) 
0 
0.2 
0.4 
0.6 
0.8
1 
Fractional Breakthrough atWater Table 
Flow/exp-m1, F-Release, Dm=3.2x10-11 m2/s 
Flow/exp-m2, F-Release, Dm=1.6x10-10 m2/s 
Flow/exp-m2, M-Release, Dm=3.2x10-11 m2/s 
Flow/exp-m2, M-Release, Dm=1.6x10-10 m2/s 
Flow/exp-m1, M-Release, Dm=3.2x10-11, m2/s 
Flow/exp-m1, M-Release, Dm=1.6x10-10 m2/s 
DTNs: LB0104AMRU0185.009, LB0104AMRU0185.010 
Figure 6.5-30. Comparisons Between Simulated Cumulative Breakthrough Curves of Conservative 
Tracer/Radionuclide Mass Arriving at the Water Table, Using Different CHn Vitric and 
Zeolitic Fracture Permeabilities with Perched Water Conceptual Model #1 
6.5.4.3 Testing to Reduce Uncertainty 
Whether radionuclides are released to matrix or to fracture rocks at repository drifts depends 
critically on the moisture condition of the tuffs immediately below the drifts. On the time scale 
of thousands of years, efforts to test or estimate long-term moisture conditions near drifts may 
prove to be difficult. However, observation could be feasible on a smaller time scale, such as 10 
to 100 years, using existing tunnels at Yucca Mountain. This may provide certain valuable 
corroborative evidence regarding a dry condition existing below a horizontal tunnel or large 
cave. In addition, tracer tests may be conducted using the ESF or ECRB to investigate tracer 
distribution and partition between matrix and fractures in rocks below the tunnels.

  
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7. SUMMARY AND CONCLUSIONS 
7.1 CONCLUSIONS AND RECOMMENDATIONS FOR UNSATURATED ZONE 
FLOW PATTERNS AND ANALYSIS 
The analyses and models presented here are in general supplemental to analyses and models 
reported in previous AMRs. The purpose of this supplemental work is to better characterize the 
nature and degree of conservatism that was incorporated into the previous work because of 
uncertainty in processes and properties and because of simplifications of processes and 
properties necessary for analysis and modeling. The supplemental work documented here has 
focused on several areas key to UZ flow and transport: synthesis of available geochemical data 
in order to allow better and more widespread use of this important data type, transport modeling 
methods intended to improve matrix diffusion characterization, improved characterization of 
several processes affecting seepage into waste emplacement drifts, and improved 
characterization and broadened uncertainty studies of flow and transport from the repository 
horizon to the water table. Except for the model results reported in Section 6.4.2, the 
investigations documented in this AMR are scoping studies to aid in determining whether work 
beyond the scope of the models and analyses used to support TSPA-SR (CRWMS M&O 2000 
[153246]) is warranted and do not support TSPA as documented in either FY01 Supplemental 
Science and Performance Analyses, Volume 2: Performance Analyses (BSC 2001 [154659]) or 
Total System Performance Assessment for the Site Recommendation (CRWMS M&O 2000 
[153246]). The model results reported in Section 6.4.2 are used for TSPA sensitivity studies as 
documented in FY01 Supplemental Science and Performance Analyses, Volume 2: Performance 
Analyses (BSC 2001 [154659], Section 3.2.2.3) Conclusions and recommendations specific to 
each study are reported below. 
7.2 CONCLUSIONS AND RECOMMENDATIONS REGARDING SYNTHESIS OF 
GEOCHEMICAL INFORMATION 
Section 6.2 presents a synthesis of available geochemical information from Yucca Mountain that 
support the conceptual models for the UZ Flow and Transport Model. The following conclusions 
can be drawn from these data: 
1. Vertical trends of ion concentrations (chloride, sulfate, sodium) in the different 
hydrogeologic units suggest at least some component of lateral flow within the 
nonwelded units. The increase in pore-water 87Sr/86Sr in the PTn tuff suggests enhanced 
water-rock interaction. The shift in dominance from divalent to monovalent cations 
reflects the ion-exchange reactions with zeolites in the CHn unit. Busted Butte tests 
show that vitric CHn exhibits strong capillary forces and matrix-dominated flow and 
tracer transport. Chloride concentrations in pore water support low infiltration (avg. ~6 
mm/yr) with small, deep percolation (0.63.3 mm/yr). 
2. 14C activities in PTn and CHn pore waters suggest that their apparent ages range from 
modern to 5,200 years. Perched water analysis has yielded dates ranging from 3,500 
11,000 years (from 14C data) and from 2,00012,000 years (from 36Cl/Cl data).

  
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3. Bomb-pulse 36Cl and 3H indicate faults/fracture zones can serve as fast flow pathways. 
However, the bulk of water moves much more slowly through the matrix. Lack of 
bomb-pulse tracers in perched water suggests no more than a small component of fastflow 
water intersects the perched zones. 
4. Due to the constraints of the geochemical studies, available geochemical evidence 
neither directly supports nor disproves the significant contribution of matrix diffusion 
in the UZ. Tests are suggested to evaluate matrix diffusion conceptual models for the 
UZ Flow and Transport Model. 
7.3 CONCLUSIONS AND RECOMMENDATIONS FOR TRANSPORT 
COMPUTATION METHODS 
Previously used transport methods and codes are reviewed and scoping studies of two methods 
for transport simulation with improved matrix diffusion characterization are conducted. Specific 
conclusions are reported below. 
7.3.1 Conclusions and Recommendations Regarding Different Transport Computation 
Methods 
For transport in fractured porous media with water flow occurring in both continua, T2R3D V1.4 
(LBNL 1999 [113942]) (with a dual continuum grid) or DCPT V1.0 (LBNL 1999 [132448]) 
software codes may be a conservative predictor of radionuclide breakthrough at the Yucca 
Mountain water table, especially at early times. By using a residence time/transfer function 
approach based on analytical solutions for a simpler system, the FEHM V2.0 particle tracking 
algorithm does not have the discretization problem associated with large matrix blocks in a dual 
continuum grid (CRWMS M&O 2000 [141418]). But it can be either a conservative or an 
optimistic predictor compared with T2R3D V1.4 (LBNL 1999 [113942]) or DCPT V1.0 (LBNL 
1999 [132448]), depending on the particular case or portion of the breakthrough because of the 
uncertainties introduced in the implementing the fracture-matrix diffusion processes. In site-scale 
transport simulations (CRWMS M&O 2000 [134732], Section 6.2.5), FEHM V2.0 (CRWMS 
M&O 2000 [141418]) is found to be generally conservative relative to DCPT V1.0 (LBNL 1999 
[132448]). However, the implementation of the fracture-matrix diffusion processes for problems 
with water flow in both continua is complicated. By using a new method for calculating 
fracture-matrix particle transfer probability, DCPT V2.0 (LBNL 2001 [154342]) has neither the 
apparent inaccuracies associated with larger matrix blocks in a dual-permeability grid that 
T2R3D V1.4 (LBNL 1999 [113942]) and DCPT V1.0 (LBNL 1999 [132448]) have, nor does it 
have the uncertainties of FEHM V2.0 (CRWMS M&O 2000 [141418]). 
Of the codes evaluated, DCPT V2.0 (LBNL 2001 [154342]) appears to be the most suitable 
simulator for such a system, considering numerical accuracy, efficiency issues, and the current 
understanding of transport processes in fractured porous media. T2R3D V1.4 (LBNL 1999 
[113942]) with a MINC grid can be an alternative, but with the associated cost of poorer 
numerical efficiency and more complicated validation requirements. 
In order to fully evaluate which code best reproduces transport at Yucca Mountain, wellcontrolled 
experiments of transport in unsaturated, fractured porous rock will be necessary to

  
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verify the numerical models used and to deepen the understanding of the fracture-matrix mass 
transfer process. No analytical solution has ever been developed in the literature for transport in 
the unsaturated fractured porous media with global water flow occurring in both continua; 
neither have any such experiments been performed. An example of a well-controlled experiment 
could be a lab experiment using tracer with a large-enough block (1 m3) of the fractured rock. 
This experiment is important for building an accurate numerical model because many aspects of 
the fracture-matrix interaction process are still unknown. Many numerical experiments show that 
fracture-matrix mass transfer is a critical process that controls how fast nuclides migrate to the 
water table. 
Development of the numerical models of flow and transport with higher spatial resolution is 
another necessary task to reduce the uncertainty of predictions. The current numerical models 
use rather coarse grids (vertically up to 60 m and laterally up to 200 m) because of limitations on 
computational resources. T2R3D and FEHM will suffer numerical mixing due to the coarser 
grids, while DCPT will suffer inaccurate interpolation of the pore velocity field. Furthermore, a 
coarse grid is expected to allow TOUGH2 to underestimate the capillary effects in the case 
where the critical layers are thin, which will lead to very different flow fields and transport 
pathways for nuclides. In such a complex and heterogeneous media as the UZ of Yucca 
Mountain, the effects on the travel time of the nuclides could be very large. Calculation of 
detailed flow fields for the UZ requires parallelization of the TOUGH2. Considerable efforts are 
also required to develop particle trackers that can simulate transport with large grids very 
efficiently. 
7.3.2 Conclusions and Recommendations Regarding Matrix Block Discretization and 
Its Effects on UZ Flow and Transport Simulations 
In Section 6.3.2, flow and transport simulations made using two-dimensional DKM and MINC 
grids are compared. The grids are a model of an east-west cross section in the northern, zeolitic 
portion of Yucca Mountain. The MINC simulation results show that under steady-state flow 
conditions all the matrix continua within a given gridblock have almost the identical water 
saturations and potentials, indicating that the matrix can be treated as a single continuum. In 
other words, the dual-permeability concept is valid for modeling steady-state flow processes in 
the unsaturated zone of Yucca Mountain. 
Comparisons between simulation results indicate that the current dual-permeability approach 
may overestimate fracture fluxes in some units, because a too-large connection distance is used 
between the fracture and matrix gridblocks. This is consistent with the noted discrepancy 
between the previously simulated fracture fluxes in the vitric Calico Hill formation and those 
implied from the tracer test results at the Busted Butte site. It is recommended to use a reduced 
connection distance in generating DKM grids for future flow simulations. The determination of 
this reduced distance needs further investigation. 
Simulation results demonstrate the significance effects of matrix diffusion and accurate 
representation of the concentration gradient near fracture-matrix interfaces on the overall 
radionuclide transport processes in the unsaturated zone of Yucca Mountain. Because the DKM 
underestimates matrix diffusion at early time, it is very likely that this model provides 
conservative estimates of the breakthrough time for radionuclide transport from the potential

  
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repository to the water table. This issue can be resolved in future site-scale flow and transport 
simulations using one of the following three approaches. 
. The most reliable approach is to directly use MINC for both flow and transport in the 
site-scale UZ model. This approach is computationally intensive. 
. The second approach is to take advantage of the finding that the DKM is valid for 
modeling steady-state flow processes as long as a reduced connection distance is used. 
In this case, flow fields are simulated with the DKM and then mapped into a MINC 
grid. The transport is simulated using the MINC grid and the computationally efficient 
T2R3D V1.4 (LBNL 1999 [113942]) which only solves the solute transport equation. 
. The third approach is to improve the current particle trackers such that they could 
handle sharp concentration gradients for a DKM grid and the corresponding flow fields. 
A detailed discussion of the current particle trackers and their capabilities is given in 
Section 6.3.1. 
7.4 CONCLUSIONS AND RECOMMENDATIONS FOR PROCESSES AFFECTING 
SEEPAGE 
Conclusions about how improved characterization of the key factors of drift degradation and 
percolation affect seepage into waste emplacement drifts are documented below. 
7.4.1 Conclusions and Recommendations for Seepage Enhancement due to Drift 
Degradation 
Conclusions about how two aspects of drift degradation, rock fall and rock bolts, affect seepage 
are reported below. 
7.4.1.1 Conclusions and Recommendations Regarding Seepage Enhancement due to 
Rockfall 
Four rockfall scenarios were selected, for which seepage calculations were conducted. Results in 
this section are based on seepage calibration model results and a review of available in situ field 
results appropriate to the Tptpmn lithostratigraphic unit and one set of data for the Tptpll unit. 
Seepage enhancement resulting from rockfall is estimated to be between 0 and 5 percent. As 
more data from these units (where the potential repository resides) are obtained in field 
measurements, parameter values, with their uncertainties and probability weightings, should be 
developed and then seepage predictions from tables in this section can be used to obtain the best 
estimates (with uncertainty ranges) for Yucca Mountain. These scoping calculations confirm that 
the approach used for seepage enhancement due to drift degradation in TSPA-SR (CRWMS 
M&O 2000 [153246]) is conservative. 
In summary, this section identifies that rockfall scenarios could have an effect on seepage into 
the drift. Seepage enhancement due to rockfall is given in DTN: LB0104AMRU0185.011.

  
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7.4.1.2 Conclusions and Recommendations Regarding the Effect of Rock Bolts on 
Seepage 
The potential for seepage enhancement due to rock bolts is investigated using a two-dimensional, 
radial model of a spherical opening with a rock bolt at the crown. A large number of model 
parameter combinations are investigated by varying the percolation rate, the formation 
capillarity, and the capillarity and permeability of the grout material surrounding the rock bolt 
and by using several models representing varying degrees of connectivity between the rock-bolt 
hole and the surrounding fractured rock near the opening. The conclusion of this investigation of 
the potential for seepage enhancement caused by rock bolts is that there is no significant 
enhancement of seepage. These scoping calculations confirm that the approach used for seepage 
enhancement due to drift degradation in TSPA-SR (CRWMS M&O 2000 [153246]) is 
conservative. 
7.4.2 Conclusions and Recommendations Regarding Focusing and Discrete Flow Paths 
in the TSw 
A series of numerical studies have been conducted to evaluate flow focusing through fractures 
from the bottom of the PTn to the potential repository horizon. The studies were carried out 
using a 100 m wide and 150 m deep 2-D flow domain and covered the upper five different 
hydrogeologic units of the TSw at Yucca Mountain. Mean fracture parameters used in the 
simulations were those developed in the Calibrated Properties Model AMR (CRWMS M&O 
2000 [144426]) as described in Section 6.4.2.2. The heterogeneous fracture permeability 
distributions were generated using a stochastic approach. The studies considered various 
percolation fluxes, correlation lengths, and uniform and nonuniform percolation-flux boundary 
conditions. The results obtained provide a quantitative analysis of flow focusing and discrete 
path formation. All simulation results indicate that the flow-focusing factor is about an order of 
magnitude smaller than the conservative value used for TSPA-SR (CRWMS M&O 2000 
[153246]) calculations. The frequency distributions of normalized flux are insensitive to 
magnitudes and spatial distributions of infiltration fluxes on the upper boundary, and to spatial 
correlation structures of the permeability fields within the UZ domains. The results of this model 
are used to support sensitivity studies for TSPA-SR (BSC 2001 [154659], Section 3.2.2.3). Flow 
focusing distributions are given in DTN: LB0104AMRU0185.012. 
7.4.3. Conclusions and Recommendations Regarding Percolation Redistribution and 
Lateral Flow in the PTn 
Percolation flux affects both waste canister performance and solute travel times to the accessible 
environment. Percolation distribution strongly depends on the infiltration rates and their spatial 
and temporal distributions. The present-day mean infiltration in the Yucca Mountain flow and 
transport models was calibrated and the percolation distribution was analyzed using pore-water 
Cl concentration data. The surface infiltration area was divided into regions according to the 
availability and range of Cl data, the range of present-day mean infiltration data, and the 
hydrostructural and the hydrogeologic features. Infiltration rates in each region were calculated 
based on the pore-water Cl concentration data and the Cl infiltration flux. Model results of threedimensional 
simulation using the calibrated infiltration map match the Cl data better compared 
with using uncalibrated infiltration map.

  
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PTn lateral flow effects on percolation and Cl distribution were studied by 3-D simulation with 
increased horizontal permeability. The degree of the effect varies by location. As expected, a 
more uniform Cl distribution under PTn was observed in most places when lateral flow effects 
increased. Further calibration can be done by adjusting layer heterogeneity and anisotropic 
permeability in different regions based on the hydrostructural features, percolation fluxes, and 
the distribution of geochemical data. 
This scoping study suggests that several approaches may be used to obtain UZ model results 
consistent with chloride data. 
7.4.4 Conclusions and Recommendations Regarding the Effect of Episodic Percolation 
on Seepage 
A two-dimensional, fracture-only model is used to conduct a scoping study to investigate the 
significance of episodic percolation at the repository level due to transient infiltration on the 
western slope of Yucca Mountain above the Solitario Canyon fault where the TSw outcrops. 
Transient infiltration events are simulated by applying all of the annual infiltration for the highest 
rate infiltration model over a one week period. The results of this model confirm the abstraction 
approach for TSPA-SR that does not include episodic percolation as a seepage enhancing factor 
(CRWMS M&O 2001 [154291], Section 6.4.4; BSC 2001 [154659], Section 3.2.2.4). 
7.5 CONCLUSIONS AND RECOMMENDATIONS FOR PROCESSES AFFECTING 
UNSATURATED ZONE FLOW AND TRANSPORT BELOW THE REPOSITORY 
HORIZON 
Conclusions reached using scoping studies for improved characterization of flow and transport 
between the repository and the water table are presented below. None of the results of studies 
documented in Section 6.5 are used for TSPA. 
7.5.1 Conclusions and Recommendations Regarding Fracture Flow in the Vitric Calico 
Hills Formation 
This section presents the incorporation of newly available data on the vitric CHn into the UZ 
Flow and Transport Model. The data, from the Busted Butte test site, suggest higher matrix 
permeability and lower matrix capillarity than the previously used data indicate. Further, tests at 
Busted Butte suggest that unsaturated flow and transport in the vitric CHn is completely matrix 
dominated. A new conceptual model in which fractures are not present in the vitric CHn is used, 
and new model parameters for these layers are estimated based prior information about the layer 
properties updated with the Busted Butte data. These new model parameters are given in DTN: 
LB0103CHVUPROP.001. Mountain-scale, three-dimensional simulations using this updated 
model show lower percolation fluxes at the water table directly under the vitric portion of the 
CHn and longer initial-breakthrough times for contaminants from the repository horizon at the 
water table. Direct validation of this model of the vitric CHn (with no fractures) is not possible 
because there are no relevant data against which to compare model predictions. However, the use 
of calibration, review of the estimated parameters for reasonableness, and technical review of the 
calibration approach through open literature as well as consistency with the Busted Butte test 
results make the model valid for its intended use of presenting an alternative model for flow and

  
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transport through the vitric CHn. At this time, further development of alternative models is not 
warranted. Rather, more data on flow and transport through the layers between the bottom of the 
TSw and the water table is needed in order to discriminate between alternative models and allow 
development of a single robust model. 
7.5.2 Conclusions and Recommendations Regarding Fault Characteristics 
The role of major faults in the vicinity of the potential repository area in flow and transport 
processes within the UZ is uncertain given the absence of information about fault hydrological 
properties below the Topopah Spring Tuff. Sensitivity of modeled flow and transport behavior to 
changes in certain key hydrological parameters assigned to major faults below the potential 
repository horizon has therefore been evaluated. Results of this study indicate that changes in 
fracture permeability within the fault zones (increased and decreased by two orders of 
magnitude) and van Genuchten parameter . for both fractures and matrix within the fault zones 
(increased and decreased by one order of magnitude) have little impact on tracer transport from 
the potential repository horizon to the water table. Of the total cumulative tracer fluxes through 
the water table, about 15% go through the Drill Hole Wash fault, followed by Sundance and 
Ghost Dance faults, which combined contribute about 5%. The total tracer fluxes through faults 
are about 20% and the case with higher capillary pressure gives about 3% higher tracer fluxes. 
It is therefore concluded that, with the current infiltration rate and conceptualization of fault 
zones and perched water, flow and transport between the potential repository horizon and the 
water table is not sensitive to these fault-zone parameters. The analysis conducted here used only 
one infiltration scenario with flow-through perched-water model. To explore all the uncertainties 
in the CHn/CFu flow and transport behavior, further studies need to be performed considering 
the combined factors of fractured or unfractured vitric CHn, permeable or impermeable faults, 
and flow-through or lateral-flow perched-water model. What may be more important is the 
percolation flux occurring within major fault zones, which is affected by infiltration rates and 
potential flow focusing within faults. 
7.5.3 Conclusions and Recommendations Regarding Perched Water Models 
Several perched water conceptual models have been examined and compared for their impact on 
the potential repository performance. Results from the 3-D UZ flow model indicate that, 
compared to the dominant processes of percolation fluxes or sorbing effects on rocks, which 
strongly affect flow and transport, perched water conceptual models have smaller effects on 
tracer or radionuclide transport from the potential repository to the water table. Perched water 
models were found to have a large impact on cumulative mass breakthrough curves of a tracer at 
the water only during the early period for a nonsorbing tracer (<30% breakthrough) with 
Conceptual Model #1. For late transport times (>30% breakthrough) of a non-sorbing tracer as 
well as the entire transport period for a sorbing tracer, different perched water conceptual models 
have only relatively small overall effects. 
A more likely scenario for perched water occurrence has been discussed. This model matches the 
observed perched water and chloride data and at the same time allows significant vertical flow 
through perched water and low permeability zeolitic zones. In addition, matrix diffusion is found 
to have large impact on non-sorbing tracer transport and should be included in developing the

  
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most reliable model scenario in estimating the groundwater travel or radionuclide transport 
times. 
7.5.4 Conclusions and Recommendations Regarding Consideration of Direct 
Radionuclide Release into Matrix Rock 
Modeling studies on radionuclide release into matrix rocks rather than fractures below repository 
drifts indicate that this type of release may have significant impact on the potential repository 
performance. In general, release-to-matrix mechanism or transport started from repository matrix 
blocks will increase radionuclide transport times in the UZ. The smaller the molecular diffusion 
coefficients are, the longer travel times will be for radionuclides released into matrix rocks under 
the currently predicted ambient percolation.

  
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8. INPUTS AND REFERENCES 
The following is a list of the references cited in this document. Column 1 represents the unique 
six digit numerical identifier, which is placed in the text following the reference callout (e.g., 
BSC 2001 [155051]). The purpose of these numbers is to assist the reader in locating a specific 
reference. Within the reference list, multiple sources by the same author (e.g., BSC 2001) are 
sorted alphabetically by title. 
8.1 CITED DOCUMENTS 
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Fractured Rock. Bear, J.; Tsang, C.F.; and de Marsily, G., eds.. 39-127. San Diego, 
California: Academic Press. TIC: 235461. 
140371 NRC (U.S. Nuclear Regulatory Commission) 1999. Issue Resolution Status Report 
Key Technical Issue: Unsaturated and Saturated Flow Under Isothermal Conditions. 
Rev. 2. Washington, D.C.: U.S. Nuclear Regulatory Commission. ACC: 
MOL.19990810.0641. 
153313 NRC (U.S. Nuclear Regulatory Commission) 2000. Issue Resolution Status Report 
Key Technical Issue: Radionuclide Transport. Rev. 2. Washington, D.C.: U.S. 
Nuclear Regulatory Commission. ACC: MOL.20010205.0058. 
155700 Olesen, T.; Moldrup, P.; Henriksen, K.; and Petersen, L.W. 1996. Modeling 
Diffusion and Reaction in Soils: IV. New Models for Predicting Ion Diffusivity. 
Soil Science, 161, (10), 633-645. [Baltimore, Maryland: Williams & Wilkins]. TIC: 
250477. 
144773 Or, D. and Ghezzehei, T.A. 2000. Dripping into Subterranean Cavities from 
Unsaturated Fractures under Evaporative Conditions. Water Resources Research, 
36, (2), 381-393. Washington, D.C.: American Geophysical Union. TIC: 246982. 
105736 Paleologos, E.K.; Neuman, S.P.; and Tartakovsky, D. 1996. Effective Hydraulic 
Conductivity of Bounded, Strongly Heterogeneous Porous Media. Water Resources 
Research, 32, (5), 1333-1341. Washington, D.C.: American Geophysical Union. 
TIC: 245760. 
155954 Pan, L. 2001. Unsaturated Zone Modeling and Synthesis. Scientific Notebook 
YMP-LBNL-GSB-LP-3. ACC: MOL.20010921.0061.

  
  202  
155875 Pan, L. and Bodvarsson, G.S. 2001. Modeling Transport in Fractured Porous Media 
with the Random-Walk Particle Method: The Transient Activity Range and the 
Particle-Transfer Probability. LBNL-84042. Berkeley, California: Lawrence 
Berkeley National Laboratory. Submit to RPC URN-0950 
105743 Philip, J.R.; Knight, J.H.; and Waechter, R.T. 1989. Unsaturated Seepage and 
Subterranean Holes: Conspectus, and Exclusion Problem for Circular Cylindrical 
Cavities. Water Resources Research, 25, (1), 16-28. Washington, D.C.: American 
Geophysical Union. TIC: 239117. 
100605 Pruess, K. 1983. GMINC - A Mesh Generator for Flow Simulations in Fractured 
Reservoirs. LBL-15227. Berkeley, California: Lawrence Berkeley Laboratory. 
ACC: NNA.19910307.0134. 
101707 Pruess, K. and Narasimhan, T.N. 1985. A Practical Method for Modeling Fluid and 
Heat Flow in Fractured Porous Media. Society of Petroleum Engineers Journal, 25, 
(1), 14-26. Dallas, Texas: Society of Petroleum Engineers. TIC: 221917. 
117112 Pruess, K.; Faybishenko, B.; and Bodvarsson, G.S. 1999. Alternative Concepts and 
Approaches for Modeling Flow and Transport in Thick Unsaturated Zones of 
Fractured Rocks. Journal of Contaminant Hydrology, 38, (1-3), 281-322. New 
York, New York: Elsevier. TIC: 244160. 
100819 Pruess, K.; Wang, J.S.Y.; and Tsang, Y.W. 1990. On Thermohydrologic 
Conditions Near High-Level Nuclear Wastes Emplaced in Partially Saturated 
Fractured Tuff, 2. Effective Continuum Approximation. Water Resources 
Research, 26, (6), 1249-1261. [Washington, D.C.]: American Geophysical Union. 
TIC: 224854. 
100642 Rautman, C.A. and Engstrom, D.A. 1996. Geology of the USW SD-12 Drill Hole 
Yucca Mountain, Nevada. SAND96-1368. Albuquerque, New Mexico: Sandia 
National Laboratories. ACC: MOL.19970613.0101. 
101008 Rautman, C.A. and Engstrom, D.A. 1996. Geology of the USW SD-7 Drill Hole 
Yucca Mountain, Nevada. SAND96-1474. Albuquerque, New Mexico: Sandia 
National Laboratories. ACC: MOL.19971218.0442. 
104252 Richards, L.A. 1931. Capillary Conduction of Liquids Through Porous Mediums. 
Physics, 1, 318-333. [New York, New York: American Physical Society]. TIC: 
225383. 
139174 Ritcey, A.C. and Wu, Y.S. 1999. Evaluation of the Effect of Future Climate 
Change on the Distribution and Movement of Moisture in the Unsaturated Zone at 
Yucca Mountain, NV. Journal of Contaminant Hydrology, 38, (1-3), 257-279. New 
York, New York: Elsevier. TIC: 244160. 
102097 Rousseau, J.P.; Kwicklis, E.M.; and Gillies, D.C., eds. 1999. Hydrogeology of the 
Unsaturated Zone, North Ramp Area of the Exploratory Studies Facility, Yucca

  
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Mountain, Nevada. Water-Resources Investigations Report 98-4050. Denver, 
Colorado: U.S. Geological Survey. ACC: MOL.19990419.0335. 
154646 Rowell, D.L.; Martin, M.W.; and Nye, P.H. 1967. The Measurement and 
Mechanism of Ion Diffusion in Soils. III. The Effect of Moisture Content and Soil- 
Solution Concentration on the Self-Diffusion of Ions in Soils. The Journal of Soil 
Science, 18, (2), 204-222. Oxford, England: Clarendon Press. TIC: 249762. 
117127 Sonnenthal, E.L. and Bodvarsson, G.S. 1999. Constraints on the Hydrology of the 
Unsaturated Zone at Yucca Mountain, NV from Three-Dimensional Models of 
Chloride and Strontium Geochemistry. Journal of Contaminant Hydrology, 38, (1- 
3), 107-156. New York, New York: Elsevier. TIC: 244160. 
105043 Sudicky, E.A. and Frind, E.O. 1982. Contaminant Transport in Fractured Porous 
Media: Analytical Solutions for a System of Parallel Fractures. Water Resources 
Research, 18, (6), 1634-1642. Washington, D.C.: American Geophysical Union. 
TIC: 217475. 
106585 Thordarson, W. 1965. Perched Ground Water in Zeolitized-Bedded Tuff, Rainier 
Mesa and Vicinity, Nevada Test Site, Nevada. TEI-862. Washington, D.C.: U.S. 
Geological Survey. ACC: NN1.19881021.0066. 
154674 USGS (U.S. Geological Survey) 2001. Simulation of Net Infiltration for Modern and 
Potential Future Climates. ANL-NBS-HS-000032 REV 00 ICN 01. 
Denver,Colorado: U.S. Geological Survey. ACC: MOL.20010405.0002. 
100610 van Genuchten, M.T. 1980. A Closed-Form Equation for Predicting the Hydraulic 
Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44, (5), 
892-898. Madison, Wisconsin: Soil Science Society of America. TIC: 217327. 
110043 Wang, J.S.Y. 1992. Variations of Hydrological Parameters of Tuff and Soil. High 
Level Radioactive Waste Management, Proceedings of the Third Annual International 
Conference, Las Vegas, Nevada, April 12-16, 1992. 1, 727-731. La Grange Park, 
Illinois: American Nuclear Society. TIC: 204231. 
104366 Wang, J.S.Y. and Elsworth, D. 1999. Permeability Changes Induced by Excavation 
in Fractured Tuff. Rock Mechanics for Industry, Proceedings of the 37th U.S. Rock 
Mechanics Symposium, Vail, Colorado, USA, 6-9 June 1999. Amadei, B.; Kranz, 
R.L.; Scott, G.A.; and Smeallie, P.H., eds. 2, 751-757. Brookfield, Vermont: A.A. 
Balkema. TIC: 245246. 
100611 Warren, J.E. and Root, P.J. 1963. The Behavior of Naturally Fractured Reservoirs. 
Society of Petroleum Engineers Journal, 3, (3), 245-255. Dallas, Texas: Society of 
Petroleum Engineers. TIC: 233671.

  
  204  
117161 Wu, Y-S.; Haukwa, C.; and Bodvarsson, G.S. 1999. A Site-Scale Model for Fluid 
and Heat Flow in the Unsaturated Zone of Yucca Mountain, Nevada. Journal of 
Contaminant Hydrology, 38, (1-3), 185-215. New York, New York: Elsevier. TIC: 
244160. 
155676 Wu, Y.S. 2001. Unsaturated Zone Modeling and Synthesis. Scientific Notebook 
YMP-LBNL-YSW-2. ACC: MOL.20010801.0330. 
117167 Wu, Y.S.; Ritcey, A.C.; and Bodvarsson, G.S. 1999. A Modeling Study of Perched 
Water Phenomena in the Unsaturated Zone at Yucca Mountain. Journal of 
Contaminant Hydrology, 38, (1-3), 157-184. New York, New York: Elsevier. TIC: 
244160. 
100194 Yang, I.C.; Rattray, G.W.; and Yu, P. 1996. Interpretation of Chemical and Isotopic 
Data from Boreholes in the Unsaturated Zone at Yucca Mountain, Nevada. Water- 
Resources Investigations Report 96-4058. Denver, Colorado: U.S. Geological 
Survey. ACC: MOL.19980528.0216. 
101441 Yang, I.C.; Yu, P.; Rattray, G.W.; Ferarese, J.S.; and Ryan, J.N. 1998. 
Hydrochemical Investigations in Characterizing the Unsaturated Zone at Yucca 
Mountain, Nevada. Water-Resources Investigations Report 98-4132. Denver, 
Colorado: U.S. Geological Survey. ACC: MOL.19981012.0790. 
149733 YMP (Yucca Mountain Site Characterization Project) 2000. Q-List. YMP/90-55Q, 
Rev. 6. Las Vegas, Nevada: Yucca Mountain Site Characterization Office. ACC: 
MOL.20000510.0177. 
155724 YMP (Yucca Mountain Site Characterization Project) 2001. Moisture Studies in the 
ESF. Field Work Package FWP-ESF-96-004, Rev. 6. Las Vegas, Nevada: Yucca 
Mountain Site Characterization Office. ACC: MOL.20010425.0002. 
155956 Zellmer, K. 2001. UZ Modeling and Synthesis. Scientific Notebook YMP-LBNLYSW-
KEZ-1. ACC: MOL.20010924.0058. 
Software Cited 
152614 Dynamic Graphics 1998. Software Code: EARTHVISION. 5.1. Silicon Graphics 
Indigo R4000. 10174-5.1-00. 
152880 Lawrence Berkeley National Laboratory 03/06/2000. Software Routine: 
minrefine3df.f. V1.0. SUN. 10472-1.0-00. 
154342 Lawrence Berkeley National Laboratory 03/31/2001. Software Code: DCPT. V2.0. 
PC w/MS Windows. STN: 10078-2.0-00. URN-0847 
146496 Lawrence Berkeley National Laboratory 1/14/2000. Software Code: TOUGH2 V1.4. 
V1.4. Sun Workstation and DEC/ALPHA. 10007-1.4-01.

  
  205  
152823 Lawrence Berkeley National Laboratory 10/17/2000. Software Routine: AddBound. 
V1.0. SUN w/Unix OS. STN: 10357-1.0-00. 
152824 Lawrence Berkeley National Laboratory 10/17/2000. Software Routine: MoveMesh. 
V1.0. SUN w/Unix OS. STN: 10358-1.0-00. 
152826 Lawrence Berkeley National Laboratory 10/17/2000. Software Routine: 
Perm2Mesh. V1.0. SUN w/Unix OS. STN: 10359-1.0-00. 
134136 Lawrence Berkeley National Laboratory 1999. Software Code: GSLIB V1.0 Module 
SISIM V1.203. V1.0. Sun, PC. 10001-1.0MSISIMV1.203-00. 
154340 Lawrence Berkeley National Laboratory 1999. Software Code: GSLIB. 
V2.0MSISIMV2.0. SUN. STN: 10098-2.0MSISIMV2.0-00. 
134754 Lawrence Berkeley National Laboratory 1999. Software Code: infil2grid V1.6. 
V1.6. PC with Windows/95 or 98. Sun or DEC Workstation with Unix OS. 10077- 
1.6-00. 
113942 Lawrence Berkeley National Laboratory 1999. Software Code: T2R3D V1.4. V1.4. 
SUN, DEC / ALPHA. 10006-1.4-00. 
112757 Lawrence Berkeley National Laboratory 1999. Software Code: ITOUGH2 
V3.2_drift. V3.2_drift. SUN. 10055-3.2_DRIFT-00. 
154337 Lawrence Berkeley National Laboratory 1999. Software Code: ITOUGH2. V3.2. 
SUN OS. STN: 10054-3.2-00. 
152828 Lawrence Berkeley National Laboratory 2000. Software Routine: CutNiche. V1.3. 
SUN w/Solaris OS. 10402-1.3-00. 
154341 Lawrence Berkeley National Laboratory 2001. Software Code: Wingridder. V1.1. 
PC w/MS Windows 98. STN: 10024-1.1-00. 
154321 Lawrence Berkeley National Laboratory 2001. Software Routine: AssignRock. 
V1.0. SUN w/Solaris OS. STN: 10465-1.0-00. 
154347 Lawrence Berkeley National Laboratory 2001. Software Routine: mddf.f. V2.0. 
SUN w/Solaris OS. STN: 10456-2.0-00. 
152871 Lawrence Berkeley National Laboratory 2001. Software Routine: Meshbd.f. V1.0. 
SUN. 10467-1.0-00. 
154343 Lawrence Berkeley National Laboratory 2001. Software Routine: MINCgridv1.f. 
V1.0. DEC-Alpha w/Unix OS. STN: 10469-1.0-00. 
152872 Lawrence Berkeley National Laboratory 2001. Software Routine: mininipresf.f. 
V1.0. SUN. 10470-1.0-00.

  
  206  
154349 Lawrence Berkeley National Laboratory 2001. Software Routine: mk_generGL.f. 
V1.0. SUN w/Solaris OS. STN: 10476-1.0-00. 
154346 Lawrence Berkeley National Laboratory 2001. Software Routine: parallelf.java. 
V1.0. PC w/Windows. STN: 10457-1.0-00. 
156137 Lawrence Berkeley National Laboratory 2001. Software Routine: RoutineRick1. 
V1.1. SUN w/Unix. STN: 10474-1.1-00. URN-0951 
154345 Lawrence Berkeley National Laboratory 2001. Software Routine: vf_con.for. V1.0. 
PC w/Windows. STN: 10466-1.0-00. 
139918 Lawrence Berkeley National Laboratory 9/16/99. Software Code: iTOUGH2. V4.0. 
SUN, DEC. 10003-4.0-00. 
154322 LBNL (Lawrence Berkeley National Laboratory) 03/31/2001. Software Code: 
TOUGH2. V1.5. SUN and DEC-Alpha w/Unix OS. STN: 10007-1.5-00. URN- 
0845 
153471 LBNL (Lawrence Berkeley National Laboratory) 2000. Software Routine: 
bot_sum.f. V1.0. SUN AND DEC. 10349-1.0-00. 
154785 LBNL (Lawrence Berkeley National Laboratory) 2001. Software Code: 
WINGRIDDER. V2.0. PC. STN: 10024-2.0-00. URN-0850 
154788 LBNL (Lawrence Berkeley National Laboratory) 2001. Software Routine: 
CalBT.for. V1.0. PC. STN: 10504-1.0-00. 
132448 LBNL 1999. Software Code: DCPT. V1.0. PC. 10078-1.0-00. 
8.2 CODES, STANDARDS, REGULATIONS, AND PROCEDURES 
AP-2.21Q, Rev. 1, BSCN 1. Quality Determinations and Planning for Scientific, Engineering, 
and Regulatory Compliance Activities. Washington, D.C.: U.S. Department of Energy, Office 
of Civilian Radioactive Waste Management. ACC: MOL.20010212.0018. 
AP-3.10Q, Rev. 2, ICN 4, ECN 1. Analyses and Models. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20010827.0114. 
AP-SI.1Q, Rev. 3, ICN 1, ECN 1. Software Management. Washington, D.C.: U.S. Department 
of Energy, Office of Civilian Radioactive Waste Management. ACC: MOL.20010705.0239. 
AP-SV.1Q, Rev. 0, ICN 2. Control of the Electronic Management of Information. Washington, 
D.C.: U.S. Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
MOL.20000831.0065.

  
  207  
QAP-2-3, Rev. 10, BSCN 2. Classification of Permanent Items. Washington, D.C.: U.S. 
Department of Energy, Office of Civilian Radioactive Waste Management. ACC: 
MOL.20010212.0283. 
YMP-LBNL-QIP-SV.0 Rev. 2, Mod. 0. Management of YMP-LBNL Electronic Data. Berkeley, 
California: Lawrence Berkeley National Laboratory. ACC: MOL.20001108.0155. 
8.3 SOURCE DATA, LISTED BY DATA TRACKING NUMBER 
147022 GS000399991221.002. Rainfall/Runoff/Run-on 1999 Simulations. Submittal date: 
03/10/2000. 
156375 GS010708312272.002. Chemical Data for Pore Water from Tuff Cores of USW 
NRG-6, USW NRG-7/7A, USW UZ-14, USW UZ-N55 and UE-25 UZ#16. 
Submittal date: 09/05/2001. URN-0954 
145617 GS950608312272.001. Chemical Data for Pore Water from Tuff Cores of USW 
NRG-6, NRG7/7a, UZ-14 and UZ-N55, and UE-25 UZ#16. Submittal date: 
05/30/1995. 
107230 GS960308312312.005. Water-Level, Discharge Rate and Related Data from the 
Pump Tests Conducted at Well USW UZ-14, August 17 through August 30, 1993. 
Submittal date: 03/15/1996. 
119786 GS970208312312.003. Water-Level and Related Data from Pump Tests Conducted 
at Well USW G-2, 4/8/96 - 12/17/96. Submittal date: 02/05/1997. 
109746 GS980508312313.001. Water-Level and Related Data Collected in Support of 
Perched-Water Testing in Borehole USW WT-24, September 10, 1997 through 
February 3, 1998. Submittal date: 05/07/1998. 
106752 GS980708312242.010. Physical Properties of Borehole Core Samples, and Water 
Potential Measurements Using the Filter Paper Technique, for Borehole Samples 
from USW WT-24. Submittal date: 07/27/1998. 
106748 GS980808312242.014. Physical Properties of Borehole Core Samples and Water 
Potential Measurements Using the Filter Paper Technique for Borehole Samples from 
USW SD-6. Submittal date: 08/11/1998. 
146134 GS990208312272.001. Analysis for Chemical Composition of Pore Water from 
Borehole USW UZ-14 and UE-25 UZ#16 and Groundwater from UE-25 UZ#16. 
Submittal date: 02/23/1999.

  
  208  
107185 GS990308312242.007. Laboratory and Centrifuge Measurements of Physical and 
Hydraulic Properties of Core Samples from Busted Butte Boreholes UZTT-BB-INJ-1, 
UZTT-BB-INJ-3, UZTT-BB-INJ-4, UZTT-BB-INJ-6, UZTT-BB-COL-5 and UZTTBB-
COL-8. Submittal date: 03/22/1999. 
109822 GS990708312242.008. Physical and Hydraulic Properties of Core Samples from 
Busted Butte Boreholes. Submittal date: 07/01/1999. 
148602 LA000000000034.001. Diffusion of Sorbing and Non-Sorbing Radionuclides. 
Submittal date: 01/22/1993. 
156281 LA0002JF12213U.002. Chemistry Data for Porewater Extracted from ESF, Cross 
Drift and Busted Butte Drill Core. Submittal date: 02/15/2000. 
145598 LA9909JF831222.004. Chloride, Bromide, and Sulfate Analyses of Busted Butte and 
Cross Drift Tunnel Porewaters in FY99. Submittal date: 09/29/1999. 
153141 LB00090012213U.001. Air K Testing in Borehole SYBT-ERCB-LA#2 at CS 17+26 
in Cross Drift. Submittal date: 11/03/2000. 
153393 LB0010SCMREV01.002. Developed Data from Seepage Calibration Modeling 
AMR U0080. Submittal date: 11/29/2000. 
153574 LB0011SMDCREV1.001. Seepage Model for PA Including Drift Collapse: 1. 
Model Input/Output Files AMR U0075 (MDL-NBS-HS-000002 REV01). Submittal 
date: 12/07/2000. 
153570 LB0011SMDCREV1.002. Seepage Model for PA Including Drift Collapse: 2. 
Tables of Seepage Percentages AMR U0075 (MDL-NBS-HS-000002 REV01). 
Submittal date: 12/07/2000. 
154586 LB0012AIRKTEST.001. Niche 5 Air K Testing 3/23/00-4/3/00. Submittal date: 
12/21/2000. 
146878 LB002181233124.001. Air Permeability and Pneumatic Pressure Data Collected 
Between October 27, 1999 through November 7, 1999 from Niche 5 (ECRB Niche 
1620) of the ESF. Submittal date: 02/18/2000. 
156336 LB0110MESHPROP.001. UZ Hydrostratigraphic Mesh with Faults and Zeolitic 
Alteration Zones. Submittal date: 10/08/2001. URN-0953 
106787 LB990501233129.001. Fracture Properties for the UZ Model Grids and Uncalibrated 
Fracture and Matrix Properties for the UZ Model Layers for AMR U0090, Analysis 
of Hydrologic Properties Data. Submittal date: 08/25/1999. 
106785 LB990701233129.001. 3-D UZ Model Grids for Calculation of Flow Fields for PA 
for AMR U0000, Development of Numerical Grids for UZ Flow and Transport 
Modeling. Submittal date: 09/24/1999.

  
  209  
125604 LB990701233129.002. 3-D Model Calibration Grid for Calculation of Flow Fields 
Using #3 Perched Water Conceptual Model (Non-Perched Water Model) for AMR 
U0050, UZ Flow Models and Submodels. Submittal date: 03/11/2000. 
122757 LB990801233129.003. TSPA Grid Flow Simulations for AMR U0050, UZ Flow 
Models and Submodels (Flow Field #3). Submittal date: 11/29/1999. 
117129 LB990801233129.004. TSPA Grid Flow Simulations for AMR U0050, "UZ Flow 
Models and Submodels" (Flow Field #4). Submittal date: 11/29/1999. 
144659 LB990801233129.019. TSPA Grid Flow Simulations for AMR U0050, UZ Flow 
Models and Submodels. Flow Field #19: Present Day Mean Infiltration Map for 
Non-Perched Water Conceptual Model. Submittal date: 03/11/2000. 
156331 LB990801233129.022. TSPA Grid Flow Simulations for AMR U0050, UZ Flow 
Models and Submodels. Flow Field #22: Present Day Mean Infiltration for Non- 
Perched Water Conceptual Model. Submittal date: 03/11/2000 
147115 LB9908T1233129.001. Transport Simulations for the Low, Mean, and Upper 
Infiltration Scenarios of the Present-Day, Monsoon, and Glacial Transition Climates 
for AMR U0050, "UZ Flow Models and Submodels". Submittal date: 03/11/2000. 
123273 LB990901233124.004. Air Permeability Cross-Hole Connectivity in Alcove 6, 
Alcove 4, and Niche 4 of the ESF for AMR U0015, In Situ Testing of Field 
Processes. Submittal date: 11/01/1999. 
125868 LB991091233129.001. One-Dimensional, Mountain-Scale Calibration for AMR 
U0035, Calibrated Properties Model. Submittal date: 10/22/1999. 
126111 LB991091233129.004. Calibrated Fault Properties for the UZ Flow and Transport 
Model for AMR U0035, Calibrated Properties Model. Submittal date: 10/22/1999. 
147328 LB991121233129.001. Calibrated parameters for the present-day, mean infiltration 
scenario, used for simulations with perched water conceptual model #1 (flow 
through) for the mean infiltration scenarios of the present-day, Monsoon and Glacial 
transition climates. Submittal date: 03/11/2000. 
147334 LB991121233129.002. Calibrated Parameters for the Present-Day, Mean Infiltration 
Scenario, Used for Simulations with Perched Water Conceptual Model #2 for the 
Mean Infiltration Scenarios of the Present-Day, Monsoon and Glacial Transition 
Climates. Submittal date: 03/11/2000. 
147119 LB991131233129.003. Analytical and Simulation Results of Chloride and Chlorine- 
36 Analysis. AMR U0050, UZ Flow Models and Submodels. Submittal date: 
03/11/2000. 
104055 LB997141233129.001. Calibrated Basecase Infiltration 1-D Parameter Set for the 
UZ Flow and Transport Model, FY99. Submittal date: 07/21/1999.

  
  210  
153777 MO0012MWDGFM02.002. Geologic Framework Model (GFM2000). Submittal 
date: 12/18/2000. 
155989 MO0109HYMXPROP.001. Matrix Hydrologic Properties Data. Submittal date: 
09/17/2001. 
156306 MO0109RDDAAMRR.003. Results from Drift Degradation Analysis. Submittal 
date: 09/24/2001. Submit to RPC URN-0949 
103769 MO9901MWDGFM31.000. Geologic Framework Model. Submittal date: 
01/06/1999. 
8.4 OUTPUT DATA, LISTED BY DATA TRACKING NUMBER 
LB0103CHVUPROP.001. Updated Site-Scale UZ Properties for the Calico Hills Vitric Units 
[Model Layers ch1v and ch(2-5)v]: 1. Updated Drift-Scale Properties. Submittal date: Upon 
completion of this AMR. 
LB0103CHVUPROP.002. Updated Site-Scale UZ Properties For The Calico Hills Vitric Units 
[Model Layers ch1v and ch(2-5)v]: 2. Inversion Modeling Input/Output Files. Submittal date: 
Upon completion of this AMR. 
LB0104AMRU0185.001. Section 6.3.1 Different Transport Computation Methods - Supporting 
Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.002. Section 6.3.2 Matrix Block Discretization and its Effects on UZ Flow 
and Transport Simulations - Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.003. Section 6.4.1.1 Drift Degradation: Rockfall - Supporting Files. 
Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.004. Section 6.4.1.2 Drift Degradation: Rockbolts - Supporting Files. 
Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.005. Section 6.4.2 Focusing and Discrete Flow Paths in the TSw - 
Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.006. Section 6.4.3 Percolation Redistribution and Lateral Flow in the PTN 
- Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.007. Section 6.4.4 The Effect of Episodic Percolation on Seepage - 
Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.008. Section 6.5.2 Modeling of the CHn and CFu: Fault Characteristics  
Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.009. Section 6.5.3 Modeling of the CHn and CFu: Perched Water Models - 
Supporting Files. Submittal date: Upon completion of this AMR.

  
  211  
LB0104AMRU0185.010. Section 6.5.4 Consideration of Radionuclide Release into Matrix 
Rock  Supporting Files. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.011. Section 6.4.1.1 Drift Degradation: Rockfall - Data Summary. 
Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.012. Section 6.4.2 Focusing and Discrete Flow Paths in the TSw - Data 
Summary. Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.013. Section 6.5.1.3 Site-Scale Modeling Results - Supporting Files. 
Submittal date: Upon completion of this AMR. 
LB0104AMRU0185.014. Section 6.3.1 Different Transport Computation Methods - Data 
Summary. Submittal date: Upon completion of this AMR.