HYDRAULIC EVALUATION OF LYSIMETERS VERSUS
ACTUAL EVAPOTRANSPIRATIVE CAPS
By

Ramil Garcia Mijares

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Civil Engineering
2011

ABSTRACT
HYDRAULIC EVALUATION OF LYSIMETERS VERSUS
ACTUAL EVAPOTRANSPIRATIVE CAPS
By
Ramil Garcia Mijares
The ability to quantify percolation through a soil profile is one of the important
considerations for geoenvironmental systems. Reliable estimates of percolation through
natural soil deposits help in determining local groundwater recharge rates. For landfills,
accurate measurement of percolation through the cap is necessary for permitting earthen
final covers. Even though percolation is generally the smallest component among water
balance parameters, quantifying its magnitude is environmentally critical and key in
evaluating the overall hydraulic performance of final covers. Direct estimation of
percolation through a soil cover is typically achieved using pan lysimeters which consist
of a drainage layer underlain by an impermeable geomembrane liner. The presence of this
hydraulic barrier in lysimeter, which is used to facilitate the collection and measurement
of percolation, alters the hydraulics of the system. This dissertation aimed to evaluate the
difference in hydraulic performance of a lysimeter versus actual earthen cap with
underlying landfilled waste. Two uncompacted and one compacted field-scale earthen
cap test sections were built and instrumented at a landfill near Detroit, Michigan to
investigate the hydraulic difference between an actual cap (underlain by waste) and
corresponding lysimeter which was used to directly measure percolation. Lysimeter pans
were installed in the middle of each test sections and the instrumented area was expanded
upslope and downslope of the lysimeter to monitor the soil water storages within and
ii

beyond the lysimeter footprint. About 35 sensors were installed in each of the test
sections to monitor water contents, water potentials, soil temperatures, water levels, and
gas pressures. The field results show soil water storage values for the uncompacted test
sections that were underlain by waste were typically greater than those for the
corresponding lysimeters. For the compacted test section, there was no significant
difference between the soil water storage for the actual cap and the lysimeter. Using the
single porosity numerical models UNSAT-H and Vadose/W, the field measured
percolation in the lysimeter as well as the variation in soil water storages were predicted
with an acceptable accuracy for the compacted test section. The presence of macropore
flow through large clods in uncompacted test sections is not accounted for in these single
porosity models. A numerical analysis showed that when a lysimeter underestimates the
soil water storage of an actual earthen cap, it corresponds to greater actual percolation
across the interface between the soil cover and the underlying waste. A lysimeter
overestimates percolation because the infiltrated water drained into the lysimeter is
immediately removed and is therefore not available for removal by evapotranspiration.
Field-scale simulations also showed that the magnitude of capillary barrier effect
introduced by the drainage layer in the lysimeters is negligible when the saturated
-5

hydraulic conductivity of the soil cover is equal to or less than 10 cm/s.

Keywords: Landfill final covers, alternative earthen caps, lysimeter, field-scale testing
and instrumentation; water balance, municipal solid waste, UNSAT-H, Vadose/W.

iii

DEDICATION

To
Mommy

†

and
†

Daddy

iv

ACKNOWLEDGMENTS

I would like to express my deepest gratitude and appreciation to the following individuals
and institutions for their valuable contributions for making this dissertation and my
graduate study in the U.S. a successful endeavor.
Prof. Milind V. Khire, my supervisor and graduate advisor, for his continued
support and guidance. I have been privileged to have an advisor who imposes a high
standard on research. His perceptive comments and constructive criticisms helped me
finish this dissertation and published papers. Thank you for the opportunity to be one of
your students, Prof. Khire. Thank you for entrusting me a variety of projects, I learned a
lot from them. I especially enjoyed the times we worked together in the field. Thank you
for the motivation and advice you have shared with me, I really appreciate it.
Prof. Thomas Wolff, Prof. Phanikumar Mantha, and Prof. Remke van Dam, my
Ph.D. Guidance Committee members, for the comments and suggestions to further
improve this manuscript; Prof. Shu-Guang Li and Prof. Karim Chatti, my Examining
Committee members, for the positive evaluation in my Ph.D. qualifying examination.
The Environmental Research and Education Foundation (EREF) and Waste
Management, Inc. for funding the projects presented in this study; the Department of
Civil and Environmental Engineering, the College of Engineering, and the Graduate
School of Michigan State University for the research/teaching assistantships and
fellowship awards to support my graduate study; the United States Universities Council
for Graduate Education and Research (USUCGER) and the Geo-Institute of the

v

American Society of Civil Engineers (ASCE) for the travel grants to attend and present
my papers in the conference.
Terry Johnson, Eric Wallis, and Paul Mazanec of Waste Management, Inc. for
their assistance on the field project at Woodland Meadows Landfill; Jason Ritter of
Campbell Scientific, Inc. for the technical support in programming the data acquisition
system used in my field and lab studies.
The faculty and staff of the Department of Civil and Environmental Engineering
at Michigan State University, headed by Prof. Ronald Harichandran, for providing an
excellent workplace where one can have an enjoyable atmosphere for doing research and
teaching; special thanks to James Brenton, and his student assistants, for the technical
assistance in the fabrication and repair of all the apparatus and equipment I used in my
experiments; thank you also to Lori Larner, Laura Taylor, Mary Mroz, and Margaret
Conner for their assistance in processing all the paperworks and performing other
administrative functions.
My family and relatives for the unending support, love, and patience. Thank you
for the sacrifices. Thank you for the prayers. Through the years, I have been blessed with
a big extended family that is very supportive especially when my parents passed away.
My colleagues and friends, who constantly supported me, thank you for the
camaraderie and the friendship.
And above all, to the Almighty God, for the countless blessings He has given me
and for always providing His eternal guidance that allows me to face the challenges that
life has to offer.

vi

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................ x
LIST OF FIGURES ......................................................................................................... xi
KEY TO ABBREVIATIONS ....................................................................................... xvi
KEY TO SYMBOLS...................................................................................................... xix
INTRODUCTION............................................................................................................. 1
BACKGROUND ON LANDFILL FINAL COVERS .................................................... 1
ALTERNATIVE EARTHEN COVERS ......................................................................... 3
LYSIMETRY .................................................................................................................. 5
Effect of Lower Boundary ........................................................................................... 7
Capillary Barrier Effect ............................................................................................... 8
NUMERICAL MODELS ................................................................................................ 9
OBJECTIVES ............................................................................................................... 10
METHODOLOGY ........................................................................................................ 11
DISSERTATION ORGANIZATION ........................................................................... 12
REFERENCES .............................................................................................................. 15
PAPER NO. 1: FIELD-SCALE EVALUATION OF LYSIMETERS VERSUS
ACTUAL EARTHEN COVERS ................................................................................... 18
ABSTRACT .................................................................................................................. 18
INTRODUCTION ......................................................................................................... 19
OBJECTIVE.................................................................................................................. 21
DESIGN AND CONSTRUCTION OF TEST SECTIONS .......................................... 21
Test Section Layout ................................................................................................... 22
Test Section Construction.......................................................................................... 23
Lysimeter Installation ............................................................................................ 25
Soil Placement ....................................................................................................... 26
Pump Set-up ........................................................................................................... 29
INSTRUMENTATION ................................................................................................. 30
Water Level and Pressure Transducers ..................................................................... 31
Water Content Sensors .............................................................................................. 32
Soil Suction and Temperature Sensors ...................................................................... 33
Percolation Monitoring.............................................................................................. 34
RESULTS AND DISCUSSION ................................................................................... 37
Soil Temperatures ...................................................................................................... 37
Soil Water Storage ..................................................................................................... 38
Phase 1: Uncompacted North and South Test Sections ......................................... 38
Phase 2: Compacted North and Uncompacted South Test Sections ..................... 43
SUMMARY AND PRACTICAL IMPLICATIONS .................................................... 47
REFERENCES .............................................................................................................. 50
vii

PAPER NO. 2: FIELD DATA AND NUMERICAL MODELING OF WATER
BALANCE OF LYSIMETER VERSUS ACTUAL EARTHEN CAP ....................... 52
ABSTRACT .................................................................................................................. 52
INTRODUCTION ......................................................................................................... 53
OBJECTIVE.................................................................................................................. 54
FIELD-SCALE TEST SECTION ................................................................................. 55
Soil Properties ........................................................................................................... 57
Instrumentation .......................................................................................................... 59
NUMERICAL WATER BALANCE MODELING ...................................................... 61
INPUT PARAMETERS FOR UNSAT-H .................................................................... 61
Soil Properties ........................................................................................................... 63
MSW Properties ........................................................................................................ 63
Meteorological Data .................................................................................................. 68
Initial Conditions ....................................................................................................... 68
Numerical Control Parameters .................................................................................. 69
FIELD DATA ............................................................................................................... 69
Soil Water Storage ..................................................................................................... 69
SUMMARY AND CONCLUSIONS............................................................................ 80
APPENDIX ................................................................................................................... 83
Material Properties .................................................................................................... 84
Uncompacted Test Section Simulations .................................................................... 89
REFERENCES .............................................................................................................. 98
PAPER NO. 3: EFFECT OF UNDERLYING WASTE LAYER ON SOIL
WATER STORAGE AND PERCOLATION ESTIMATES FOR LANDFILL
EARTHEN CAPS ......................................................................................................... 101
ABSTRACT ................................................................................................................ 101
INTRODUCTION ....................................................................................................... 101
LYSIMETER VERSUS ACTUAL ET CAP .............................................................. 102
OBJECTIVE................................................................................................................ 105
WATER BALANCE MODEL.................................................................................... 105
Material Properties .................................................................................................. 107
Meteorological Data ................................................................................................ 112
Initial and Boundary Conditions and Numerical Control Parameters ..................... 113
RESULTS.................................................................................................................... 116
Semi-arid Climate.................................................................................................... 116
Humid Climate ........................................................................................................ 121
SUMMARY AND CONCLUSIONS.......................................................................... 124
REFERENCES ............................................................................................................ 127
PAPER NO. 4: EVALUATION OF GEOSYNTHETIC CAPILLARY BREAK
IN EARTHEN COVER LYSIMETERS..................................................................... 130
ABSTRACT ................................................................................................................ 130
INTRODUCTION ....................................................................................................... 130
OBJECTIVES ............................................................................................................. 134
NUMERICAL MODELING ....................................................................................... 135
viii

Material Properties .................................................................................................. 135
Initial and Boundary Conditions and Numerical Control Parameters ..................... 140
RESULTS.................................................................................................................... 142
Constant Infiltration Simulations ............................................................................ 142
Practical Implications .............................................................................................. 146
Field-scale Simulations ........................................................................................... 150
Semi-arid Climate ................................................................................................ 150
Humid Climate ..................................................................................................... 155
SUMMARY AND CONCLUSIONS.......................................................................... 162
REFERENCES ............................................................................................................ 164
PAPER NO. 5: NUMERICAL ASSESSMENT OF PAN LYSIMETERS USED
FOR ESTIMATION OF GROUNDWATER RECHARGE FOR NATURAL
SYSTEMS ...................................................................................................................... 167
ABSTRACT ................................................................................................................ 167
INTRODUCTION ....................................................................................................... 168
OBJECTIVE................................................................................................................ 169
LABORATORY SOIL COLUMN ............................................................................. 170
NUMERICAL MODELING ....................................................................................... 172
Material Properties .................................................................................................. 175
Laboratory Soil Column ...................................................................................... 175
Field-scale Simulations........................................................................................ 177
Initial and Boundary Conditions ............................................................................. 177
Laboratory Soil Column ...................................................................................... 177
Field-scale Simulations........................................................................................ 179
Numerical Control Parameters ................................................................................ 180
RESULTS.................................................................................................................... 180
Laboratory Soil Column .......................................................................................... 180
Field-scale Simulations ........................................................................................... 184
Semi-arid Climate ................................................................................................ 184
Sub-humid Climate .............................................................................................. 189
Practical Implications.......................................................................................... 192
SUMMARY AND CONCLUSION ............................................................................ 195
REFERENCES ............................................................................................................ 197
SUMMARY AND CONCLUSIONS ........................................................................... 199

ix

LIST OF TABLES

Table 1-1: Properties of cover soils used in the test sections. .…….……...........….... 27
Table 2-1: Physical properties of the soils. ..……………………………………....... 59
Table 2-2: Saturated and unsaturated hydraulic properties of the soils and waste. ....

64

Table 2-3: Saturated and unsaturated hydraulic properties of the cap components
for the uncompacted test section. ……………..…………………...…..... 84
Table 3-1: Saturated and unsaturated hydraulic properties of soils used in the
instrumented field test sections of Khire et al. (1997). ……………...…... 108
Table 3-2: Saturated and unsaturated hydraulic properties of geotextile and waste
used in the simulations. ……………………………………........………. 109
Table 4-1: Saturated and unsaturated hydraulic properties. ……………….…...…… 137
Table 5-1: Saturated and unsaturated hydraulic properties of the materials used to
build the laboratory soil column. ……………………………...………… 172
Table 5-2: Saturated and unsaturated hydraulic properties of the soils used to
simulate groundwater recharge rates. ………………….………...……… 177

x

LIST OF FIGURES

Figure I-1:

Final cover system for MSW landfills (EPA 1992). .................................... 2

Figure I-2:

Evapotranspirative caps: monolithic caps (a) and capillary barriers (b). ..... 4

Figure I-3:

Schematic of a typical lysimeter showing the water balance
parameters. ................................................................................................... 6

Figure I-4:

Conceptual model of evapotranspirative caps consisting of lysimeter
only (a); and actual cap (b) with underlying waste (Khire and Mijares
2008). ............................................................................................................ 8

Figure 1-1:

Typical cross-section of instrumented three field test sections. ................. 24

Figure 1-2:

Proctor compaction curves and field water contents and unit weights. ..... 28

Figure 1-3:

Comparison between on-site and NOAA recorded precipitation. .............. 30

Figure 1-4:

Water contents measured in the field using water content
reflectometers versus using Shelby tube samples. ..................................... 33

Figure 1-5:

Lysimeter water level, volume, and percolation relations.......................... 35

Figure 1-6:

TDR and water level sensor correlation. .................................................... 36

Figure 1-7:

Seasonal temperature variation across the test sections. ............................ 37

Figure 1-8:

Soil water storages (a); and cumulative precipitation and percolation
(b) for uncompacted test sections. .............................................................. 39

Figure 1-9:

Correlation between measured soil water storages for lysimeters versus
actual caps for uncompacted test sections. ................................................. 41

Figure 1-10: Water contents in the test section and in the underlying waste. ................. 42
Figure 1-11: Soil water storage and cumulative precipitation and percolation for
compacted north test section (a); and uncompacted south test section
(b). .............................................................................................................. 44
Figure 1-12: Correlation between measured soil water storages for lysimeter versus
actual cap for the compacted north test section. ......................................... 46
Figure 2-1:

Cross-section of instrumented field test section. ........................................ 56

Figure 2-2:

Proctor compaction curves and field water contents and unit weights. ..... 58
xi

Figure 2-3:

Conceptual model for numerical simulation of a lysimeter (a); and an
actual cap with underlying waste (b). ......................................................... 62

Figure 2-4:

Measured water retention curves (a); and unsaturated hydraulic
conductivity functions (b) for the waste. .................................................... 66

Figure 2-5:

Measured water contents (a); and gas pressures and suctions (b) in the
waste. .......................................................................................................... 67

Figure 2-6:

Measured soil water storages and surficial temperatures for the
lysimeter and actual caps. ........................................................................... 70

Figure 2-7:

Correlation between measured soil water storage for an actual cap and
its corresponding lysimeter. ....................................................................... 71

Figure 2-8:

Measured volumetric water contents for the lysimeter (a) and actual
cap (b). ........................................................................................................ 73

Figure 2-9:

Measured water content profiles for the lysimeter and actual caps on 1
Feb. (a) and 1 Oct. 2010 (b). ...................................................................... 74

Figure 2-10: Measured and simulated cumulative percolation for the lysimeter and
the actual cap. ............................................................................................. 75
Figure 2-11: Measured and simulated soil water storage for the lysimeter. ................... 77
Figure 2-12: Simulated soil water storage for the lysimeter and the actual cap. ............ 78
Figure 2-13: Field water contents and unit weights for the uncompacted test section. .. 83
Figure 2-14: Measured soil water characteristic curves (a); and predicted hydraulic
conductivity function (b) for the cap components for uncompacted test
section. ........................................................................................................ 86
Figure 2-15: Typical mesh used for modeling in Vadose/W for: a lysimeter only (a);
and an actual earthen cap with underlying waste (b). ................................ 88
Figure 2-16: Field measured and numerically simulated cumulative percolation for
the uncompacted test section. ..................................................................... 89
Figure 2-17: Measured volumetric water contents for the lysimeter (a) and actual
cap (b). ........................................................................................................ 91
Figure 2-18: Calculated hydraulic gradient across the bottommost two sensors for
the lysimeter and actual cap in the uncompacted test section. ................... 92
Figure 2-19: Field measured and numerically simulated soil water storage for the
uncompacted test section. ........................................................................... 93
xii

Figure 2-20: Correlation between measured soil water storage for actual cap versus
lysimeter for the uncompacted test section. ............................................... 94
Figure 2-21: Correlation between the simulated soil water storage for an actual cap
versus its corresponding lysimeter with varying hydraulic properties of
soil cover (Mijares et al. 2010). .................................................................. 95
Figure 3-1:

Conceptual model for numerical simulation of alternative capping
system consisting of a lysimeter only (a); and a typical ET cap with
underlying waste (b). ................................................................................ 106

Figure 3-2:

Soil water characteristic curves (a); and hydraulic conductivity
functions (b) for the soils used in the Wenatchee test section,
nonwoven geotextile, and MSW. ............................................................. 114

Figure 3-3:

Soil water characteristic curves (a); and hydraulic conductivity
functions (b) for the soils used in the Atlanta test section, nonwoven
geotextile, and MSW. ............................................................................... 115

Figure 3-4:

Simulated cumulative percolation and soil water storage for
Wenatchee soil, with 0.6-m thick storage layer, in a semi-arid climate
boundary condition. .................................................................................. 117

Figure 3-5:

Simulated soil water storage for actual cap versus lysimeter for
Wenatchee soil, with 0.6-m thick storage layer, in a semi-arid climate
boundary condition. .................................................................................. 119

Figure 3-6:

Simulated cumulative percolation and soil water storage for
Wenatchee soil, with 0.9-m thick storage layer, in a semi-arid climate
boundary condition. .................................................................................. 120

Figure 3-7:

Simulated cumulative percolation and soil water storage for Atlanta
soil, with 0.9-m thick storage layer, in a humid climate boundary
condition. .................................................................................................. 121

Figure 3-8:

Simulated soil water storage for actual cap versus lysimeter for Atlanta
soil, with 0.9-m thick storage layer, in a humid climate boundary
condition. .................................................................................................. 122

Figure 3-9:

Simulated cumulative percolation and soil water storage for Atlanta
soil, with 1.5-m thick storage layer, in a humid climate boundary
condition. .................................................................................................. 124

Figure 4-1:

Conceptual model used to simulate a lysimeter without (a) and with (b)
a nonwoven GT and an actual cap with waste layer (c). .......................... 136

Figure 4-2:

Measured soil water characteristic curves (a); and predicted hydraulic
conductivity function (b) for nonwoven geotextile and MSW................. 138
xiii

Figure 4-3:

Unsaturated hydraulic conductivity functions of the cap soils and the
underlying nonwoven GT to illustrate the contrast in K(ψ)
relationships which is conducive to the occurrence of capillary barrier
effect. ........................................................................................................ 139

Figure 4-4:

Simulated cumulative percolation and soil water storage for OK110
fine sand under specified flux boundary condition. ................................. 143

Figure 4-5:

Simulated cumulative percolation and soil water storage for SM soil
under specified flux boundary condition. ................................................. 144

Figure 4-6:

Simulated cumulative percolation and soil water storage for SM-ML
soil under specified flux boundary condition. .......................................... 145

Figure 4-7:

Water retention curves (a); and unsaturated hydraulic conductivity
functions (b) for fine-textured soil cap and coarse-textured GT or
MSW. ....................................................................................................... 147

Figure 4-8:

Relative magnitude of capillary barrier effect as a function of applied
specified flux for SM and SM-ML soils. ................................................. 149

Figure 4-9:

Simulated cumulative percolation and soil water storage for
Wenatchee soil under semi-arid climate boundary condition. ................. 151

Figure 4-10: Simulated cumulative percolation and soil water storage for SM soil
under semi-arid climate boundary condition. ........................................... 152
Figure 4-11: Simulated cumulative percolation and soil water storage for SM-ML
soil under semi-arid climate boundary condition. .................................... 153
Figure 4-12: Simulated soil water storage for lysimeter with GT versus without GT
under semi-arid climate boundary condition. ........................................... 155
Figure 4-13: Simulated cumulative percolation and soil water storage for Atlanta
soil under humid climate boundary condition. ......................................... 156
Figure 4-14: Simulated cumulative percolation and soil water storage for SM soil
under humid climate boundary condition. ................................................ 157
Figure 4-15: Simulated cumulative percolation and soil water storage for SM-ML
soil under humid climate boundary condition. ......................................... 158
Figure 4-16: Simulated soil water storage for lysimeter with GT versus without GT
under humid climate boundary condition. ................................................ 160
Figure 4-17: Annual percolation difference between lysimeter without GT and
lysimeter with GT for semi-arid (a); and humid climates (b). ................. 161

xiv

Figure 5-1:

Photo and schematic of instrumented laboratory soil column. ................ 171

Figure 5-2:

Water retention curves (a); and predicted hydraulic conductivity
functions (b) for the materials used in the laboratory soil column. .......... 176

Figure 5-3:

Soil water characteristic curves (a); and predicted hydraulic
conductivity functions (b) for the soils used to simulate groundwater
recharge rates. ........................................................................................... 178

Figure 5-4:

Measured and simulated UNSAT-H cumulative percolation and soil
water storage for OK110 sand column. .................................................... 181

Figure 5-5:

Measured and simulated water content profile for OK110 fine sand
column at breakthrough. ........................................................................... 183

Figure 5-6:

Schematic of a lysimeter (a); and a monolithic natural system (b) used
to estimate natural groundwater recharge rates. ....................................... 185

Figure 5-7:

Simulated natural groundwater recharge rates and lysimeter
percolations for SP soil in a semi-arid climate. ........................................ 186

Figure 5-8:

Simulated natural groundwater recharge rates and lysimeter
percolations for SM soil in a semi-arid climate. ...................................... 188

Figure 5-9:

Simulated natural groundwater recharge rates and lysimeter
percolations for SP-SM soil in a semi-arid climate. ................................. 189

Figure 5-10: Simulated natural groundwater recharge rates and lysimeter
percolations for SM soil in a sub-humid climate. .................................... 190
Figure 5-11: Simulated natural groundwater recharge rates and lysimeter
percolations for SM-ML soil in a sub-humid climate. ............................. 191
Figure 5-12: Simulated natural groundwater recharge rates and lysimeter
percolations for ML soil in a sub-humid climate. .................................... 192
Figure 5-13: Ratio of natural groundwater recharge and percolation estimates for
various lysimeter profile thicknesses in semi arid (a); and sub-humid
(b) climates. .............................................................................................. 193
Figure 5-14: Ratio of natural groundwater recharge and percolation estimates for
various saturated hydraulic conductivity of the soil. ................................ 194

xv

KEY TO ABBREVIATIONS

1-D

= one-dimensional

2-D

= two-dimensional

ASTM = American Society for Testing and Materials
BGS

= below ground surface

CB

= bottom nest of the compacted north test section

CFR

= Code of Federal Regulations

CL

= lean clay

CM

= middle nest of the compacted north test section

CT

= top nest of the compacted north test section

ET

= evapotranspiration/evapotranspirative

GCL

= geosynthetic clay liner

GDL

= geocomposite drainage layer

GP

= uniformly graded gravel

GT

= nonwoven geotextile; unit gradient boundary at the base of the nonwoven
geotextile that lines the OK110 soil column

GW

= constant water table at the base of a 90-cm thick coarse gravel that was
hypothetically placed underneath the OK110 soil column

HDMP = heat dissipation matric potential
HDPE

= high-density polyethylene

IPM

= instantaneous profile method

LL

= liquid limit

xvi

MDE

= Maryland Department of the Environment

ML

= low plasticity silt

MSW

= municipal solid waste

NB

= bottom nest of the uncompacted north test section

NM

= middle nest of the uncompacted north test section

NOAA = National Oceanic and Atmospheric Administration
NT

= top nest of the uncompacted north test section

OK 110 = uniformly graded fine sand
P/PET

= precipitation to potential evapotranspiration ratio

PE/P

= potential evaporation to precipitation ratio

PI

= plasticity index

PVC

= polyvinyl chloride

RCRA

= Resource Conservation and Recovery Act

SAIC

= Science Applications International Corporation

SB

= bottom nest of the uncompacted south test section

SM

= silty sand; middle nest of the uncompacted south test section

SM-ML = nonplastic sandy silt
SP

= uniformly graded medium sand

SP-SM = poorly graded sand with silt
ST

= top nest of the uncompacted south test section

SWS

= soil water storage

TDR

= time domain reflectometry

UG

= unit gradient boundary at the base of the monolithic OK110 soil column

xvii

US

= United States

USCS

= Unified Soil Classification System

USEPA = United States Environmental Protection Agency
WL

= waste layer

xviii

KEY TO SYMBOLS

A

=

curve fitting parameter for Haverkamp et al. (1977) function

B

=

curve fitting parameter for Haverkamp et al. (1977) function

Cc

=

coefficient of gradation

Cu

=

uniformity coefficient

D10

=

effective size or diameter in the particle-size distribution curve
corresponding to 10% finer

D50

=

diameter in the particle-size distribution curve corresponding to 50% finer

D60

=

diameter in the particle-size distribution curve corresponding to 60% finer

E

=

surface evaporation

ET

=

evapotranspiration

Gs

=

specific gravity of soil solids

K

=

saturated hydraulic conductivity

Kint

=

ordinate of the intersection of unsaturated hydraulic conductivity functions
for the coarse-textured and fine-textured materials where K(ψc ) = K(ψf )

K L (ψ )

=

unsaturated hydraulic conductivity for a given ψ

Ks

=

saturated hydraulic conductivity

Ksat

=

saturated hydraulic conductivity

KSL

=

saturated hydraulic conductivity of the storage layer
xix

K T (ψ )

=

isothermal water vapor conductivity for a given ψ

KWL

=

saturated hydraulic conductivity of municipal solid waste

KΨ

=

unsaturated hydraulic conductivity

k (ψ )

=

hydraulic conductivity of the porous media for a given ψ

Κ(ψ)

=

unsaturated hydraulic conductivity

K(ψf)

=

unsaturated hydraulic conductivity for a fine-textured material with ψf

n

=

curve fitting parameter for van Genuchten (1980) function

p

=

estimated lysimeter percolation (mm)

P

=

precipitation

Pr

=

percolation; basal percolation

q

=

applied or specified flux

qVT

=

thermal vapor flux density

RO

=

surface runoff

S

=

degree of saturation; sink term that represents the water uptake by
vegetation as a function of both depth and time

t

=

time

T

=

plant transpiration

V

=

equivalent volume of water stored in the lysimeter (gal)

x

=

period measured by the water content reflectometer (µs)
xx

z

=

vertical coordinate; depth of water in the lysimeter (cm)

α

=

curve fitting parameter for van Genuchten (1980) function; curve fitting
parameter for Haverkamp et al. (1977) function

β

=

curve fitting parameter for Haverkamp et al. (1977) function

γd

=

dry unit weight

∆

=

change

∆S

=

change in soil water storage

θ

=

volumetric water content

θc

=

volumetric water content for a coarse-textured material

θf

=

volumetric water content for a fine-textured material

θr

=

residual water content

θs

=

saturated water content

ψ

=

matric suction head

ψ

=

matric suction

ψc

=

matric suction for a coarse-textured material

ψf

=

matric suction for a fine-textured material

ψint

=

abscissa of the intersection of unsaturated hydraulic conductivity functions
for the coarse-textured and fine-textured materials where ψc = ψf

ω

=

gravimetric water content
xxi

INTRODUCTION

BACKGROUND ON LANDFILL FINAL COVERS
Landfills are the most widely used facilities for disposal of municipal solid wastes
(MSW). The United States Environmental Protection Agency (USEPA) estimated that
there are about 1,750 active landfills across the country as of 2006 and over 10,000 old
municipal landfills. Current per capita waste generation in the U.S. is about 4.6 pounds
per person per day which would translate to a total of roughly 250 million tons of MSW
per year. Even though efforts to recycle wastes have significantly increased,
approximately 55% of MSW is still being disposed off into landfills (EPA 2007).
Once these landfills reach their volumetric capacity and are scheduled for closure,
final cover systems are installed. Final cover systems are used to control the amount of
moisture infiltrating into the wastes, separate wastes from disease vectors and other
nuisances, control landfill gas emissions and odors, and meet aesthetic requirements.
Well-designed landfill final covers also promote good surface drainage, resist erosion,
prevent slope failure, minimize long-term maintenance, and provide suitability for other
eventual use of the site. Potential end-uses for closed MSW landfills are nature or
recreation park, wilderness area or animal refuge, golf course, ski or toboggan hill, and
parking lot (EPA 1995).
Conventional designs for landfill final cover systems are based on the
requirements set forth in the Resource Conservation and Recovery Act (RCRA). Under
RCRA Subtitle D (40 CFR 258.60), the minimum criteria for final cover system for
MSW landfills depend on the existing bottom liner system. Accordingly, landfill final

1

cover system must have a permeability less than or equal to that of the bottom liner
system, or less than or equal to 10

-5

cm/s, whichever is less. A minimum 18 inches of

this earthen material shall be used to minimize infiltration through the closed landfill unit.
It must also have a minimum 6 inches of soil erosion layer that is capable of sustaining
native plant growth.
Figure I-1 shows an example of a typical RCRA Subtitle D landfill final cover
system. This design has been imposed to restrict the flow of water through the cover and
into the waste. Such design would prevent the landfill from filling up with leachate that is
primarily generated from infiltration of precipitation. This phenomenon is commonly
referred to as “bathtub effect” and is therefore highly unwanted.
In practice, the presence of a geomembrane in the bottom liner system infers the
use of a geomembrane in the final cover system (SAIC 2000). Installation of these
conventional final covers that use geomembrane costs between $80,000 and $500,000 per
acre (MDE 2003), with the bulk of the expenses allotted for the use of the geomembrane.

Figure I-1: Final cover system for MSW landfills (EPA 1992).
“For interpretation of the references to color in this and all other figures, the reader is
referred to the electronic version of this dissertation.”
2

ALTERNATIVE EARTHEN COVERS
In lieu of RCRA design, RCRA guidelines also stipulate that alternative designs may be
approved by regulatory agencies if it can be demonstrated that the proposed alternative
provides equivalent performance with regard to reduction in percolation, erosion
protection, and other applicable criteria.
Several alternative final cover designs have been proposed and investigated in the
past decade (Benson and Khire 1995; Nyhan et al. 1997; Ward and Gee, 1997; Stormont
and Morris 1998; Khire et al. 1999; Benson et al 2002; Albright et al. 2003; Scanlon et al.
2005). Collectively, the mechanisms in which these alternative final covers perform rely
on the water-holding capability of native soils and a huge percentage of precipitation
returns to the atmosphere through evapotranspiration. Hence the term “evapotranspirative
caps” is often used to refer to these alternative final covers.
Evapotranspirative caps are often classified into two types: (1) monolithic caps
and (2) capillary barriers. Monolithic caps have relatively simple cross-sectional profile
consisting of 6 to 18 inches thick of topsoil layer underlain with a thick storage layer of
earthen material with low hydraulic conductivity and high water storage capacity. The
topsoil layer provides medium for vegetative growth for effective erosion protection and
removal of water from the soil through transpiration. The thickness of the storage layer is
designed such that most infiltration during “wet season” is stored in the soil until
withdrawn back by evapotranspiration. Capillary barriers consist of finer-grained soil
layer underlain with coarser-grained layer. The contrast in hydraulic properties between
the two layers forms a capillary interface forcing water to be stored in the finer-grained
layer and delaying or preventing infiltration into the underlying coarser-grained layer.

3

Capillary barriers also usually have a topsoil layer for plant growth and erosion
protection. Figure I-2 shows the general profile of the two most commonly used
evapotranspirative cap designs.
Distinct difference between RCRA Subtitle D final covers and evapotranspirative
caps is the absence of geomembrane in the latter. This directly translates to significant
cost reduction in landfill final cover installation. Hauser et al (2001) estimated the
benefits and costs advantages for evapotranspirative caps and has shown a potential
savings of 50% on landfill cover construction costs. Long-term performance of
evapotranspirative caps is also anticipated as the root system of its vegetation develops
through time improving slope stability in contrast with prescribed caps where slope
failure has been a great concern. The inherent high cost of prescriptive caps and its
uncertain

long-term

performance

has

led

to

initiate

extensive

research

evapotranspirative caps.

Vegetative Layer
Vegetative Layer

Finer-Grained Layer
Storage Layer
Coarser-Grained Layer

Waste

Waste

(b) Capillary Barriers

(a) Monolithic Caps

Figure I-2: Evapotranspirative caps: monolithic caps (a) and capillary barriers (b).
4

on

LYSIMETRY
As per RCRA regulations, acceptance of alternative designs including evapotranspirative
caps for landfill final covers requires field demonstration to assess its performance under
site-specific field conditions. Demonstration of hydraulic equivalency is usually attained
when the resulting percolation rate from evapotranspirative cap is less than or equal to the
percolation rate from prescribed final covers under identical field conditions (SAIC
2000).
In order to evaluate equivalent performance of evapotranspirative caps with the
prescribed final covers, direct quantitative method of estimating the amount of percolated
water across the landfill cap is needed (Benson et al 2001). This is typically
accomplished by installing water-balance lysimeters wherein an entire cross-section of
evapotranspirative cap is underlained with an impermeable geomembrane allowing
collection of drainage through this bottom boundary. Key feature of a lysimeter is the
ability to directly measure percolation rate and with a good precision of about 0.5 mm/yr
(Benson et al. 1994; Ward and Gee 1997).
Figure I-3 shows a typical layout of a lysimeter. A high-density polyethylene
geomembrane is usually used to line the lysimeter. Most lysimeters include a gravel or
geosynthetic drainage layer at the soil and geomembrane interface to direct the
percolation to the collection system (Benson et al. 2001). Aside from percolation
measurements, lysimeters are also used to measure the changes in the soil water storage
of the cap. This is accomplished either directly through weighing or monitoring the water
content across the profile using water content sensors. A diversion berm is constructed
along the perimeter in order to divert surface runoff from upslope of the lysimeter while

5

directing the surface runoff within the monitoring area to the collection system.
Precipitation is usually measured at the site using a tipping bucket.

LYSIMETER

Figure I-3: Schematic of a typical lysimeter showing the water balance parameters.

Water balance of the lysimeter can be expressed as:
ET = P – Pr – RO – ∆S

6

(I-1)

where ET is evapotranspiration, P is precipitation, Pr is percolation, RO is surface
runoff, and ∆S is the change in soil water storage during a specified period of time.
Hence, evapotranspiration can be estimated if precipitation, percolation, runoff and soil
water storage are measured. The calculated evapotranspiration is often compared to the
site-specific estimates of potential evapotranspiration to confirm the accuracy of the
estimate.

Effect of Lower Boundary
The most significant disadvantage of using lysimeters to estimate percolation rate is the
presence of artificial no-flow boundary induced by the hydraulic barrier at the base of the
lysimeter (Abichou et al. 2006). This bottom boundary, which does not exist in an actual
landfill final cover, prevents the upward and downward flux of liquid and vapor across
the base of the lysimeter thereby possibly underestimating or overestimating the actual
percolation rate.
Several studies have identified this concern (Benson et al. 2001; Abichou et al.
2006). However, there has been a lack of data in the literature where the effect of this
artificial boundary on percolation is quantified until Khire and Mijares (2008) presented a
result from numerical modeling of lysimeters versus the corresponding actual
evapotranspirative caps covering a waste layer as shown in Figure I-4. Results of the
numerical analyses indicated that percolation rates obtained from lysimeters are
conservative by factors ranging from 2 to 10.
Lysimeter is the only available tool that directly estimates percolation through
evapotranspirative caps (Benson et al. 2001; Albright et al. 2002). Hence detailed
7

understanding on its ability to capture actual flux on landfill covers is highly
indispensable. Percolation values measured in the lysimeters need to be re-evaluated by
carrying-out numerical modeling that incorporates the underlying waste for actual
evapotranspirative cap scenarios (Khire and Mijares 2008).

(a) Lysimeter

(b) Actual Cap

Figure I-4: Conceptual model of evapotranspirative caps consisting of lysimeter only (a);
and actual cap (b) with underlying waste (Khire and Mijares 2008).

Capillary Barrier Effect
The use of a geocomposite drainage layer at the base of the lysimeter to facilitate the
collection and measurement of percolated water through the earthen cap has been
perceived to create a capillary barrier effect (Stormont and Morris 2000; Scanlon et al.
2005). This geocomposite drainage layer which is placed above the geomembrane that
lines conventional pan lysimeter consists of a geonet sandwiched between two nonwoven
8

geotextiles. Published studies indicate that non-woven geotextiles have water retention
function that is similar to those of coarse-textured soils such as sands and gravels creating
a capillary break with the overlying fine-textured cover soil (Iryo and Rowe 2003; Park
and Fleming 2006; Bathurst et al. 2007).
Benson et al. (2005) and Bohnhoff et al. (2009) investigated the effect of capillary
break on percolation estimates by conducting parametric evaluation using several water
balance models. They reported that regardless of the capillary break, predicted
percolation was less than field measured percolation. Due to the inherent uncertainty in
the field boundary condition, it is critical to identify when the presence of capillary
barrier effect will be significant or minimal on the measured percolation.

NUMERICAL MODELS
Several models have been developed to simulate the water balance of earthen caps.
Among these, the numerical models UNSAT-H (Fayer 2000) and VADOSE/W (GeoSlope 2007) are among the commonly used in engineering practice for simulating water
balance in saturated and unsaturated porous media (Benson 2007). In this study, these
three computer models were used to simulate the hydrology of landfill earthen final
covers.
Each model numerically solves a modified form of Richards’ equation to estimate
the flow of water through both saturated and unsaturated soil media. A one-dimensional
(1-D) form of Richards’ equation can be expressed as follows:

∂θ
∂ 
∂ψ

= k (ψ )
+ k (ψ ) − S
∂t ∂z 
∂z

9

(I-2)

where

θ

is the volumetric water content,

ψ

is the matric suction head,

corresponding hydraulic conductivity of the porous media for a given
term,

k (ψ ) is the

ψ, S

is the sink

z is the vertical coordinate, and t is the time. UNSAT-H is a 1-D code that uses

finite-difference scheme in solving Equation I-2. VADOSE/W is a finite-element model
that can be run either under 1-D or two-dimensional (2-D) modes. These numerical
models have been extensively used in simulating landfill final covers (Khire et al. 1997;
Roesler et al. 2002; Benson et al. 2004; Bohnhoff et al. 2009).
The use of numerical models to predict percolation rates and compare it to
measured values obtained from lysimeters has been widely considered (Khire et al. 1997;
Khire et al. 2000; Albright et al. 2004; Benson et al. 2005). However it has been reported
that these models failed to capture pulses of field measured percolation rates due to
inability of these models to account water flow through preferential flow paths in soil
(Khire et al. 1997). The formation of macrodefects or fractures on soils greatly influences
the water balance parameters, especially percolation.

OBJECTIVES
The key objectives of this dissertation are to: (1) build and instrument large-scale
evapotranspirative landfill final cover test sections that are capable of monitoring the
difference between the hydraulic performance of a lysimeter and the corresponding actual
cap (underlain by waste) under field conditions; (2) assess the capability of numerical
models in predicting the water balance of an earthen cover with a vented lysimeter pan
that does not use geocomposite drainage layer; (3) conduct field-scale simulations to
determine the effect of the underlying landfilled waste on percolation estimates for actual
10

caps; and (4) determine key considerations regarding the occurrence of capillary barrier
effect and its implications on percolation when using conventional pan lysimeter that use
the synthetic geocomposite drainage layer.

METHODOLOGY
Field-scale evapotranspirative caps were constructed in a landfill located near Detroit,
Michigan which is operated by Waste Management, Inc. Two tests sections, each having
a dimension of 15 m by 30 m, were built on top of a landfill site that is scheduled for
final closure. Performance monitoring for the test sections was divided into two phases:
(1) uncompacted earthen cover investigation from September 2007 to September 2009;
and (2) compacted earthen cover investigation from October 2009 to present.
In order to measure the net percolation across the caps, 8.5 m x
8.5 m x 0.6 m deep vented lysimeters (with provisions for pressure control) were
constructed in the middle of each test section. The rest of the test section was built on an
existing intermediate cover that is temporarily covering the underlying waste that was
placed in the landfill cell in 1990s. The instrumented area of the test section was
expanded upslope and downslope of the lysimeter to monitor the water content within
and beyond the lysimeter footprint in order to assess the resulting flux between actual
evapotranspirative cover and underlying waste.
Over 70 sensors consisting of time domain reflectometry-based water content and
heat dissipation matric potential sensors as well as an automated meteorological station
were installed at the site. Water balance parameters as well as gas pressures within the
cap and the waste were monitored. The data obtained from the field investigation were

11

used to evaluate the hydraulic differences between a lysimeter and the corresponding
actual cap. A numerical study was conducted to determine the effect of the underlying
landfilled waste on percolation estimates for actual caps and the presence of capillary
barrier effect introduced by the geocomposite in the drainage layer on lysimeters.

DISSERTATION ORGANIZATION
This dissertation has been organized into five sections. Each section is written as a
standalone technical paper.
The first paper describes the design and construction of field-scale
evapotranspirative cap test sections that were built to evaluate the difference in the
hydraulic performance of a lysimeter versus actual cap (with underlying intermediate
cover or waste). The unique design of these fully instrumented test sections allows
comparative evaluation between the water balance of a lysimeter and actual cap under
field meteorological conditions.
The second paper compares the measured water balance data obtained from the
field test sections to the predictions made using the numerical models UNSAT-H and
VADOSE/W. The calibrated numerical model was used to estimate the percolation across
the interface between the soil cap and underlying waste.
The third paper evaluates the effect of the underlying landfilled waste on
percolation estimates for actual caps. Long-term field-scale simulations using UNSAT-H
were conducted to determine the correlation between the soil water storage and
percolation estimates for an actual cap and its corresponding lysimeter.

12

The fourth paper discusses the occurrence of capillary barrier effect when using
geocomposites as drainage layer at the base of the lysimeters. A numerical investigation
using UNSAT-H was performed to assess capillary break over different soil types
subjected to a wide range of specified fluxes. The fundamental mechanism involved
when capillary barrier effect occurs was presented and several lysimeter field case studies
were re-analyzed to map key factors that identify significant capillary barrier effect.
The fifth paper presents a numerical method to estimate the natural recharge in a
vadose zone system using water balance models. A simple 1-D laboratory column test
was conducted to verify the proposed approach.

13

REFERENCES

14

REFERENCES
Abichou, T., Liu, X., Tawfiq, K. (2006). “Design Considerations for Lysimeters Used to
Evaluate Alternative Earthen Final Covers,” Journal of Geotechnical and
Geoenvironmental Engineering, 132 (12): 1519 – 1525.
Albright, W., Gee, G., Wilson, G., and Fayer, M. (2002). “Alternative Cover Assessment
Project: Phase I Report,” Publication No. 41183. Report to US EPA. Desert
Research Institute, NV.
Albright, W., Benson, C., Gee, G., Abichou, T., Roesler, A., and Rock, S. (2003),
“Evaluating the Alternatives,” Civil Engineering, 73 (1): 70-75.
Albright, W., Benson, C., Gee, G., Roesler, A., Abichou, T., Apiwantragoon, P.,
Lyles, B., and Rock, S. (2004). “Field Water Balance of Landfill Final Covers,”
Journal of Environmental Quality, 33 (6): 2317-2332.
Bathurst, R., Ho, A., and Siemens. G. (2007). “A Column Apparatus for Investigation of
1-D Unsaturated-Saturated Response of Sand-Geotextile Systems,” Geotechnical
Testing Journal, 30 (6): 1-9.
Benson, C. (2007). “Modeling Unsaturated Flow and Atmospheric Interactions,”
Theoretical and Numerical Unsaturated Soil Mechanics, 113: 187-201.
Benson, C. and Khire, M. (1995). “Earthen Covers for Semi-Arid and Arid Climates,”
Landfill Closures, GSP No. 53, ASCE, Reston, VA: 201-217.
Benson, C., Bosscher, P., Lane, D., and Pliska, R. (1994). “Monitoring System for
Hydrologic Evaluation of Landfill Final Covers,” Geotechnical Testing Journal,
17 (2): 138-149.
Benson, C., Abichou, T., Albright, W., Gee, G., and Roesler, A. (2001). “Field
Evaluation of Alternative Earthen Final Covers,” International Journal of
Phytoremediation, 3 (1): 105-127.
Benson, C., Albright, W., Roesler, A., and Abichou, T. (2002). “Evaluation of Final
Cover Performance: Field Data from the Alternative Cover Assessment Program
(ACAP),” Proceedings, Waste Management 2002, Tucson, AZ.
Benson, C., Bohnhoff, G., Apiwantragoon, P., Ogorzalek, A., Shackelford, C., and
Albright, W. (2004). “Comparison of Model Predictions and Field Data for an ET
Cover,” Proceedings, Tailings and Mine Waste 2004, Balkema, Leiden,
Netherlands: 137-142.
Benson, C., Bohnhoff, G., Ogorzalek, A., Shackelford, C., Apiwantragoon, P., and
Albright, W. (2005). “Field Data and Model Predictions for an Alternative Cover,”
Waste Containment and Remediation, GSP No. 142, ASCE, Reston, VA: 1-12.

15

Bohnhoff, G., Ogorzalek, A., Benson, C., Shackelford, C., and Apiwantragoon, P. (2009).
“Field Data and Water-Balance Predictions for a Monolithic Cover in a Semiarid
Climate,” Journal of Geotechnical and Geoenvironmental Engineering, 135 (3):
333–348.
EPA. (1992). “Subtitle D Clarification.” 40 CFR 257 and 258. Federal Register.
EPA. (1995). “Decision Maker’s Guide to Solid Waste Management, Volume II,”
EPA 530-R-95-023.
EPA. (2007). “Municipal Solid Waste Generation, Recycling, and Disposal in the United
States: Facts and Figures for 2006,” EPA 530-F-07-030.
Fayer, M. (2000). “UNSAT-H Version 3.0: Unsaturated Soil Water and Heat Flow Model
– Theory, User Manual, and Examples.” PNNL-13249, Pacific Northwest
Laboratories, Richland, Washington.
Geo-Slope. (2007). “Vadose Zone Modeling with VADOSE/W 2007: An Engineering
Methodology,” Geo-Slope International Ltd, Alberta, Canada.
Hauser, V. L., Weand B. L., and Gill, M. D. (2001). “Natural Covers for Landfills and
Buried Waste,” Journal of Environmental Engineering, 127 (9): 768-775.
Iryo, T., and Rowe, R. (2003). “On the Hydraulic Behavior of Unsaturated Nonwoven
Geotextiles,” Geotextiles and Geomembranes, 21: 381-404.
Khire, M., and Mijares, R., 2008, “Influence of the Waste Layer on Percolation Estimates
for Earthen Caps Located in a Sub-humid Climate,” Proceedings, GeoCongress
2008, GSP No. 177, Geotechnics of Waste Management and Remediation, ASCE,
Reston, VA: 88-95.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering,
123 (8): 744-754.
Khire, M., Benson, C., and Bosscher, P. (1999). “Field Data From a Capillary Barrier and
Model Predictions with UNSAT-H,” Journal of Geotechnical and
Geoenvironmental Engineering, 125: 518–528.
Khire, M., Benson, C., and Bosscher, P. (2000). “Capillary Barriers: Design Variables
and Water Balance,” Journal of Geotechnical and Geoenvironmental Engineering,
126 (8): 695-708.
MDE. (2003). “Estimated Costs of Landfill Closure Fact Sheet,” Maryland Department
of the Environment, Baltimore, MD.

16

Nyhan, J., Schofield, T., and Starmer, R. (1997). “A Water Balance Study of Four
Landfill Cover Designs Varying in Slope for Semi-Arid Region,” Journal of
Environmental Quality, 26: 1385-1392.
Park, K., and Fleming, I. (2006). “Evaluation of a Geosynthetic Capillary Barrier,”
Geotextiles and Geomembranes, 24: 64-71.
Roesler, A., Benson, C., and Albright, W. (2002). “Field Hydrology and Model
Predictions for Final Covers in the Alternative Assessment Program – 2002,” GeoEngineering Report 02-08. University of Wisconsin, Madison.
SAIC. (2000). “Quality Assurance Project Plan, Alternative Cover Assessment Project,”
Science Applications International Corporation, Report to USEPA Contract No.
68-C5-0036.
Scanlon, B., Reedy, R., Keese, K., and Dwyer, S. (2005). “Evaluation of
Evapotranspiration Covers for Waste Containment in Arid and Semiarid Regions in
the Southwestern USA,” Vadose Zone Journal, 4: 55-71.
Stormont, J. and Morris, C. (1998). “Method to Estimate Water Storage Capacity of
Capillary Barriers,” Journal of Geotechnical and Geoenvironmental Engineering,
124 (4): 297 – 302.
Stormont, J., and Morris, C. (2000). “Characterization of Unsaturated Nonwoven
Geotextiles,” Proceedings, Geo-Denver 2000, GSP No. 99, Advances in
Unsaturated Geotechnics, ASCE, Reston, VA: 153–164.
Ward, A. and Gee, G. (1997). “Performance Evaluation of a Field-Scale Surface Barrier,”
Journal of Environmental Quality, 26: 694-705.

17

PAPER NO. 1: FIELD-SCALE EVALUATION OF LYSIMETERS
VERSUS ACTUAL EARTHEN COVERS

ABSTRACT
This paper presents the design, construction, and monitoring of two uncompacted and one
compacted clay field-scale test sections that were built and instrumented at a landfill near
Detroit (Michigan) to capture the differences in the hydraulic and hydrologic responses of
actual caps overlying the municipal solid waste (MSW) versus the corresponding
lysimeters. While the lysimeter pans were installed in the middle of each of the three test
sections to measure percolation, the instrumented area of the test section was expanded
upslope and downslope of the lysimeter to evaluate the effect of the lower boundary.
About 35 sensors were installed in each of the three test sections to monitor water
contents, water potentials, soil temperatures, water levels, and gas pressures. The soil
water storages for the uncompacted test sections that were underlain by the waste were
typically greater than those for the corresponding lysimeters. However, for the compacted
test section, there was no significant difference between the soil water storage for the
actual cap and the lysimeter. The percolation for the compacted clay test section was
about few millimeters per year versus it was in tens of centimeters for the uncompacted
test sections due to about two orders greater field hydraulic conductivities. The field data
collected in this project validates previously published numerical results regarding
hydraulic differences in lysimeters versus actual caps.

18

INTRODUCTION
Earthen covers, or evapotranspirative (ET) caps, or ET final covers are synonyms for
alternative form of final covers that have been permitted in the U.S. for municipal solid
waste (MSW) landfills during the last two decades. Field-scale hydrologic evaluation of
ET covers requires direct or indirect method of quantifying percolation through the soil
covers. For direct quantification, it is typically accomplished by installing water-balance
lysimeters where the earthen cap is underlain by a drainage layer which is underlain by
an impermeable geomembrane to facilitate the collection of all percolation through the
bottom boundary. Key feature of a lysimeter is the ability to directly measure percolation
rate with a precision of about 0.5 mm/yr (Benson et al. 1994; Ward and Gee 1997;
Albright et al. 2002).
Lysimeter studies have been performed since the end of the 17th century (Seiler
and Gat 2007). In the past, lysimeters are generally constructed using deep cylindrical
2

pots with an open surface area of about 1 m . These cylindrical lysimeters were typically
used for estimating groundwater recharge and were mechanically balanced to accurately
measure fluctuations in soil water storage and measure the deep percolation. For landfill
final cover application, pan lysimeters are more common. These lysimeters have much
larger surface area to capture the field-scale heterogeneities such as soil macropores and
fractures (Benson et al. 1994; Khire et al. 1997).
Changes in the soil water storage are determined by installing water content
sensors to monitor the water content across the soil cover profile. A diversion berm is
usually placed around the perimeter of the lysimeter in order to divert surface runoff from

19

upslope of the lysimeter while directing the surface runoff within the lysimeter to the
collection system. Water balance of pan lysimeter can be expressed using Equation 1-1.

ET = P – Pr – RO – ∆S

where

(1-1)

ET is evapotranspiration, P is precipitation, Pr is percolation, RO is surface

runoff, and ∆S is the change in the soil water storage during a specified period of time.
ET is estimated if all other parameters in Equation 1-1 are measured. The estimated ET is
then compared from site-specific estimates of potential and actual ET.
While a lysimeter allows measurement of percolation through the test section, it is
important to evaluate the magnitude of percolation from a lysimeter versus through the
actual cover constructed on the waste surface. The lower boundary of a lysimeter is a
zero flux boundary with lateral drainage occurring through a geocomposite or gravel
drainage layer (Khire et al. 1997; Abichou et al. 2006). The bottom boundary in an actual
landfill final cover allows upward and downward flux of liquid, vapor and heat across the
interface of the waste (Khire and Mijares 2008). Hence, even though lysimeters represent
one of the best means of measuring percolation through a soil cover, it alters the
hydraulics and hydrology of the system.
Khire and Mijares (2008) carried out numerical modeling of lysimeters versus the
corresponding actual earthen caps placed on a waste layer using the 2-D water balance
model Vadose/W (Geo-Slope 2007). Results from this numerical study indicate that
percolation rates obtained from lysimeters are greater than those for earthen caps that are
20

underlain by MSW. Mijares et al. (2010) illustrated numerically that the soil water
storage for lysimeters is typically less than that for earthen caps that are underlain by
MSW and that greater soil water storage capacity corresponds to a lower percolation rate.
Because regulations often require percolation to be relatively small, it is critical to
evaluate the equivalency of percolation measured by a lysimeter to an equivalent cap that
is underlain by MSW. Geo-Slope (2007), Bews et al. (1997), and Parent et al. (2006)
have presented numerical results of lysimeters and the effect of depth of lysimeter pan on
the percolation measured by lysimeter. Geo-Slope (2007) study is based on fixed
infiltration upper boundary. In addition, the lysimeter simulated in Geo-Slope (2007) is
horizontal. The field study presented in this paper focuses on inclined lysimeter which
had atmospheric boundary (transient flux).

OBJECTIVE
The key objective of the field study presented in this paper is to assess the hydraulic and
hydrologic differences between an actual cap and the corresponding lysimeter. In order to
meet the objective, three earthen cap test sections were instrumented and field data was
collected for a period ranging from one to three years.

DESIGN AND CONSTRUCTION OF TEST SECTIONS
Field-scale ET caps were constructed at a landfill located near Detroit, Michigan. The
landfill site is situated in a sub-humid climate where the average annual precipitation is
approximately 84 cm and potential evaporation to precipitation ratio (PE/P) is about 1.2.
Two tests sections, each 15 m wide by 30 m long, were built on the westward facing side

21

slope of the landfill. Performance monitoring for the test sections was divided into two
phases: (1) uncompacted earthen cover investigation from September 2007 to September
2009; and (2) compacted earthen cover investigation from October 2009 to present. To
construct the test sections that represent an ET final cover for the site, native glacial till
soils (USCS Classification: CL) were used for constructing the soil water storage layer.
The Phase 1 construction and monitoring consisted of assessing the earthen caps
under a scenario where the native clay was not compacted. The reason the test sections
were not compacted was to simulate a conservative scenario for higher overall hydraulic
conductivity of the storage layer of the cap, potentially resulting in less increase or no
increase in the overall hydraulic conductivity of the clay due to root penetration and
desiccation. In addition, to enhance ET from the test sections by providing more pore
space for the plant roots to reach greater depths quickly in the test sections. The Phase 2
consisted of constructing and evaluating a test section that was compacted at dry of
optimum water contents to reduce the overall hydraulic conductivity of the cap which is
the typical practice for covers designed as hydraulic barriers.

Test Section Layout
During the Phase 1, which was completed in September 2007, two 15 m by 30 m field
test sections were constructed side-by-side on a landfill side slope. These dimensions
were selected based on previous field studies which indicated that these dimensions are
large enough to capture the field-scale effects (Khire et al. 1997; Albright et al. 2002).
Average slope in the area is about 1V to 6H consisting of an existing intermediate cover
that was placed in the landfill cell in 1990s. One test section was located on the north side

22

and the other on the south side. In the Phase 2, during October 2009, the north test section
was excavated and removed and a new compacted test section was constructed and
instrumented. However, the south test section constructed in the Phase 1 is still being
monitored. The north and south test sections constructed in the Phase 1 consisted of 1.0
m and 1.5 m thick uncompacted native clay cover overlain with a 0.3-m thick topsoil
layer, respectively. In Phase 2, the new north test section was constructed using 1.5-m
thick compacted native clay overlain with a 0.3-m thick topsoil layer.
Figure 1-1 shows the typical cross-section of the instrumented test sections
illustrating the relative locations of the sensor nests including the lysimeter pan. The
lysimeter consisted of a trapezoidal excavation in the middle of each of the test sections
having plan view dimensions of about 8.5 m x 8.5 m x 0.6 m deep. As shown in
Figure 1-1, the instrumented area of the test section was expanded upslope and
downslope of the lysimeter to monitor the water contents, water potentials, and soil
temperatures within and beyond the lysimeter footprint to assess and compare the
hydrologic response of the lysimeter versus the actual earthen cap placed on the
underlying waste.

Test Section Construction
Construction of the uncompacted field test sections was undertaken from August to
September 2007. The construction began with excavating and scraping off the
intermediate cover followed by the installation of pan lysimeter in the middle of each of
the test sections. The clay cover was placed using a track dozer to build the earthen cap.
The clay lift thickness was 30 cm. A specialized company was subcontracted to install

23

Figure 1-1: Typical cross-section of instrumented three field test sections.

24

sensors in the MSW underlying the top and bottom sensor nests as shown in Figure 1-1.
The entire test section was seeded with native grass seeds to promote vegetation growth
for erosion protection and to enhance ET. A 1.5 m deep diversion trench was constructed
upslope of the test sections to divert surface runoff from uphill.
In the Phase 2, during October 2009, the north test section was excavated and
removed and a new compacted test section was constructed and instrumented.

Lysimeter Installation
In order to directly measure percolation, an 8.5 m by 8.5 m lysimeter pan with an average
depth of 0.6 m was installed in the middle of each of the three test sections (Figure 1-1).
The lysimeter was lined using a geosynthetic clay liner (GCL) overlain by a 1.5 mm thick
high-density polyethylene (HDPE) geomembrane. The lysimeter pan was filled with
clean pea gravel having an average hydraulic conductivity equal to 1 cm/s. An insect
mesh made up of polymer having an average opening size of 1 mm was placed on the top
of the gravel surface before the clay was placed to minimize the intrusion of fines into the
lysimeter. A perforated 7.5 cm diameter HDPE pipe was installed in the upper 10 cm of
the pea gravel and vented to the atmosphere to create a vented drainage boundary
(Figure 1-1). This boundary can be subjected to a fixed or variable pressure (or suction)
to create other boundary condition effects for future research studies. During the phases
of the study presented in this paper, the upper boundary of the gravel layer was at
atmospheric pressure. The lower boundary was impermeable to allow collection and
monitoring of percolation. Mijares et al. (2010) carried out numerical modeling of the
lysimeters using UNSAT-H and Vadose/W and showed that while the pea gravel

25

drainage layer theoretically could act as a capillary break, practically, it did not perform
as a capillary break.
Quantity of water percolated through the cap directly above the lysimeter has
been measured by a water level transducer placed at the bottom of each lysimeters as
shown in Figure 1-1. A 30 cm long time domain reflectometry (TDR) water content
sensor was vertically placed in the gravel next to the water level transducer to have a
back-up measurement of the water level for data verification. Another water level
transducer and a TDR water content sensor were installed about halfway upslope within
the lysimeter. The lower water level sensor was placed inside a 10 cm diameter HDPE
perforated HDPE pipe placed at the bottom of the lysimeter pan which ran across the
entire width (8.5 m) of the lysimeter. A set of two 1 cm diameter flexible HDPE tubing
was placed in the conduit to pump the drainage collected in the lysimeter.

Soil Placement
Native clay (CL) was used to construct the earthen cover test sections and was obtained
from on-site borrow pits. During Phase 1, the soil was placed with minimal compaction
effort using a track dozer at its natural water content of about 10%. The clay was placed
in 30 cm thick lifts. Soil samples were collected for further laboratory testing and
characterization. Table 1 shows the physical properties of the soils used for the test
sections. Low plasticity clay was used for the soil water storage/hydraulic barrier layer in
the soil cover whereas low plasticity silt was used for the topsoil layer. The hydraulic
conductivity of the uncompacted clay was measured in the field using a 1 m by 1 m
single-ring infiltrometer (ASTM D5126; Guyonnet et al. 2000) and the average value of

26

the conductivity is 10

-4

cm/s. The water contents and dry unit weights of the

uncompacted clay were measured in the field using Shelby tube samples collected from
the various lifts (Figure 1-2). The dry unit weight of the uncompacted clay was about
85% of the maximum dry unit weight for the Standard Proctor effort.

Table 1-1: Properties of cover soils used in the test sections.

Property

Topsoil

Storage Layer
(Native Glacial Till)

USCS Classification

ML

CL

D10 (mm)

0.00092

0.00020

D50 (mm)

0.070

0.0065

D60 (mm)

0.091

0.014

Cu

99

70

Cu

11

0.70

Liquid Limit (LL)

25

29

Plasticity Index (PI)

3

13

Optimum Water Content (%) for
Standard Proctor Effort

15.7

13.4

Maximum Dry Unit Weight (kN/m ) for
Standard Proctor Effort

17.4

18.5

Hydraulic Conductivity (cm/s) –
Uncompacted Test Sections

1 x 10 (Lab)

1 x 10 (Field)

-4

2 x 10 (Lab)

3

-4

Hydraulic Conductivity (cm/s) –
Compacted Test Sections

1 x 10 (Lab)

27

-4

-7

-6

1 x 10 (Field)

S = 60%

80%

100%

Native Glacial Till (CL)
Modified
Proctor

3

Dry Unit Weight, γ (kN/m )

20

Gs = 2.72
K ~ 10-6 cm/s
(Field Infiltrometer)

d

19
Compacted
North Test
Section

18

Standard
Proctor

17

K ~ 10-7 cm/s
(Lab: Flexible Wall Permeameter)
K ~ 10-4 cm/s
(Field Infiltrometer)

Uncompacted
Test Sections

16
5

Higher Water Content due
to Rainfall after compaction
but before measurement

10

15

20

25

Water Content, ω (%)

Figure 1-2: Proctor compaction curves and field water contents and unit weights.

For Phase 2, where a compacted clay cover was constructed, the clay from the
same borrow area was used to build the test section. The clay lifts were compacted using
a sheepsfoot compactor at the dry of optimum water content. The clay was compacted in
30-cm thick lifts. The water content and dry unit weight of the compacted clay was
measured using a nuclear gauge (Figure 1-2). The field water contents, on average, are
about 4% dry of the optimum water content. The field dry unit weights, on average, are
about 98% of the maximum dry unit weight for the Standard Proctor effort. The average
hydraulic conductivity measured using 10 cm diameter sample in a flexible wall
28

permeameter was 2.2 x 10

-7

cm/s (ASTM D5084). The hydraulic conductivity of the

compacted clay was also measured in the field using a 1 m by 1 m single-ring
infiltrometer and the average value of the conductivity is 10

-6

cm/s. The field

conductivity is representative of the test sections because the size of the clay sampled is
larger than the size of the clay clods observed in the field. A 30 cm thick topsoil layer
consisting of uncompacted silt was placed on top of the compacted clay using a track
dozer and seeded to grow native grass and shrubs.

Pump Set-up
A pumping system was installed at the site for the removal of percolated water that was
collected by the lysimeter pan. A 0.5-hp self-priming utility pump was attached to the
drainage tubes that extended from the lowest point in the lysimeter pan (Figure 1-1). The
lower boundary of the lysimeter was impermeable to collect and store the percolation
until it was pumped. The upper boundary of the gravel layer was vented to the
atmosphere to maintain atmospheric pressure on the lysimeter pan which is consistent
with previous lysimeter studies. A check valve was used at the inlet port of the pump to
maintain sufficient amount of water inside the pump for self priming. The pumps
discharged outside and below the catchment of the monitoring area.
The pump was controlled remotely using an electrical relay switch which was
turned on or off based on the level of water in the lysimeter pan. The lysimeter was not
allowed to overflow by monitoring the water level in the lysimeter on a weekly basis
based on the readings continuously recorded by the datalogger for all the sensors at
30-min interval over a period that ranged from to 1 to 3 years for the three test sections.
29

INSTRUMENTATION
Instrumentation at the site consisted of two weather stations and sensors to monitor insitu volumetric water contents, soil water potentials, temperatures, gas pressures, and
water levels of percolated water in the lysimeter pans. Figure 1-3 illustrates the
comparison of the measured precipitations from the two on-site weather stations and a
weather station located about 15 km from the site that is monitored by National Oceanic
and Atmospheric Administration (NOAA) which also included the snow measurements.

Cumulative Precipitation (cm)

50

40
NOAA Data

30

On-Site
Weather Station (1)
On-Site
Weather Station (2)

20

10
2010

0
10/May

10/Jun

10/Jul

10/Aug

10/Sep

Figure 1-3: Comparison between on-site and NOAA recorded precipitation.
30

Nests of sensors were installed upslope and downslope of the lysimeter pans in all
test sections as shown in Figure 1-1. The instrumentation also extended into the
underlying MSW to about 4.4 m depths below the earthen caps. The weather stations
recorded: hourly precipitation and air temperatures, barometric pressures, relative
humidity, wind speed, and solar radiation. The data was recorded using a datalogger
installed at the site which was accessed remotely using a wireless modem.

Water Level and Pressure Transducers
Pressure transducers were used to measure the water level in the lysimeter pans. The
pressure transducers are made by Keller (Model No. CS431). These sensors have a
measurement range of 0 to 90 cm with 0.1% accuracy. Similar transducers rated for a
higher pressure of up to 105 kPa were used to monitor the gas pressures in the cap and
the underlying MSW. These sensors are 8.5 cm long and have a diameter of 1.2 cm. The
sensor provides a temperature-compensated analog output proportional to the ambient
pressure or the water level above the transducer. It also consists of a 2-mm diameter vent
tube that connects the hollow chamber behind the diaphragm to the atmosphere, therefore
requiring no barometric pressure compensation. A thermistor is embedded within the
transducer to measure ambient temperature to correct errors in the vibrating wire
measurement caused by the changes in the temperature. Prior to installation in the field,
the pressure transducers were calibrated and tested for accuracy.

31

Water Content Sensors
Volumetric water contents were measured using time domain reflectometers
manufactured by Campbell Scientific (Model CS 616). The sensor consisted of two
stainless steel rods, each 30 cm long with a diameter of 3.2 mm spaced 3.2 cm apart. A
calibration curve was developed for the soils used to build the test sections as well as for
the MSW that existed below the test sections. Equation 1-2 presents the calibration
equation that converts the time period, x (µs) measured by the water content
reflectometer to the volumetric water content (θ ) of the clay (CL) used as the storage
layer.

3

2

θ = 3.86E-05x - 2.55E-03x + 6.89E-02x - 6.15E-01

(1-2)

Accuracy of the field measured water contents using the water content
reflectometers were checked from time to time by collecting soil samples from various
depths within the test sections which included the topsoil as well as the underlying clay.
The destructive samples were collected from outside the footprint of the lysimeter or at
least 8 m away from any instrumentation to minimize any influence on the long-term
measurements. Figure 1-4 shows the water content profile obtained from the samples
collected in the field (October 2009) compared to the water content profile obtained using
the in-situ water content reflectometers at the time of the physical sampling.

The

calibrated water contents measured by the sensors closely match the field measurements
using Shelby tube samples. Equation 1-3 presents the calibration equation that converts

32

the time period,

x

(µs) measured by the water content reflectometer to the volumetric

water content (θ ) of MSW that was sampled from below the test sections.

θ = (47.58 - 1.04x) ^ (-0.83)

(1-3)

0
Uncompacted North Test Section
20

Solid Line - Field Measured (TDR)
Dashed Line - Lab Measured
(Shelby Tube)

Depth (cm)

40
60

80

Top Nest
(NT)

Middle Nest
(NM)

100

(θ ~0.38)
s

120

Bottom Nest (NB)
140
0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Vol. Water Content (cm ³/cm³)
Figure 1-4: Water contents measured in the field using water content reflectometers
versus using Shelby tube samples.

Soil Suction and Temperature Sensors
Heat dissipation matric potential (HDMP) sensors were used to measure the soil water
potential in the field. The senor is manufactured by Campbell Scientific and has a model
33

number 229-L. The sensor consists of a cylindrical-shaped porous ceramic matrix with
heating element and a thermocouple embedded in its center. Hence, it also measures soil
temperature. The total length of the sensor is 6 cm and it has a diameter of 1.5 cm. Soil
water potential is indirectly determined using heat dissipation. The sensor is gradually
heated for a fixed time period by applying a current to the heating element and the
increase in temperature is measured by the thermocouple. The magnitude of the
temperature rise represents the heat that is not dissipated and is controlled by the water
content of the porous ceramic matrix, which changes as the surrounding soil wets and
dries, because water conducts heat more readily than air or vacuum.
Soil water potentials ranging from -2500 to -10 kPa can be captured using these
sensors. The air entry pressure of the sensor is about -10 kPa and therefore it cannot
measure potentials above this value because the matrix remains saturated until it reaches
the air entry value. Because of variability of heat transfer properties among sensors, all
heat dissipation sensors used in the field were calibrated individually before they were
deployed in the field. The procedure is presented by Flint et al. (2002). A thermistor
sensor that looks similar to a pencil was inserted in the ground surface of each of the test
sections to monitor the ground freeze and thaw.

Percolation Monitoring
Percolation collected by the lysimeter pan installed in the middle of each of the three test
sections was monitored by measuring the depth of water. Water levels were measured
directly using two pressure transducers and indirectly using 30 cm long time domain
reflectometers placed vertically next to the pressure transducers. Thus, the upper TDR

34

water content sensor was placed in the upper 30 cm of the gravel drainage layer which
was in direct contact with the clay soil of the ET covers.
Figure 1-5 shows the calibration curve for estimating the lysimeter percolation
from the depth of water ponded in the lysimeter pan. Figure 1-5 also shows the equivalent
volume of water in the lysimeter as a function of the measured water level. The
calibration curve was determined from volumes estimated for specific water levels using
the as-built dimensions and layout of the lysimeter pan. This has been verified during
pumping events wherein the water outflow rates that were independently measured are
compared with the estimated rate of decrease in the volume of water stored in the

Percolation Capacity
of Lysimeter

3.0

40
2.5
30

For Depth of Water < 60 cm:
6

5

p = 2E-09z - 3E-07z + 2E-05z
3

4

2

- 0.0005z + 0.0116z - 0.0148z

20

Volume
Capacity
of Lysimeter

(z = water level)

1.5
1.0

Percolation
and Volume

10

2.0

0.5

3

Volume of Water in the Lysimeter (m )

Estimated Lysimeter Percolation, p (mm)

50

0

0.0
0

15

30

45

60

Recorded Depth of Water in the Lysimeter, z (cm)

Figure 1-5: Lysimeter water level, volume, and percolation relations.
35

lysimeter pan. The maximum water level in the lysimeter before the lysimeter would
overflow is 60 cm. At the maximum water level, the corresponding maximum percolation
3

that can be recorded is about 35 mm or 2.5 m . Thus, about 1 cm rise in the water level
correspond to about 0.5 mm percolation.
Figure 1-6 shows the use of TDR sensors to indirectly monitor and confirm the
water level in the lysimeters. Figure 1-6 shows that the water content versus the water
level relationship is close to linear. While the water content readings recorded by the
TDR sensors installed in the gravel drainage layer of the lysimeters were never used to

Water Level in the Lysimeter, z (cm)

38
36
34
32
30
28
26
24
22
20
18
0.20

0.22

0.24

0.26

0.28

0.30

0.32

0.34

Water Content Measured by TDR, θ
Figure 1-6: TDR and water level sensor correlation.
36

0.36

0.38

estimate the quantity of percolation, the data served as an independent check on water
levels monitored by the pressure transducers. The pressure transducer readings coupled
with outflow measurements were used to monitor percolation.

RESULTS AND DISCUSSION

Soil Temperatures
Figure 1-7 presents an example of seasonal variation of soil temperatures observed across
the uncompacted south test section. The plot shows the values measured by the
temperature probe placed on the ground surface as well as the built-in thermistor in heat

30

Uncompacted South Test Section
Lysimeter Nest (SM)

o
Soil Temperature ( C)

25

Depth
BGS
(cm):

20
15
10

165
135

5

75
45
15

0
-5
07/Sep

Ground
Surface

08/Mar

08/Sep

09/Mar

09/Sep

Figure 1-7: Seasonal temperature variation across the test sections.
37

10/Mar

dissipation matric water potential sensors installed at various depths at the middle nest of
the uncompacted south test section. The expected trend is evident in the data wherein the
soil temperature drops during winter and peaks during summer. It can also be seen that
the soil temperature on the ground surface fluctuates significantly since it is directly
exposed to atmospheric condition. On the other hand, the soil temperatures at succeeding
depths show successive damping of fluctuations. This pattern is also observed for the
other nests of sensors from both test sections.

Soil Water Storage

Phase 1: Uncompacted North and South Test Sections
Soil water storage of all three test sections (Phases 1 and 2) was calculated by integrating
the recorded volumetric water contents across the profile using the 30-min readings.
Figure 1-8 presents the measured soil water storages obtained from the sensor nests
placed within the lysimeters versus upslope and downslope of the lysimeters constructed
during the Phase 1. Percolation was measured for the middle nest of sensors which was
installed above the lysimeter pan.
Figure 1-8(a) shows that, generally, the soil water storages for the portions of the
test sections that are placed on the MSW (NT, ST, NB) are greater than those for the
portions placed above the lysimeters (NM and SM). For the uncompacted north test
section, the average soil water storage for the lysimeter nest (NM) was 31.2 cm whereas
the storages were 40.3 cm and 33.1 cm for the top (NT) and bottom (NB) nests,
respectively, that were placed in the portions of the test sections which were underlain by

38

70
ST = Actual Cap: Top Nest
NT = Actual Cap: Top Nest
NB = Actual Cap: Bottom Nest

Soil Water Storage (cm)

60

50

NT
NB

Uncompacted
South Test
Section

Lysimeter

40

(SM)

Actual Cap

Uncompacted
North Test
Section

30
Phase 1
20
08/May

Cumulative Precipitation or Percolation (cm)

Actual Cap

ST

Lysimeter

(a)

(NM)
08/Jul

08/Sep

08/Nov

09/Jan

09/Mar

80
Phase 1

70

Uncompacted Test Sections

60

NM = North Lysimeter (1.35 m Thick)
SM = South Lysimeter (1.8 m Thick)

50
40
30

Precipitation

20
NM
10

Percolation

(b)

SM
0
08/May

08/Jul

08/Sep

08/Nov

09/Jan

09/Mar

Figure 1-8: Soil water storages (a); and cumulative precipitation and percolation (b) for
uncompacted test sections.
39

MSW. The peak soil water storage for NM was 44.2 cm whereas it was 48.6 cm and
42.9 cm for NT and NB, respectively. The average soil water storage for the lysimeter is
less than that for the actual caps.
For the uncompacted south test section, which had about additional 45 cm of clay
compared to the north test section, the average soil water storage for the lysimeter nest
(SM) was 50.5 cm whereas the storage was 51.0 cm for the top (ST) nest that was placed
above the MSW (Figure 1-1). The peak soil water storage for SM was 62.2 cm whereas it
was 63.3 cm for ST. The bottom nest in the south test section was placed in the existing
intermediate cap placed on the landfill cell in 1996. Data for that nest is not presented in
this paper. That data is being used to assess long-term changes in the water holding
capacity of the test sections. During July to September 2008, the soil water storage in the
upper portion of the south test section (ST) drops below the lysimeter portion of the test
section (SM). During this period, according to Figure 1-8(b), relatively small
precipitation and percolation were recorded. This shows that the soil water storage was
depleted primarily due to ET.
Figure 1-9 shows the comparison of measured soil water storages for the actual
caps in the north and south test sections versus the soil water storages for the
corresponding lysimeters. The 1:1 line indicates equal soil water storages for the
lysimeter and the actual cap for the measurements done at the same moment. The points
above the line indicate that the soil water storage for the actual cap is greater than that for
the corresponding lysimeter and vice versa. About 97% of the data points cluster together
above the 1:1 line for the north test section while about 69% of the data for the south test
section. The average of the ratios of soil water storages for the actual caps to those for the

40

corresponding lysimeters for the uncompacted north and south test sections are 1.17 and
1.00, respectively.

Soil Water Storage for Actual Caps (cm)

70
Uncompacted North
Test Section
Uncompacted South
Test Section

60

50
Uncompacted South
Test Section
40

30
Uncompacted North
Test Section

1:1 Line

Phase 1

20
20

30

40

50

60

70

Soil Water Storage for Lysimeter (cm)
Figure 1-9: Correlation between measured soil water storages for lysimeters versus actual
caps for uncompacted test sections.

Using the numerical model Vadose/W, Mijares et al. (2010) demonstrated that the
soil water storages for lysimeters are expected to be less than those for the corresponding
actual caps because depending upon the soil water retention functions, the soil cover in
the actual cap is able to pull water upwards from the waste layer to maintain its higher
soil water storage. In addition, they also concluded that as the thickness of the cap
41

increases, the difference in soil water storages between the actual cap and the
corresponding lysimeter shrinks. Thus, the soil water storage of the south lysimeter,
which is thicker than the north test section, is closer to the corresponding cap.
Furthermore, Mijares et al. (2010) also numerically demonstrated that greater soil water
storage represents lower percolation. Hence, while percolation values for the actual caps
cannot be measured in the absence of a lysimeter, it can be inferred that the percolation
measured in the uncompacted north lysimeter is on the conservative side compared to the
percolation that must have entered into the waste in the north test section while the
percolation measured in the uncompacted south lysimeter is closer to the percolation that
must have entered into the waste in the south test section.

0.45
Depth BGS*
(cm)

MSW (2.6 m
below Cap)

120

3

Vol. Water Content (cm /cm )

0.40

75

0.35

3

45

0.30
MSW (2.3 m
below Cap)

0.25
0.20

15
(Topsoil)

0.15
0.10

Uncompacted North
Test Section
Location: Top Nest (NT)

0.05
07/Sep

08/Jan

08/May

*BGS = Below Ground Surface

08/Sep

09/Jan

09/May

09/Sep

10/Jan

Figure 1-10: Water contents in the test section and in the underlying waste.
42

Figure 1-10 shows the water contents measured in the NT nest of the north test
section. Figure 1-10 shows that the changes in the water contents during a given period of
time are greater at shallower depths compared to at deeper depths. In addition, the
increase or decrease in the water contents from top down (or opposite direction) follows a
relatively sequential pattern similar to sinusoidal waves with phase shift. The water
content of the underlying waste also increases and decreases as the water contents of the
clay cap increase or decrease. Thus, in an actual cap, there is continuity in the water flux
across the cap and the waste interface which impacts the magnitude of the flux depending
upon the hydraulic properties of the cap and the waste (Mijares and Khire 2008).

Phase 2: Compacted North and Uncompacted South Test Sections
The soil water storages and cumulative percolation for the compacted north test section
constructed during the Phase 2 of the project are presented in Figure 1-11. The Phase 2
data spans from the end of October 2009 to October 2010. For comparison, the soil water
storages and cumulative percolation for the uncompacted south test section are presented
in Figure 1-11(b). The compacted north and uncompacted south test sections are both
1.8 m thick and contain 1.5 m thick native clay storage layer. Comparison of
Figures 1-11(a) and (b) demonstrates that the changes in the soil water storage for the
uncompacted test section are larger and steeper following precipitation events or when
the soils dry out between the successive precipitation events. The compacted test section,
which has about two orders lower hydraulic conductivity compared to the uncompacted
test section, is shedding more water as runoff (or lateral flow within the vegetative layer)

43

67

Soil Water Storage (cm)

57

0.7

Irrigation
(20.8 cm)

0.6

CB - Bottom Sensor Nest
CM - Middle Sensor Nest
(Lysimeter)
CT - Top Sensor Nest

0.5

CB

52

CT
0.3

47

CM
(Lysimeter)

42

Percolation

37
32
09/Nov

Phase 2
10/Jan

10/Mar

10/May

UNCOMPACTED SOUTH
TEST SECTION

10/Jul

10/Sep

0.0
10/Nov

Irrigation
(9.7 cm)

70
60

62

SM - Middle Sensor Nest
(Lysimeter)
ST - Top Sensor Nest

57

50
40

52

SM

42

Precipitation

30

ST

47

20

Percolation
10

37

(b)
32
09/Nov

Phase 2
10/Jan

10/Mar

10/May

10/Jul

10/Sep

0
10/Nov

Cumulative Precipitation or Percolation (cm)

67

0.2
0.1

(a)

Soil Water Storage (cm)

0.4

Cumulative Percolation (cm)

62

COMPACTED NORTH
TEST SECTION

Figure 1-11: Soil water storage and cumulative precipitation and percolation for
compacted north test section (a); and uncompacted south test section (b).
44

and hence not showing increase in the storage as rapid as seen for the uncompacted test
sections.
The compacted test section reached peak soil water storage of about 65.6 cm
versus the uncompacted test section that reached peak storage of about 60.7 cm which
occurred at about the same time as that for the compacted test section. Due to lower
hydraulic conductivity, the compacted test section was able to store more water. More
soil water storage translates into lower percolation (Mijares et al. 2010). The compacted
test section had about 6.7 mm of percolation during the one year monitoring period and a
majority of the percolation was observed when the soil water storage peaked in July 2010
(Figure 1-11a). During the same time period, the uncompacted south test section had 157
mm of cumulative percolation.
Figure 1-12 shows the comparison of measured soil water storages for the actual
cap in the compacted north test section versus the soil water storages for the
corresponding lysimeter. About 80% of the data points are above and about 20% of the
data points are below the 1:1 line for the compacted test section. The average of the ratios
of soil water storages for the actual caps to those for the corresponding lysimeter for the
compacted north test section is 1.07. This average value of the ratio is about the same as
that for the uncompacted south test section. Mijares et al. (2010) concluded that as the
thickness of the cap increases or the hydraulic conductivity of the cap decreases, the
difference in soil water storages between the actual cap and the corresponding lysimeter
shrinks. Hence, due to lower hydraulic conductivity, the soil water storage of the
compacted north lysimeter is about the same as the corresponding actual cap.

45

Soil Water Storage for Actual Cap (cm)

70
Compacted North
Test Section

65

1:1 Line

60
55
50
45
Top Nest vs. Middle Nest

40

Bottom Nest vs. Middle Nest

35
Phase 2
30
30

35

40

45

50

55

60

65

70

Soil Water Storage for Lysimeter (cm)
Figure 1-12: Correlation between measured soil water storages for lysimeter versus actual
cap for the compacted north test section.

Using numerical simulations carried out using Vadose/W, Mijares et al. (2010)
demonstrated that when the soil water storage of the lysimeter is about the same as that
for the actual cap, the percolation measured from the lysimeter can be assumed
representative of the percolation entering the waste in an actual cap. Hence, while
percolation values for the actual caps cannot be measured in the absence of a lysimeter,
it can be inferred that the percolation measured from the compacted north lysimeter
(~ 6.7 mm/yr) is closer to the percolation that must have entered into the waste in the
compacted north test section.
46

SUMMARY AND PRACTICAL IMPLICATIONS
This paper presents the design and construction of two uncompacted and one compacted
field-scale earthen cap test sections that were built and instrumented at a landfill to
evaluate the differences in the hydraulic and hydrologic response of actual caps
(underlain by the waste) versus the corresponding lysimeters which are used to measure
percolation. Lysimeter pans were installed in the middle of each of the three test sections.
The instrumented area of the test section was expanded upslope and downslope of the
lysimeter to monitor the soil water storages within and beyond the lysimeter footprint to
evaluate the effect of lysimeter lower boundary.
About 35 sensors were installed in each of the three test sections to monitor water
contents, water potentials, soil temperatures, water levels, and gas pressures. The data
collected during the Phase 1 shows the hydrologic performance of two uncompacted test
sections having 1.35 m and 1.8 m total thicknesses. The Phase 2 data shows the
hydrologic performance of two test sections having the same thickness (1.8 m) but
-4

-6

different hydraulic conductivities (~10 cm/s and 10 cm/s) due to one being compacted
and the other not.
The soil water storages for the uncompacted test sections underlain by the waste
were typically greater than those for the corresponding lysimeters. However, for the
compacted north test section constructed in the Phase 2, there was no significant
difference observed between the soil water storages for the actual cap and the lysimeter.
The field data collected in this project validates the numerical findings of Khire and
Mijares (2008) and Mijares et al. (2010) which demonstrated that lysimeters would
underestimate the soil water storage and overestimate the percolation. However, the
47

difference in these parameters for lysimeters and actual caps shrink as the thickness of the
cap is increased and/or the hydraulic conductivity is lowered.

48

REFERENCES

49

REFERENCES
Abichou, T., Liu, X., and Tawfiq, K. (2006). “Design Considerations for Lysimeters
Used to Evaluate Alternative Earthen Final Covers,” Journal of Geotechnical and
Geoenvironmental. Engineering, 132 (12): 1519-1525.
Albright, W., Gee, G., Wilson, G., and Fayer, M. (2002). “Alternative Cover Assessment
Project: Phase I Report,” Publication No. 41183, Report to US EPA, Desert
Research Institute, NV.
Benson, C., Bosscher, P., Lane, D., and Pliska, R. (1994). “Monitoring System for
Hydrologic Evaluation of Landfill Final Covers,” Geotechnical Testing Journal,
17 (2): 138-149.
Bews, B., O’Kane, M., Wilson, G., and Williams, D. (1997). “The Design of a Low Flux
Cover System Including Lysimeters for Acid Generating Waste Rock in Semiarid Environments,” Fourth International Conference on Acid Rock Drainage,
Vancouver, BC: 747-762.
Flint, A., Campbell, G., Ellett, K., and Calissendorff, C. (2002). “Calibration and
Temperature Correction of Heat Dissipation Matric Potential Sensors,” Soil
Science Society of America Journal, 66: 1439–1445.
Geo-Slope. (2007). “Vadose Zone Modeling with VADOSE/W 2007: An Engineering
Methodology,” Geo-Slope International Ltd., Alberta, Canada.
Guyonnet, D., Amraoui, N., and Kara, R. (2000). “Analysis of Transient Data from
Infiltrometer Tests in Fine-Grained Soils,” Ground Water, 38 (3): 396-402.
Khire, M., and Mijares, R. (2008). “Influence of the Waste Layer on Percolation
Estimates for Earthen Caps Located in a Sub-humid Climate,” Proceedings,
GeoCongress 2008, GSP No. 177, Geotechnics of Waste Management and
Remediation, ASCE, Reston, VA: 88-95.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering,
123 (8): 744-754.
Mijares, R., Khire, M., and Johnson T. (2010). “Lysimeters Versus Actual Earthen Caps:
Numerical Assessment of Soil Water Storage,” Proceedings, GeoFlorida 2010,
GSP No. 199, Advances in Analysis, Modeling and Design, ASCE, Reston, VA:
2849-2858.
Parent, S., Cabral, A., Gras, G. and Marinho, F. (2006). “Design and Installation of ZeroTension Lysimeter in an Inclined Cover,” Proceedings, 6th International
Conference on Unsaturated Soils, April 2-6, Carefree, AZ: 625-633.

50

Seiler, K., and Gat, J. (2007). Groundwater Recharge from Run-off, Infiltration and
Percolation, Water Science and Technology Library, Vol. 55, Springer, The
Netherlands, 244 p.
Ward, A., and Gee, G. (1997). “Performance Evaluation of a Field-scale Surface
Barrier,” Journal of Environmental Quality, 26: 694–705.

51

PAPER NO. 2: FIELD DATA AND NUMERICAL MODELING OF
WATER BALANCE OF LYSIMETER VERSUS ACTUAL EARTHEN
CAP

ABSTRACT
In order to evaluate the differences in the hydrological performance of actual earthen cap
overlying municipal solid waste (MSW) versus lysimeter which is commonly used to
measure the hydrologic water balance, a field-scale test section (30 m X 20 m X 2 m) of
an earthen cap made up of compacted native glacial clay was constructed and
instrumented at a landfill near Detroit, Michigan. Lysimeter pan was installed within the
middle of the test section and the instrumented area of the test section was expanded
upslope and downslope of the lysimeter to monitor water balance parameters within and
beyond the lysimeter footprint to evaluate the effect of artificial drainage boundary
introduced by the lysimeter. About 50 sensors were installed to monitor meteorological
parameters, water contents, water potentials, soil temperatures, water levels, gas
pressures, percolation, and subsurface lateral flow.
Water balance model UNSAT-H was used to simulate the water balance of the
test section. UNSAT-H was able to predict the percolation relatively accurately. Relative
changes or trends in the soil water storage were generally accurately captured by the
numerical model. The numerical model that was validated for the lysimeter was used to
simulate the water balance of the actual cap where the cap was placed on MSW. The net
percolation over the monitoring period estimated by UNSAT-H across the interface
between the cap and the underlying landfilled waste was negative (upward) as well as
positive (downward into the waste). However, net percolation from the actual cap

52

estimated by UNSAT-H was relatively close to that measured by the lysimeter. Thus, the
field data and modeling results indicate that the soil cap is able to pull moisture from the
underlying waste under evapotranspirative gradients. In addition, the numerical
simulation results indicate that soil water storage can be used as an indicator of relative
percolation for the actual cap with respect to the percolation measured by the lysimeter.

INTRODUCTION
Earthen caps, also known as evapotranspirative (ET) covers, have been commonly
permitted for landfills located in arid, semi-arid, and sub-humid climates (Khire et al.
1999; Albright et al. 2004; Scanlon et al. 2005) in lieu of prescriptive caps which require
the use of flexible membrane liner (FML) or geomembrane (GM). Typically, evaluating
the hydrologic performance of ET caps requires the installation of lysimeters at the
proposed site to measure the percolation through the cap.
Because field demonstration projects usually span only for few years, numerical
models are often used to predict the long-term performance of the earthen cap. Numerical
studies on lysimeters typically neglect the effect of the underlying waste (Khire et al.
2000; Benson et al. 2005) because percolation is immediately collected through a
drainage layer placed above the geomembrane that lines its bottom boundary. While the
geomembrane allows the infiltrated water through the cap to be physically collected and
measured, it prevents the upward flux of liquid and vapor from the waste mass or
subgrade layer located below the cap under evapotranspirative gradients (Khire and
Mijares 2008; Mijares et al. 2010). It may also alter the heat flux from the waste mass
that is present below the cap which may influence the estimated percolation for the actual

53

cap. When proposed alternative earthen cap is approved and constructed, the
geomembrane and the drainage layers used for the lysimeter during field demonstration
are not placed. Several studies have identified this conceptual difference (Scanlon and
Milly 1994; Abichou and Musagasa 2008; Khire and Mijares 2008). The concern stems
due to the inherent hydraulic differences in the lysimeter and the actual cap influencing
the percolation. The percolation needs to be relatively small (few mm per year) in order
for the regulatory agencies to approve the alternative cap. Hence, the accuracy in
measuring and projecting long-term percolation for the actual cap needs to be relatively
high.
A field-scale demonstration project was undertaken to evaluate the use of earthen
cap in Detroit, MI which is considered to have sub-humid climate. The test section was
built and instrumented at a landfill site. Lysimeter pan was installed in the middle of the
test section to measure percolation. Moreover, the instrumented area of the test section
was expanded upslope and downslope of the lysimeter to monitor the soil water storage
within and beyond the lysimeter footprint. The unique design of the test section allowed
comparative hydrologic evaluation between an actual earthen cap (underlain by MSW)
versus the corresponding lysimeter.

OBJECTIVE
The key objective of the study was to evaluate the hydrological differences between an
actual earthen cover versus the corresponding lysimeter. Percolation and soil water
storage measured from the lysimeter portion of an instrumented field-scale test section
were used to verify the numerical model UNSAT-H. Because percolation cannot be

54

directly measured without the lysimeter pan, the validated numerical model was used to
predict the percolation for the actual cap placed on the existing MSW.

FIELD-SCALE TEST SECTION
A field-scale earthen cover test section, 30 m long by 20 m long, was constructed at a
landfill located in Detroit, Michigan. The site is situated in sub-humid climate where the
average annual precipitation is 84 cm and has a potential evaporation to precipitation
ratio (PE/P) of about 1.2. Average slope of the landfill is about 1V to 6H consisting of an
existing intermediate cover that was placed on the waste in late 1990s. The test section
was constructed using a 1.5-m thick native glacial till (clay) which was overlain by a
0.3-m thick topsoil layer. The clay was compacted at dry of optimum water contents to
minimize potential for desiccation cracking.
Figure 2-1 shows the cross-section of the instrumented test section illustrating the
relative locations of the sensor nests including the lysimeter pan. The lysimeter consisted
of a trapezoidal excavation in the middle of the test section having plan view dimensions
of about 8.5 m by 8.5 m with an average depth of 0.6 m. The lysimeter was lined using a
geosynthetic clay liner (GCL) overlain by a 1.5 mm thick high-density polyethylene
(HDPE) geomembrane. The lysimeter pan was filled with clean pea gravel having an
average hydraulic conductivity equal to 1 cm/s. A polymer insect mesh having an average
opening size of 1 mm was placed on top of the gravel surface before the clay was placed
to physically separate the clay from the drainage gravel during field placement. An
HDPE pipe having 7.5 cm diameter was installed within the pea gravel and vented to the
atmosphere to create a vented drainage boundary. This boundary can be subjected to a

55

Figure 2-1: Cross-section of instrumented field test section.

56

fixed or variable pressure (or suction) to simulate other field conditions for future
research.
The instrumented area of the test section was expanded upslope and downslope of
the lysimeter (Figure 2-1) to monitor the water content, water potential, gas pressure, and
soil temperature within and beyond the lysimeter footprint in order to assess and compare
the hydrologic performance of the lysimeter versus the actual cover placed on the
underlying waste. The upper and lower sensor nests were placed diagonally or cross slope
(in plan view) with respect to the central lysimeter nest so that the sensor nests located
upgradient on the slope could not influence the water balance measured by the sensor
nests located downgradient.

Soil Properties
Native soil which is a glacial till was used to build the earthen cover test section. The clay
was compacted in 30-cm thick lifts using a sheepsfoot compactor at dry of optimum
water contents as shown on the compaction curve in Figure 2-2. Soil samples were
collected for further laboratory testing and hydraulic characterization. Table 2-1 shows
the physical properties of the soils used for the test sections. Low plasticity clay (CL) was
used as the storage layer whereas low plasticity silt (ML) was used for the topsoil layer.
The water content and dry unit weight of the compacted clay were measured
using a nuclear densometer (Figure 2-2). The field water contents, on average, are about
4% dry of the optimum water content. The field dry unit weights, on average, are about
98% of the maximum dry unit weight of the Standard Proctor effort. The hydraulic
conductivity of the compacted clay was measured in the lab using 10 cm diameter

57

samples in a flexible wall permeameter (ASTM D5084). The average lab value of the
hydraulic conductivity was 2.2 x 10

-7

cm/s. The hydraulic conductivity of the compacted

clay was also measured in the field using a 1 m by 1 m single-ring infiltrometer (ASTM
D5126; Guyonnet et al. 2000) and the average value of the conductivity is 4.4 X
-6

10

cm/s. Field conductivity was used for the modeling because it is considered more

representative due to the larger size of the soil sampled. A 30 cm thick topsoil layer
consisting of uncompacted silt was placed on top of the compacted clay using a track
dozer and seeded to grow native grass and shrubs. Single-ring infiltrometer tests were

Native Glacial Till (CL)

Modified
Proctor

Gs = 2.72

3

Dry Unit Weight, γ (kN/m )

20

-6

K ~ 4 x 10 cm/s
(Field: Infiltrometer)

19

d

Field Test
Section

Higher Water Content due
to Rainfall after compaction
but before measurement

18

Standard
Proctor

17

-7

K ~ 2 x 10 cm/s
(Lab: Flexible Wall Permeameter)
S = 60%

16
5

10

100%
80%

15

20

Water Content, ω (%)
Figure 2-2: Proctor compaction curves and field water contents and unit weights.
58

25

Table 2-1: Physical properties of the soils.

Property

Topsoil

Storage Layer
(Native Glacial Till)

USCS Classification

ML

CL

D10 (mm)

0.00092

0.00020

D50 (mm)

0.070

0.0065

D60 (mm)

0.091

0.014

Cu

99

70

Cc

11

0.70

Liquid Limit (LL)

25

29

Plasticity Index (PI)

3

13

Optimum Water Content (%) for
Standard Proctor Effort

15.7

13.4

17.4

18.5

-2

2 x 10 (Lab)

3

Maximum Dry Unit Weight (kN/m ) for
Standard Proctor Effort
Hydraulic Conductivity (cm/s)

1 x 10 (Field)

-7

-6

4.4 x 10 (Field)

also carried out on the vegetative layer and the average value of the conductivity is about
-2

1 X 10 cm/s.

Instrumentation
Instrumentation at the site consisted of two weather stations and sensors to monitor insitu volumetric water contents, soil water potentials, temperatures, gas pressures, and
water level of percolated water in the lysimeter pan. Subsurface lateral flow through the
59

topsoil layer was measured using a lateral trench connected to a tipping bucket
(Figure 2-1).
Total three nests of sensors were installed within the lysimeter catchment and upgradient and down-gradient of the lysimeter as shown in Figure 2-1. The instrumentation
also extended into the underlying MSW to about 2.5 m depth below the earthen cap to
monitor the water contents, temperatures, suctions, and gas pressures. The weather
stations recorded precipitation, air temperature, barometric pressure, relative humidity,
wind speed, and solar radiation. The data was recorded at 30-min interval using a
datalogger installed at the site which could be accessed remotely using a wireless modem.
Quantity of water percolated through the cap directly above the lysimeter was
measured by a water level transducer placed at the bottom of the lysimeter (Figure 2-1).
A 30 cm long time domain reflectometry (TDR) water content sensor was vertically
placed in the gravel next to the water level transducer to have a back-up measurement of
the water level. Another water level transducer and TDR water content sensor were
installed about halfway upslope within the lysimeter. The lower water level sensor was
placed inside a 10 cm diameter perforated HDPE pipe placed at the bottom of the
lysimeter pan which ran across the entire width (8.5 m) of the lysimeter (Figure 2-1). A
set of two 1 cm diameter flexible HDPE tubing was placed in the conduit to pump the
drainage collected in the lysimeter.
A 0.5-hp self-priming pump was installed at the site for the removal of percolated
water that was collected in the lysimeter pan. The pump discharged water outside and
below the catchment of the test section. The lysimeter recharge (percolation) was

60

measured and confirmed by continuously monitoring: (1) water level in the lysimeter; (2)
water content of the drainage layer of the lysimeter; and (3) rate of pumped outflow.

NUMERICAL WATER BALANCE MODELING
The public domain finite-difference water balance model UNSAT-H Ver. 3.0 (Fayer
2000) was used to numerically simulate the hydrologic performance of the instrumented
test section. UNSAT-H numerically solves a modified form of Richards’ equation to
calculate the flow of water through both saturated and unsaturated soil(s). UNSAT-H can
simulate water and heat flow processes in one dimension (1-D) and is capable of
simulating steady-state and transient conditions. This model has been routinely used for
water balance modeling of earthen caps (Khire et al. 1997; Khire et al. 2000; Benson et
al. 2005; Scanlon et al. 2005; Ogorzalek et al. 2008; Bohnhoff et al. 2009). For this study,
1-D simulations were carried out using UNSAT-H Version 3. UNSAT-H is not capable
of simulating flow through macropores that may not follow capillarity and hence cannot
be represented by Richards’ equation. UNSAT-H also does not consider air/gas
pressures. Therefore, if air/gas pressures develop during rapid infiltration events, the
model is unable to simulate the flow accurately.

INPUT PARAMETERS FOR UNSAT-H
A schematic of the conceptual models used to simulate the field test section is shown in
Figure 2-3. To simulate the lysimeter as represented by the middle nest (Figure 2-1), the
lower boundary was assigned unit gradient to simulate the vented lower boundary. Low
magnitude percolation was collected in the lysimeter throughout the year which indicates

61

(a)

(b)

Figure 2-3: Conceptual model for numerical simulation of a lysimeter (a); and an actual cap with underlying waste (b).
62

that unit gradient boundary is appropriate to simulate the lysimeter. In order to simulate
the actual earthen caps which are represented by the top or bottom nests (Figure 2-1) of
the test section, the cap was assumed to have underlain by a 10 m thick MSW layer
which is representative of the cross section at the site. The lower MSW boundary was
simulated as unit gradient boundary.

Soil Properties
Table 2-1 summarizes the index, compaction, and the saturated hydraulic properties of
the soils used for the test section. Table 2-2 presents the unsaturated hydraulic
parameters. The soil water characteristic curves are described by Haverkamp et al. (1977)
function and were obtained from the water contents and soil suctions measured in the
field. The unsaturated hydraulic conductivities were estimated by applying the
instantaneous profile method (Meerdink et al. 1996) to the water contents and suctions
measured in the field using co-located sensors (Figure 2-1).

MSW Properties
In order to simulate the actual earthen caps located upslope and downslope of the
lysimeter, numerical simulations included the underlying MSW layer. The MSW was
simulated by assigning saturated and unsaturated hydraulic properties of MSW that were
measured in the laboratory for MSW collected from the landfill from 6 to 12 m depths.
The MSW sample was obtained using a 45 cm diameter auger. The waste, without sorting
or screening, was placed in a relatively large PVC cell (30 cm diameter, 25 cm tall) to
measure the saturated hydraulic conductivity using the falling head test (ASTM D5084)

63

Table 2-2: Saturated and unsaturated hydraulic properties of the soils and waste.

Material

θs

3

θr

3

3

3

(cm /cm ) (cm /cm )

α

β

Ks

(1/cm)

(cm/s)

Α

Β
(1/cm)

Vegetative
Layer
or Topsoil
(Sandy Silt;
ML)

0.41

0.025

147.26 0.668 1.0 x 10

-2

6,261

2.64

Storage
Layer
(Lean Clay
with Sand; CL)

0.35

0.033

403.87 0.658 4.4 x 10

-6

2,530,849

2.73

Landfilled
Waste
(Measured;
MSW)

0.67

0.20

-2

1.80

1.46

1.62

0.293 1.0 x 10

and the same sample was spun in a geotechnical centrifuge at up to 40 g gravitational
force added to the sample in 1 to 3 g increments to measure the water retention function
(ASTM D6836). The centrifuge not only allowed the measurement of the water retention
function relatively rapidly, it also simulated the normal stress experienced by the waste at
the depth it was collected. The dry density of the waste at the vertical stress simulated in
3

the centrifuge was 0.69 g/cm . The method developed by Passioura (1977) was applied to
the water retention data collected from the centrifuge test to estimate the unsaturated
hydraulic conductivities for the waste.
The hydraulic properties measured for the waste are summarized in Table 2-2 and
are plotted in Figure 2-4. The water retention function measured for the waste was also
64

confirmed by plotting the water contents and suctions measured in the waste at various
depths during the two year monitoring period. Figure 2-5 shows the water contents,
suctions, and gas pressures measured in the field at various depths in the waste.
Figure 2-5(b) shows that the suctions and gas pressures are about the same (60 to 90 kPa)
and are relatively constant at shallow depths (immediately below the cap). Thus, it can be
assumed that the water content and gas pressures (or suctions) are in equilibrium. Hence,
the water contents and suctions were plotted on the water retention function of the waste
measured in the lab (Figure 2-4a). The boxed regions in Figure 2-4(a) indicate the
equilibrium water contents and suctions measured in the field. Because it is expected that
the waste in the landfill would vary in its composition, for comparison, the water
retention function and unsaturated hydraulic conductivities measured by Kazimoglu et al.
(2005, 2006) for loosely compacted MSW are also included in Figure 2-4. Kazimoglu et
al. (2005, 2006) determined the waste retention properties for a waste specimen prepared
in the laboratory which had composition similar to the waste found in Lyndhurst landfill
3

in Australia that was located at shallow depth with a dry density of 0.57 g/cm . Stoltz and
Gourc (2007) published similar waste retention curves for loosely compacted MSW
3

having a dry unit weight equal to 0.54 g/cm . For loosely compacted MSW such as those
found within landfills at shallow depth (i.e., immediately beneath the final cover), a
saturated hydraulic conductivity of 10

-3

cm/s has been reported (Mukherjee 2008;

Breitmeyer et al. 2010). Hence, for modeling the actual cap and simulate possible
scenarios, the hydraulic properties of the waste input to the model were for measured
values as well as those published by Kazimoglu et al. (2005, 2006).

65

10

5

10

4

Matric Suction (cm)

(a)

10

3

10

2

10

Measured
(Centrifuge Testing)

1

10
10

Measured
(Kazimoglu et al. 2006)
Measured
(Field Data)

0

-1

MSW
-2

10 0.1

0.2

0.3

0.4

0.5

0.6

0.7

Volumetric Water Content

10

0

-1

10
10

-4

10

-5

10

-6
-7

10

-8

(b)

cm/s

-3

10

-2

Measured Ks = 10

-2

10

Hydraulic Conductivity (cm/s)

10

Measured
(Centrifuge Test)
-3

Assumed Ks = 10

Measured
(Kazimoglu et al. 2006)

MSW

10

-2

10

cm/s

-1

10

0

10

1

10

2

10

3

10

4

Matric Suction (cm)
Figure 2-4: Measured water retention curves (a); and unsaturated hydraulic conductivity
functions (b) for the waste.
66

0.60
(a)
390 cm BGS

0.50

3

3

Vol. Water Content (cm /cm )

MSW Water Contents

225 cm BGS

0.40

360 cm BGS

0.30

UNSAT-H
Simulated

0.20
195 cm BGS

0.10
1000

Gas Pressure or
Soil Suction (cm of water)

Field Gas Pressures and Soil Suctions
435 cm BGS
(waste gas pressure)

(b)

Soil Suction at:
105 cm BGS
135 cm BGS

100

300 cm BGS
(waste gas pressure)

120 cm BGS
(soil gas pressure)

10
08/Nov 09/Feb 09/May 09/Aug 09/Nov 10/Feb 10/May 10/Aug 10/Nov
Figure 2-5: Measured water contents (a); and gas pressures and suctions (b) in the waste.
67

Meteorological Data
The two weather stations installed in the field provided hourly precipitation, air
temperature, barometric pressure, relative humidity, wind speed and direction, and solar
radiation.
UNSAT-H requires daily values for maximum and minimum air temperature, dew
point temperature, total solar radiation, average wind speed, average cloud cover, and
total precipitation. Daily dew point temperatures were estimated from the daily average
temperature and relative humidity. Average cloud cover was assumed to be zero because
net solar radiation was measured at the site. UNSAT-H assumes a sinusoidal variation in
air temperature throughout the day and assumes that the daily minimum temperature
occurs at 3:00 a.m. and the daily maximum temperature occurs at 3:00 p.m. The dewpoint
temperature, wind speed, and cloud cover were assumed to remain constant throughout
the day. The daily variation of solar radiation was approximated by a sine function with
the peak value occurring at 12:00 noon. Precipitation was applied at an hourly frequency
specifically during the time intervals it occurred during a particular day.

Initial Conditions
The initial conditions applied in the model were consistent with those measured in the
field test section at the time corresponding to the start date of the simulation. The sensors
in the underlying waste were installed a year prior to the construction of the lysimeter.
Hence, the water balance simulation period was about a year, starting in Nov. 2009.
Initial conditions for UNSAT-H were specified across the depth of the soil profile using
the matric suctions corresponding to the measured in-situ water contents across the nest

68

of sensors in the test section. A variable flux boundary was applied at the ground surface
(Figure 2-3) for lysimeter as well as for the actual cap(s). The variable flux boundary
corresponds to infiltration rate if it is raining on a given time period or evaporation rate if
otherwise.

Numerical Control Parameters
Spatial discretization of the model domain was optimized by conducting sensitivity
analysis. This was done by repeatedly refining the nodal spacing until insignificant
changes in simulated water balance parameters were achieved. The nodal spacing
between the nodes located near the upper and lower boundaries, as well as near the
interface between layers, was relatively small (~1 mm).
-7

A maximum time step of 0.1 hr and a minimum time step of 10 hr were used for
the simulations. This was necessary to accurately evaluate the extreme drying and
wetting conditions typically encountered at the ground surface. At any given time step,
the maximum allowable mass balance error for the whole profile was set at 10

-5

cm. For

all numerical analyses, mass balance errors of less than 1 mm/yr were achieved.

FIELD DATA

Soil Water Storage
Figure 2-6 shows the soil water storage of the test section estimated by integrating the
water contents measured by the three nests of water content sensors located within the
lysimeter and the actual caps located upslope and downslope of the lysimeter (see
69

Figure 2-1). While the soil water storage of the lysimeter and the actual caps are
relatively close, there are these subtle differences: (1) drop in soil water storage of the
lysimeter during winter 2010; (2) sharp but small changes in soil water storage observed
for lysimeter which are absent in the actual cap soil water storages; and (3) greater and
more rapid decrease in the soil water storage from Aug. 2010 and onwards observed for
the lysimeter.

Soil
Temperature

65

8
Irrigation (only lysimeter)
(20.8 cm)

Actual Cap
(Top and
Bottom Nest)

60

6

Actual Cap
(Bottom Nest) 4

55
50
45

2
o

0 C

0
Lysimeter

Lysimeter

-2

Actual Cap
(Top Nest)

40
35
Soil Water Storage
30
09/Nov

10/Jan

10/Mar

Lysimeter vs. Actual Cap
10/May

10/Jul

10/Sep

-4
-6

Measured Soil Temperature (°C)

Measured Soil Water Storage (cm)

70

-8
10/Nov

Figure 2-6: Measured soil water storages and surficial temperatures for the lysimeter and
actual caps.

Figure 2-7 shows the hourly soil water storages of the lysimeter plotted against
the soil water storages of the upper and lower nests representing the actual caps. The data
70

points shown are for the period from Nov. 2009 to June 2010, which corresponds to the
period before the lysimeter section was subjected to 20.8 cm irrigation which the actual
caps did not receive. The 1:1 line shows the region where the soil water storage values
are the same for the actual caps and the lysimeter. Points above the 1:1 line correspond to
greater soil water storage for the cap compared to the lysimeter and vice versa. Figure 2-7
shows that, the soil water storage of the actual caps is about the same as the soil water
storage of the lysimeter.

60

Measured Soil Water Storage
for Actual Cap (cm)

Top Nest
55

Bottom Nest
Bottom Nest
(Measured)

50

45
Top Nest
(Measured)

40

35

Measured Soil Water Storage

1:1 Line
30
30

35

40

45

50

55

60

Measured Soil Water Storage
for Lysimeter (cm)
Figure 2-7: Correlation between measured soil water storage for an actual cap and its
corresponding lysimeter.

71

Water Contents
The water contents measured at various depths within the lysimeter and the actual cap
(upper nest) are presented in Figure 2-8. The water content profiles on 1 Feb. 2010 and
1 Oct. 2010, being typical for the seasons, are presented in Figure 2-9. The water content
profiles of the lysimeter (Figure 2-9) show that the hydraulic gradient in the lowermost
portion is downward throughout the monitoring period. This observation is consistent
with the field observation that the lysimeter collected low magnitude percolation
throughout the year (Figure 2-10). In addition, the water content profile of the lysimeter
does not show capillary barrier effect due to the presence of gravel layer used for
collecting percolation. When and if capillary barrier effect occurs, the water content of
the lowest point in the upper finer-grained soil layer needs to be the highest when the
percolation breakthrough occurs. Hence, while the cap in the lysimeter section is
underlain by pea gravel, a coarser-grained soil, capillary barrier effect is non-existent.
This observation is consistent with the finding by Mijares and Khire (2010) that when the
cover soils have hydraulic conductivities less than 10

-5

cm/s, the capillary barrier effect,

even if may occur, would have insignificant effect on percolation. The cover soils of the
-6

lysimeter have hydraulic conductivity of about 4 x 10 cm/s.
Figure 2-9 also shows that the relative magnitudes of water contents in the actual
cap are slightly but subtly different when compared to the water contents within the
lysimeter section. In the actual cap, the water contents of the lowermost portion of the
cap (cap and waste interface) are slightly greater than the water contents at locations
above the interface. Thus, the hydraulic gradient in the actual cap at the cap and waste

72

Irrigation
(20.8 cm)

0.40

0.35

BGS (cm)

(Lysimeter; Middle Nest)

135

3

3

Vol. Water Content (cm /cm )

Volumetric Water Contents

105

0.30

165

Fig. 9a
0.25

45

0.20

75

0.15

15

(a)
0.10
09/Nov

Fig. 9b

10/Jan

10/Mar

10/May

10/Jul

10/Sep

10/Nov

0.40
BGS (cm)

0.35

(Actual Cap; Top Nest)

105
165

3

3

Vol. Water Content (cm /cm )

Volumetric Water Contents

0.30

135
75
45

0.25

0.20
Fig. 9b
0.15

(b)
0.10
09/Nov

Fig. 9a

10/Jan

10/Mar

15
10/May

10/Jul

10/Sep

10/Nov

Figure 2-8: Measured volumetric water contents for the lysimeter (a) and actual cap (b).
73

Depth Below Ground Surface (cm)

0

(a)

Actual Cap:
50
Lysimeter

Bottom Nest

100

Top Nest
Flux

150

Flux

Cap
MSW

200
250
300
350
400
0.05

Water Content Profile
Feb. 1, 2010
0.10

0.15

0.20

0.25

0.30

0.35
3

0.40

0.45

0.50

3

Vol. Water Content (cm /cm )

Depth Below Ground Surface (cm)

0
Actual Cap:
Bottom Nest
Top Nest

50
Lysimeter

(b)

100
Flux

150
200

Cap
MSW

250
300
350
400
0.05

Water Content Profile
Oct. 1, 2010
0.10

0.15

0.20

0.25

0.30

0.35
3

0.40

0.45

0.50

3

Vol. Water Content (cm /cm )

Figure 2-9: Measured water content profiles for the lysimeter and actual caps on
1 Feb. (a) and 1 Oct. 2010 (b).
74

3

Measured or Simulated
Cumulative Percolation (cm)

Lysimeter vs. Actual Cap
2

Measured

1

(Lysimeter)

0

UNSAT-H
(Lysimeter)

-1

UNSAT-H
(Actual Cap)
-2

-3
09/Nov

10/Jan

10/Mar

10/May

10/Jul

10/Sep

10/Nov

Figure 2-10: Measured and simulated cumulative percolation for the lysimeter and the
actual cap.

interface is vertically upwards which would result in negative percolation into the waste.
In addition, the water contents in the waste are lowest closer to the cap and waste
interface and they increase deeper towards the leachate collection system. This trend in
the water content profile indicates that the degree of saturation of the waste is expected to
be higher near the leachate collection system, which is consistent with the field
observations. However, below the cap, the waste has relatively low degree of saturation
during various times of the monitoring period indicating that the magnitude of flux across
the cap/waste interface would be relatively small.

75

NUMERICAL MODELING RESULTS
UNSAT-H simulations were conducted to predict the percolation and soil water storage
for the test section for the period starting from November 2009 to October 2010. During
this period, the site received 71.4 cm of precipitation. In addition, the lysimeter section
was subjected to 20.8 cm of precipitation over a 48-hr period. During the monitoring
period, the lateral flow collected from the topsoil layer (Figure 2-1) was negligible
(~0.5 cm) and occurred only after relatively few precipitation events.

Soil Water Storage
Figure 2-11 shows the measured and simulated soil water storage for the lysimeter. The
numerical model was able to capture the seasonal trends in the measured soil water
storage. However, it did not predict the measured soil water storage accurately.
Generally, the simulated soil storage is lower than the measured soil water storage which
is also reported by Ogorzalek et al. 2008. During Winter 2010, UNSAT-H overestimated
soil water storage because the model does not account the effect of frozen ground surface
(Khire et al. 1999). In the field when the ground surface is frozen (Figure 2-6),
subsequent infiltration is impeded whereas UNSAT-H allowed precipitation to infiltrate
during this period causing the increase in soil moisture. Figure 2-6 shows that the ground
surface of the lysimeter was frozen during Winter 2010 while it did not freeze for the
actual cap. The heat flux from the waste in the landfill may have maintained slightly
higher temperature for the actual cap compared to the lysimeter. The simulated soil water
storage also showed smaller seasonal variation relative to the measured soil water storage
which is similar to the findings of Fayer et al. (1992) and Khire et al. (1994). Fayer et al.

76

(1992) pointed out that the discrepancy is due to the overestimation of evaporation during
winter and the underestimation of evaporation during the remainder of the year by
UNSAT-H.

70

Measured or Simulated
Soil Water Storage (cm)

65
60
55

Measured
(Lysimeter)

50
45
40

UNSAT-H
35
30
09/Nov

(Lysimeter)

10/Jan

10/Mar

10/May

10/Jul

10/Sep

10/Nov

Figure 2-11: Measured and simulated soil water storage for the lysimeter.

Figure 2-12 shows the time series plot of comparison of simulated soil water
storages for the lysimeter and the actual cap (underlain by MSW). Figure 2-12 shows that
the soil water storage for the actual cap is always slightly greater than the soil water
storage for the corresponding lysimeter except during sharp wetting events when both
storages equate for a brief period of time. Measured soil water storage of the actual caps
77

is about the same as that for the lysimeter except when the lysimeter was subjected to
irrigation wherein the lysimeter storage exceeded the actual caps and after Aug. 2010
when the soil water storage of the lysimeter steadily dropped and stayed below the
storage of the actual caps (Figure 2-6).

70

Simulated
Soil Water Storage (cm)

65

Lysimeter vs. Actual Cap

60
55

UNSAT-H
(Actual Cap)

50
45
40

UNSAT-H
(Lysimeter)

35
30
09/Nov

10/Jan

10/Mar

10/May

10/Jul

10/Sep

10/Nov

Figure 2-12: Simulated soil water storage for the lysimeter and the actual cap.

Percolation
Figure 2-10 shows the measured and simulated cumulative percolation for the lysimeter.
During the one year monitoring period, the lysimeter received about 0.7 cm of
percolation from about 71.4 cm of precipitation and 20.8 cm of irrigation carried out in
78

July 2010. The cumulative percolation predicted by UNSAT-H is relatively close to the
measured percolation. There is a slight difference in the rate of change of percolation
which occurred around Aug. 2010 in the field while the model simulated it in July 2010.
UNSAT-H simulated volumetric water contents in test section are relatively close to the
field water contents (Figure 2-8). While plants were simulated in the model, the amount
of transpiration simulated by the model was negligible. It is due to the relatively short
growing season in Detroit (~90 days) and less than 30 cm deep rooting depth observed in
the field.
Percolation predicted by UNSAT-H for the actual caps which included the
underlying waste layer with measured hydraulic properties of the waste input to the
model is presented in Figure 2-10. The cumulative percolation predicted by the model
was determined from the interlayer flux between the clay cover and the MSW interface.
A positive value corresponds to a downward flux across the interface while a negative
value corresponds to an upward flux. Figure 2-10 shows that the percolation for the
actual cap is negative till about late June 2010. Negative flux indicates removal of water
from the waste due to capillary pull from the overlying cap. In June 2010, the actual cap
which was simulated using UNSAT-H was subjected to the 20.8 cm irrigation which the
lysimeter was subjected to in the field to compare the lysimeter and actual cap under the
same conditions. Figure 2-10 shows that the irrigation resulted in simulated percolation
for the actual cap that was positive (downward). However, the net percolation for the
actual cap simulated by UNSAT-H is about zero. It is consistent with the direction of the
hydraulic gradient observed at the cap/waste interface which was mostly upward
(Figure 2-9). This observation is also consistent with the simulated soil water storage

79

values that are presented in Figure 2-12. Figures 2-8 and 2-12 show that the simulated
soil water storage for the lysimeter was lower than the actual cap and hence the simulated
percolation for the lysimeter was greater than simulated percolation for the actual cap.
When Kazimoglu et al. (2005, 2006) hydraulic properties (Figure 2-4) were used
to simulate the waste layer of the actual cap, the net cumulative percolation was negative
(~ -2 cm) throughout the modeling period. Thus, the modeling results confirm that the
percolation for the actual cap was less than the lysimeter. The results also demonstrate
that even though the interlayer flux between the clay cover and the underlying MSW
cannot be physically measured in the field, relative soil water storages can be used to
estimate the relative magnitude of percolation for an actual cap.

SUMMARY AND CONCLUSIONS
Instrumented field-scale test section of a compacted native glacial till was constructed at
a landfill located in Detroit, Michigan to compare the water balance of actual cap versus
the lysimeter. Soil water contents, matric suctions, gas pressures, soil temperatures, and
percolation were monitored using sensors for more than a year. The water balance model
UNSAT-H was used to simulate and evaluate the differences in the hydrologic
performance of an actual cap versus the corresponding lysimeter.
While the soil water storage of the lysimeter and the actual caps only had slight
but subtle differences, the soil water content profiles indicated vertically downward
hydraulic gradient for the lysimeter and primarily vertically upward hydraulic gradient
for the actual cap throughout the monitoring period. The model predicted percolation and
soil water storages were relatively similar to the field data. The model, which was

80

validated using the field data, predicted that the soil water storage for the actual cap
would be slightly greater than that for the lysimeter and the model indicated negative as
well as positive percolation with a net percolation close to zero for the actual cap.
Thus, the field data coupled with numerical modeling indicates that while
percolation measured by a lysimeter for compacted clay soils which have relatively low
hydraulic conductivity is greater than the percolation estimated for an actual cap which is
placed on the waste, water balance of a lysimeter is relatively close to that of an actual
cap. Hence, field-scale lysimeters, when designed and instrumented properly could be
and should be used to assess the performance of an actual cap.

81

APPENDIX

82

APPENDIX
The numerical study presented in this paper was extended to model the field data
obtained from the uncompacted test section. The uncompacted test section is identical to
the compacted test section (Figure 2-1) except that the native clay that was used to build
the storage layer was placed by a track dozer without any compaction effort (Figure
2-13). The reasons one of the test sections was not compacted are: (1) to simulate a
conservative scenario for higher overall hydraulic conductivity of the storage layer of the
cap, potentially less increase or no increase in the overall hydraulic conductivity of the
clay due to root penetration and desiccation; and (2) to enhance ET from the test sections

S = 60% 80%
Modified
Proctor

3

Dry Unit Weight, γ (kN/m )
d

20

100%

Native Glacial Till (CL)
Gs = 2.72
-6

K ~ 10 cm/s
(Field Infiltrometer)

19

Higher Water Content due
to Rainfall after compaction
but before measurement

Compacted
North Test
Section

18

Standard
Proctor

17

-7

K ~ 10 cm/s
(Lab: Flexible Wall Permeameter)
-4

K ~ 10 cm/s
(Field Infiltrometer)

Uncompacted
Test Sections

16
5

10

15

20

Water Content, ω (%)
Figure 2-13: Field water contents and unit weights for the uncompacted test section.
83

25

by providing more void space for the plant roots to reach greater depths quickly in the
test sections.

Material Properties
For the uncompacted test section, UNSAT-H (Fayer 2000) and Vadose/W (Geo-Slope
2007) simulations have been conducted. Table 2-3 presents the saturated and unsaturated
hydraulic properties of the soils, as described in terms of the Haverkamp et al. (1977)
fitting parameters, for the uncompacted test section. Field tracer tests and physical
observations indicated that the uncompacted test section contained relatively large clods
(15 to 60 cm in diameter) and relatively large inter-clod voids. Such field structure
cannot be simulated in the lab with the conventional techniques. Hence, in order to
predict the water balance of the uncompacted test section, the soil water characteristic
curves and unsaturated hydraulic conductivity functions were estimated from the field

Table 2-3: Saturated and unsaturated hydraulic properties of the cap components for the
uncompacted test section.

Soil

θr

θs
3

3

3

3

(cm /cm ) (cm /cm )

β

Ks

(1/cm)

α

(cm/s)

Topsoil

0.35

0.10

30

0.87

1.6 x 10

Storage
Layer

0.35

0.00

3000

0.6

1.3 x 10

Landfilled
Waste

0.58

0.14

18.74

0.972

1.0 x 10

84

Β

Α

(1/cm)

-3

120

1.14

-4

620

1.21

-3

6

1.88 x 10

5.246

recorded water contents and water potentials. Figure 2-14(a) shows the data points from
the field measurements and the fitted soil water characteristic curves. Figure 2-14(b)
shows the data points obtained using instantaneous profile method (Meerdink et al. 1996)
and the fitted unsaturated hydraulic conductivity function. Haverkamp et al. (1977) fitting
equations were used because the soil water characteristic curves and unsaturated
hydraulic conductivity functions are independently determined and described.
Furthermore, Kazimoglu et al. (2005, 2006) hydraulic properties (Figure 2-4 and 2-14)
were used to simulate the waste layer of the actual cap.
For UNSAT-H, the saturated and unsaturated hydraulic properties tabulated in
Table 2-3 were used as input for the material properties in the simulations. For
Vadose/W, apart from the hydraulic properties listed in Table 2-3, material thermal
properties are also required by the program. In contrast with UNSAT-H where isothermal
water flow can be specifically chosen, Vadose/W couples water and heat flow. Hence,
Vadose/W requires these thermal properties as input: (1) volumetric specific heat
function; and (2) thermal conductivity function. The volumetric specific heat functions
were estimated using De Vries (1963) estimation method. A built-in Vadose/W tool
estimates the function from the specified water retention curves. Soil mineral specific
heat values of 0.8 and 1.674 kJ/g/°C were assumed for the topsoil and storage clay layer,
respectively. A mass specific heat value of 0.71 kJ/g/°C was assumed for the landfilled
waste. The thermal conductivity functions for each material were estimated using the
built-in Vadose/W estimation tool. The thermal conductivity – volumetric water content
relations were predicted using the Johansen (1975) estimation method with assumed soil

85

6

10

5

10

4

10

3

10

2

10

1

10

Matric Suction (cm)

10

0

10

Clay
(Field Measured)

Topsoil
(Field Measured)

Topsoil

MSW
(Kazimoglu et al. 2006)

-1

0

10
Hydraulic Conductivity (cm/s)

(a)
Clay

0.1

0.2
0.3
0.4
Volumetric Water Content

0.5

0.6

0

10

-2

10

-4

10

-8

(b)

-6

10

Topsoil; Field Measured
(Instantaneous Profile Method)
Clay

Topsoil

10

-12

10

Clay; Field Measured
(Instantaneous Profile
Method)

-10

10

MSW Measured
(Kazimoglu et al. 2006)

-14

10

MSW

-1

10

0

10

1

10

2

10

3

10

4

10

5

10

6

Matric Suction (cm)
Figure 2-14: Measured soil water characteristic curves (a); and predicted hydraulic
conductivity function (b) for the cap components for uncompacted test section.
86

mineral thermal conductivity of 280, 130, and 216 kJ/day/m/°C for the topsoil, clay
cover, and landfilled waste, respectively. These typical values of thermal properties were
obtained from the Vadose/W database (Geo-Slope 2007).
For Vadose/W simulations, the model requires daily values for maximum and
minimum air temperature, maximum and minimum relative humidity, average wind
speed, total precipitation, start and end times of precipitation, and total solar radiation or
potential evapotranspiration. A sinusoidal climate distribution pattern was selected to
distribute daily values of air temperature, relative humidity, solar radiation, and
precipitation. The air temperature and relative humidity was assumed to be at their
minimum values at sunrise and at their maximum values at 12:00 noon. The solar
radiation was assumed to be zero before sunrise and after sunset and reached its peak
value at 12:00 noon. The latitude of the location of the field test section (42.38° North)
was used to approximate the sunrise and sunset times. Wind speed was applied as a
constant value throughout the day. The daily precipitation was assumed to follow a
sinusoidal distribution over the specified start and end times with its peak value occurring
at the midpoint of the specified time interval.
Spatial discretization of the model domain was optimized by conducting
sensitivity analysis. This was done by repeatedly refining the nodal spacing until
insignificant changes in simulated water balance parameters were achieved. The nodal
spacing between the nodes located near the upper and lower boundaries, as well as near
the interface between layers, was relatively small (1 mm). Figure 2-15 shows the

87

Climate
Boundary

(a)

Climate
Boundary

Topsoil

0.3 m

Topsoil

Storage
Layer

1.5 m

Storage
Layer

~ 3.0 m

(b)

Waste
Layer

Unit Gradient
Boundary

Unit Gradient
Boundary

Figure 2-15: Typical mesh used for modeling in Vadose/W for: a lysimeter only (a); and
an actual earthen cap with underlying waste (b).
88

snapshots of the model generated in Vadose/W for actual cap and its corresponding
lysimeter simulations.

Uncompacted Test Section Simulations
UNSAT-H and Vadose/W simulations were conducted to predict the percolation and soil
water storage for the uncompacted test section for the period from June 2008 to March
2009. During this period, the site received 68.5 cm of precipitation. Figure 2-16 shows
that the cumulative percolation measured in the field from the lysimeter installed in the

Uncompacted Test Section
Measured or Simulated
Cumulative Percolation (cm)

20

15

Vadose/W
10

Measured
5

UNSAT-H
Actual Cap
0
08/Jun

(Vadose/W)

Lysimeter

08/Aug

08/Oct

08/Dec

09/Feb

09/Apr

Figure 2-16: Field measured and numerically simulated cumulative percolation for the
uncompacted test section.
89

middle of the uncompacted test section is about 16.2 cm. Since the clay cover was
constructed without compaction, tracer tests and physical observations showed relatively
large inter-clod voids in the clay which resulted to preferential flow for water. Hence,
percolation from the uncompacted test section was significantly higher than that from the
compacted test section. The percolation was about 24% of the applied precipitation. The
preferential flow of water, also known as a macropore flow, is evident in Figure 2-16 as
indicated by the sharp increases in the cumulative percolation plot. Figure 2-16 also
shows the simulated cumulative percolation for the lysimeter using UNSAT-H and
Vadose/W. UNSAT-H under predicted while Vadose/W over predicted the percolation.
UNSAT-H failed to capture the sharp percolation pulses that occurred in the field.
Vadose/W performed better since it was able to predict the onsets of percolation.
However, the simulated percolation overestimated the field measured percolation. The
simulated sharp increases in percolation also occurred earlier than those observed in the
field.
Vadose/W was also used to estimate the percolation for the actual cap with
underlying MSW located within the uncompacted test section. The resulting percolation
across the interface between the soil cover and the underlying waste was relatively small.
Upward flux of water (negative percolation) can be observed from the cumulative
percolation plot. This is consistent with the data presented in Figures 2-17 and 2-18. The
volumetric water contents measured at various depths within the lysimeter and the actual
cap (upper nest) for the uncompacted test section are shown in Figure 2-17. The
corresponding time series plot of the hydraulic gradient across the bottommost two
sensors is shown in Figure 2-18. For actual cap, it can be seen that the bottommost two

90

0.45

BGS
(cm)

3

Vol. Water Content (cm /cm )

0.40

Volumetric Water Contents
(Lysimeter; Middle Nest)

3

0.35

165

0.30
105
0.25

30

75

0.20
15

0.15
0.10

Uncompacted
Test Section

(a)
0.05
08/Jun

08/Aug

0.40

08/Oct

08/Dec

BGS (cm)

0.35

165

3

3

Vol. Water Content (cm /cm )

135

09/Feb

09/Apr

Uncompacted
Test Section

120
0.30
0.25

75
30

0.20
0.15

15

0.10

Volumetric Water Contents
(Actual Cap; Top Nest)

(b)
0.05
08/Jun

08/Aug

08/Oct

08/Dec

09/Feb

09/Apr

Figure 2-17: Measured volumetric water contents for the lysimeter (a) and actual cap (b).
91

3000

Hydraulic Gradient

2500

Uncompacted Test Section

2000

1500

1000

Lysimeter

500

Actual
Cap

Upward
Flux

0
08/Jun

08/Aug

08/Oct

08/Dec

09/Feb

09/Apr

Figure 2-18: Calculated hydraulic gradient across the bottommost two sensors for the
lysimeter and actual cap in the uncompacted test section.

water content readings at a given time indicate upward flux of moisture. For the
lysimeter, similar observation can be seen and the resulting downward percolation
observed is therefore indicative of macropore flow across inter-clod voids in the
uncompacted clay test section.
Figure 2-19 shows the field measured soil water storage for the lysimeter installed
in the middle of the uncompacted test section. Figure 2-19 also shows the simulated soil
water storage using UNSAT-H and Vadose/W. Both numerical models were able to
capture the fluctuations observed in the field. Neither models predicted the measured soil

92

water storage accurately. The simulated soil water storage for an actual cap with
underlying MSW is generally higher compared to the simulated soil water storage for the
corresponding lysimeter. This corresponds to lower percolation for the actual cap as
illustrated in Figure 2-16.

65

65

Actual Cap

(Vadose/W)

60

Lysimeter

55

Measured

55

50

50

45

45

40

40

Vadose/W

35

35

Numerically Simulated
Soil Water Storage (cm)

Field Measured
Soil Water Storage (cm)

60

Actual Cap

(Measured)

UNSAT-H
30

30

Uncompacted Test Section
25
08/Jun

25
08/Aug

08/Oct

08/Dec

09/Feb

09/Apr

Figure 2-19: Field measured and numerically simulated soil water storage for the
uncompacted test section.

Similar observation can be seen from the field measured soil water storage for an
actual cap versus a lysimeter for the uncompacted test section. In contrast with the
compacted test section wherein the soil water storage values for the lysimeter and the
actual cap are close, Figure 2-20 shows that, for the uncompacted test section, the
lysimeter has lower soil water storage than the actual cap. This is consistent with the
93

findings of Mijares et al. (2010). In their study, numerical simulations using Vadose/W
were carried out for a range of hydraulic properties of the overlying soil cover to
determine its effect on the soil water storage response of a lysimeter versus an actual cap.

Soil Water Storage for Actual Cap (cm)

65

60

55

50

Top Nest

45

Uncompacted Test Section
(Field Measured Soil Water Storage)

1:1 Line
40
40

45

50

55

60

65

Soil Water Storage for Lysimeter (cm)
Figure 2-20: Correlation between measured soil water storage for actual cap versus
lysimeter for the uncompacted test section.

Figure 2-21 shows that as the saturated hydraulic conductivity of the soil cover increases,
the soil water storage for a lysimeter greatly underestimates the soil water storage for an
actual cap. This is because the underlying MSW acts as a capillary break due to its water
retention curve that emulates a coarser soil. Mijares et al. (2010) further found out that
94

capillary barrier effect is significant only for a soil cover with saturated hydraulic
-5

conductivity greater than 10

cm/s. A high saturated hydraulic conductivity is evident

for the uncompacted test section and therefore the measured soil water storage for the
lysimeter is generally lower than the measured soil water storage for the actual cap of the
uncompacted test section.

70
K

(cm/s)
10

65

SWS of Actual Cap (cm)

SL

-7

10

55

K

-4

-4

SL

SL

-5

10

60

-5

= 10 cm/s

-6

10

K

K

= 10 cm/s

-7 to -6

SL

= 10

cm/s

50

45
SWS Actual Cap = SWS Lysimeter
40
40

45

50

55

60

65

70

SWS of Lysimeter (cm)
Figure 2-21: Correlation between the simulated soil water storage for an actual cap versus
its corresponding lysimeter with varying hydraulic properties of soil cover (Mijares et al.
2010).

95

The simulation of the field response of the uncompacted test section showed that
percolation obtained from the lysimeter was significantly greater than the estimated
percolation of the actual cap (i.e., flux across the interface between the soil cover and
underlying waste). Consequently, the simulated soil water storage of the actual cap for
the uncompacted test section was generally higher compared to the simulated soil water
storage of its equivalent lysimeter. This was consistent with the field measured soil water
storages of both lysimeter and actual cap underlain by landfilled waste.

96

REFERENCES

97

REFERENCES
Abichou, T., and Musagasa, J. (2008). “ET Covers: Construction and Tree Development
Inside and Outside of Lysimeters,” Proceedings, GeoCongress 2008, GSP No. 177,
Geotechnics of Waste Management and Remediation, ASCE, Reston, VA: 72-79.
Albright, W., Benson, C., Gee, G., Roesler, A., Abichou, T., Apiwantragoon, P.,
Lyles, B., and Rock, S. (2004). “Field Water Balance of Landfill Final Covers,”
Journal of Environmental Quality, 33 (6): 2317-2332.
Benson, C., Bohnhoff, G., Ogorzalek, A., Shackelford, C., Apiwantragoon, P., and
Albright, W. (2005). “Field Data and Model Predictions for an Alternative Cover,”
Waste Containment and Remediation, GSP No. 142, ASCE, Reston, VA: 1-12.
Bohnhoff, G., Ogorzalek, A., Benson, C., Shackelford, C., and Apiwantragoon, P. (2009).
“Field Data and Water-Balance Predictions for a Monolithic Cover in a Semiarid
Climate,” Journal of Geotechnical and Geoenvironmental Engineering, 135 (3):
333-348.
Breitmeyer, R., Benson, C., Edil, T., and Barlaz, M. (2010). “Hydrologic Properties of
Municipal Solid Waste,” Research Project Poster, GeoEngineering Program,
University of Wisconsin – Madison, Madison, WI.
De Vries, D. (1963). “Thermal Properties of Soils,” Physics of Plant Environment, NorthHolland Publishing Company, Amsterdam, The Netherlands: 210-235.
Fayer, M., Rockhold, M., and Campbell, M. (1992). “Hydraulic Modeling of Protective
Barriers: Comparison of Field Data and Simulation Results,” Soil Science Society of
America Journal, 56: 690-700.
Fayer, M. (2000). “UNSAT-H Version 3.0: Unsaturated Soil Water and Heat Flow Model
– Theory, User Manual, and Examples,” PNNL-13249, Pacific Northwest
Laboratories, Richland, Washington.
Geo-Slope. (2007). “Vadose Zone Modeling with Vadose/W 2007: An Engineering
Methodology,” GEO-SLOPE International Ltd., Alberta, Canada.
Guyonnet, D., Amraoui, N., and Kara, R. (2000). “Analysis of Transient Data from
Infiltrometer Tests in Fine-grained Soils,” Ground Water, 38 (3): 396-402.
Haverkamp, R., Valcin, M., Touma, J., Wierenga, P., and Vauchaud, G. (1977). “A
Comparison of Numerical Simulation Models for One-dimensional Infiltration,”
Soil Science Society of America Journal, 41: 285-294.
Johansen, O. (1975). “Thermal Conductivity of Soils,” Ph.D. Thesis, University of
Trondheim, Norway, CRREL Draft English Translation 637, US Army Corps of
Engineers, Cold Regions Research and Engineering Laboratory, Hanover, NH.

98

Kazimoglu, Y., McDougall, J., and Pyrah, I. (2005). “Moisture Retention and Movement
in Landfilled Waste,” Proceedings, GeoProb 2005: International Conference on
Problematic Soils, Famagusta, Northern Cyprus, May 2005.
Kazimoglu, Y., McDougall, J., and Pyrah, I. (2006). “Unsaturated Hydraulic
Conductivity of Landfilled Waste,” Proceedings, Unsaturated Soils 2006, GSP No.
147, ASCE, Reston, VA: 1525-1534.
Khire, M., and Mijares, R. (2008). “Influence of the Waste Layer on Percolation
Estimates for Earthen Caps Located in a Sub-humid Climate,” Proceedings,
GeoCongress 2008, GSP No. 177, Geotechnics of Waste Management and
Remediation, ASCE, Reston, VA: 88-95.
Khire, M., Benson, C., and Bosscher, P. (1994). “Final Cover Hydrologic Evaluation:
Phase III,” Environmental Geotechnics Report 94-4, University of Wisconsin –
Madison, Madison, WI.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering,
123 (8): 744-754.
Khire, M., Benson, C., and Bosscher, P. (1999). “Field Data from a Capillary Barrier and
Model Predictions with UNSAT-H,” Journal of Geotechnical and
Geoenvironmental Engineering, 125: 518–528.
Khire, M., Benson, C., and Bosscher, P. (2000). “Capillary Barriers: Design Variables
and Water Balance.” Journal of Geotechnical and Geoenvironmental Engineering,
126 (8): 695-708.
Meerdink, J., Benson, C., and Khire, M. (1996). “Unsaturated Hydraulic Conductivity of
Two Compacted Barrier Soils,” Journal of Geotechnical and Geoenvironmental
Engineering, 122 (7): 565-576.
Mijares, R., and Khire, M. (2010). “Evaluation of Geosynthetic Capillary Break in
Earthen Cover Lysimeters,” Journal of Geotechnical and Geoenvironmental
Engineering, in review.
Mijares, R., Khire, M., and Johnson, T. (2010). “Lysimeters versus Actual Earthen Caps:
Numerical Assessment of Soil Water Storage,” Proceedings, GeoFlorida 2010,
GSP No. 199, Advances in Analysis, Modeling and Design, ASCE, Reston, VA:
2849-2858.
Mukherjee, M. (2008). “Instrumented Permeable Blankets for Estimating Subsurface
Hydraulic Conductivity and Confirming Numerical Models Used for Subsurface
Liquid Injection,” Ph.D. Dissertation, Michigan State University, East Lansing,
Michigan, 278 p.

99

Ogorzalek, A., Bohnhoff, G., Shackelford, C., Benson, C., and Apiwantragoon, P. (2008).
“Comparison of Field Data and Water-balance Predictions for a Capillary Barrier
Cover,” Journal of Geotechnical and Geoenvironmental Engineering, 134 (4):
470-486.
Passioura, J. (1977). “Determining Soil Water Diffusivities from One-step Outflow
Experiments,” Australian Journal of Soil Research, 15 (1): 1-8.
Scanlon, B., and Milly, P. (1994). “Water and Heat Fluxes in Desert Soils 2: Numerical
Simulations,” Water Resources Research, 30: 721-733.
Scanlon, B., Reedy, R., Keese, K., and Dwyer, S. (2005). “Evaluation of
Evapotranspirative Covers for Waste Containment in Arid and Semiarid Regions in
the Southwestern USA,” Vadose Zone Journal, 4: 55-71.
Stoltz, G., and Gourc, J. (2007). “Influence of Compressibility of Domestic Waste on
Fluid Conductivity,” Proceedings, 18th Congres Francais de Mecanique, Grenoble,
France.
van Genuchten, M. (1980). “A Closed-form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils,” Soil Science Society of America Journal, 44:
892-898.

100

PAPER NO. 3: EFFECT OF UNDERLYING WASTE LAYER ON
SOIL WATER STORAGE AND PERCOLATION ESTIMATES FOR
LANDFILL EARTHEN CAPS

ABSTRACT
Lysimeters are commonly used for field-scale assessment of water balance of earthen
caps, commonly referred to as alternative or evapotranspirative (ET) caps. While
lysimeters can measure percolation through a cap, the lower hydraulic boundary of a
lysimeter is not the same as an actual ET cap. In this study, numerical simulations of
water balance of lysimeters and ET caps were carried out using UNSAT-H for a range of
hydraulic properties of the cover soils and waste for semi-arid and humid climates. The
numerical results show that due to the presence of waste underlying the cap, the soil
water storage of an ET cap is generally greater than its corresponding lysimeter. This
greater water storage capacity in an actual ET cap results in lower percolation as
compared to its corresponding lysimeter. The numerical results also suggest that thicker
cover soils would consistently have much lower lysimeter percolation as well as actual
cap percolation. Furthermore, wetter climate, with high precipitation to potential
evapotranspiration ratio, would generally have smaller difference in the soil water storage
and percolation for an actual ET cap versus its corresponding lysimeter.

INTRODUCTION
When landfill reaches its capacity, a final capping system is installed. In the U.S., the
minimum required design is a conventional cap which may consists of, among other
components, a geomembrane liner and/or a compacted clay barrier layer [Resource

101

Conservation and Recovery Act (RCRA), Subtitle D, USEPA]. Capital construction cost
of the conventional cap is usually greater than alternative earthen caps. RCRA includes a
provision that allows alternative final cap design as long as it is capable of achieving an
equivalent reduction in infiltration and protection from erosion that prescriptive caps may
provide.
Several types of alternative caps, also known as earthen or evapotranspirative
(ET) caps, have been considered for landfills primarily located in areas with arid and
semi-arid climates (Khire et al. 1999; Albright et al. 2004; Scanlon et al. 2005). The best
known method for assessing the performance of these alternative caps involves the
installation of lysimeters at the proposed site to directly measure the percolation through
the proposed cap. Numerical studies on lysimeters generally employ simulations that
neglect the effect of the underlying waste (Khire et al. 2000; Benson et al. 2005) because
percolation is collected through a drainage layer constructed above a geomembrane.
While the geomembrane allows collection of infiltration through the cap, it prevents
upward migration of moisture from the waste under evapotranspirative gradients. When
an actual earthen cap is constructed, the geomembrane layer used for a lysimeter is not
placed.

LYSIMETER VERSUS ACTUAL ET CAP
ET covers have been commonly used for landfills located in arid and semi-arid climates
in lieu of prescriptive caps which require the use of geomembranes. Key advantages of
ET caps include: (1) lower construction cost compared to prescriptive caps which contain
a relatively expensive geomembrane layer (Hauser et al. 2001); and (2) greater soil depth

102

available for establishment of deeper roots for the vegetation which may reduce longterm erosion compared to the prescriptive caps. These benefits may allow additional
options for end use of the landfill.
Approval of the use of an ET cover in lieu of a prescriptive cover typically
requires site-specific demonstration of equivalency. Field demonstration of proposed ET
cover usually entails the installation of lysimeter to directly measure the percolation
through the landfill cap. These lysimeters have a relatively impermeable geomembrane at
the bottom boundary to facilitate the collection of drainage in a drainage layer located
immediately above the geomembrane layer (Khire et al. 1997; Benson et al. 2001).
The water balance of a lysimeter which includes percolation through the cap is a
function of many site-specific and design-specific parameters including the boundary
conditions. While the upper surface boundaries of a lysimeter cap and an actual ET cap
are identical, the lower boundaries are significantly different. Lysimeters contain an
impermeable (zero flux) lower boundary (Abichou et al 2006; Khire and Mijares 2008).
This bottom boundary is hydraulically permeable in an actual ET cap. The lower zeroflux boundary in a lysimeter prevents the upward flux of liquid and vapor from the waste
mass or subgrade layer located below the cap. This bottom boundary in a lysimeter may
also restrict the heat flux from the waste mass present below the cap which may influence
the actual percolation rate. Several studies have identified this concern (Benson et al
2001; Abichou and Musagasa 2008; Khire and Mijares 2008).
Khire and Mijares (2008) carried out numerical water balance simulations of ET
caps and corresponding lysimeters. Khire and Mijares (2008) have presented the ratio of
average annual percolation for an actual ET cap and average annual percolation for the

103

corresponding lysimeter for a range of hydraulic properties of the cap components. It has
been observed that cumulative percolation for lysimeters would be typically greater than
the percolation at the bottom of corresponding ET cap. Thus, percolation measured by
lysimeter is conservative. Khire and Mijares (2008) showed that the percolation measured
by lysimeters can be up to an order of magnitude greater than the actual cap depending
upon the saturated and unsaturated hydraulic properties of the soils and underlying waste
layer.
Hardt (2008) carried out numerical evaluation of percolation through ET caps and
the corresponding lysimeters using the dual permeability option in HYDRUS (beta
version) (Simunek et al 2008; Simunek and van Genuchten 2008). Hardt (2008) found
that the magnitude of percolation measured by a lysimeter is 1 to 3 orders of magnitude
greater than the percolation in an actual ET cap when soil layers of the cap contain
preferential flow channels (e.g., desiccation cracks). Thus, when numerical results of
Khire and Mijares (2008) are combined with findings by Hardt (2008), it can be inferred
that a lysimeter will likely further overestimate the percolation as the bulk hydraulic
conductivity of the cap potentially increases with the age of the cap due to various factors
(Benson et al 2007). A lysimeter overpredicts percolation because the infiltrated water
drained into the lysimeter is immediately removed. Hence, it is not available for removal
by evapotranspiration. In ET caps, where a geomembrane does not exist below the cap,
percolation into the waste may be temporarily stored in the waste and can be removed by
evapotranspiration.

104

OBJECTIVE
While it is not possible to directly measure percolation without a lysimeter, it is possible
to measure soil water storage in an ET cap using established techniques (Khire et al.
1999) and numerically estimate percolation using a calibrated model. Hence the key
objective of the numerical study presented in this paper is to estimate percolation for
actual ET caps using the measured soil water storage and percolation of corresponding
lysimeter. In the field, the soil water storage is typically determined by integrating the
water content values over the thickness of the cap. Comparative predicted soil water
storage variations and percolation rates through lysimeters and actual caps (without
lysimeters) were evaluated for semi-arid and humid climates for caps with varying
hydraulic properties of landfilled waste.

WATER BALANCE MODEL
The finite-difference water balance model UNSAT-H (Fayer 2000) was used in this
study. UNSAT-H numerically solves a modified form of Richards’ equation to compute
the flow of water through both saturated and unsaturated soil. This model has been
routinely used for water balance modeling of earthen caps (Khire et al. 1997; Khire et al.
2000; Benson et al. 2005; Scanlon et al. 2005; Ogorzalek et al. 2008; Bohnhoff et al.
2009). For this study, one-dimensional simulations were carried out using UNSAT-H
Version 3.0.
A schematic of the conceptual model used in the numerical simulations is shown
in Figure 3-1. For the lysimeter, the soil cap was underlain with a geocomposite drainage
layer, similar to its typical installation in the field. In order to simulate an actual cap, the

105

soil cap was assumed to have underlain by a 3-m thick waste layer. Additional
simulations with thicker waste layer were carried out. However, thicker waste layer did
not significantly influence the percolation and soil water storage of the simulated caps.
Landfill soil covers consisting of a topsoil layer and a compacted clay layer was
considered in this study. This cross section is a relatively basic form for an alternative
earthen cap. The compacted clay layer provides the required storage for the ET cap to
temporarily store infiltrated water during wet periods and releases it back to the
atmosphere during dry periods via evapotranspiration. The topsoil layer provides a
medium for vegetation to develop in order to enhance transpiration. It also protects the
underlying compacted clay against desiccation.

(a) Lysimeter

(b) Actual Cap

Figure 3-1: Conceptual model for numerical simulation of alternative capping system
consisting of a lysimeter only (a); and a typical ET cap with underlying waste (b).

106

The ET caps considered in this study are based from the instrumented earthen
final cover test sections built by Khire et al. (1997). A test section was constructed in East
Wenatchee, Washington to assess the water balance of earthen cap in a semi-arid climate.
The instrumented soil cap consisted of a 15-cm thick silty topsoil layer underlain with a
60-cm compacted Wenatchee silty clay as storage layer. A test section was also
constructed in Atlanta, Georgia to assess the water balance of earthen cap in a humid
climate. The instrumented soil cap also consisted of a 15-cm thick silty topsoil layer.
However, a thicker storage layer was placed to accommodate the inherent wetter
condition in this area. A 90-cm thick compacted Georgia red clay was used to build the
test section. Underneath both test sections, a geocomposite drainage layer was placed
above the textured geomembrane lining to facilitate the collection and drainage of
percolated water to a measuring or monitoring device(s).

Material Properties
Table 3-1 summarizes the saturated and unsaturated hydraulic properties of the original
soils used to build the instrumented test sections in Wenatchee and Atlanta (Khire et al.
1997). The soil water characteristic curve was expressed by the Haverkamp function:

θ −θ r
α
=
θ s −θ r α + Ψ β
where

(3-1)

θ is the volumetric water content for a given matric suction, Ψ ; θ s is the

saturated water content;

θr

is the residual water content; and

107

α and β are the curve

fitting parameters. Similarly, the unsaturated hydraulic conductivity function was
expressed by the Haverkamp equation:

KΨ
A
=
KS
A+ ΨB

(3-2)

where KΨ and KS are the unsaturated and saturated hydraulic conductivities,
respectively; and

A and B are the curve fitting parameters (Haverkamp et al. 1977).

Both the soil water characteristic curve and the unsaturated hydraulic conductivity data
were independently measured by Khire et al. (1997).

Table 3-1: Saturated and unsaturated hydraulic properties of soils used in the
instrumented field test sections of Khire et al. (1997).

Soil

θr

θs
3

3

3

3

(cm /cm ) (cm /cm )

α

β

Ks

(1/cm)

(cm/s)

Wenatchee
Topsoil

0.40

0.05

80

0.60

4.5 x 10

Wenatchee
Compacted
Silt Clay

0.36

0.05

72

0.60

2.2 x 10

Atlanta
Topsoil

0.40

0.08

200

0.65

1.0 x 10

Atlanta
Compacted
Red Clay

0.52

0.08

17

0.40

3.2 x 10

108

Α

Β
(1/cm)

-5

300

2.2

-7

400

1.3

-4

1

1.45

-6

8

1.15

Table 3-2 presents the saturated and unsaturated hydraulic properties of the
additional materials used in the simulations (i.e., geotextile and waste properties). Water
characteristic curves were obtained from published literatures as indicated in the table.
Unsaturated hydraulic conductivity functions were estimated using the closed-form van
Genuchten-Mualem expression where the pore interaction term was set to 0.5 (van
Genuchten 1980). Afterwards, the Haverkamp fitting parameters were determined for the
water

characteristic

curves

and

unsaturated

hydraulic

conductivity functions.

Table 3-2: Saturated and unsaturated hydraulic properties of geotextile and waste used in
the simulations.

Material

θs

θr

3
3
3
3
(cm /cm ) (cm /cm )

α

β

Ks

(1/cm)

(cm/s)

Geotextile
(Park and
Fleming 2006)

0.82

0

Loose Waste
(Measured;
Landfilled
MSW)

0.67

0.20

1.62

0.293 1.0 x 10

-2

Loose Waste
(Kazimoglu
et al. 2006)

0.58

0.14

18.74

0.972 1.0 x 10

-3

Dense Waste
(Breitmeyer
et al. 2010)

0.61

0.011

10.38

0.58 4.0 x 10

-5

22307.2 3.533 1.5 x 10

Β

Α

-1

5.24 x 10

(1/cm)

10

9.4

2

2.5

6

5.246

1

2.96

1.00 x 10

1.88 x 10

1.00 x 10

Hydraulic properties of nonwoven geotextile were obtained from Park and
Fleming (2006). The nonwoven, polypropylene, needle-punched, continuous fiber
109

2

geotextile has a mass per unit area of 550 g/m with a thickness of 4.0 mm and an
opening size of 0.05 to 0.15 mm. It has similar properties to that of the geotextile used in
the study of Stormont and Morris (2000). Haverkamp fitting parameters were obtained
based from the data points measured by Park and Fleming (2006) for the geotextile’s
water retention curve.
For actual ET cap simulations, due to inherent heterogeneity of municipal solid
waste (MSW), two MSW properties were considered: (1) a loosely compacted MSW
typically found on landfills at shallow depth, and (2) a densely compacted MSW which is
commonly found buried deep in landfills. For loose MSW, two properties were further
used in the simulations.
The first was measured in the laboratory for MSW collected from the landfill
from 6 to 12 m depths. The MSW sample was obtained using a 45 cm diameter auger.
The waste, without sorting or screening, was placed in a relatively large PVC cell (30 cm
diameter, 25 cm tall) to measure the saturated hydraulic conductivity using the falling
head test (ASTM D5084) and the same sample was spun in a geotechnical centrifuge at
up to 40 g gravitational force added to the sample in 1 to 3 g increments to measure the
water retention function (ASTM D6836). The centrifuge not only allowed the
measurement of the water retention function relatively rapidly, it also simulated the
normal stress experienced by the waste at the depth it was collected. The dry density of
3

the waste at the vertical stress simulated in the centrifuge was 0.69 g/cm . The saturated
hydraulic conductivity of the specimen is 10

-2

110

cm/s. The method developed by Passioura

(1977) was applied to the water retention data collected from the centrifuge test to
estimate the unsaturated hydraulic conductivities for the waste.
Hydraulic properties of MSW reported by Kazimoglu et al. (2005, 2006) were
also assumed to represent the loose MSW layer in the actual cap. Kazimoglu et al. (2005,
2006) determined the waste retention properties for a laboratory prepared waste specimen
which has composition similar to the waste found in Lyndhurst landfill in Australia that is
3

located at shallow depth with a dry density of 0.57 g/cm . Stoltz and Gourc (2007)
published similar waste retention curves for loosely compacted MSW having a dry unit
3

weight equal to 0.54 g/cm . For loosely compacted MSW such as those found within
landfills at shallow depth (i.e. beneath the final cover), a saturated hydraulic conductivity
of 10

-3

cm/s has been reported (Mukherjee 2008). Hence, this estimated value for MSW

was adopted for this study. The corresponding predicted unsaturated hydraulic
conductivity function shows good agreement, at high suction, with the measured
unsaturated

hydraulic

conductivity

function

using

one-step

outflow

method

(Kazimoglu, 2006).
Since MSW is generally heterogeneous with highly varying properties, a dense
MSW with lower hydraulic conductivity was also considered to determine its relative
impact on the resulting soil water storage and percolation for the ET cap. Breitmeyer
et al. (2010) presented the measured water characteristic curve and unsaturated hydraulic
3

conductivity function for a dense MSW with dry density of 0.81 g/cm using hanging
column and multi-step outflow method, respectively. The saturated hydraulic
-5

conductivity of the specimen is 4.0 x 10

cm/s. The measured and predicted unsaturated
111

hydraulic conductivity function show good agreement across the entire range of suction
(Breitmeyer et al. 2010).
Figure 3-2 shows the water characteristic curves and the hydraulic conductivity
functions for the soils used to build the instrumented test section in Wenatchee as well as
the geotextile and the waste presented in Table 3-2. Figure 3-3 shows the water
characteristic curves and the hydraulic conductivity functions for the soils used to build
the instrumented test section in Atlanta as well as the geotextile and the waste presented
in Table 3-2.

Meteorological Data
Daily meteorological data were compiled by Khire et al. (1997) for Wenatchee and
Atlanta test sections. Field measurements were obtained for daily maximum and
minimum air temperatures, average dew point temperature, total solar radiation, average
wind speed, average cloud cover, and total precipitation. These meteorological data were
used as input to UNSAT-H.
For all numerical analyses, precipitation was applied at an hourly frequency
specifically during the time intervals it occurred during a particular day. The first year of
field measured data for both test sections was used in the simulations. Annual
precipitation for the landfill site in Wenatchee is 26.5 cm with an annual potential
evapotranspiration of 109.1 cm (P/PET ~ 0.24). Annual precipitation for the landfill site
in Atlanta is 153.6 cm with an annual potential evapotranspiration of 109.8 cm (P/PET ~
1.40).

112

Initial and Boundary Conditions and Numerical Control Parameters
A variable flux boundary was applied at the ground surface (Figure 3-1) for the lysimeter
as well as the actual cap. A unit gradient boundary condition was imposed on the lower
boundary of the model domains. The unit gradient boundary used for the lysimeter was
applied under two scenarios: (1) at the bottom of the compacted clay layer for lysimeter
without considering the geotextile layer, and (2) at the bottom of the geotextile layer for
lysimeter considering the geocomposite drainage layer. The unit gradient boundary used
for the actual cap was applied at the bottom of the waste layer. Khire and Mijares (2008)
and Mijares et al. (2010) have used the same lower boundary condition for simulations
with waste layer. Initial conditions for UNSAT-H were specified using matric suctions
corresponding to in-situ water contents measured by Khire et al. (1997) for both test
sections. For actual cap simulations, the initial conditions for the waste layer were based
from the matric suctions corresponding to the in-situ MSW water contents measured from
the field test sections discussed in Paper No. 1.
Spatial discretization of the model domain was optimized by conducting
sensitivity analysis. This was done by repeatedly refining the nodal spacing until
insignificant changes in simulated water balance parameters were achieved. The nodal
spacing between the nodes located near the upper and lower boundaries, as well as near
the interface between layers, was relatively small (1 mm). A maximum time step of 0.1 hr
-7

and a minimum time step of 10 hr were used for all the simulations. This was necessary
to accurately evaluate the extreme drying and wetting conditions typically encountered at
the ground surface. At any given time step, the maximum allowable mass balance error

113

6

10

Loose MSW
(Kazimoglu et al. 2006)

5

(a)

10

Loose MSW
(Measured)

Matric Suction (cm)

4

10

Dense MSW
(Breitmeyer et al. 2010)

3

10

Nonwoven Geotextile
(Park and Fleming 2006)

2

10

1

10

Clay
(Khire et al. 1997)

0

10
10

-1

Topsoil
(Khire et al. 1997)

-2

10 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Volumetric Water Content

Hydraulic Conductivity (cm/s)

10

0

10

-2

10

-4

10

-6

10

-8

Nonwoven Geotextile
(Park and Fleming 2006)

10

Loose MSW
(Kazimoglu et al. 2006)
Clay
(Khire et al. 1997)

-12

10

Loose MSW
(Measured)

-10

10

(b)

-14

Dense MSW
(Breitmeyer et al. 2010)
Topsoil
(Khire et al. 1997)

10

-1

10

0

10

1

10

2

10

3

10

4

10

5

10

6

Matric Suction (cm)
Figure 3-2: Soil water characteristic curves (a); and hydraulic conductivity functions (b)
for the soils used in the Wenatchee test section, nonwoven geotextile, and MSW.
114

6

10

Loose MSW
(Kazimoglu et al. 2006)

5

(a)

10

Loose MSW
(Measured)

Matric Suction (cm)

4

10

Dense MSW
(Breitmeyer et al. 2010)

3

10

2

Nonwoven Geotextile
(Park and Fleming 2006)

10

1

10

0

Topsoil
(Khire et al. 1997)

-1

Clay
(Khire et al. 1997)

10
10

-2

10 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Volumetric Water Content

Hydraulic Conductivity (cm/s)

10

0

-2

Nonwoven Geotextile
(Park and Fleming 2006)

10

-4

Loose MSW
(Measured)

10

-6

10

10

-8

10

-14

Clay
(Khire et al. 1997)

Topsoil
(Khire et al. 1997)

-12

10

Loose MSW
(Kazimoglu et al. 2006)

-10

10

(b)

10

Dense MSW
(Breitmeyer et al. 2010)

-1

10

0

10

1

10

2

10

3

10

4

10

5

10

6

Matric Suction (cm)

Figure 3-3: Soil water characteristic curves (a); and hydraulic conductivity functions (b)
for the soils used in the Atlanta test section, nonwoven geotextile, and MSW.
115

for the whole profile was set at 10

-5

cm. For all numerical analyses, total mass balance

errors were less than 1%.

RESULTS

Semi-arid Climate
Figure 3-4 shows the simulated percolation and soil water storage (SWS) for the
Wenatchee test section. The graph presents simulation results using the original soils
used to build the instrumented earthen cover in semi-arid climate. The saturated hydraulic
conductivity of the compacted silty clay cover is 2.2 x 10

-7

cm/s. Field measured

lysimeter percolation obtained by Khire et al. (1997) shows that the test section yielded
0.79 cm of percolation during the first year of its monitoring period. As shown in
Figure 3-4, numerically simulated lysimeter percolation using unit gradient boundary at
the bottom of the compacted clay layer for lysimeter (without considering the geotextile
layer) relatively captured the field measured percolation. Lysimeter simulation
considering a geotextile layer underneath the earthen cover showed much lower
percolation compared to that without the geotextile layer.
For actual ET cap simulations, loose and dense MSW were considered underneath
the earthen cover. The resulting percolation for actual ET caps corresponds to the
interlayer flux across the interface between the earthen cover and the underlying
landfilled waste and is a function of the hydraulic properties for the MSW layer. Positive

116

4

28

Wenatchee Test Section

0.75 m Thick Cap
Cap w/ K

WL

3

=
25

-2

10 cm/s
2

22

1

SWS

Lysimeter
w/o GT

Field
(Measured)

19
Lysimeter w/ GT

0

Soil Water Storage (cm)

Cumulative Percolation (cm)

Semi-arid Climate

16

-5

10 cm/s

Percolation

-3

10 cm/s
-1

13
0

60

120

180

240

300

360

Time (days)
Figure 3-4: Simulated cumulative percolation and soil water storage for Wenatchee soil,
with 0.6-m thick storage layer, in a semi-arid climate boundary condition.

percolation values represent downward flux of moisture from the earthen cover to the
waste layer. Negative percolation values represent upward flux of moisture wherein the
earthen cover pulls the moisture up from the waste layer. As shown from Figure 3-4, as
the saturated hydraulic conductivity of the waste decreases, the percolation rate for the
actual cap also decreases. Actual ET cap with underlying loose MSW with a saturated
-2

hydraulic conductivity of 10

cm/s and unsaturated hydraulic properties measured from

centrifuge testing had percolation greater than lysimeter percolation. However, actual ET

117

cap percolations with typical MSW having saturated hydraulic conductivity of 10
-5

10

-3

and

cm/s generally have negative percolation which indicates much lower percolation

than the corresponding lysimeter (i.e., lysimeter percolation is generally conservative).
The reduction in percolation is attributed to: (1) the ability of the waste to impede the
downward flow of water from the overlying soil cap; and (2) the temporary storage of
percolated water by the underlying waste and removal of the stored water under
evapotranspirative gradients as evident in Figure 3-4 showing the decrease in the
cumulative percolation across the cap to waste interface. This particularly occurs during
dry periods where the fine-grained soils have the capability to pull water up due to
capillary action. For lysimeters, the infiltrated water drains as percolation and hence
cannot be extracted later via evapotranspiration.
The reduction in percolation provided by the waste layer generally corresponds to
an increase in the SWS of the overlying ET cap as compared to the corresponding
lysimeter (Khire and Mijares 2010). However, due to the relatively small difference in
the percolation rate between actual ET cap and lysimeter, as well as the inherently low
saturated hydraulic conductivity of the cover soil, the resulting SWS of the actual ET cap
and lysimeter appear similar (Figure 3-4). In order to compare the SWS, simulated SWS
within actual ET caps were plotted against simulated SWS within lysimeter (without
geotextile layer) for all simulations for the same time period (Figure 3-5). The 1:1 line
shows the region where SWS values are the same for an actual cap and corresponding
lysimeter. Points above the 1:1 line correspond to greater SWS for the cap compared to
the lysimeter and vice versa. Closer look at Figure 3-5 reveals that SWS within actual ET
caps are indeed generally larger than the SWS within the corresponding lysimeter for
118

typical MSW with KWL equal to 10

-3

and 10

-5

cm/s, albeit small difference in

magnitude. For all cases, greater soil water storage corresponded to a lower percolation
or vice versa. When the difference in SWS relatively small, it is associated with relatively
small difference in percolation.

Soil Water Storage - Actual Cap (cm)

30

Wenatchee Test Section

1:1
Line

Semi-arid Climate
25

20

K
15

K
K

-2

WL

cm/s

-5

WL

cm/s

-3

WL

cm/s

= 10
= 10
= 10

10
10

15

20

25

30

Soil Water Storage - Lysimeter (cm)
Figure 3-5: Simulated soil water storage for actual cap versus lysimeter for Wenatchee
soil, with 0.6-m thick storage layer, in a semi-arid climate boundary condition.

Figure 3-6 shows the simulated percolation and SWS for actual ET caps and
lysimeter consisting of Wenatchee soil with a much thicker soil cap (0.9-m thick storage
layer). All other variables were kept the same. It can be seen that for lysimeter
119

simulations, as the thickness of the cap increases, the resulting percolation decreases.
Similar trend can be observed for actual cap simulations, regardless of the hydraulic
conductivity of the underlying waste. For silty clay such as the Wenatchee soil, the
relatively low hydraulic conductivity produces an average percolation of about few mm
per year. Simulation results show that lysimeter generally overestimates the actual ET
cap by about two times.

3

35

Wenatchee Test Section

Cap w/ K

WL

=

-2

2

32

10 cm/s
Lysimeter
Lysimeter w/ GT
w/o GT

1

0

26

-5

10 cm/s
Percolation
-3

-1

29

23

10 cm/s

SWS

Soil Water Storage (cm)

Cumulative Percolation (cm)

Semi-arid Climate

1.05 m Thick Cap

-2

20
0

60

120

180

240

300

360

Time (days)
Figure 3-6: Simulated cumulative percolation and soil water storage for Wenatchee soil,
with 0.9-m thick storage layer, in a semi-arid climate boundary condition.

120

Humid Climate
Figure 3-7 shows the simulated percolation and SWS for the Atlanta test section. The
graph presents simulation results using the original soils used to build the instrumented
earthen cover in a humid climate. The saturated hydraulic conductivity of the compacted
-6

clayey silt cover is 3.2 x 10

cm/s. Field measured lysimeter percolation obtained by

Khire et al. (1997) shows that the test section yielded 12.98 cm of percolation during the
first year of its monitoring period. Due to inherent high precipitation in humid climate,
the test section yielded much higher percolation. Numerically simulated lysimeter

48

14
12

46

Cap w/
K =
WL

44

10
-2

10 cm/s
42

8
SWS

40

6

38

-3

10 cm/s

4
Lysimeter
w/o GT

2

36
-5

10 cm/s

Percolation

34

0

Lysimeter w/ GT
0

60

Soil Water Storage (cm)

Cumulative Percolation (cm)

Field (Measured)

Atlanta Test Section
Humid Climate

120

1.05 m Thick Cap

180

300

240

360

32

Time (days)
Figure 3-7: Simulated cumulative percolation and soil water storage for Atlanta soil, with
0.9-m thick storage layer, in a humid climate boundary condition.
121

percolation using unit gradient boundary at the bottom of the compacted clay layer for
lysimeter (without considering the geotextile layer) and lysimeter simulation considering
a geotextile layer underneath the earthen cover both showed much lower percolation
predictions compared to the field measured percolation. Furthermore, lysimeter
simulation considering a geotextile layer underneath the earthen cover still showed much
lower percolation compared to that without the geotextile layer.

Soil Water Storage - Actual Cap (cm)

50

Atlanta Test Section
Humid Climate

1:1
Line

45

40

K
35

K
K

-2

WL

cm/s

-5

WL

cm/s

-3

WL

cm/s

= 10
= 10
= 10

30
30

35

40

45

50

Soil Water Storage - Lysimeter (cm)
Figure 3-8: Simulated soil water storage for actual cap versus lysimeter for Atlanta soil,
with 0.9-m thick storage layer, in a humid climate boundary condition.

122

For actual ET cap simulations, as the underlying waste is assumed to be more
dense having a lower hydraulic conductivity, the percolation rate for the actual cap
consistently decreases due to the reasons presented in the preceding subsection. This
observation is consistent with the trends obtained for the semi-arid climate. Similarly, the
SWS response of an actual ET cap and the corresponding lysimeter are close to each
other (Figures 3-7 and 3-8) because the predicted percolations are about the same. It can
be noted that for humid climate, net positive percolations have been observed regardless
of the hydraulic properties of the underlying landfilled waste. This is because in humid
climate, the magnitude of precipitation is relatively large compared to the semi-arid
climate which results in the soil cover to remain relatively wet more often. Hence, the
cover is less often able to develop upward hydraulic gradients to pull water from the
underlying waste layer.
Figure 3-9 shows the simulated percolation and SWS for actual ET caps and
lysimeter consisting of Atlanta soil with a much thicker soil cap (1.5-m thick storage
layer). All other variables were kept the same. Similar to the semi-arid climate, the
numerical results suggest that thicker cover soils would consistently have much lower
lysimeter percolation as well as actual cap percolations. The presence of the waste layer
underneath actual ET caps indeed affects the SWS response and the resulting percolation
for the earthen covers. Consequently, a reduction in percolation has been observed
whenever there is an increase in the SWS. The waste layer acts as a barrier that impedes,
but not prevents, the downward flow of water.

123

72

Humid Climate

Cap w/
K =
WL

10

-2

10
cm/s

SWS

70
68
66
64

5
Lysimeter
w/o GT
Percolation

-3

60

-5

10 cm/s

0

62

Lysimeter
w/ GT

Soil Water Storage (cm)

Cumulative Percolation (cm)

Atlanta Test Section

58

10 cm/s
1.65 m Thick Cap

0

60

120

180

240

300

360

56

Time (days)
Figure 3-9: Simulated cumulative percolation and soil water storage for Atlanta soil, with
1.5-m thick storage layer, in a humid climate boundary condition.

SUMMARY AND CONCLUSIONS
Financial savings associated with ET caps and their sustainability due to more options for
end use has resulted in more state regulatory agencies to consider earthen final caps. The
earthen caps eliminate the use of relatively expensive geomembranes in landfill final
covers. While lysimeters are commonly used to assess the water balance of alternative
caps, lysimeters are not hydraulically equivalent to an actual ET cap due to the difference
in the lower hydraulic boundary. Actual caps are typically underlain by permeable
subgrade/waste layers. The numerical results from this study indicate that the soil water
storage of an actual ET cap would generally be greater than the soil water storage of the

124

corresponding lysimeter. Greater soil water storage corresponds to lower percolation and
vice versa. The reduction in the soil water storage capacity of lysimeters is associated
with the removal of infiltrated water from the lower boundary resulting in greater
percolation. In an actual ET cap, where it is underlain by waste, the percolation through
the cap is generally less because of the capillary break and water storage capacity offered
by the underlying waste layer. Because it is not possible to directly measure percolation
without a lysimeter, the percolation values measured in the field should be re-evaluated
by carrying out site-specific numerical analysis for representative field-scale hydraulic
properties of the waste to simulate the long-term percolation scenario for the actual final
cap. The numerical results presented in this study also suggest that thicker cover soils
would consistently have much lower lysimeter percolation as well as actual cap
percolation. Furthermore, wetter climate (with high precipitation to potential
evapotranspiration ratio) would typically have smaller difference in the soil water storage
and percolation for an actual ET cap versus its corresponding lysimeter.

125

REFERENCES

126

REFERENCES
Abichou, T., Liu, X., and Tawfiq, K. (2006). “Design Considerations for Lysimeters
Used to Evaluate Alternative Earthen Final Covers,” Journal of Geotechnical and
Geoenvironmental Engineering, 132 (12): 1519-1525.
Abichou, T., and Musagasa, J. (2008). “ET Covers: Construction and Tree Development
Inside and Outside of Lysimeters,” Proceedings, GeoCongress 2008, GSP No. 177,
Geotechnics of Waste Management and Remediation, ASCE, Reston, VA: 72-79.
Albright, W., Benson, C., Gee, G., Roesler, A., Abichou, T., Apiwantragoon, P., Lyles,
B., and Rock, S. (2004). “Field Water Balance of Landfill Final Covers,” Journal of
Environmental Quality, 33(6): 2317-2332.
Benson, C., Abichou, T., Albright, W., Gee, G., and Roesler, A. (2001). “Field
Evaluation of Alternative Earthen Final Covers,” International Journal of
Phytoremediation, 3 (1): 105-127.
Benson, C., Bohnhoff, G., Ogorzalek, A., Shackelford, C., Apiwantragoon, P., and
Albright, W. (2005). “Field Data and Model Predictions for an Alternative Cover,”
Waste Containment and Remediation, GSP No. 142, ASCE, Reston, VA: 1-12.
Benson, C., Sawangsuriya, A., Trzebiatowski, B., and Albright, W. (2007).
“Postconstruction Changes in the Hydraulic Properties of Water Balance Cover
Soils,” Journal of Geotechnical and Geoenvironmental Engineering, 133 (4):
349-359.
Bohnhoff, G., Ogorzalek, A., Benson, C., Shackelford, C., and Apiwantragoon, P. (2009).
“Field Data and Water-Balance Predictions for a Monolithic Cover in a Semiarid
Climate,” Journal of Geotechnical and Geoenvironmental Engineering, 135 (3):
333-348.
Breitmeyer, R., Benson, C., Edil, T., and Barlaz, M. (2010). “Hydrologic Properties of
Municipal Solid Waste,” Research Project Poster, GeoEngineering Program,
University of Wisconsin Madison.
Fayer, M. (2000). “UNSAT-H Version 3.0: Unsaturated Soil Water and Heat Flow Model
– Theory, User Manual, and Examples.” PNNL-13249, Pacific Northwest
Laboratories, Richland, Washington.
Hardt, C. (2008). “Numerical Evaluation of Preferential Flow Through
Evapotranspirative Landfill Covers,” Masters Thesis, Michigan State University,
East Lansing, Michigan, 67 p.
Hauser, V., Weand, B., and Gill, M. (2001). “Natural Covers for Landfills and Buried
Waste.” Journal of Environmental Engineering, 127 (9): 768-775.

127

Haverkamp, R., Valcin, M., Touma, J., Wierenga, P., and Vauchaud, G. (1977). “A
Comparison of Numerical Simulation Models for One-Dimensional Infiltration,”
Soil Science Society of America Journal, 41: 285-294.
Kazimoglu, Y., McDougall, J., and Pyrah, I. (2005). “Moisture Retention and Movement
in Landfilled Waste,” Proceedings, GeoProb 2005: International Conference on
Problematic Soils, Famagusta, Northern Cyprus, May 2005.
Kazimoglu, Y., McDougall, J., and Pyrah, I. (2006). “Unsaturated Hydraulic
Conductivity of Landfilled Waste,” Proceedings, Unsaturated Soils 2006, GSP No.
147, ASCE, Reston, VA: 1525-1534.
Khire, M., and Mijares, R. (2008). “Influence of the Waste Layer on Percolation
Estimates for Earthen Caps Located in a Sub-humid Climate,” Proceedings,
GeoCongress 2008, GSP No. 177, Geotechnics of Waste Management and
Remediation, ASCE, Reston, VA: 88-95.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering, 123
(8): 744-754.
Khire, M., Benson, C., and Bosscher, P. (1999). “Field Data From a Capillary Barrier and
Model Predictions with UNSAT-H,” Journal of Geotechnical and
Geoenvironmental Engineering, 125: 518–528.
Khire, M., Benson, C., and Bosscher, P. (2000). “Capillary Barriers: Design Variables
and Water Balance,” Journal of Geotechnical and Geoenvironmental Engineering,
126 (8): 695-708.
Mijares, R., Khire, M., and Johnson T. (2010). “Lysimeters Versus Actual Earthen Caps:
Numerical Assessment of Soil Water Storage,” Proceedings, GeoFlorida 2010, GSP
No. 199, Advances in Analysis, Modeling and Design, ASCE, Reston, VA: 28492858.
Mukherjee, M. (2008). “Instrumented Permeable Blankets for Estimating Subsurface
Hydraulic Conductivity and Confirming Numerical Models Used for Subsurface
Liquid Injection,” Ph.D. Dissertation, Michigan State University, East Lansing,
Michigan, 278 p.
Ogorzalek, A., Bohnhoff, G., Shackelford, C., Benson, C., and Apiwantragoon, P. (2008).
“Comparison of Field Data and Water-Balance Predictions for a Capillary Barrier
Cover,” Journal of Geotechnical and Geoenvironmental Engineering, 134 (4): 470486.
Park, K., and Fleming, I. (2006). “Evaluation of a Geosynthetic Capillary Barrier,”
Geotextiles and Geomembranes, 24: 64-71.

128

Passioura, J. (1977). “Determining Soil Water Diffusivities from One-step Outflow
Experiments,” Australian Journal of Soil Research, 15 (1): 1-8.
Scanlon, B., Reedy, R., Keese, K., and Dwyer, S. (2005). “Evaluation of
Evapotranspirative Covers for Waste Containment in Arid and Semiarid Regions in
the Southwestern USA,” Vadose Zone Journal, 4: 55-71.
Simunek, J., and van Genuchten, M. (2008). “Modeling Nonequilibrium Flow and
Transport Processes Using HYDRUS,” Vadose Zone Journal, 7 (2): 782-797.
Simunek, J., van Genuchten, M., and Sejna, M. (2008). “The HYDRUS-1D Software
Package for Simulating the One-Dimensional Movement of Water, Heat, and
Multiple Solutes in Variably-Saturated Media: Version 4.0.” Dept. of
Environmental Sciences, University of California, Riverside.
Stoltz, G., and Gourc, J. (2007). “Influence of Compressibility of Domestic Waste on
Fluid Conductivity,” Proceedings, 18th Congres Francais de Mecanique, Grenoble,
France.
Stormont, J., and Morris, C. (2000). “Characterization of Unsaturated Nonwoven
Geotextiles,” Proceedings, Geo-Denver 2000, GSP No. 99, Advances in
Unsaturated Geotechnics, ASCE, Reston, VA: 153–164.
van Genuchten, M. (1980). “A Closed-Form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils,” Soil Science Society of America Journal, 44:
892-898.

129

PAPER NO. 4: EVALUATION OF GEOSYNTHETIC CAPILLARY
BREAK IN EARTHEN COVER LYSIMETERS

ABSTRACT
In this study, the numerical unsaturated flow model UNSAT-H was used to evaluate the
capillary break developed by nonwoven geotextile component of geocomposite drainage
layer that is commonly used to collect percolation in lysimeters. Lysimeters are used to
evaluate the water balance of landfill covers. The numerical modeling included constant
flux simulations of coarse to fine-grained soils underlain by nonwoven geotextile
followed by simulations of two instrumented lysimeters constructed in humid and semiarid climates. Evidence of a geotextile capillary break was evident from higher soil water
storage as well as a delay in the onset of percolation. The results indicate that the
capillary break introduced by a nonwoven geotextile in lysimeters maybe significant only
when the saturated hydraulic conductivity of the soils is greater than 10

-5

cm/s. However,

irrespective of the hydraulic conductivity of the soils or the regional climate, the capillary
break did not have significant impact on the long-term percolation.

INTRODUCTION
There are about 1,600 active municipal solid waste (MSW) landfills in the United States.
These landfills will require a final cover once they are closed. The U.S. federal
regulations imply emulating landfill liner which requires a geomembrane layer, for
landfill final cover. Alternative final covers that only use earthen materials offer financial
savings, greater end-use options (wood harvesting), and better long-term erosion
protection due to deeper plant roots. Hence, alternative covers, which are also referred to
130

as evapotranspirative (ET) caps have been tested in the field since 1980s for long-term
capping of municipal solid waste (MSW) landfills as well as radioactive waste sites.
Since then, ET caps have been widely used in arid and semi-arid climates and are being
tested and permitted in sub-humid and humid climates on a case by case basis. Often the
performance of ET caps is evaluated by constructing a lysimeter to collect the percolation
that infiltrates through the cap. Based on the magnitude of the annual percolation
collected in the lysimeter, the ET cap is approved, disapproved, or redesigned (Khire and
Mijares 2008; Mijares et al. 2010).
The lysimeter usually contains a geocomposite drainage layer (GDL) installed at
the base of the ET cap to collect and drain the percolation to a measuring or monitoring
device(s). This GDL, which is placed above the geomembrane that lines conventional pan
lysimeter, consists of a geonet sandwiched between two geotextiles. Often the geotextile
(GT) present in the GDL is nonwoven. Published studies indicate that nonwoven
geotextiles have water retention function that is similar to those of coarse-textured soils
such as sand and gravel (Stormont et al. 1997; Stormont and Morris 2000; Park and
Fleming 2006). Hence, it has been indicated that nonwoven geotextile layer acts as a
capillary break. If it acts as a capillary break, it allows greater storage of moisture in the
soil layers above the geotextile before the percolation breakthrough occurs. In addition, a
capillary break can reduce the total percolation by enhancing evapotranspiration because
more soil water is available for an extended duration for potential removal via
evaporation and transpiration (Benson and Khire 1995; Ward and Gee 1997; Khire et al.
2000).

131

Capillary break occurs during unsaturated conditions at the interface between the
fine-textured soil cover and underlying coarse-textured material. The contrast in the
unsaturated hydraulic conductivity, under relatively high matric suctions, between the
two layers impedes the downward movement of water. This will result in the buildup of
moisture in the overlying finer layer and consequently decrease its matric suction
especially near the interface. Once the matric suction at the interface drops to the waterentry suction of the coarse-textured material, capillary barrier is breached and water will
continue to infiltrate into the underlying coarse layer.
Several studies have been published to understand the physics of capillary barrier
effect between fine-grained and coarse-grained soils. Laboratory tests have been
conducted to observe capillary break (Baker and Hillel 1990; Stormont and Anderson
1999; Tami et al. 2004) and field-scale demonstration projects have been implemented to
assess its performance (Nyhan et al. 1990; Ward and Gee 1997; Khire et al. 1999; Benson
et al. 2002; Albright et al. 2004; Ogorzalek 2008). However, limited actual case studies
have addressed the magnitude of capillary barrier effect when nonwoven GT is used.
Although numerical studies have shown that capillary break develops when a geotextile
is placed below a fine-textured soil (Iryo and Rowe 2003; Park and Fleming 2006),
physical evidence showing the magnitude of capillary barrier effect due to nonwoven GT
on percolation through an earthen cap has been scarce.
Laboratory column tests conducted by Stormont and Morris (2000) and Bathurst
et al. (2007) showed that the presence of a single layer of geotextile in the system
impedes the downward movement of wetting front. This demonstrates the presence of
capillary break. Stormont and Morris (2000) carried out constant infiltration tests on a

132

column consisting of a silty sand over coarse sand and compared it to the response of
identical column where a nonwoven geotextile was placed between the two layers.
Additional column test was conducted wherein a nonwoven geotextile was placed
between two layers of silty sand. All tests compare the suction response of the soil
immediately above and below the soil interface when breakthrough occurs. Results show
that the suction head developed above the interface during breakthrough for columns with
geotextile layer is significantly lower than those without the geotextile. Lower suction
indicates greater water content which is caused by the presence of the geotextile.
Similarly, Bathurst et al. (2007) evaluated the effect of a woven geotextile layer
sandwiched between two sand layers under constant head infiltration. Pore water pressure
time response developed in the sand located above the geotextile interface showed a
detectable positive increase as the wetting front reach the geotextile layer. This was not
observed in the identical column without the geotextile. The jump in positive pore water
pressure corresponds to instantaneous water ponding above the geotextile layer which
indicates the presence of capillary barrier effect.
Numerical simulations have been conducted to evaluate the effect of a geotextile
layer on the water balance of earthen covers under actual meteorological conditions
(Benson et al. 2005; Scanlon et al. 2005; Ogorzalek et al. 2008; Bohnhoff et al. 2009). In
contrast with a typical unit gradient boundary, a seepage face boundary is used to
approximate the capillary break formed at the base of the lysimeter due to the geotextile
layer. Alternatively, a seepage face boundary can also be represented by including a thin
layer of coarse-grained soil (e.g. gravel) at the base of the profile (Scanlon et al. 2002).
Ogorzalek et al. (2008) and Bohnhoff et al. (2009) have shown that regardless of which

133

lower boundary conditions were used, the resulting soil water storage, runoff, and
evapotranspiration are unaffected. With regard to the resulting percolation, Benson et al.
(2005) and Ogorzalek et al. (2008) showed little difference on simulated percolation.
Bohnhoff et al. (2009) observed minimal difference while Scanlon et al. (2005) noticed
significant difference on percolation values. Scanlon et al. (2005) also found an
overestimation of soil water storage which has caused the underestimation of free
drainage indicating capillary barrier effect.
The presence or absence of capillary barrier effect due to the geocomposite
drainage layer that lines the base of earthen cover lysimeters is not straightforward.
Hence, the need to quantify the magnitude of capillary barrier effect introduced by the
geotextile is important in order to assess lysimeter measured percolation. Parameters such
as soil hydraulic properties, infiltration rate, and meteorological conditions are
hypothesized to be key factors that determine occurrence of capillary break.

OBJECTIVES
The key objectives of the study presented in this paper are to: (1) determine the
magnitude of capillary barrier effect due to the geocomposite drainage layer used in
lysimeters to evaluate the water balance of earthen caps; (2) identify the factors that
facilitate formation of capillary break; and (3) compare the capillary barrier effect due to
the presence of a geotextile in lysimeters to that due to the waste layer that is present in
actual caps.
In this numerical study, the effect of GDL consisting of a nonwoven geotextile on
the water balance of the cap was evaluated by numerically simulating three monolithic

134

earthen covers. 1-D soil columns with a height of 90 cm were simulated as lysimeters or
actual caps (with underlying waste) using UNSAT-H. Constant infiltration simulations
were conducted to easily identify and quantify when capillary break occurs. In addition,
long-term simulations were carried out to quantify the magnitude of capillary barrier
effect under actual meteorological conditions in semi-arid and humid climates.

NUMERICAL MODELING
The finite-difference model UNSAT-H (Fayer 2000) was used in this study. UNSAT-H
numerically solves a modified form of Richards’ equation to compute the flow of water
through both saturated and unsaturated soil. This model has been routinely used for water
balance modeling of earthen caps (Khire et al. 1997; Khire et al. 2000; Benson et al.
2005; Scanlon et al. 2005; Ogorzalek et al. 2008; Bohnhoff et al. 2009). For this study,
one-dimensional simulations were carried out using UNSAT-H Version 3.0.
A schematic of the conceptual model used in the numerical simulations is shown
in Figure 4-1. For the lysimeter, the lower boundary either included or did not include a
nonwoven geotextile. In order to simulate an actual cap, the soil cap was assumed to have
underlain by a 30-cm thick waste layer. Additional simulations with thicker waste layer
were also carried out. However, thicker waste layer did not significantly influence the
percolation and soil water storage of the simulated caps.

Material Properties
Table 4-1 summarizes the saturated and unsaturated hydraulic properties of the soils and
the waste used to simulate the lysimeter presented in Figure 4-1. Unsaturated hydraulic

135

conductivity functions were estimated using the closed-form van Genuchten-Mualem
expression where the pore interaction term was set to 0.5 (van Genuchten 1980).
Hydraulic properties of the municipal solid waste (MSW) reported by Kazimoglu et al.
(2005, 2006) were assumed to represent the waste layer in the actual cap. Kazimoglu
et al. (2005, 2006) determined the waste retention properties for a laboratory prepared
waste specimen which has composition similar to the waste found in Lyndhurst landfill in
3

Australia that is located at shallow depth with a dry density of 0.57 g/cm . Stoltz and
Gourc (2007) published similar waste retention curves for loosely compacted MSW

(a)

(b)

(c)

GT = Nonwoven Geotextile
WL = Municipal Solid Waste

Figure 4-1: Conceptual model used to simulate a lysimeter without (a) and with (b) a
nonwoven GT and an actual cap with waste layer (c).
136

3

having a dry unit weight equal to 0.54 g/cm . For loosely compacted MSW such as those
found within landfills at shallow depth (i.e. beneath the final cover), a saturated hydraulic
-3

conductivity of 10 cm/s has been reported (Mukherjee 2008).
Hydraulic properties of nonwoven geotextile were obtained from Park and
Fleming (2006). The nonwoven, polypropylene, needle-punched, continuous fiber
2

geotextile has a mass per unit area of 550 g/m with a thickness of 4.0 mm and an
opening size of 0.05 to 0.15 mm. It has similar properties to that of the geotextile used in
the study of Stormont and Morris (2000). van Genuchten fitting parameters were
obtained based from the data points measured by Park and Fleming (2006) for the
geotextile’s water retention curve (Figure 4-2).
Figure 4-2 shows the soil water characteristic curves and the hydraulic
conductivity functions for the geotextile and the waste presented in Table 4-1.

Table 4-1: Saturated and unsaturated hydraulic properties.

Soil/Material

θs

θr

α

3 [1/cm-H2O]
[cm /cm ] [cm /cm ]
-1
3

3

3

n

Ks
[cm/s]

Reference

(kPa )

Geotextile

0.82

0

0.066 (0.66) 3.99

1.5 x 10

OK 110
Fine Sand

0.35

0.03

0.016 (0.16)

2.5

6.4 x 10

SM Soil

0.42

0.02

0.005 (0.05) 1.48

2.7 x 10

SM-ML Soil

0.35

0.02

0.012 (0.12) 1.123 9.0 x 10

Waste

0.58

0.14

0.15 (1.5)
137

1.6

1.0 x 10

-1 Park and Fleming
-3
-4
-6
-3

(2006)
Mukherjee
(2008)
Khire et al.
(2000)
Khire et al.
(2000)
Kazimoglu et al.
(2006)

4

10

(a)

Matric Suction (cm)

3

10

MSW
(Kazimoglu et al. 2006)
2

10

Non-woven
Geotextile

1

10

0

10

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Volumetric Water Content

Hydraulic Conductivity (cm/s)

10

0

(b)

Non-woven
Geotextile

-2

10

MSW
-4

10

-6

10

MSW Measured
(Kazimoglu et al. 2006)

-8

10

-10

10

10

0

1

2

10

10

3

10

Matric Suction (cm)

Figure 4-2: Measured soil water characteristic curves (a); and predicted hydraulic
conductivity function (b) for nonwoven geotextile and MSW.
138

Figure 4-2(b) shows that the unsaturated hydraulic conductivities of the nonwoven
geotextile and low unit weight MSW are about the same at matric suctions greater than
20 cm.

0

Hydraulic Conductivity, K(ψ) (cm/s)
ψ

10

Geotextile

-2
-4

Capillary Barrier Effect

OK110
Fine Sand
SM

10
10

Capillary Barrier Effect

SM-ML

-6

10

Capillary Barrier Effect

-8

10

-10

10

-12

10

-14

10

10

-1

0

10

1

10

2

10

10

3

Matric Suction, Ψ (cm)

10

4

10

5

Figure 4-3: Unsaturated hydraulic conductivity functions of the cap soils and the
underlying nonwoven GT to illustrate the contrast in K(ψ) relationships which is
conducive to the occurrence of capillary barrier effect.

Figure 4-3 shows the unsaturated hydraulic conductivity functions for the three
soils used to simulate the monolithic earthen cap and the underlying geotextile (GT) layer
for lysimeter. In order for capillary barrier effect to occur, the minimum condition is that
the unsaturated hydraulic conductivity of the underlying coarser-grained porous material
139

needs to be less than the overlying finer-grained soil layer (Khire et al. 2000). Figure 4-3
shows that the unsaturated hydraulic conductivity of the geotextile (GT) is less than the
overlying OK110 sand at matric suctions greater than about 20 cm. At 20 cm suction, the
hydraulic conductivity of OK110 sand is relatively high (~ 6.0 x 10

-3

cm/s). Figure 4-3

also shows that for the SM-ML soil, at about matric suction equal to 70 cm, the hydraulic
conductivity of the GT drops below that of the SM-ML soil. The hydraulic conductivity
of the SM-ML soil at 70 cm suction is about 10

-7

cm/s, which is relatively low. Hence,

while capillary barrier effect may occur for all three soils, its effect on percolation is
-6

expected to be relatively small when SM-ML soil (Ks = 9.0 x 10 cm/s) is used.

Initial and Boundary Conditions and Numerical Control Parameters
For constant infiltration simulations, a specified flux was applied at the ground surface
(Figure 4-1) for the lysimeter as well as for the actual cap. While the upper boundary of
the cap is typically modeled as an atmospheric boundary, a specified flux boundary
provides a condition to readily identify and quantify when capillary break occurs. The
specified flux was 1.5 x 10

-4

cm/s, 6.1 x 10

-6

-7

cm/s, and 2.1 x 10

cm/s for the OK110

fine sand, the SM soil, and the SM-ML soil, respectively. The flux values were selected
such that no runoff would be generated for the simulated cap and the value was low
enough to simulate unsaturated conditions in the cap. A unit gradient boundary condition
was imposed on the lower boundary of the model domains. The unit gradient boundary
used for the actual cap was applied to the bottom of the waste layer. Fayer et al. (1992)
and Khire et al. (1997) have used this boundary condition for lysimeters. Khire and
140

Mijares (2008) and Mijares et al. (2010) have used the same lower boundary condition
for simulations with waste layer.
Initial conditions were specified using matric suctions corresponding to an
average degree of saturation of about 40%. This value was used for all simulations for
consistency. A relatively drier (or wetter) initial condition for soil caps impacted the
onset of percolation but did not impact steady-state soil water storage and rate of
percolation. Spatial discretization of the model domain was optimized by conducting
sensitivity analysis. This was done by repeatedly refining the nodal spacing until
insignificant changes in simulated water balance parameters were achieved. The nodal
spacing between the nodes located near the upper and lower boundaries was relatively
small (1 mm). A maximum time step of 0.1 hr and a minimum time step of 10

-7

hr were

used for all the simulations. At any given time step, the maximum allowable mass
balance error for the whole profile was set at 10

-5

cm. For all numerical analyses, total

mass balance errors were less than 1%.
For field-scale simulations, monolithic earthen covers that were instrumented in
the field and numerically modeled by Khire et al. (1997) were reanalyzed in this study.
Instrumented field lysimeter test sections in East Wenatchee, Washington and Atlanta,
Georgia provided water balance assessment of earthen covers under semi-arid and humid
climates, respectively. In this paper, numerical simulations conducted by Khire
et al. (1997) were extended to incorporate a geocomposite drainage layer at the base of
the actual soil profiles to determine whether a capillary break occurs due to the GT for
the two test sections. Soil properties, meteorological data, boundary and initial
conditions, spatial discretization, and numerical controls were patterned from the original
141

simulations of Khire et al. (1997). Aside from including a geotextile layer at the base of
the models, additional simulations using SM and SM-ML soils were carried out to
determine the effect of soil properties on occurrence of capillary break under field
meteorological conditions. In all scenarios, the first year meteorological data was
repeated three times to model the long-term soil water storages and percolation.
Extending the simulation results to additional 10 years did not change the long-term
predictions.

RESULTS

Constant Infiltration Simulations
Figure 4-4 presents the cumulative percolation and soil water storage for OK 110 sand
subjected to a specified flux equal to 1.5 x 10

-4

cm/s at the upper boundary. The

predicted cumulative percolation and soil water storage for OK110 sand with geotextile
or with waste are almost identical. However, without GT, the soil water storage is
relatively low and percolation onset is early. The cumulative percolation without GT is
about 250% of the cumulative percolation with GT or waste. The difference in the
percolation is about 5 cm. Due to the relatively low unsaturated hydraulic conductivities
of GT or waste when they are relatively dry, the soil water storage of OK110 sand builds
up high enough to increase the degree of saturation of the GT or the waste high enough to
increase their hydraulic conductivities to carry the imposed flux at the top boundary.
Figure 4-4 shows the evidence of capillary break created by nonwoven GT or waste layer
when the overlying soil is a relatively permeable soil such as OK110 sand.

142

30

30
OK110 Fine Sand
K = 6.4 x 10
s

q = 1.5 x 10

-4

Capillary
barrier effect

cm/s

SWS - w/ GT or
w/ Waste

cm/s

20

25
20

SWS - w/o GT

15

15

10

10

Perc - w/ Waste
Perc - w/o GT

5

5
Perc - w/ GT

0
-5

0

0.2

0.4

0.6
0.8
Time (days)

1

Soil Water Storage (cm)

Cumulative Percolation (cm)

25

-3

0

1.2

-5

Figure 4-4: Simulated cumulative percolation and soil water storage for OK110 fine sand
under specified flux boundary condition.

Figure 4-5 presents the cumulative percolation and soil water storage for SM soil
subjected to a specified flux equal to 6.1 x 10

-6

cm/s at the upper boundary. The

predicted cumulative percolation and soil water storage for SM soil with a geotextile and
with waste are slightly different. The cumulative percolation without GT is about 210%
of the cumulative percolation with GT or waste. The difference in the percolation is about
5 cm. The percolation onset for the lysimeter with GT is slightly early compared to the
waste. However, without GT, the soil water storage is relatively low and percolation

143

onset occurs much earlier. Figure 4-5 shows the evidence of capillary break created by
nonwoven GT or waste layer when the overlying soil is an SM soil.

45

45
SM Soil

40

K = 2.7 x 10

-4

cm/s

40

q = 6.1 x 10

-6

SWS - w/ GT
SWS - w/ Waste

cm/s

30

35

SWS - w/o GT

s

35

30

25

25

20

20
Perc - w/o GT

15

15

10

10
Perc - w/ Waste

5

5
Perc - w/ GT

0
-5

Soil Water Storage (cm)

Cumulative Percolation (cm)

Capillary
barrier effect

0

12.5

25

37.5

50

62.5

0
75

-5

Time (days)
Figure 4-5: Simulated cumulative percolation and soil water storage for SM soil under
specified flux boundary condition.

Figure 4-6 presents the cumulative percolation and soil water storage for SM-ML
-7

soil subjected to a specified flux equal to 2.1 x 10

cm/s at the upper boundary. The

predicted cumulative percolation and soil water storage for SM-ML soil with a geotextile,
without geotextile, and with waste are about the same. The cumulative percolation
without GT is about 50% of the cumulative percolation with GT or waste. The difference
144

in the percolation is about 0.7 cm. Thus, while Figure 4-3 shows that the capillary barrier
effect is possible based on the differences in hydraulic conductivities of the SM-ML soil
and the GT or the waste interface, due to relatively low hydraulic conductivity of the
SM-ML soil, the capillary barrier effect does not yield lower percolation or significantly
greater soil water storage when a GT or waste layer exists below the cap. Thus, capillary
barrier effect is less pronounced when the soils used for the cap have relatively low
hydraulic conductivity.

15

35

K = 9.0 x 10

-6

s

10

q = 2.1 x 10

-7

Negligible capillary
barrier effect

cm/s
30

cm/s

SWS - All

5

25

Perc - w/GT or w/o GT

0

-5

20

Perc - w/Waste

0

200

400

600
800
Time (days)

1000

Soil Water Storage (cm)

Cumulative Percolation (cm)

SM-ML Soil

15
1200

Figure 4-6: Simulated cumulative percolation and soil water storage for SM-ML soil
under specified flux boundary condition.

145

Practical Implications
Based on the numerical results (Figures 4-4 to 4-6), evidence of capillary barrier effect is
characterized either by a significant relative delay in the onset of percolation or
difference in the peak soil water storage of the soil cover. For a monolithic soil cover, if
the underlying geotextile that is typically used at the lower boundary in a lysimeter is not
used, in order to satisfy the unit gradient lower boundary condition for the specified flux
at the top boundary, the matric suction at the lower boundary of the soil shall equate the
suction value corresponding to K( ψf ) = q (the applied or specified flux) as shown in
Figure 4-7. This suction shall correspond to ψf in the unsaturated hydraulic function of
the soil where its unsaturated hydraulic conductivity is equal to the applied infiltration
rate q. Hence, the soil profile would acquire a uniform water content equal to θf as
determined from its soil water characteristic curve (Figure 4-7a).
For a soil cap with underlying coarser layer, such as in a lysimeter with a
geotextile or an actual cap overlying a waste layer, the imposed unit gradient lower
boundary condition would require the matric suction in the coarser layer to drop to ψc,
which corresponds to the unsaturated hydraulic conductivity of the layer at the applied
infiltration rate q (Figure 4-7b). Consequently, at the interface, the suction is ψc in the
GT (or waste) and the overlying soil layer to satisfy continuity. Hence, the suction
distribution across the soil profile would be ψc at the bottom, increasing nonlinearly

146

Figure 4-7: Water retention curves (a); and unsaturated hydraulic conductivity functions (b) for fine-textured soil cap and coarsetextured GT or MSW.
147

upwards satisfying Richards’ equation but would not exceed a value of ψf. Because ψc is
less than ψf, θc would be greater than θf. This phenomenon, also referred to as the
capillary barrier effect, results in an increase in the soil water storage of the soil cap when
a geotextile layer (or waste layer) is present. The increase in soil water storage results in a
significant delay in the onset of percolation as shown in Figures 4-4 and 4-5.
Figures 4-4 to 4-7 show that while capillary break is always present when a
nonwoven geotextile layer is placed below a soil cap, the magnitude of the capillary
barrier effect varies depending upon the hydraulic properties of the soil cap and the
infiltration rate. Generally, as q decreases, the difference between ψc and ψf increases
relatively rapidly and results in significant increase in the soil water storage. Thus, the
degree or magnitude of capillary barrier effect is higher when the infiltration rate is
smaller. As shown in Figure 4-7b, capillary break only occurs whenever q < Kint. For a
typical atmospheric boundary condition that exists for caps, the infiltration rate varies.
While the scenarios modeled in Figures 4-4 to 4-6 assume constant infiltration rate to
illustrate the magnitude of capillary barrier effect for soils having varying saturated
hydraulic conductivity, for earthen caps, the net infiltration rate fluctuates by orders of
magnitude on a weekly to seasonal time scales.
Hence, in order to evaluate the magnitude of the capillary barrier effect, the
specified rate of infiltration was varied by several orders of magnitude for both SM soil
and SM-ML soil and the resulting effect on the SWS of the cap, with and without GT, is
presented in Figure 4-8. SWS ratio was calculated by dividing the SWS of the cap with
the GT layer by the SWS of the cap without GT. SWS ratio closer to one indicates
148

minimal capillary barrier effect while higher SWS ratio signifies greater capillary barrier
effect. Figure 4-8 shows that the SWS ratio is close to 1.0 for specified fluxes close to the
saturated hydraulic conductivity of the SM soil and SM-ML soil (no capillary barrier
effect), respectively. As the specified flux was decreased, the difference in the soil water
storage became consistently higher. For SM soil, a sharp increase in the SWS ratio
occurred indicating the presence of capillary break over a wide range of specified fluxes.

9

Thickness of
Cover Profile:
90 cm

8
7
180 cm

6

Less Capillary More Capillary
Barrier Effect Barrier Effect

SWS Ratio (SWS w/ GT / SWS w/o GT)

10

5
4
3
2
1
0

10

-15

SM Soil
-4
K = 2.7 x 10 cm/s
s

No Capillary
Barrier Effect
(SWS Ratio = 1.0)

SM-ML Soil
-6
K = 9.0 x 10 cm/s
s
90-cm or
180-cm thick
-13

10

10

-11

SWS Ratio = 1.0

10

-9

10

-7

-5

10

Specified Flux, q (cm/s)
Figure 4-8: Relative magnitude of capillary barrier effect as a function of applied
specified flux for SM and SM-ML soils.
149

For SM-ML soil, decrease in specified flux resulted only to slight increased in SWS ratio
indicating a lower degree of capillary barrier effect.
A set of simulations was repeated by considering a thicker soil cap (180-cm thick)
for both SM and SM-ML soils to determine whether cap thickness would have an impact
on SWS ratio. As shown in Figure 4-8, the thickness of the cap had insignificant effect on
the SWS ratio.
Thus, for earthen cover lysimeters which are typically built in arid and semi-arid
climates where the net infiltration rate through the cap is generally smaller than in humid
climates, the magnitude of capillary barrier effect would be higher and therefore needs to
be considered in modeling the cap or assessing the field results of lysimeter. However,
the results also show that regardless of the infiltration rate, earthen covers made up of
soils having relatively low hydraulic conductivities (less than 10

-5

cm/s) would result in

insignificant capillary barrier effect.

Field-scale Simulations
To confirm the key findings of the previously presented constant infiltration simulations,
selective field-scale simulations were conducted for instrumented field-scale lysimeters
located in semi-arid and humid climates.

Semi-arid Climate
Figure 4-9 shows the simulated percolation and SWS for a soil profile instrumented in
East Wenatchee, Washington by Khire et al. 1997. This simulation represents an earthen
cap in a semi-arid climate built with 60-cm thick compacted Wenatchee silty clay as
150

cover soil having a saturated hydraulic conductivity of 2.2 x 10

-7

cm/s. A 15-cm thick

topsoil layer is included with a saturated hydraulic conductivity of 4.5 x 10

-5

cm/s for

surface vegetation.
For the first year, the measured percolation is 0.79 cm, whereas simulated by
UNSAT-H without including the GT is 1.08 cm and 0.05 cm when the GT was included.
For the second year, the simulated percolation by UNSAT-H without including the GT is
1.53 cm and 0.86 cm when the GT was included. For the third year, the simulated
percolation is 1.57 cm (without GT) versus 0.87 cm (with GT). Due to the effect of the

30

30

22.5

25

SWS - w/ GT

15

20

SWS - w/o GT

7.5

15
Measured
(Khire et al. 1997)

0

0

Perc - w/o GT

Soil Water Storage (cm)

Cumulative Percolation (cm)

Wenatchee Soil
Semi-arid Climate

Long Term
Annual Percolation

Perc - w/ GT

365

730

10
1095

Time (days)
Figure 4-9: Simulated cumulative percolation and soil water storage for Wenatchee soil
under semi-arid climate boundary condition.
151

initial condition, while there is difference in the simulated percolation with and without
GT, the difference in percolation is relatively small whether GT is considered or not
when long-term values of percolation are compared (3rd year in this case). Figure 4-9
shows that the simulated SWS when GT was considered versus when GT was not
considered are almost identical. Hence, it can be inferred that, at this semi-arid site, the
effect of capillary break introduced by the GT on long-term percolation is insignificant.
Figures 4-10 and 4-11 show the simulated percolation and SWS for SM soil and
SM-ML soil, respectively, with and without GT under a semi-arid climate similar to the

60

30

SM Soil

55

Semi-arid Climate

50
45

25

40
SWS - w/ GT

35

Perc - w/o GT
Perc - w/ GT

30

20

25
20
15

15

Soil Water Storage (cm)

Cumulative Percolation (cm)

Long Term
Annual
Percolation

10
5
0

SWS - w/o GT

0

365

730

10
1095

Time (days)
Figure 4-10: Simulated cumulative percolation and soil water storage for SM soil under
semi-arid climate boundary condition.

152

60

30

SM-ML Soil

55

Semi-arid Climate

45

25
SWS - w/ GT

40
35
30

20

25

SWS - w/o GT
Long Term
Annual Percolation

20
15

15

Perc - w/ GT

Soil Water Storage (cm)

Cumulative Percolation (cm)

50

Perc - w/o GT

10
5
0

0

365

730

10
1095

Time (days)
Figure 4-11: Simulated cumulative percolation and soil water storage for SM-ML soil
under semi-arid climate boundary condition.

Wenatchee soil cap. The thickness of the soil profile and all other variables were kept the
same except for the topsoil layer wherein relatively permeable uniformly graded medium
sand (SP) was used to reduce or eliminate runoff to allow a consistent platform to
compare the results. The saturated hydraulic conductivity assigned to the SP topsoil was
-3

2.9 x 10 cm/s.
As shown in Figure 4-10, for the SM soil, the resulting SWS with GT is generally
higher than SWS without GT. Consequently, the percolation for a lysimeter with GT is
less than the percolation for a lysimeter without GT which indicates significant capillary
153

barrier effect. In contrast, for the SM-ML soil, minimal difference between simulated soil
water storage and percolation occurred for lysimeter without GT versus lysimeter with
GT (Figure 4-11). Hence, the difference in the simulated percolation for the SM-ML soil
with and without GT is relatively small.
Peak SWS for SM soil with GT is 26.0 cm while for SM soil without GT is
19.1 cm or a 36% increase in storage capacity due to significant capillary barrier effect.
Whereas the peak SWS for SM-ML soil with and without GT are both 27.3 cm. For the
original Wenatchee soil, peak SWS with GT is 25.8 cm while peak SWS without GT is
25.5 cm. Thus, the peak soil water storage can be used as an indicator for assessing the
magnitude of the capillary barrier effect as shown in SWS plots presented in Figures 4-8
to 4-11.
In order to compare the simulated SWS for all soil types with and without GT,
simulated SWS for lysimeters with GT was plotted against simulated SWS for lysimeters
without GT (Figure 4-12). The 1:1 line shows the region where SWS values are the same
for a lysimeter with and without GT. Points above the 1:1 line correspond to higher SWS
for earthen cap lysimeters underlined with GT and indicates the presence of capillary
barrier effect. As shown in Figure 4-12, SWS values for the original Wenatchee soil are
scattered near the 1:1 line indicating that there is insignificant difference between the soil
cap with GT and without GT for field conditions that covered dry periods as well as wet
periods. Similar trend is observed for SM-ML soil. Data points for SM soil are scattered
far from the 1:1 line, in the upper left corner. Few data points for SM soil that are near
the 1:1 line represent the initial condition wherein the same starting values of soil suction
was applied for both simulations with and without GT. As the initial wetting front moves

154

through the SM soil, the soil cap with GT retains more water compared to the soil cap
without GT resulting in the data points to shift above the 1:1 line. This indicates that
capillary barrier effect is indeed significant for SM soil.

28

Soil Water Storage - w/ GT (cm)

26

Wenatchee
Soil

SM Soil

24
SM-ML Soil

22
20
18
16
14

Semi-arid Climate

1:1 Line
12
12

14

16

18

20

22

24

26

28

Soil Water Storage - w/o GT (cm)
Figure 4-12: Simulated soil water storage for lysimeter with GT versus without GT under
semi-arid climate boundary condition.

Humid Climate
Figure 4-13 shows the simulated percolation and SWS for an instrumented lysimeter
located in Atlanta with and without GT. The field measured percolation and SWS for this
155

lysimeter are presented in Khire et al. (1997). The earthen cap in this humid climate
consisted of 90-cm thick compacted Georgia red clay as cover soil having a saturated
-6

hydraulic conductivity of 3.2 x 10 cm/s. The cap also consisted of a 15-cm thick topsoil
-4

layer having a saturated hydraulic conductivity of 1.0 x 10 cm/s.

50

100

Atlanta Soil
SWS - w/ GT

80
45
60
40
40
SWS - w/o GT

20

0
0

Measured
(Khire et al. 1997)

35

Soil Water Storage (cm)

Cumulative Percolation (cm)

Humid Climate

Long Term
Perc - w/ GT or w/o GT Annual Percolation

365

730

1095

30

Time (days)
Figure 4-13: Simulated cumulative percolation and soil water storage for Atlanta soil
under humid climate boundary condition.

The first year percolation simulated by UNSAT-H without GT is similar to the
result published by Khire et al. (1997). The resulting percolation is 4.15 cm for a
lysimeter without GT and 4.18 cm for a lysimeter with GT. UNSAT-H underpredicted
156

percolation because it overestimated the surface runoff (Khire et al. 1997). For the third
year which would represent a long-term scenario, the resulting percolation is 2.69 cm
(without GT) versus 3.10 cm (with GT). It can also be observed that percolation for
simulation with GT is slightly greater than that for simulation without GT. The relatively
small difference is attributed to the mass balance error reported by the model which is
about the same as the observed difference. Nevertheless, negligible difference between
simulated percolations occurs for earthen cap without GT versus with GT. Figure 4-13
also shows that simulated SWS for earthen cap without GT is very close to the simulated

48

400
Perc - w/o GT

SM Soil
Humid Climate

Long Term
Annual Percolation
Perc - w/ GT

300
250

41.5

SWS - w/ GT

35

200
150

28.5

100

Soil Water Storage (cm)

Cumulative Percolation (cm)

350

50
SWS - w/o GT

0
0

365

730

22
1095

Time (days)
Figure 4-14: Simulated cumulative percolation and soil water storage for SM soil under
humid climate boundary condition.

157

400

SM-ML Soil
Humid Climate

300

41.5
SWS - w/ GT

250
200

35

150
SWS - w/o GT

100
Perc - w/ GT or w/o GT

Long Term
Annual Percolation

28.5

Soil Water Storage (cm)

Cumulative Percolation (cm)

350

48

50
0
0

365

730

22
1095

Time (days)
Figure 4-15: Simulated cumulative percolation and soil water storage for SM-ML soil
under humid climate boundary condition.

SWS with GT. Thus, the peak SWS ratio is close to one. Hence, it can be inferred that the
magnitude of capillary barrier effect for this field study was insignificant.
Figures 4-14 and 4-15 show the simulated percolation and SWS for SM soil and
SM-ML soil, respectively, with and without GT for the humid site. The thickness of the
soil profile and all other variables were kept the same except for the topsoil layer where
SP soil was used instead. For SM soil, the resulting SWS with GT are greater than the
SWS without GT. In fact, the maximum SWS for the soil cap without GT is only
approximately equal to the minimum SWS for soil cap with GT. Peak SWS for SM soil

158

without GT is 36.7 cm while peak SWS for SM soil with GT is 42.6 cm or a 16%
increase in storage capacity. Although this signifies significant capillary break, the
increase in SWS due to capillary barrier effect in a humid climate is not as high as the
increase in SWS for a semi-arid climate. The inherent frequently high precipitation rate at
the humid location compared to the semi-arid location results in higher net infiltration
rate for the soil cap. The resulting infiltration rate is often closer to the saturated
hydraulic conductivity of the soil cap. As Figure 4-8 illustrates, the magnitude of
capillary barrier effect under such conditions is less significant.
For SM-ML soil, peak SWS with and without GT is about the same (38.1 cm).
Hence, capillary barrier effect is insignificant because both soil caps, with and without
GT, achieved similar water content at the onset of percolation breakthrough. This is also
evident from the cumulative percolation plot shown in Figure 4-15 wherein both curves
(with and without GT) overlap.
Figure 4-16 shows the comparison of simulated SWS for lysimeters with GT
versus lysimeters without GT for all soil types for the humid site. Data points for both
SM-ML soil and the original Atlanta soil spread near the 1:1 line indicating negligible
capillary barrier effect. In contrast, data points for SM soil are scattered far from the 1:1
line signifying greater magnitude of capillary barrier effect.
Results of the field-scale simulations agree with the observations obtained from
constant infiltration simulations. The hydraulic properties of cover soils and the applied
infiltration rate(s) determine whether significant capillary barrier effect can be expected
or not when a nonwoven GT is considered or not in the numerical simulation. The
magnitude of capillary barrier effect, as defined by the effect on long-term percolation,

159

48

Soil Water Storage - w/ GT (cm)

46
Atlanta
Soil

44
42
40
SM Soil

38
36
34
32
30

SM-ML Soil

28
26

Humid Climate

1:1 Line

24

22
22 24 26 28 30 32 34 36 38 40 42 44 46 48
Soil Water Storage - w/o GT (cm)
Figure 4-16: Simulated soil water storage for lysimeter with GT versus without GT under
humid climate boundary condition.

introduced by the non-woven geotextile in the geosynthetic drainage layer of a lysimeter
is negligible when the saturated hydraulic conductivity of the cap is less than 10

-5

cm/s.

Figure 4-17 summarizes the annual percolation difference between the lysimeter without
GT and the lysimeter with GT for the first year and long-term scenarios. Because landfill
earthen caps more often consist of soils having hydraulic conductivity that is less than or
equal to 10

-5

cm/s, the effect of GT on the long-term percolation is expected to be

160

∆ Annual Percolation (cm)
(Percolation w/o GT - Percolation w/ GT)

14

Semi-arid Climate

12
10
8

1st Year
6
4
2
Long-Term

0
-2

Wenatchee Soil

(K = 2.2 x 10

-7

∆ Percolation (cm)
(Percolation w/o GT - Percolation w/ GT)

s

SM-ML Soil

cm/s) (K = 9.0 x 10

-6

s

SM Soil

cm/s) (K = 2.7 x 10

-4

s

cm/s)

14

Humid Climate

12
10
8
6

1st Year

4
2
Long-Term

0
-2

SM-ML Soil

Atlanta Soil

(K = 3.2 x 10
s

-6

cm/s) (K = 9.0 x 10
s

-6

SM Soil

cm/s) (K = 2.7 x 10
s

-4

cm/s)

Figure 4-17: Annual percolation difference between lysimeter without GT and lysimeter
with GT for semi-arid (a); and humid climates (b).
161

insignificant. Previous study of Scanlon et al. (2005) where significant capillary barrier
effect have been observed under a long-term (25-yr) numerical simulation of an earthen
cover for their Texas site. The saturated hydraulic conductivity of the soil cover that was
simulated is 2.3 x 10

-4

cm/s. Hence, the results of Scanlon et al. (2005) are consistent

with the findings of this study. The capillary barrier effect may be significant if the
-5

hydraulic conductivity is greater than 10 cm/s.

SUMMARY AND CONCLUSIONS
This numerical study demonstrates that capillary break is introduced when an earthen cap
is underlain by a nonwoven geotextile or low unit weight municipal solid waste. While a
geotextile or a waste layer both create a capillary break, the magnitude of the capillary
barrier effect on the simulated percolation is negligible when the saturated hydraulic
-5

conductivity of the cover soils is 10 cm/s or less.
Results from the field-scale simulations further show that whenever capillary
break exists, the capillary barrier effect maybe significant during the first year,
irrespective of the soil type or meteorological conditions. As the soil water storage of the
cap increases due to precipitation and when percolation occurs, capillary break is
breached and will only be restored if the cap dries up and returns to the original state
prior to percolation breakthrough. For humid climates, the capillary barrier effect is not
as significant as for the drier climates regardless of the hydraulic conductivity of the
soils. Hence, for long-term percolation prediction, nonwoven geotextile may not be
considered when modeling earthen cap lysimeters.

162

REFERENCES

163

REFERENCES
Albright, W., Benson, C., Gee, G., Roesler, A., Abichou, T., Apiwantragoon, P., Lyles,
B., and Rock, S. (2004). “Field Water Balance of Landfill Final Covers,” Journal of
Environmental Quality, 33 (6): 2317-2332.
Baker, R., and Hillel, D. (1990). “Laboratory Tests of a Theory of Fingering During
Infiltration into Layered Soils,” Soil Science Society of America Journal, 54: 20–30.
Bathurst, R., Ho, A., and Siemens, G. (2007). “A Column Apparatus for Investigation of
1-D Unsaturated-Saturated Response of Sand-Geotextile Systems,” Geotechnical
Testing Journal, 30 (6): 1-9.
Benson, C., and Khire, M. (1995). “Earthen Covers for Semi-arid and Arid Climates,
Landfill Closures, GSP No. 53, ASCE, Reston, VA: 201-217.
Benson, C., Albright, W., Roesler, A., and Abichou, T. (2002). “Evaluation of Final
Cover Performance: Field Data from the Alternative Cover Assessment Program
(ACAP),” Proceedings, Waste Management 2002, Tucson, AZ.
Benson, C., Bohnhoff, G., Ogorzalek, A., Shackelford, C., Apiwantragoon, P., and
Albright, W. (2005). “Field Data and Model Predictions for an Alternative Cover,”
Waste Containment and Remediation, GSP No. 142, ASCE, Reston, VA: 1-12.
Bohnhoff, G., Ogorzalek, A., Benson, C., Shackelford, C., and Apiwantragoon, P. (2009).
“Field Data and Water-Balance Predictions for a Monolithic Cover in a Semiarid
Climate,” Journal of Geotechnical and Geoenvironmental Engineering, 135 (3):
333–348.
Fayer, M., Rockhold, M., and Campbell, M. (1992). “Hydrologic Modeling of Protective
Barriers: Comparison of Field Data and Simulation Results,” Soil Science Society of
America Journal, 56: 690-700.
Fayer, M. (2000). “UNSAT-H Version 3.0: Unsaturated Soil Water and Heat Flow Model
– Theory, User Manual, and Examples.” PNNL-13249, Pacific Northwest
Laboratories, Richland, Washington.
Iryo, T., and Rowe, R. (2003). “On the Hydraulic Behavior of Unsaturated Nonwoven
Geotextiles,” Geotextiles and Geomembranes, 21: 381-404.
Kazimoglu, Y., McDougall, J., and Pyrah, I. (2005). “Moisture Retention and Movement
in Landfilled Waste,” Proceedings, GeoProb 2005: International Conference on
Problematic Soils, Famagusta, Northern Cyprus, May 2005.
Kazimoglu, Y., McDougall, J., and Pyrah, I. (2006). “Unsaturated Hydraulic
Conductivity of Landfilled Waste,” Proceedings, Unsaturated Soils 2006, GSP No.
147, ASCE, Reston, VA: 1525-1534.

164

Khire, M., and Mijares, R. (2008). “Influence of the Waste Layer on Percolation
Estimates for Earthen Caps Located in a Sub-humid Climate,” Proceedings,
GeoCongress 2008, GSP No. 177, Geotechnics of Waste Management and
Remediation, ASCE, Reston, VA: 88-95.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering, 123
(8): 744-754.
Khire, M., Benson, C., and Bosscher, P. (1999). “Field Data From a Capillary Barrier and
Model Predictions with UNSAT-H,” Journal of Geotechnical and
Geoenvironmental Engineering, 125: 518–528.
Khire, M., Benson, C., and Bosscher, P. (2000). “Capillary Barriers: Design Variables
and Water Balance,” Journal of Geotechnical and Geoenvironmental Engineering,
126 (8): 695-708.
Mijares, R., Khire, M., and Johnson T. (2010). “Lysimeters Versus Actual Earthen Caps:
Numerical Assessment of Soil Water Storage,” Proceedings, GeoFlorida 2010,
GSP No. 199, Advances in Analysis, Modeling and Design, ASCE, Reston, VA:
2849-2858.
Mukherjee, M. (2008). “Instrumented Permeable Blankets for Estimating Subsurface
Hydraulic Conductivity and Confirming Numerical Models Used for Subsurface
Liquid Injection,” Ph.D. Dissertation, Michigan State University, East Lansing,
Michigan, 278 p.
Nyhan, J., Hakonson., T., and Drennon, B. (1990). “A Water Balance Study of Two
Landfill Cover Designs for Semiarid Regions,” Journal of Environmental Quality,
19: 281-288.
Ogorzalek, A., Bohnhoff, G., Shackelford, C., Benson, C., and Apiwantragoon, P. (2008).
“Comparison of Field Data and Water-Balance Predictions for a Capillary Barrier
Cover,” Journal of Geotechnical and Geoenvironmental Engineering, 134 (4):
470–486.
Park, K., and Fleming, I. (2006). “Evaluation of a Geosynthetic Capillary Barrier,”
Geotextiles and Geomembranes, 24: 64-71.
Scanlon, B., Christman, M., Feedy, R., Porro, I., Simunek, J., and Flerchinger, G. (2002).
“Intercode Comparisons for Simulating Water Balance of Surficial Sediments in
Semiarid Regions,” Water Resources Research, 38: 1323-1339.
Scanlon, B., Reedy, R., Keese, K., and Dwyer, S. (2005). “Evaluation of
Evapotranspirative Covers for Waste Containment in Arid and Semiarid Regions in
the Southwestern USA,” Vadose Zone Journal, 4: 55-71.

165

Stoltz, G., and Gourc, J. (2007). “Influence of Compressibility of Domestic Waste on
Fluid Conductivity,” Proceedings, 18th Congres Francais de Mecanique, Grenoble,
France.
Stormont, J., Henry K., and Evans, T. (1997). “Water Retention Functions of Four
Nonwoven Polypropylene Geotextiles,” Geosynthetics International, 2 (6):
661-672.
Stormont, J., and Anderson, C. (1999). “Capillary Barrier Effect from Underlying
Coarser Soil Layer,” Journal of Geotechnical and Geoenvironmental Engineering,
125: 641–648.
Stormont, J., and Morris, C. (2000). “Characterization of Unsaturated Nonwoven
Geotextiles,” Proceedings, Geo-Denver 2000, GSP No. 99, Advances in
Unsaturated Geotechnics, ASCE, Reston, VA: 153–164.
Tami, D., Rahardjo, H., Leong E., and Fredlund, D. (2004). “A Physical Model for
Sloping Capillary Barriers,” Geotechnical Testing Journal, 27: 1–16.
van Genuchten, M. (1980). “A Closed-Form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils,” Soil Science Society of America Journal, 44:
892-898.
Ward, A., and Gee, G. (1997). “Performance Evaluation of a Field-Scale Surface
Barrier,” Journal of Environmental Quality, 26: 694–705.

166

PAPER NO. 5: NUMERICAL ASSESSMENT OF PAN LYSIMETERS
USED FOR ESTIMATION OF GROUNDWATER RECHARGE FOR
NATURAL SYSTEMS

ABSTRACT
A laboratory soil column consisting of fine sand with a saturated hydraulic conductivity
of 4.5 x 10

-3

cm/s was built and instrumented to measure its hydraulic response to

constant infiltration of 1.5 x 10

-4

cm/s. The numerical model UNSAT-H with a water

table lower boundary condition was able to accurately predict the percolation and soil
water storage of the column. The calibrated numerical model was used for field-scale
simulations that were conducted to determine whether percolation estimates obtained
from pan lysimeters are representative of the groundwater recharge rate for the
corresponding natural system. Natural systems consisting of monolithic soil profile were
simulated for semi-arid and sub-humid climates. This study demonstrates that when pan
lysimeters are used for estimating groundwater recharge, the lysimeter should be thick
enough to overcome the capillary barrier effect introduced by the lower drainage
boundary. Thinner soil profiles used for constructing lysimeter underestimate the
recharge due to the capillary barrier effect. The higher the hydraulic conductivity of the
soil profile, the thicker the soil profile needs to become in order for the lysimeter to
estimate the recharge accurately. Furthermore, in wetter climates, the thickness of the soil
profile for the lysimeter could be less than the required profile thickness for a drier
climate. Generally, a lysimeter thickness of 1.2 m would be enough to capture the
groundwater recharge for the natural system.
167

INTRODUCTION
The primary source of groundwater recharge for natural systems is precipitation. The
groundwater recharge rate, which is also known as the rate of replenishment of the water
in aquifers, is dependent on the rate of infiltration across the vadose zone. Estimating
groundwater recharge may be undertaken under different spatial and temporal scales
depending on the required application and accuracy. Scanlon et al. (2002) categorized the
techniques used in quantifying groundwater recharge based on the three hydrologic
zones: surface water, unsaturated zone, and saturated zone. Within each of these zones,
the estimation techniques are further classified as physical, tracer, or numerical modeling.
Among all the techniques used for recharge estimation, the only method that is
considered direct for estimating natural groundwater recharge from the ground surface is
via the construction of a pan lysimeter. A pan lysimeter also can provide accurate
measurement of the various components of field water balance which include percolation,
surface runoff, soil water storage, basal percolation, and evapotranspiration. Lysimeter
studies have been performed since the end of the 17th century (Seiler and Gat 2007). In
the past, lysimeters are generally constructed using deep cylindrical pots with an open
2

surface area of about 1 m . These cylindrical lysimeters were typically used for
estimating groundwater recharge and were mechanically balanced to accurately measure
fluctuations in soil water storage and measure the deep percolation. For landfill earthen
cover application, pan lysimeters are more common. These lysimeters have much larger
surface area to capture the field-scale heterogeneities such as soil macropores and
fractures (Benson et al. 1994; Khire et al. 1997). Changes in the soil water storage are
determined by installing water content sensors to monitor the water content across the
168

soil profile. A diversion berm is constructed along the perimeter in order to divert surface
runoff from upslope of the lysimeter while directing the surface runoff within the
monitoring area to the collection system. The deep percolation is collected by installing a
pea gravel drainage layer or a geocomposite drainage layer at the lower boundary of the
pan lysimeter.
Recharge rates obtained from a lysimeter can be estimated at time scales from
minutes to years with a good precision of at least 1 mm/year (Gee and Hillel 1988;
Scanlon et al. 2002). Because lysimeters yield good data to study recharge mechanisms,
Gee and Hillel (1988) pointed out that quantification of drainage across a soil profile
using lysimeters for a long period under field meteorological conditions could provide the
basis for calibrating numerical models used for estimating regional or local groundwater
recharge. Flow of infiltrated water through the unsaturated zone to the water table is
controlled by the saturated and unsaturated hydraulic properties of the soil
(Krishnamurthi et al. 1977). In addition to the hydraulic properties, boundary conditions
also influence the estimation of recharge when pan lysimeters are used because the
lysimeters introduce a drainage boundary that does not exist in the natural system it
attempts to emulate.

OBJECTIVE
The key objective of the study presented in this paper is to numerically evaluate the
accuracy of the use of pan lysimeter to estimate natural recharge. Natural groundwater
recharge rate is defined in this paper as the resulting rate of deep drainage that reaches the
groundwater table as a consequence of redistribution of water across the soil profile in

169

response to the gradients in the energy state of the water (Fayer 2000). Lysimeter basal
percolation rate is compared to the deep drainage rate to evaluate the accuracy of using
pan lysimeter in estimating natural groundwater recharge. The key parameters evaluated
include hydraulic conductivity, thickness of the soil profile, and climate. In order to
validate the unsaturated flow model, a laboratory soil column underlain by a
geocomposite drainage layer was built and instrumented to monitor its soil water storage
and deep percolation under constant infiltration. The calibrated numerical model was
used to conduct numerical simulations to predict groundwater recharge rates in semi-arid
and sub-humid climates using pan lysimeters.

LABORATORY SOIL COLUMN
A soil column consisting of OK110 fine sand underlain with a geocomposite drainage
layer was built and instrumented to monitor its response under a one-dimensional
constant infiltration event. OK110 is a uniformly graded sand having D50 equal to
0.11 mm and USCS classification of SP (poorly graded sand). Figure 5-1 shows the photo
and the schematic of the 30 cm diameter soil column which was 90 cm tall. The column
was made up of a PVC pipe that was capped at its bottom. The PVC cap was modified by
inserting a circular plane to create a sloping impermeable bottom boundary where a
geocomposite drainage layer was placed. The geocomposite drainage layer consisted of a
geonet sandwiched between two nonwoven geotextiles. Table 5-1 shows the properties of
the soil and the geotextile used to fabricate the soil column. A perforated plastic tubing
was placed around the circumference of the geocomposite drainage layer to facilitate
drainage of infiltrated water. A 2-cm diameter outlet tubing was placed at the bottommost
170

point to collect the percolation and measure the resulting outflow rate. The entire set-up
was placed on top of a weighing scale to accurately measure and record the changes in
the soil water storage.

Figure 5-1: Photo and schematic of instrumented laboratory soil column.

The laboratory soil column was instrumented with water content sensors to
monitor the soil water storage. Six time domain reflectometry (TDR)-based water content
sensors were placed across the soil column with a vertical spacing of 15 cm. The miniTDR water content sensor has three pointed stainless steel rods mounted into a polymer
head. The probe rods are 6 cm long, have a diameter of 0.15 cm, and are spaced by
171

0.6 cm. The mini-TDR water content sensor was placed horizontally in the initially dry
column of fine sand and was connected to a multiplexer and a datalogger to continuously
monitor and record the apparent dielectric constant. The empirically derived calibration
equation by Topp et al. (1980) was used to convert the measured dielectric constants to
the instantaneous volumetric water contents.
To facilitate the application of a constant flux at the surface of the sand column,
an elevated Mariotte bottle was connected to a coil of perforated tubing placed on the
sand surface that irrigated the column. A 15-cm thick pea gravel layer wrapped with a
polymer insect mesh was also placed on top of the soil column to achieve a uniform
wetting front.

Table 5-1: Saturated and unsaturated hydraulic properties of the materials used to build
the laboratory soil column.

Soil/Material

θs
3

θr
3

3

3

α

(cm /cm ) (cm /cm ) (1/cm)

n

Ks
(cm/s)

Reference

OK110
Fine Sand

0.36

0.03

0.016

6.5

Geotextile

0.82

0

0.066

3.99

0.15

Park and Fleming
(2006)

GP Soil

0.30

0.01

0.574

2.44

1.0

Khire et al.
(2000)

-3

4.5 x 10

Mukherjee
(2008)

NUMERICAL MODELING
The finite-difference water balance model UNSAT-H (Fayer 2000) was used in this study
to mathematically simulate the response of the instrumented laboratory soil column
172

subjected to constant flux. Once UNSAT-H was validated for the lab sand column, it was
extended to conduct field-scale simulations to evaluate how lysimeter can simulate
groundwater recharge rates.
UNSAT-H numerically solves a modified form of Richards’ equation to compute
the flow of water through both saturated and unsaturated soil and is capable of simulating
steady-state and transient conditions. Equation 5-1 shows the governing equation that
UNSAT-H solves to mathematically simulate the flow of water in soil:

∂θ ∂ψ
∂ 
∂ψ

= −  K T (ψ )
+ K L (ψ ) + qVT  − S ( z , t )
∂ψ ∂t
∂z 
∂z


where

(5-1)

θ is the volumetric water content; ψ is the matric suction head; z is the vertical

coordinate,

t

is time;

K L (ψ )

is the unsaturated hydraulic conductivity for a given ψ ,

K T (ψ ) = K L (ψ ) + K V (ψ ) where K T (ψ ) is the isothermal water vapor
conductivity for a given

ψ ; qVT

is the thermal vapor flux density; and S is the sink

term that represents the water uptake by vegetation as a function of both depth and time.
The thermal vapor flux density is calculated by applying Fick’s law of vapor diffusion.
Equation 5-1 assumes that fluid is incompressible, liquid water flow is isothermal, and air
phase is continuous and at constant atmospheric pressure. Khire et al. (1997) summarizes
key features of UNSAT-H as they apply to simulating field-scale pan lysimeters.
UNSAT-H assesses the water balance of the soil profile using Equation 5-2:

173

Pr = P – RO – E – T – ∆S
where Pr is the basal percolation,

(5-2)

P is the precipitation, RO is the surface runoff, E

is the surface evaporation, T is the plant transpiration, and ∆S is the change in soil
water storage during a specified period of time. At the ground surface, UNSAT-H
separates the applied precipitation input into infiltration and surface runoff. The model
does not include as input the surface run-on or overland flow that runs onto the area being
modeled. It does not have algorithms for snowmelt and ground freezing during winter.
UNSAT-H also does not consider interception of water by the plant canopy nor delayed
infiltration of collected water in depressions on the soil surface. Whenever precipitation
exceeds the infiltration capacity of the soil profile, surface runoff is generated to prevent
ponding on the surface. Once water has infiltrated, it moves upward or downward across
the soil profile, depending on the prevailing evapotranspirative and hydraulic gradients.
Potential evapotranspiration is calculated from daily maximum and minimum air
temperatures, daily average dewpoint, net solar radiation, wind speed, and cloud cover
using a modified form of the Penman equation as reported by Doorenbos and Pruitt
(1977). Surface evaporation is calculated using an integrated form of Fick’s law of
diffusion that addresses the interrelationships between these three processes: (1) the flow
of heat to and from the soil surface; (2) the flow of water to the soil surface from below;
and (3) transfer of water vapor from the soil surface to the atmosphere (Hillel 1980;
Fayer 2000). Transpiration is calculated by applying the potential transpiration demand,
which is a function of the leaf area index and the growing season for the vegetation,
across the root zone in proportion to the relative root density at a particular depth. Soil

174

water storage is calculated by integrating the volumetric water content across the soil
profile. The resulting flux along the lower boundary is the basal percolation or deep
drainage for the soil profile. UNSAT-H was specifically developed to estimate deep
drainage rates. This model has also been routinely used for water balance modeling of
earthen caps (Khire et al. 1997; Khire et al. 2000; Benson et al. 2005; Scanlon et al. 2005;
Ogorzalek et al. 2008; Bohnhoff et al. 2009). For this study, one-dimensional simulations
were carried out using UNSAT-H Version 3.0.

Material Properties
Laboratory Soil Column
Saturated and unsaturated hydraulic properties of the materials used to build and simulate
the laboratory soil column are presented in Table 5-1. Unsaturated hydraulic conductivity
functions were estimated using the closed-form van Genuchten-Mualem expression
where the pore interaction term was set to 0.5 (van Genuchten 1980).
Hydraulic properties of nonwoven geotextile were obtained from Park and
Fleming (2006). The nonwoven, polypropylene, needle-punched, continuous fiber
2

geotextile has a mass per unit area of 550 g/m with a thickness of 4.0 mm and an
opening size of 0.05 to 0.15 mm. It has similar properties to that of the geotextile used in
the study of Stormont and Morris (2000). van Genuchten fitting parameters were
obtained based from the data points measured by Park and Fleming (2006) for the
geotextile’s water retention curve (Figure 5-2).

175

3

10
Matric Suction (cm)

10

2

10

1

Pea Gravel
(GP)

10

OK110
Fine Sand

0

Geotextile

10

-1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Vol. Water Content

Hydraulic Conductivity (cm/s)

10

2

10

0

10

-2

10

-4

10

-6

10

-8

10

OK110
Fine Sand
Geotextile
Pea Gravel
(GP)

-10

10

-1

10

0

10

1

10

2

10

3

Matric Suction (cm)

Figure 5-2: Water retention curves (a); and predicted hydraulic conductivity functions (b)
for the materials used in the laboratory soil column.
176

Field-scale Simulations
Table 5-2 shows the saturated and unsaturated hydraulic properties of the soils used to
simulate the groundwater recharge for natural systems. The natural system considered in
this study consisted of monolithic soil profile under semi-arid and sub-humid climates.
Figure 5-3 shows the soil water characteristic curves and the unsaturated hydraulic
conductivity functions for the soils presented in Table 5-2.

Table 5-2: Saturated and unsaturated hydraulic properties of the soils used to simulate
groundwater recharge rates.

Soils

θr

θs
3

3

3

3

(cm /cm ) (cm /cm )

α
(1/cm)

n

Ks
(cm/s)

GP Soil

0.30

0.01

0.574

2.44

1.0

SP Soil

0.40

0.01

0.038

2.69

2.9 x 10

SM Soil

0.42

0.02

0.005

1.48

2.7 x 10

SM-ML Soil

0.35

0.02

0.012

1.123

9.0 x 10

ML Soil

0.52

0.08

0.035

1.25

3.2 x 10

-3
-4
-6
-6

Reference
Khire et al.
(2000)
Khire et al.
(2000)
Khire et al.
(2000)
Khire et al.
(2000)
Khire et al.
(2000)

Initial and Boundary Conditions
Laboratory Soil Column
The initial condition was specified using a matric suction corresponding to the initially
dry OK110 fine sand. A specified flux was applied at the surface of the OK110 soil
column (Figure 5-1) which was equal to the actual rate of sprinkled water during the
laboratory experiment. These lower boundary conditions were simulated to determine
177

6

10
Matric Suction (cm)

10

5

10

4

10

3

10

2

SM

SP

10

1

10

0

10

GP

ML

-1

0.0

10
Hydraulic Conductivity (cm/s)

SM-ML

0

10

0.6

-6

10

0.5

GP

-4

10

0.2
0.3
0.4
Vol. Water Content

-2

10

0.1

-8

10

-10

10

-12

10

-14

10

SP
SM

-16

10

SM-ML
ML

-1

10

0

10

1

10

2

10

3

10

4

10

5

10

6

Matric Suction (cm)

Figure 5-3: Soil water characteristic curves (a); and predicted hydraulic conductivity
functions (b) for the soils used to simulate groundwater recharge rates.
178

which would better predict the measured response of laboratory soil column under the
constant infiltration event: (1) a unit gradient boundary at the base of the OK110 sand
column; (2) a unit gradient boundary at the base of the nonwoven geotextile that lines the
OK110 soil column; and (3) a constant water table at the base of a 90-cm thick coarse
gravel (GP) that was hypothetically placed underneath the OK110 soil column. The
coarse gravel was necessary to be able to apply a constant water table boundary condition
and the thickness was selected such that no upward flux of water will be generated on the
OK110 soil column due to capillarity of the gravel layer. Similar lower boundary has
been used for the field-scale pan lysimeters built in Detroit as presented in Paper No. 1.

Field-scale Simulations
For field-scale simulations, an atmospheric boundary condition was applied at the surface
of the monolithic natural system. The meteorological data obtained by Khire et al. (1997)
for East Wenatchee, Washington and Mijares et al. (2010) for Wayne, Michigan were
used to simulate the semi-arid and sub-humid climate conditions, respectively. The
precipitation was applied at an hourly frequency specifically during the time intervals it
occurred during a particular day. To simulate long-term scenario, the meteorological data
was successively repeated at least 10 times to generate a cyclic multi-year data. The total
number of years of simulations or the number of times the meteorological data was
repeated varied depending on the soil profile. To determine the long-term steady-state
condition, the criterion that was met was that the annual initial and final soil water
storage of the system should be equal. This was done to minimize the effect of the initial
conditions on the simulated water balance quantities.

179

Numerical Control Parameters
Spatial discretization of the model domain was optimized by conducting sensitivity
analysis. This was done by repeatedly refining the nodal spacing until insignificant
changes in simulated water balance parameters were achieved. The nodal spacing
between the nodes located near the upper and lower boundaries was relatively small
(1 mm). A maximum time step of 0.1 hr and a minimum time step of 10

-7

hr were used

for all the simulations. At any given time step, the maximum allowable mass balance
error for the whole profile was set at 10

-5

cm. For all numerical analyses, total mass

balance errors were less than 1%.

RESULTS
Laboratory Soil Column
Figure 5-4 shows the measured cumulative percolation and soil water storage response of
-4

the OK110 sand column subjected to a constant infiltration rate of 1.5 x 10

cm/s

(6 mL/min) at its surface. The flux that was selected was low enough to maintain
unsaturated conditions in the soil column and that no surface water ponding would be
generated. A much smaller flux value would not have been possible due to the limitation
of the Mariotte bottle and the perforated tubing used to irrigate water on the top surface
of the sand column.

180

30

30

K = 4.5 x 10

25

-3

s

GW

cm/s

25

Solid Lines - Measured
Dashed Lines - Simulated
GT
Measured SWS
(Weighing)

15

20

GT

20

15

UG
SWS
(Simulated)

10

10
UG

5

0

GW

Measured SWS
(TDR-Based)

0

0.5

Percolation
(Measured)

5

Percolation
(Simulated)

1

1.5

2

2.5

Soil Water Storage (cm)

Cumulative Percolation (cm)

OK110 Fine Sand

3

0

Elapsed Time (days)
Figure 5-4: Measured and simulated UNSAT-H cumulative percolation and soil water
storage for OK110 sand column.

As shown in Figure 5-4, the initially dry soil column reached a steady-state
condition after 1.75 days of constant infiltration. Beyond this period, percolation
breakthrough occurred and the resulting rate of outflow became equal to the applied
inflow rate. The measured soil water storage was determined by integrating the measured
water contents from the six mini-TDR sensors that were placed within the soil column.
The measured soil water storage agrees well with the measured increase in the mass of
the soil column obtained from the weighing scale where the soil column was placed as a
weighing lysimeter. Figure 5-4 shows that the soil water storage initially increased at a

181

rate approximately equal to the applied infiltration rate. Afterwards, it reached its
maximum value of about 24 cm after 1.75 days which corresponds to the time when
percolation breakthrough occurred.
The measured cumulative percolation and soil water storage obtained from the
laboratory soil column experiment provides a dataset to validate the UNSAT-H model for
various lower boundary conditions that are typically used. In addition the validated model
is used to make predictions for field scenarios. Several boundary conditions were
considered to determine which condition would better simulate the measured flow in the
OK110 sand column. Figure 5-4 shows the simulated cumulative percolation and soil
water storage obtained from three types of lower boundary conditions used in the model:
(1) UG which is a unit gradient boundary at the base of the monolithic OK110 soil
column; (2) GT which is a unit gradient boundary at the base of the nonwoven geotextile
that lines the OK110 soil column; and (3) GW which is a constant water table at the base
of a 90-cm thick coarse gravel (GP) that was hypothetically placed underneath the
OK110 soil column.
As presented in Figure 5-4, the simulated cumulative percolation and soil water
storage obtained when the lower boundary is simulated as a fixed GW within a gravel
layer best predicts the measured cumulative percolation and soil water storage,
respectively. The UG and GT lower boundary conditions underestimated the time when
percolation breakthrough occurs. Both UG and GT lower boundary conditions also
underestimated the maximum soil water storage reached by the soil column under steadystate condition.

182

For the fixed GW within a gravel layer lower boundary, the measured and
simulated water content profiles are about the same. It can also be observed from
Figure 5-5 that due to the presence of the geocomposite drainage layer in the OK110 soil
column, water builds up near the base of the soil column when percolation breakthrough
occurs. This phenomenon indicates the occurrence of capillary barrier effect. Khire and
Mijares (2010) pointed out that a geosynthetic capillary break occurs when the saturated
hydraulic conductivity of the finer grained soil layer in the capillary barrier is greater than
-5

10 cm/s. This finding is consistent with the data collected from the sand column.

0

OK110 Fine Sand

10

K = 4.5 x 10
s

20

cm/s

Simulated
(GW Lower Boundary
Condition)

30

Depth (cm)

-3

40
50

Measured

60
70
Water content profile
at breakthrough

80
90
0

0.05

0.1

0.15

0.2

0.25
3

0.3

0.35

0.4

3

Vol. Water Content (cm /cm )
Figure 5-5: Measured and simulated water content profile for OK110 fine sand column at
breakthrough.
183

Field-scale Simulations
Field-scale simulations were conducted to predict natural groundwater recharge rates in
semi-arid and sub-humid climates. Annual precipitation for East Wenatchee, Washington
is 26.5 cm with an annual potential evapotranspiration of 109.12 cm (PET/P ~ 4.12) was
selected to represent the semi-arid condition. Annual precipitation for Wayne, Michigan
is 86.2 cm with an annual potential evapotranspiration of 87.30 cm (PET/P ~ 1.01) was
selected to represent the sub-humid condition.
Monolithic natural systems consisting of 7.5 m thick soil profile were simulated
to determine the resulting groundwater recharge rates from the applied meteorological
data. A deeper soil profile up to 60 m thick was also considered to determine whether the
thickness affected the estimates for groundwater recharge. Actual fluxes were determined
at different depths of the soil profile and compared to lysimeter simulations. Lysimeter
simulations consisted of the same soil profile with thickness equal to the depths where the
actual fluxes for the natural system were determined. Figure 5-6 shows the conceptual
model of the monolithic natural system and lysimeter used for the simulations. Based on
the accuracy of GW boundary observed from the sand column experiment, a fixed GW
within a gravel layer lower boundary condition was used to determine the percolation
through a lysimeter and the recharge for the natural system.

Semi-arid Climate
Figure 5-7 shows the simulated groundwater recharge rates for a natural system
-3

consisting of SP soil (poorly graded sand; Ksat = 2.9 x 10

184

cm/s) under a semi-arid

(a)

(b)

Figure 5-6: Schematic of a lysimeter (a); and a monolithic natural system (b) used to
estimate natural groundwater recharge rates.
185

16

16

14

12
Natural Recharge (cm)

1.8 m
1.2 m
0.9 m

12

10

10

1.8 m
1.2 m

8

8

0.6 m
6

0.6 m
6

0.3 m

7.5 m

4

Lysimeter
(Thickness)

6.0 m
4.5 m

2

2

3.0 m
0

Soil Profile: SP

Natural Recharge
(Depth)

Semi-arid Climate

-2
0

50

100

150

4

Lysimeter Percolation (cm)

14

200

250

300

350

0
-2
400

Time (days)

Figure 5-7: Simulated natural groundwater recharge rates and lysimeter percolations for
SP soil in a semi-arid climate.

climate. The annual long-term recharge rate is about 14.0 cm which is approximately
53% of the precipitation received at the ground surface. Figure 5-7 also shows the actual
fluxes at different depths across the soil profile. Because the simulation represents longterm scenario under steady-state condition, the cumulative fluxes at various depths across
the soil profile are the same. This finding is consistent with the continuity and
conservation of mass that must be satisfied. However, as shown in Figure 5-7, the plot of
cumulative flux at shallower depths shows greater fluctuations. At deeper depths, the
fluctuations dampen because the effect of evapotranspirative gradient is less significant.
186

Figure 5-7 also presents the cumulative percolation obtained by simulating
corresponding lysimeters having soil profile thickness ranging from 0.6 m to 1.8 m.
Figure 5-7 shows that lysimeter having soil profile thickness less than 1.2 m
underestimates the groundwater recharge. As the lysimeter thickness increases, the
percolation captured by the lysimeter more closely approximates the groundwater
-3

recharge. Thus, for SP soil, which has a Ksat of 2.9 x 10

cm/s, under a semi-arid

climate, would require at least 1.2 m thick soil profile for the lysimeter to be
representative of the natural system.
Figure 5-8 shows the simulated groundwater recharge rates for a natural system
consisting of SM soil (silty sand; Ksat = 2.7 x 10

-4

cm/s) under a semi-arid climate. The

annual long-term recharge rate is 0 cm. This shows that the hydraulic conductivity of the
soil impacts the natural recharge. Lower hydraulic conductivity yield a lower recharge
rate. Similar to SP soil, the plot of cumulative flux at shallower depths shows greater
fluctuations and the fluctuations dampen at deeper depths. However, in this particular
case, due to the hydraulic conductivity of the SM soil being an order of magnitude lower
than SP soil, the resulting groundwater recharge becomes zero. Lysimeter simulations
consisting of 0.6 to 1.2 m thick profiles also predicted zero percolation for the SM soil in
the semi-arid climate. Field measured percolation for the Hanford site (Fayer et al. 1999)
in Richmond, Washington similarly resulted to zero percolation rates for 1.0 and 1.5 m
thick silt loam lysimeters.

187

8

8

Soil Profile: SM

7

7

Semi-arid Climate
Natural Recharge (cm)

Fayer et al. (1999):
1.0 & 1.5-m Thick; Measured

5

5
4

4
0.3 m

3

3
0.6 m

Natural
Recharge
(Depth)

2

1.8 m
2.4 m
3.0 m

1
0

4.5 m

-1
0

50

Lysimeter
(0.6 & 1.2-m
Thick)

1.2 m

100

150

200

1
0

6.0 m
250

2

Lysimeter Percolation (cm)

6

6

300

350

-1
400

Time (days)

Figure 5-8: Simulated natural groundwater recharge rates and lysimeter percolations for
SM soil in a semi-arid climate.

Since the SM soil profile yielded zero recharge rate and lysimeter percolation for
the semi-arid climate, an SP-SM soil having hydraulic conductivity in between SP and
-4

SM was simulated. SP-SM soil (poorly graded sand with silt) has a Ksat of 5.8 x 10 cm/s
and has unsaturated hydraulic properties that are similar to the SP soil. Figure 5-9 shows
the simulated groundwater recharge rates for a natural system consisting of SP-SM soil.
The annual long-term recharge rate is about 13.3 cm and is slightly lower than the annual
long-term recharge rate for the SP soil due to a lower hydraulic conductivity. Figure 5-9
also shows that a lysimeter having a soil profile thickness of at least 0.9 m would be
188

needed to capture the natural groundwater recharge rate. This thickness is less compared
to that required for SP soil due to a lower hydraulic conductivity. Thus, a lower hydraulic
conductivity of a soil profile requires less thick lysimeter to be equivalent to the natural
system.

16

16
14

1.2 m
0.9 m
0.6 m

10

10
Lysimeter
(Thickness)

1.2 m

8

7.5 m

0.6 m
6

8

6.0 m
6

0.3 m
4.5 m

4

4
3.0 m

2
1.8 m
0

2

Soil Profile: SP-SM

Natural Recharge
(Depth)

Semi-arid Climate

-2
0

50

100

Lysimeter Percolation (cm)

12

12
Natural Recharge (cm)

14

150

200

250

300

350

0
-2
400

Time (days)

Figure 5-9: Simulated natural groundwater recharge rates and lysimeter percolations for
SP-SM soil in a semi-arid climate.

Sub-humid Climate
Figure 5-10 shows the simulated groundwater recharge rates for a natural system
consisting of SM soil in a sub-humid climate. The annual long-term recharge rate is about

189

15.5 cm which is approximately 18% of the precipitation. Figure 5-10 also shows the
cumulative percolation obtained from lysimeter simulations with different thicknesses
(1.8 to 6.0 m thick). It can be seen that the lysimeter underestimates the groundwater
recharge rate. A lysimeter with a thickness greater than 6.0 m is necessary to capture the
annual groundwater recharge rate.

20

20

Soil Profile: SM
Sub-humid Climate
15
6.0 m
0.6 m
10

4.8 m
Natural
Recharge
(Depth)

5

7.5
6.0
4.8
3.6
3.0
1.8
1.2

0
0.6 m
0.3 m

-5
0

50

100

m
m
m
m
m
m
m

150

3.6 m
1.2 m
3.0 m
1.8 m

10

5

Lysimeter Percolation (cm)

Natural Recharge (cm)

15

0

Lysimeter
(Thickness)
200

250

300

350

-5
400

Time (days)

Figure 5-10: Simulated natural groundwater recharge rates and lysimeter percolations for
SM soil in a sub-humid climate.

Figures 5-11 and 5-12 present the simulated groundwater recharge rates for a
natural system consisting of SM-ML and ML soils, respectively, under a sub-humid

190

-6

climate. SM-ML is sandy silt with Ksat = 9.0 x 10

cm/s and ML soil is silt with Ksat =

-6

3.2 x 10 cm/s. In order to eliminate surface runoff, a 0.6 m thick topsoil layer consisting
of SM soil was considered. The annual long-term recharge rate for SM-ML soil is
approximately 6.65 cm and 5.66 cm for ML soil due to lower hydraulic conductivities.
For both soils in sub-humid climate, Figures 5-11 and 5-12 show that at least 0.6 cm thick
lysimeter (with a 0.6 cm topsoil layer) is necessary to capture the annual groundwater
recharge rate for the natural system.

8

8

Soil Profile: SM-ML
Sub-humid Climate
6

4.8 m
6.0 m

4

4
7.5 m

3.6 m

Natural
Recharge
(Depth)

2

2.4 m
2

1.8 m
Lysimeter
(1.8-m Thick)

1.2 m
0.9 m
0.6 m

0

Lysimeter
(0.6-m Thick)

0.3 m
-2
0

50

100

150

200

250

300

350

Lysimeter Percolation (cm)

Natural Recharge (cm)

6

0

-2
400

Time (days)

Figure 5-11: Simulated natural groundwater recharge rates and lysimeter percolations for
SM-ML soil in a sub-humid climate.

191

7

7

Soil Profile: ML
Sub-humid Climate

6

5

5
7.5 m
3.6 m
2.4 m
1.8 m

4

3

4
Lysimeter
(1.2-m Thick)

1.2 m
Natural
Recharge
(Depth)

2

3

0.9 m
2
0.6 m

1

Lysimeter
(0.6-m Thick)
1

0.3 m

0
0

50

100

150

200

Lysimeter Percolation (cm)

Natural Recharge (cm)

6

250

300

350

0
400

Time (days)

Figure 5-12: Simulated natural groundwater recharge rates and lysimeter percolations for
ML soil in a sub-humid climate.

Practical Implications
Figure 5-13 shows the ratio of groundwater recharge rate for a natural system and
percolation estimates obtained from a lysimeter using various thicknesses of the soil
profile. Figure 5-13(a) shows that for semi-arid climates, for soils with saturated
-3

hydraulic conductivity greater than 10 cm/s, the lysimeter needs to be relatively thick to
obtain representative recharge estimates. Whereas for sub-humid climates as shown in
-5

Figure 5-13(b), for soils with saturated hydraulic conductivity greater than 10

192

cm/s, the

1

Natural Recharge (cm)
Lysimeter Percolation (cm)

10

(a)
1.2-m Thick
See Figure 5-14

SP
SP-SM
0

10

Natural Recharge (cm)
Lysimeter Percolation (cm)

Lysimeter
representative
of natural
system

SM

Semi-arid Climate
1.0

10.0

Thickness (m)

1.2-m Thick
See Figure 5-14

(b)

1

10

SM

SM-ML
0

10

Lysimeter
representative
of natural
system

Sub-humid Climate

ML

1.0

10.0
Thickness (m)

Figure 5-13: Ratio of natural groundwater recharge and percolation estimates for various
lysimeter profile thicknesses in semi arid (a); and sub-humid (b) climates.
193

10

1

Natural Recharge (cm)
Lysimeter Percolation (cm)

Thickness of Lysimeter Soil Profile = 1.2 m

Sub-humid
Climate
SM
Soil
ML SM-ML
Soil Soil

10

SP-SM
Soil

SP
Soil

0

Semi-arid
Climate

10

-6

-5

10

10

-4

10

-3

-2

10

Saturated Hydraulic Conductivity (cm/s)

Figure 5-14: Ratio of natural groundwater recharge and percolation estimates for various
saturated hydraulic conductivity of the soil.

lysimeter needs to be very thick (6 m or more) to obtain representative recharge
estimates. This is because the capillary barrier effect is significant for these permeable
soils that would cause the lysimeter to measure lower percolation, thereby
underestimating the recharge rate. Figure 5-14 shows the ratio of groundwater recharge
rate for a natural system and percolation estimates obtained from a 1.2 m thick lysimeter
for various saturated hydraulic conductivity of the soil. It can be seen that for a given
lysimeter thickness, as the soil becomes permeable, the lysimeter percolation further
underestimates the recharge rate.
194

SUMMARY AND CONCLUSION
This study presents a numerical assessment of recharge rate estimated by lysimeters as a
function of thickness of soil profile, hydraulic properties of soils, and the climate. A
laboratory soil column consisting of fine sand underlain by a geocomposite drainage
layer was built and instrumented to monitor its response under constant infiltration of
water from the surface. Among the UNSAT-H simulations that were carried out, the
numerical model with a fixed GW table within a gravel layer lower boundary condition
was able to capture the measured cumulative percolation and soil water storage for the
instrumented soil column relatively accurately. The calibrated model was used for fieldscale simulations to determine natural groundwater recharge rates for natural systems
consisting of monolithic soil in semi-arid and sub-humid climates. Lysimeter simulations
were also conducted to determine whether percolation estimates obtained from a
lysimeter are representative of the groundwater recharge rate for the corresponding
natural system.
The numerical results suggest that the lysimeter soil profile needs to be thick
enough to minimize the capillary barrier effect that is inevitably introduced at the lower
boundary. The capillary barrier effect results in the underestimation of natural
groundwater recharge rate. In general, in wetter climates, the thickness of the soil profile
for the lysimeter could be less than that required for a drier climate. In addition, a lower
hydraulic conductivity soil profile would require a thinner soil profile to capture the
recharge as opposed to a higher hydraulic conductivity soil profile. Therefore, site
specific water balance simulations need to be carried out to size the lysimeter in order to
account for the effect of these key parameters.

195

REFERENCES

196

REFERENCES
Benson, C., Bosscher, P., Lane, D., and Pliska, R. (1994). “Monitoring System for
Hydrologic Evaluation of Landfill Final Covers,” Geotechnical Testing Journal,
17 (2): 138-149.
Benson, C., Bohnhoff, G., Ogorzalek, A., Shackelford, C., Apiwantragoon, P., and
Albright, W. (2005). “Field Data and Model Predictions for an Alternative Cover,”
Waste Containment and Remediation, GSP No. 142, ASCE, Reston, VA: 1-12.
Bohnhoff, G., Ogorzalek, A., Benson, C., Shackelford, C., and Apiwantragoon, P. (2009).
“Field Data and Water-Balance Predictions for a Monolithic Cover in a Semiarid
Climate,” Journal of Geotechnical and Geoenvironmental Engineering, 135 (3):
333–348.
Doorenbos, J., and Pruitt, W. (1977). “Guidelines for Predicting Crop Water
Requirements,” FAO Irrigation Paper No. 24, 2nd ed., Food and Agriculture
Organization of the United Nations, Rome, Italy: 1-107.
Fayer, M., Murphy, E., Downs, J., Khan, F., Lindenmeier, C., and Bjornstad, B. (1999).
“Recharge Data Package for the Immobilized Low-Activity Waste 2001
Performance Assessment,” PNNL-13033, Pacific Northwest National Laboratory,
Richland, Washington.
Fayer, M. (2000). “UNSAT-H Version 3.0: Unsaturated Soil Water and Heat Flow Model
– Theory, User Manual, and Examples,” PNNL-13249, Pacific Northwest
Laboratories, Richland, Washington.
Gee, G., and Hillel, D. (1988). “Groundwater Recharge in Arid Regions: Review and
Critique of Estimation Methods,” Hydrological Processes, 2: 255–266.
Hillel, D. (1980). Applications of Soil Physics, Academic Press, Inc., New York.
Khire, M., and R. Mijares. (2010). “Effect of Geocomposite Drainage Layer on Water
Balance of Earthen Cap Lysimeters,” Proceedings, 2010 Global Waste
Management Symposium, San Antonio, TX.
Khire, M., Benson, C., and Bosscher, P. (1997). “Water Balance Modeling of Earthen
Final Covers,” Journal of Geotechnical and Geoenvironmental Engineering,
123 (8): 744-754.
Khire, M., Benson, C., and Bosscher, P. (2000). “Capillary Barriers: Design Variables
and Water Balance,” Journal of Geotechnical and Geoenvironmental Engineering,
126 (8): 695-708.
Krishnamurthi, N., Sunada, D., and Longenbaugh, R. (1977). “Mathematical Modeling of
Natural Groundwater Recharge,” Water Resources Research, 13 (4): 720-724.

197

Mijares, R., Khire, M., and Johnson T. (2010). “Lysimeters Versus Actual Earthen Caps:
Numerical Assessment of Soil Water Storage,” Proceedings, GeoFlorida 2010, GSP
No. 199, Advances in Analysis, Modeling and Design, ASCE, Reston, VA:
2849-2858.
Mukherjee, M. (2008). “Instrumented Permeable Blankets for Estimating Subsurface
Hydraulic Conductivity and Confirming Numerical Models Used for Subsurface
Liquid Injection,” Ph.D. Dissertation, Michigan State University, East Lansing,
Michigan, 278 p.
Ogorzalek, A., Bohnhoff, G., Shackelford, C., Benson, C., and Apiwantragoon, P. (2008).
“Comparison of Field Data and Water-Balance Predictions for a Capillary Barrier
Cover,” Journal of Geotechnical and Geoenvironmental Engineering, 134 (4):
470-486.
Park, K., and Fleming, I. (2006). “Evaluation of a Geosynthetic Capillary Barrier,”
Geotextiles and Geomembranes, 24: 64-71.
Scanlon, B., Healy, R., and Cook, P. (2002). “Choosing Appropriate Techniques for
Quantifying Groundwater Recharge,” Hydrogeology Journal, 10: 18-39.
Scanlon, B., Reedy, R., Keese, K., and Dwyer, S. (2005). “Evaluation of
Evapotranspiration Covers for Waste Containment in Arid and Semiarid Regions in
the Southwestern USA,” Vadose Zone Journal, 4: 55-71.
Seiler, K., and Gat, J. (2007). Groundwater Recharge from Run-off, Infiltration and
Percolation, Water Science and Technology Library, Vol. 55, Springer, The
Netherlands, 244 p.
Stormont, J., and Morris, C. (2000). “Characterization of Unsaturated Nonwoven
Geotextiles,” Proceedings, Geo-Denver 2000, GSP No. 99, Advances in
Unsaturated Geotechnics, ASCE, Reston, VA: 153–164.
Topp, G., Davis, J., and Chinnick, J. (1980). “Electromagnetic Determination of Soil
Water Content: Measurements in Co-axial Transmission Lines,” Water Resources
Research, 16 (3): 574-582.
van Genuchten, M. (1980). “A Closed-Form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils,” Soil Science Society of America Journal, 44:
892-898.

198

SUMMARY AND CONCLUSIONS

This dissertation aimed to evaluate the difference in the hydraulic performance of a
lysimeter versus an actual earthen cap with underlying landfilled waste.
Field-scale test sections were built and instrumented at a landfill near Detroit,
Michigan consisting of compacted and uncompacted native glacial till (clay) soils. These
caps were 1.8 m thick. Lysimeter pans were installed in the middle of each test sections
to collect and quantify the percolation through the soil covers. The instrumented area of
the test section was expanded upslope and downslope of the lysimeter to monitor the soil
water storages within and beyond the lysimeter footprint in order to evaluate the effect of
a lysimeter lower boundary.
Water balance models UNSAT-H and Vadose/W were used to simulate the field
measured percolation and soil water storage and to estimate the percolation across the
interface between the overlying soil cap and the underlying landfilled waste. Field-scale
simulations under semi-arid and humid climates were also conducted to determine the
effect of the hydraulic properties of the cover soils and the underlying waste, as well as
the presence of a nonwoven geotextile, on percolation values measured by the lysimeter.
The key findings of this study are as follows:
(1)

Percolation for the compacted clay test section was about few millimeters per year
versus it was in tens of centimeters for the uncompacted test section due to about
two orders greater field hydraulic conductivity.

(2)

The soil water storages for the portions of the uncompacted test section that were
underlain by the waste were typically greater than those for the corresponding

199

lysimeters. However, for the compacted test section, there was no significant
difference between the soil water storage for the actual cap and the lysimeter.
(3)

UNSAT-H and Vadose/W were able to simulate the measured percolation through
the compacted test section. However, both numerical models were not able to
capture the macropore flow through the uncompacted test section primarily due to
incapability of these models to simulate non-Darcian flow. Variations in the field
measured soil water storages were generally captured by the numerical models.

(4)

Estimated percolation across the interface between the overlying soil cap and the
underlying landfilled waste showed upward fluxes of water which indicates that
the overlying soil cap has the capability to pull moisture from the underlying
material under evapotranspirative gradients. Thus, net percolation for actual caps
predicted by the validated models was negative.

(5)

The numerical results indicate that lower soil water storage corresponds to greater
percolation, and vice versa. The lysimeter generally has lower soil water storage
than the corresponding actual cap. The lysimeter, in general, results in greater
percolation compared to the corresponding actual cap. The lysimeter versus actual
cap hydrologic performance difference becomes relatively small if the hydraulic
-6

conductivity of the soil is less than 10 cm/s.
(6)

The capillary barrier effect that is introduced by a nonwoven geotextile used as a
drainage layer in a lysimeter influences the long-term percolation significantly
only when the saturated hydraulic conductivity of the soil is greater than

200

-5

10

cm/s. In addition, for humid climates, the capillary barrier effect is not as

significant as for the drier climates regardless of the hydraulic conductivity of the
soil.

201