Original Research

C.A. Garcia*
B.J. Andraski
D.A. Stonestrom
C.A. Cooper
J. Šimůnek
S.W. WheatcraftInteracting Vegetative and Thermal
Contributions to Water Movementin Desert Soil
Thermally driven water-vapor flow can be an important component of total water movement in bare soil and in deep unsaturated zones, but this process is o en neglected when
considering the eﬀects of soil–plant–atmosphere interactions on shallow water movement.
The objectives of this study were to evaluate the coupled and separate eﬀects of vegetative and thermal-gradient contributions to soil water movement in desert environments.
The evaluation was done by comparing a series of simulations with and without vegetationand thermal forcing during a 4.7-yr period (May 2001–December 2005). For vegetated soil,
evapotranspiration alone reduced root-zone (upper 1 m) moisture to a minimum value (25mm) each year under both isothermal and nonisothermal conditions. Variations in the leaf
area index altered the minimum storage values by up to 10 mm. For unvegetated isothermal and nonisothermal simulations, root-zone water storage nearly doubled during thesimulation period and created a persistent driving force for downward liquid fluxes below
the root zone (total net flux ?1 mm). Total soil water movement during the study period
was dominated by thermally driven vapor fluxes. Thermally driven vapor flow and condensation supplemented moisture supplies to plant roots during the driest times of each year.
The results show how nonisothermal flow is coupled with plant water uptake, potentiallyinfluencing ecohydrologic relations in desert environments.
Abbreviations: ET, evapotranspiration; LAI, leaf area index; PET, potential evapotranspiration.

Vegetation provides important controls on hydrologic fluxes in desert ecosystems.
Coupled and separate effects ofvegetative and thermal-gradientcontributions to arid soil-water movement are evaluated using simulations
with and without vegetation andthermal forcing. Thermal gradients
interact with root uptake to limit subroot-zone percolation and provide
supplemental moisture to plants inlate summer.
C.A. Garcia, B.J. Andraski, U.S. Geological
Survey, 2730 N. Deer Run Road, Carson City,
NV 89701; D.A. Stonestrom, U.S. Geological
Survey, 345 Middlefield Road, Menlo Park,CA 94025; C.A. Cooper, Desert ResearchInstitute, 2215 Raggio Parkway, Reno, NV
89512; J. Šimůnek, Dep. of Environmental Sciences, Univ. of California Riverside,
Riverside, CA, 92521; S.W. Wheatcraft,
Wheatcraft & Associates LLC, 3155
Heatheridge Lane, Reno, NV 89509. *Corresponding author (cgarcia@usgs.gov).
Vadose Zone J. 10:552–564
doi:10.2136/vzj2010.0023
Received 12 Feb. 2010.
Posted online 30 Mar. 2011.
© Soil Science Society of America
5585 Guilford Rd., Madison, WI 53711 USA.

All rights reserved. No part of this periodical may
be reproduced or transmi ed in any form or by anymeans, electronic or mechanical, including photocopying, recording, or any information storage andretrieval system, without permission in writing fromthe publisher.

2011, Vol. 10

When considering water resources, waste isolation, and contaminant transport, a thoroughunderstanding of soil–plant–atmosphere interactions that control subsurface moisture
fluxes is essential. Because water fluxes in arid environments are often small, an evaluation of subsurface processes requires a combination of adequate field measurements andnumerical models (Phillips, 1994; Scanlon and Milly, 1994).
Previous studies showed that desert plants have a considerable effect on water flow processes in shallow desert soils (the upper 1 m) and thick unsaturated zones (10s of meters).
One- to 12-yr field studies by Fischer (1992), Andraski (1997a), and Scanlon et al. (2003)
showed a predominantly upward driving force for isothermal flow below the root zone ofdesert shrubs. The presence of native vegetation in arid and semiarid environments has
been shown to eliminate deep drainage by limiting root-zone soil moisture accumulation(Gee et al., 1994). An 8-yr lysimeter study near the Nevada Test Site in southern Nevada
indicated that evapotranspiration (ET) from vegetated soils reduced soil water storage at 10times the rate of evaporation from bare soil alone (Scanlon et al., 2005a). This behavior was
also reflected in numerical modeling studies by Walvoord et al. (2002, 2004) and Scanlon
et al. (2003), which indicated that sparsely vegetated, thick vadose zones in the arid western United States are dominated by low water potentials and upward hydraulic gradients.
Thermally driven water vapor flow is an important process that can affect the water balance,water movement, and contaminant transport in arid climates as a result of dry soils andsteep temperature gradients (Scanlon and Milly, 1994; Andraski et al., 2005; Saito et al.,2006). Field-based analytical models of contaminant movement through native, vegetatedsoil in the Amargosa Desert indicate that shallow vapor-phase tritium fluxes were upward
and one to three orders of magnitude greater than liquid tritium fluxes (Andraski et al.,2005). Numerical models simulating water flow in the arid southwestern United Statesindicate that thermally driven vapor fluxes are dominant throughout most of the unsaturated zone (Scanlon et al., 2003; Walvoord et al., 2004). Shallow water flow simulations
evaluating vegetative controls on water movement within natural and engineered soil in

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arid regions typically focus on liquid water flow (Dong et al., 2003;
Scanlon et al., 2005b; Young et al., 2006), however, neglecting thepotential for water vapor transport. Yin et al. (2008) incorporated
thermal vapor flow when simulating shallow paleowater fluxes, but
their results documented total water fluxes rather than isothermal
and thermal liquid water and water vapor components.
The objectives of this study were to evaluate vegetative and thermal
vapor controls on soil water movement in an arid environment. The
approach was to compare numerical simulations of coupled liquidwater, water vapor, and heat flow in vegetated and unvegetated soil
and to compare simulations with and without heat flow in vegetated soil. The model was accepted a priori as providing an accurate
theoretical basis for exploring the processes incorporated therein;
therefore no attempt was made to calibrate the model. Sensitivity
analyses of leaf area index (LAI) and soil texture (sediment lithology)
were used to understand the factors controlling water movement.
In contrast to previous modeling studies (Walvoord et al., 2002;
Scanlon et al., 2003; Mayers et al., 2005), which applied a constant-head root sink at a fi xed sub-root-zone depth to represent
ET from a sparsely vegetated landscape, this study simulated the
dynamic processes of evaporation, transpiration, and subsurface
water flow in response to climate variability. The study used a heatand-mass modeling approach similar to that of Yin et al. (2008),
who evaluated changes in plant water uptake and Cl− mass balance during the last 18,000 yr of reconstructed climate change.
The current study executed a detailed analysis of the effects ofheat flow on soil water movement in and beneath the root zoneof vegetated soil during a recent 4.7-yr period. The analysis represents the first known attempt to differentiate the separate andcombined influences of gas and liquid water movement as theyinteract with vegetation in the current arid environment. The study
period included El Niño Southern Oscillation driven precipitation
extremes, including the driest and third wettest years on record.

6 Methods

Field Site and Data Collection

The Amargosa Desert Research Site is located in the northern
Mojave Desert, about 17 km south of Beatty, NV, and 20 km eastof Death Valley National Park (Fig. 1). In the Basin and Range
Province, the Amargosa Desert is bounded by Paleozoic rock andTertiary volcanic rock mountains (Fischer, 1992). Surface soils
are mapped as the Yermo (loamy-skeletal)–Arizo (sandy-skeletal)
association (NRCS, 2004). Sediments are predominantly fluvial
deposits consisting of several sand and gravel sequences (Nichols,
1987). Precipitation averages 112 mm yr−1 (1981–2005) and ishighly variable from month to month and year to year (Johnson
et al., 2007). Depth to the water table ranges from 85 to 115 m
below the land surface (Fischer, 1992). The sparsely vegetated studysite is dominated by creosote bush [Larrea tridentata (Sessé & Moc.
ex DC.) Coville], an evergreen shrub (Smith et al., 1997). The root

Fig. 1. Location map showing the Amargosa Desert Research Site
(ADRS) near Beatty, NV. Base from USGS digital data (Universal
Transverse Mercator projection, Zone 11, North American Datumof 1983).

system of creosote bush can exceed 4 m radially (Gile et al., 1998)
and the rooting depth generally corresponds with the typical penetration depth of precipitation (<1 m; Andraski, 1997a). Water
accumulation and deeper percolation are limited by plant transpiration, soil evaporation, and a capillary break formed by a gravelly
layer underlying finer textured root-zone soil (Fischer, 1992;
Andraski, 1997b).
Continuous 15-min eddy-covariance ET measurements were collected at the site from May 2002 to December 2005 (Johnson etal., 2007). Field ET data were collected about 200 m from theweather station where precipitation (collected at 1-m height) andsolar radiation were measured. Daily ET rates represent the sumof 15-min data during a 24-h period.

Numerical Model
The HYDRUS-1D numerical code was used to simulate coupledliquid water, water vapor, and heat flow in variably saturated soil(Šimůnek et al., 2008). A one-dimensional modeling approach
was accepted a priori as providing an acceptably accurate theoretical basis for initial exploration of the complex plant–soil–waterinteractions incorporated therein. Actual flow can be strongly
three-dimensional, especially at shallow depths immediately after
rainfall. Nevertheless, the one-dimensional approach was deemed
appropriate because the modeled domain is relatively large (0–13m). The one-dimensional results provide a foundation for future,high-resolution modeling of near-surface dynamics.
The extended version of Richards’ equation, modified by Philipand de Vries (1957) to include temperature gradients in addition
to pressure head gradients, was used to model interactions between
liquid water, thermal (temperature-driven) vapor, isothermal (pressure-head-driven) vapor, and heat flow.
The governing equation for liquid and water vapor flow is

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∂q
∂q
∂θ
= − L − v −S
∂t
∂z
∂z

[1]

where θ is the total volumetric water content (liquid and vapor)[L3 L−3]; qL and qv are volumetric fluxes of liquid water and water
vapor [L T−1] (upward positive), respectively; t is time [T]; z is thespatial coordinate [L]; and S is a sink term representing root water
uptake [T−1]. The flux of liquid water, separated into isothermal,
qLh,, and thermal, qLT, liquid fluxes is
⎛ ∂h
⎞
∂T
qL = qLh + qLT = −K Lh ⎜⎜⎜+ 1⎟⎟⎟ − K LT
⎝ ∂z
⎠
∂z

[2]

where KLh [L T−1] and KLT [L2 K−1 T−1] are the isothermal andthermal liquid hydraulic conductivities, respectively; h is pressure
head [L]; and T is temperature [K]. The flux of water vapor, separated into isothermal, qvh, and thermal, qvT, vapor fluxes is
q v = q v h + q v T = −K v h∂h∂T− K vT∂z∂z[3]where Kvh [L T−1] and KvT [L2 K−1 T−1] are the isothermal andthermal vapor hydraulic conductivities, respectively, described inŠimůnek et al. (2008). The root water uptake function defined by
Feddes et al. (1978) isS ( h ) = ε ( h ) Sp[4]

where ε(h) is the root water uptake response function (dimensionless), controlled by the soil pressure head; and Sp is the potential
water uptake rate [T−1]. Plant root and soil matrix water fluxes
are fully coupled and equations are solved simultaneously during
the same time step. Heat transport by convection–dispersion forvariably saturated media is∂ C pT
∂t

+ L0

∂q T
∂θ v
∂ ⎡
∂T ⎤
=
⎢λ ( θ )⎥ −C w L∂t∂ z ⎢⎣∂ z ⎥⎦∂z∂ q vT
∂qv
−C v
− L0
− C w ST
∂z
∂z

[5]

where λ(θ) is the apparent thermal conductivity of the soil [J L−1
T−1 K−1]; Cp, Cw, and Cv are volumetric heat capacities [J L−3 K−1]of the moist soil, liquid phase, and vapor phase, respectively; and L0
is the volumetric latent heat of vaporization of liquid water [J L−3].
The one-dimensional model domain extended to 13 m in the z
direction and was divided into six lithologic intervals (Andraski
and Jacobson, 2000). Although detailed investigation of the model
results focused on the upper 2 m of the profi le, the model domain
extended to 13 m to minimize boundary effects on the numericalsimulations. Model intervals were composed of loamy sand, gravelly coarse sand, and gravelly coarse sandy loam (Fig. 2A). Soil
hydraulic and thermal properties are given in Table 1. Andraski

Fig. 2. (A) Model domain and initial conditions for (B) temperatureand (C) pressure head. Model discretization increased at lithologic
interval boundaries. The vegetated soil root-zone corresponds with
the 0–1-m depth interval.

and Jacobson (2000) suggested that the saturated isothermal liquid
hydraulic conductivity value determined from laboratory measurements on disturbed samples (43.2 cm d−1; Andraski, 1996) mightunderestimate the actual value. Thus, a preliminary sensitivity
analysis (data not shown) was performed and evaluated by comparing simulated and previously measured pressure head trends(Andraski, 1997a) and simulated and concurrently measured watercontent trends (Johnson et al., 2007). The results confirmed that
increasing the laboratory-measured value by one order of magnitude (432 cm d−1) improved agreement between the simulated andobserved trends.
Creosote bush root water uptake parameters controlled by pressure
head were inferred from field observations and associated measurements of root-zone water storage and water potentials (Andraski,
1997a, Fig. 9a). Maximum plant vigor and water uptake generally
corresponded with periods when root-zone pressure heads were
between −2000 and −7000 cm. Plant vigor generally decreased
during early to mid-summer when pressure heads were between−7000 and −40,000 cm. The pressure head at which plants nolonger transpire was assigned an approximate wilting point forcreosote bush (−80,000 cm) based on Odening et al. (1974). The
potential limiting transpiration rate parameters were based on
HYDRUS-1D default values. The input water stress parameters forcreosote bush for the Feddes et al. (1978) root water uptake model
were: pressure head below which roots start to extract water, 0 cm;
pressure head below which roots extract water at the maximum
possible rate, −2000 cm; limiting pressure head values below whichroots can no longer extract water at the maximum rate, higher
limit −7000 cm, lower limit −40,000 cm (assuming a potential
transpiration rate of 0.5 and 0.1 cm d−1, respectively); pressure
head below which root uptake ceases, −80,000 cm.

Boundary Conditions
The soil surface water-flow boundary was controlled by a timevariable atmospheric boundary condition including potential
evaporation, potential transpiration, air temperature, andwww.VadoseZoneJournal.org | 554

Table 1. Input parameters describing the soil hydraulic (van Genuchten, 1980) and thermal (Campbell, 1985) properties of the model domain including
residual (θ r) and saturated (θ s) water content; saturated hydraulic conductivity (Ks); curve-fitting parameters (α and n); volumetric heat capacities ofthe mineral soil (C hs), water (Cw), and organic matter (Co); volume fraction of organic matter (φ o), solids (φ n), clay (φ c), quartz (φ q), and other minerals (φ m); and thermal longitudinal dispersivity (DL).
Hydraulic properties
Lithologic
interval
Soil type θ r†

Thermal properties
Volumetric heat capacity

θ s†

Ks †

α‡

——cm3 cm−3 —— cm d−1

cm−1

n‡

C hs†

Cw§

Co §

φ o¶

φ n§

φ c§

φ q§

φ m§

———— J cm−3 K–1 ————

DL#
cm

1

loamy
sand

0

0.29

432.0

0.036

1.29

2.32

4.18

2.5

0.0025

0.7

0.04

0.01

0.69

0.1

2, 4, 6

gravelly 0coarsesand

0.16

1036.8

7.150

1.18

2.28

4.18

2.5

0.0025

0.8

0.01

0.10

0.70

0.1

3, 5

gravelly 0coarse
sandy
loam

0.22

319.7

0.436

1.15

2.29

4.18

2.5

0

0.75

0.06

0.09

0.66

0.1

† Andraski and Jacobson (2000); Ks in Lithologic Interval 1 is one order of magnitude greater than the reference.
‡ Mayers et al. (2005).
§ Campbell (1985).
¶ California Soil Resource Lab.
# Hatch et al. (2006).

precipitation. Input values were based on daily data from the studysite micrometeorological station (air temperature, solar radiation,and precipitation; Johnson et al., 2007). The lower water-flow
boundary (13-m depth) was assumed to be controlled by gravity andwas assigned a unit hydraulic gradient. The time-variable air temperature and constant bottom temperature (21.7°C; Fischer, 1992)
were used for the upper and lower heat flow boundaries, respectively.
The minimum pressure head (at residual water content) at the soil
surface was assigned −5 × 104 m, the lower limit of allowable values
in HYDRUS-1D. This value is greater than the oven-dry soil value(−9.2 × 104 m) used by Andraski (1996) but is similar to (i) thelowest shallow-soil (0–1-cm) field value (−4 × 104 m) determinedfrom periodic water activity measurements made over several years
and (ii) modeled soil surface values using the Rossi–Nimmo (−4.3
× 104 m) and Brooks–Corey (−3.6 × 104 m) retention functions(Andraski and Jacobson, 2000). Runoff at the study site was assumed
negligible and the maximum thickness of the surface water layer was
assigned 4 cm accordingly based on depression storage.
Potential evapotranspiration (PET), potential evaporation (PE),and potential transpiration (PT) were estimated and partitioned
using methods similar to Kemp et al. (1997). The daily maximum
PET (PETmax) [M L−2 T−1] was computed as a simple functionof measured daily maximum air temperature (Ta) [K] and solar
radiation (Smax) [W L−2] (Campbell, 1977, p. 141):⎡ a (Ta + b ) Smax ⎤⎦PETmax = ⎣Lw[6]where Lw is the latent heat of vaporization [J M−1], and a =0.025°C−1 and b = 4.6°C are constants. The daily PET was

computed by integrating PETmax across the day (from 0 to π)
assuming a sinusoidal course of energy and temperature (average
daily PET = 2 PETmax/π), multiplying the average PET by the
daylight hours, and converting units [L T−1]. Daily PET was partitioned into PT for the canopy and PE for the soil surface using
a Beer’s law relation:
PT = PET ⎡⎣1 − exp ( k LAI )⎤⎦[7]

PE = PET exp (−k LAI )[8]

where k is the radiation extinction coefficient (dimensionless) and
LAI is leaf area per unit ground area (dimensionless). The parameter k can vary with the sun angle and plant and leaf distribution;
this study used k = 0.6 as suggested by Kemp et al. (1997).
The LAI input for the model was determined by extrapolating fieldbased literature estimates of LAI for a single creosote bush to theentire plant community. Maximum (1.9; Asner, 1998) and minimum (0.51; Gibson et. al., 2004) literature values for plant-scale LAI
were averaged (1.2) and multiplied by the fractional cover of plants
across the landscape. Fractional cover was determined from quarterly field measurements along four, 200-m-long transects using theline-transect method (Smith, 1974). Transect estimates of fractional
cover within each quarter were averaged and interpolated between
quarters. Fractional cover ranged from 0.04 to 0.10 and averaged
0.06. Although the measurements encompassed a mixed species
plant community (Garcia et al., 2009), the model was parameterized as a single-species community because of creosote bush’s relative
dominance (on average, >80%) and evergreen character.

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Initial Conditions
Initial conditions include temperature, pressure head, and root distribution profi les. The temperature profi le (Fig. 2B) was estimatedby interpolating between the average air temperature on Day Zeroand the constant bottom boundary temperature of 21.7°C. The
pressure head profi le (Fig. 2C) was estimated using in situ fieldmeasurements made in vegetated soil under similar antecedentmoisture conditions (Andraski, 1997a). Osmotic heads observed at
the site (0 to −50 m; Fischer, 1992) were considered small relative
to pressure heads and therefore were not considered in the numerical simulations. Vertical distribution of creosote bush roots (Table2) was assumed to be similar to that for the Chihuahuan Desert(Kemp et al., 1997). Simulations began in May 2001.

Table 2. Input root distributions of creosote bush (Larrea tridentata)for the model domain.
Depth

Root distribution†

cm
0–10

0

10–20

0.1

20–30

0.2

30–40

0.2

40–60

0.3

60–80

0.1

80–1000.1† Kemp et al. (1997).

Numerical Simulations
Individual 4.7-yr simulations that combined liquid water, water
vapor, and heat flow were run with and without vegetation to evaluate vegetative controls on soil water movement. Simulations withand without vegetation also were run without heat flow (isothermal) to determine thermal vapor controls on water movement. Daily
input and output data were used to evaluate temporal responses toclimate variability. Numerical solutions were solved using a variable
time discretization (10−6–10−3 d) that was automatically adjusted
based on the iterations necessary to reach convergence (Šimůnek etal., 2008). The 13-m soil profile was divided equally into 133 nodes
with increasing discretization at surface–subsurface and materialinterfaces (Andraski and Jacobson, 2000). Field measurements indicated that a capillary break in the soil at the base of the root zone
(the interface between loamy sand and gravelly coarse sand) probably
impedes deeper liquid percolation. Therefore model sensitivity to
the capillary break was tested for the aforementioned simulations
by reducing the soil profi le to a single lithologic material (loamysand). A sensitivity analysis was also performed with variations in
the LAI for the vegetated model with heat flow (described above)to improve understanding of biological factors controlling shallow
water movement. Model sensitivity to the LAI, the primary surface
component constraining simulated plant transpiration, was tested
by varying its value for 100% cover from 0.51 (Gibson et al., 2004)
to 1.9 (Asner, 1998). Simulations represent the LAI expressed on aplant-community basis.

6 Results and Discussion

Vegetated and Unvegetated Soil Simulations
with Heat Flow
Precipitation and Air Temperature

Cumulative precipitation measured during the 4.7-yr study period(May 2001–December 2005) totaled 555 mm. Daily precipitationand daily average air temperature are shown in Fig. 3. Although
70% of the precipitation fell from October to April during thestudy, large monthly precipitation was measured in July 2001 (33mm) and September 2005 (31 mm). Annual precipitation averaged
122 mm (2002–2005) and was 9% above the long-term averageFig. 3. Measured daily average air temperature and daily precipitation( Johnson et al., 2007).

(112 mm, 1981–2005; Johnson et al., 2007). The study captured
La Niña (dry summer and winter, February 2002–February 2003)
and El Niño (wet winter, November 2004–March 2005) events.
The second year of the study, 2002, was the driest on record, with
4 mm of precipitation; 2005 was the third wettest year on record
with 178 mm. Annual precipitation during 2004 and 2005 was
55 and 59% above average (174 and 178 mm, respectively). Air
temperature averaged 18.3°C, with the warmest month (July)
averaging 31.7°C and the coldest month (December) averaging
6.4°C (Johnson et al., 2007).

Water Storage
Major simulated changes in water storage were limited to the rootzone (upper 1 m). The largest increases occurred during March
2004, October 2004, January 2005, and September 2005 in
response to large precipitation pulses (20–31 mm d−1) (Fig. 4).
Root-zone water storage for vegetated soil decreased to a “baseline”
value of about 25 mm by the end of each summer and showed little
long-term change during the study. In contrast, storage for baresoil showed a long-term increase of about 39 mm (86%) between
May 2001 and January 2006. Rates of moisture depletion after
precipitation were also greatest for the vegetated soil. For example, during March to June 2005, vegetated soil values decreased

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the shallow gravelly layer (1–2 m) all showed long-term increases(Fig. 5B). Bare-soil pressure heads at the 25-, 50-, 101-, and 150-cm
depths increased by 66, 75, 94, and 35%, respectively, during thesimulation period.

Fig. 4. Simulated root-zone (0–1-m depth) water storage for vegetated and unvegetated soil and measured daily precipitation( Johnson et al., 2007).

twice as fast as those for unvegetated soil and reached the annual
minimum within about 6 mo (Fig. 4).

Pressure Head
Simulated pressure heads for vegetated and unvegetated soil are
shown with precipitation in Fig. 5A–5B. Pressure heads within
the root zone of the vegetated soil increased rapidly (up to 80 m in
1 d at the 25-cm depth, November 2004; Fig. 5A) in response to
precipitation. These large increases were followed by large decreases
at rates of up to 10 m d−1 (25- and 50-cm depths, spring 2005). For
the unvegetated soil, these wetting and drying cycles were considerably more muted, as pressure heads at depths above and in

Pressure head gradients in the root zone of the vegetated soil typically provided a downward driving force for isothermal flow duringcooler, wetter months and an upward driving force during warmer,
drier months (Fig. 3 and 5A). Gravitational heads were small (0to −13 m) with respect to pressure heads and effects on isothermal flow were considered negligible. Pressure head gradients inthe unvegetated soil followed similar trends; however, accumulating moisture dampened these gradients as the simulation time
progressed (Fig. 5B).
Simulated pressure heads in the sub-root-zone shallow gravel (Fig.
5A and 5B; 101- and 150-cm depths) oscillated seasonally. For thevegetated soil, the driving force for isothermal flow between the
101- and 150-cm depths was primarily upward, with the exceptionof the spring of 2005 El Niño event, when precipitation penetrated
below the root zone, inverting the pressure head gradient and isothermal flow direction (Fig. 5A). For the unvegetated soil, pressure
heads throughout the shallow gravelly layer decreased with increasing depth, providing a downward driving force for flow.
Below the shallow gravelly layer (>200-cm depth), variations inpressure heads for the vegetated and unvegetated soils were similar,reflective of initial conditions (Fig. 2C), and showed no long-termchange or response to El Niño precipitation. Pressure head gradients showed a persistent upward
driving force for isothermal f low
between the 2.4- and 13-m depths forthe unvegetated soil and between the2- and 13-m depths for the vegetatedsoil (data not shown). Vegetated-soilpressure heads at and below 2.5 m
increased with depth and showed small
seasonal fluctuations, averaging −492
± 9, −351 ± 0.2, and −330 ± 0.3 m atthe 2.5-, 7-, and 12-m depths, respectively. Temperatures at these depths
averaged 19.8 ± 2.3, 20.6 ± 0.3, and21.5 ± 0.03°C, respectively.

Fig. 5. Simulated pressure heads for (A) vegetated and (B) unvegetated soil with heat flow and (C) vegetated and (D) unvegetated soil without heat flow and measured daily precipitation ( Johnson et al.,2007). The root zone and shallow gravel extend from 0 to 1 and 1 to 2 m, respectively.

www.VadoseZoneJournal.org | 557

Simulated pressure heads for the vegetated and unvegetated soils weregenerally consistent with a previous
field study where water potentials(driven primarily by pressure head)
were measured continuously for 5
yr using thermocouple psychrometers (Andraski, 1997a). For example,
within the root zone of the vegetatedsoil, simulated and measured values both showed rapid increases
above −100 m following precipitation and often dipped below therange of psychrometer measurement (less than −800 m) during soil
drying. For the unvegetated soil, simulated and measured values
near 50 and 75 cm below the land surface remained elevated (morethan −100 m). In addition, the simulated seasonal oscillations inheads for the sub-root-zone gravelly layer were consistent with fielddata collected at both vegetated and unvegetated soil sites.

Evapotranspiration
A comparison between cumulative simulated unvegetated soil
evaporation and vegetated soil ET is shown in Fig. 6 along withthe measured precipitation. Total evaporation for the unvegetatedsoil was 42 mm less than precipitation and averaged 114 mm
annually (2002–2005). In contrast, simulated cumulative ET forthe vegetated soil was about 11 mm greater than the cumulative
precipitation and averaged 120 mm annually (2002–2005). The
11-mm difference was attributed to the initial (May 2001) evapotranspirative removal of antecedent moisture from storage. Greater
cumulative ET than precipitation indicates that the soil–plant–
atmosphere system removed water from storage and inhibitedlong-term accumulation of infi ltrating precipitation. The greatest
monthly ET for the vegetated and unvegetated soils was simulated
for February 2005 (45 and 48 mm, respectively), while the lowest
was simulated for October 2003 (0 mm).
Total cumulative ET for the vegetated soil was 566 mm (Fig. 6), of
which 424 mm was attributed to evaporation and 142 mm to transpiration. Therefore, the total simulated evaporation/transpiration(E/T) flux ratio for the vegetated soil was 3:1. This ratio is similar to
the average ratio determined by a 2.4-yr field study at the Amargosa
Desert Research Site where eddy covariance and chamber-based
bare-soil evaporation measurements were combined to estimate
continuous ET, bare-soil E, and plant T (Garcia et al., 2009).
A qualitative comparison between daily simulated vegetated-soil
ET and daily field ET reported by Johnson et al. (2007) for 1 May
2002 through 31 Dec. 2005 is shown in Fig. 7. Simulated andfield-determined (eddy-covariance) ET followed similar temporal
trends, with greater fluxes following precipitation and minimal
fluxes during dry periods. As illustrated in the Fig. 7 inset, however, simulated ET responses to precipitation were often greaterin magnitude but shorter in duration than field ET responses.
In contrast to the spiky nature of the simulated ET time series,
the field ET record generally showed more gradual, exponential
declines following precipitation. Recognizing the synthetic natureof simulated ET fluxes, such differences are not surprising, butthey do highlight potential uncertainties in the multiyear simulations of water and heat flow. For example, the use of a simple PET
model (Eq. [6]) might have led to artificially high simulated ET
when water was readily available immediately following precipitation. Also, inaccuracies in the prescribed (but not optimized) soil
water retention function and soil hydraulic properties could have

Fig. 6. Cumulative simulated unvegetated soil (US) evaporation andvegetated soil (VS) evapotranspiration, and measured precipitation( Johnson et al., 2007).

Fig. 7. General trends in simulated vegetated soil evapotranspirationand field-determined eddy-covariance evapotranspiration with measured daily precipitation ( Johnson et al., 2007).

affected the simulated amount of water lost to the atmosphere byevaporation as well as the amount of infi ltration.

Water Movement
Simulated fluxes of total water, isothermal and thermal liquid water,
and isothermal and thermal water vapor within and just below theroot zone of the vegetated and unvegetated soils are shown in Fig.
8. Although absolute flux values are highly uncertain due to theuncertainty of hydraulic properties (both isothermal and thermal),comparisons within and between simulations provide insight into
the physical processes driving water movement. Root-zone total
water fluxes for vegetated and unvegetated soil followed similar
trends at all depths throughout the study, but downward total
water fluxes at the 50-cm depth following precipitation in February
2004 and October to December 2004 were typically greater for theunvegetated soil (Fig. 8A–8B). For example, following February
2004 precipitation, the peak total water flux at the 50-cm depth forthe unvegetated soil was an order of magnitude greater than for thevegetated soil (−0.1 and −0.03 mm d−1, respectively).

www.VadoseZoneJournal.org | 558

on average at the 101-cm depth) (Fig.
8C–8F). In response to the 2004–
2005 El Niño, however, a small (10−3
mm d−1) but sustained downward
isothermal liquid flux led to moisturepenetration and increased water content (0.024 m 3 m−3) just below thecapillary break at 100 cm. During thefollowing summer, ET of root-zonewater fostered upward isothermal
liquid fluxes that removed this deeper
penetrating liquid. This was also
shown following the La Niña event(February 2002–February 2003)
when extended root-zone drying
caused a shift in liquid water fluxes at
the 150-cm depth from downward to
upward. In contrast, in unvegetatedsoil, isothermal liquid fluxes throughout the gravelly layer were consistently
downward during the study.

Fig. 8. Simulated total water and isothermal and thermal liquid water and water vapor fluxes for (A, C,
E, G, I) vegetated and (B, D, F, H, J) unvegetated soil with measured daily precipitation ( Johnson et al.,2007). The root zone extends from 0- to 1-m depth. Sign convention is that downward fluxes are negative. Scales for A to D differ from E to F.

The relatively large downward total fluxes following fall to spring
precipitation in 2004 and 2005 were dominated by isothermal
liquid water movement through the root zone, during whichtime thermally driven liquid water fluxes were comparatively
negligible (Fig. 8A–8B vs. 8C–8D). Isothermal liquid fluxes forunvegetated soil were typically greater than those for vegetatedsoil and often penetrated deeper as a result of moisture accumulation and associated increases in isothermal liquid conductivities.
Just below the capillary break at the root zone–gravelly layerinterface (100-cm depth), liquid water fluxes for the vegetatedsoil trended upward and downward seasonally but were predominantly negligible with respect to root-zone fluxes (10−5 mm d−1

Although the isothermal liquid water
flux dominated downward water movement during short time periods, total
moisture transport during the 4.7-yr
simulation period was dominated bythermal water vapor fluxes (Fig. 8). For
example, at the 50-cm depth, the thermal vapor flux was dominant nearly
90 and 60% of the time and averaged−10−3 and −10−4 mm d−1 for vegetatedand unvegetated soil, respectively.
Within the sub-root-zone gravelly
layer, thermal vapor flux directions
varied seasonally and magnitudes
averaged ?10 −4 mm d−1 (data notshown); these fluxes were dominantnearly 100% of the time.

As shallow moisture accumulated with simulation time for theunvegetated soil, water vapor fluxes were dampened with respect
to the vegetated soil. For example, although similar in magnitude
near the start of the simulation, isothermal water vapor fluxes
at the 25-cm depth were, on average, two orders of magnitude
greater than those for the unvegetated soil beyond winter 2004
(Fig. 8G–8H). A similar trend was shown for thermal water
vapor fluxes at 25 cm; although initially similar, fluxes for thevegetated soil were twice as great as those for the unvegetated soil
near the end of the simulation (Fig. 8I–8J). At and below 50 cm,
thermal water vapor fluxes for the vegetated soil were, on average,
about 50% greater than the unvegetated fluxes.

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Simulated fluxes beneath the root zone of vegetated and unvegetated soil were consistent with previous studies where fluxes werecomputed analytically using field data. For example, for vegetatedsoil, the magnitude of fluxes calculated by Andraski (1997a) for
the shallow gravelly layer were about 10−11 to 10−10 mm d−1 forisothermal liquid water, 10−5 mm d−1 for thermal vapor, and about
10−7 mm d−1 for isothermal vapor during September 1990 and
September 1992. Simulated fluxes for the month of September(2001–2005) were about 10−11 to 10−10 mm d−1 for isothermal
liquid water, 10−4 to 10−3 mm d−1 for thermal vapor, and 10−6
to 10−5 mm d−1 for isothermal vapor. In a previous study, Fischer(1992) computed average monthly thermal vapor fluxes ranging
from 10−4 to 10−1 mm d−1 in the gravelly layer. Simulated averagemonthly thermal vapor fluxes for vegetated soil also ranged from10−4 to 10−1 mm d−1 in the gravelly layer.
Cumulative total water fluxes for vegetated and unvegetated soil
indicate that water movement below the root zone is minimal
under current climatic conditions. Cumulative total water flux
profi les for vegetated and unvegetated soil are shown in Fig. 9.
The cumulative total water flux in the vegetated soil was upward
but minimal (0.93 mm during 4.7 yr at the 101-cm depth, corresponding to a flux of 0.2 mm yr−1). In the unvegetated soil, thetotal water flux was downward to a depth of 150 cm, with a net
flux of −1.3 mm during 4.7 yr at the 101-cm depth (corresponding
to −0.3 mm yr−1). Previous field studies (Fischer, 1992; Andraski,
1997b) suggested that a capillary break in the soil at the base of theroot zone (the interface between loamy sand and gravelly coarsesand) might partly explain the lack of deeper water penetration.
Additional simulations for vegetated and unvegetated soil using
a homogeneous soil profi le (loamy sand) indicated that the capillary break had little effect on cumulative total water fluxes for thevegetated case but relatively large effects for the unvegetated case(Fig. 9). The cumulative water flux for the vegetated soil at the
101-cm depth increased by 0.5 mm in the absence of layering (Fig.
9A), whereas the corresponding unvegetated soil flux increased by
34 mm (Fig. 9B).

Thermal Water Vapor Contributions
to Water Movement
Water storage simulated with and without heat flow is shown in
Fig. 10. For the vegetated soil, peak water storage values following
precipitation were similar for simulations with and without heat.
Depletion of accumulated water was consistently greater whenheat flow was included, however, and this resulted in late summer
to early fall storage values that were 0.5 to 2 mm less than thosefor the no-heat simulation (Fig. 10A). These differences arelinked to plant water uptake during mid- to late summer (discussed below). For unvegetated soil, the no-heat-flow simulation
produced storage values that were up to 5 mm greater than thosewith heat flow (Fig. 10B). Thermal vapor flow probably redistributed the available moisture below the evaporation extinction

Fig. 9. Simulated cumulative total subsurface water flux during a 4.7-yr
period for (A) vegetated and (B) unvegetated soil. Fluxes are for simulations with heat flow in layered and homogeneous soil and without heatflow in layered soil. Sign convention is that downward fluxes are negative.

depth (about 50 cm), allowing condensation and greater moistureaccumulation.
Pressure heads simulated without heat flow for vegetated andunvegetated soil are shown in Fig. 5C–5D. Within and just below
the root zone, pressure heads for the simulation without heat flow
showed no seasonal fluctuation (Fig. 5C), whereas simulations
with heat flow (Fig. 5A) and field measurements (Andraski, 1997a)

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upward and driven by isothermal vapor flow while those simulated with heat trended upward and downward seasonally with a
combination of thermal and isothermal vapor flow (Fig. 8A). At
the 25-cm depth, isothermal and thermal vapor flux magnitudes
were similar, thus the total water flux was similar for simulations
with and without heat flow. At the 50-cm depth, however, theexclusion of heat flow during dry periods typically decreased total
water fluxes and isothermal vapor fluxes by an order of magnitude.
As with the lack of seasonal dynamics observed for pressure heads
in simulations without heat flow, isothermal liquid fluxes justbelow the capillary break (i.e., the 101-cm depth) were essentiallyconstant and upward (10−6 mm d−1 on average), whereas thosesimulated with heat flow trended upward during warmer months
and downward during cooler months (10−6 mm d−1 on average).
Below the 101-cm depth (data not shown), the magnitude of thetotal water flux for the simulations without heat was, on average,
one to three orders of magnitude less than the simulation with heat.

Fig. 10. Simulated root-zone (0–1-m depth) water storage with andwithout heat flow for (A) vegetated and (B) unvegetated soil andmeasured daily precipitation ( Johnson et al., 2007). Inset shows anexample of differences in storage during winter and summer months.

both showed substantial seasonal changes. Thus, the simulation
without heat flow did not capture the dynamics of pressure headchanges that can affect the rates and directions of water flow. For
unvegetated soil, annual and multiyear pressure head trends for the
no-heat-flow simulation (Fig. 5D) were similar to those with heatflow (Fig. 5B) as moisture accumulated with time.
Total root-zone water fluxes following precipitation were similar for
simulations without and with heat because the isothermal liquid
flux was predominant (see, for example, winter 2004–2005 resultsin Fig. 8A and 8C). In contrast, during dry periods total fluxes
for the simulation without heat (data not shown) were primarily

Root water uptake simulated with and without heat flow is shownin Fig. 11. The simulation with heat flow indicated that shallow
root water uptake (25–30-cm depth interval) can occur during
droughts and often persisted for a longer period than for thesimulation without heat flow. An even more dramatic difference
between root water uptake for the simulations with and without
heat flow is illustrated by the results for the 95- to 100-cm depth
interval. For example, the simulation with heat flow showed threenotable increases in uptake at this interval that peaked in Augustof 2002, 2003, and 2004 (Fig. 11A), but no such increases were
simulated without heat flow (Fig. 11B). The periods of increased
uptake for the simulation with heat (accumulating to ?1 mm on
average) corresponded directly with the previously noted differencein water storage and the seasonal increase in pressure head to peakvalues at the 101-cm depth (Fig. 5A). A combination of downward
thermal vapor fluxes within the root zone and upward liquid water
fluxes from just below the root zone probably led to the amassing ofmoisture at depth (95–100-cm depths) and the increased availability of liquid water for plant uptake. This combination of processes
is similar to a sand column experiment simulated by Sakai etal. (2009), where water vapor driven downward by temperature

Fig. 11. Root water uptake for selected
depth intervals simulated (A) with and(B) without heat flow in vegetatedsoil with measured daily precipitation( Johnson et al., 2007).

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gradients condensed at the cooler base of the column and pressure head gradients subsequently drove liquid water upward. Basedon current simulation results, we hypothesize that such a process
could provide a small but noteworthy source of water for plants
at the driest time of the year; however, field or laboratory measurements will be necessary to test this hypothesis. If verified, thispreviously unrecognized source of moisture could have ecohydrological implications for desert plant communities.
Total cumulative ET for the vegetated soil was similar for the simulations with and without heat flow (data not shown). The proportionsof ET (E/T ratio) attributed to plant transpiration varied by 2%
between simulations with and without heat. While the totals weresimilar, differences that did occur were concentrated during thesummer months when increased root water uptake was simulatedwith heat flow. For the unvegetated soil, cumulative E simulated
without heat flow was about 1 mm greater than with heat flow.

Fig. 12. Simulated root-zone (0–1-m depth) water storage showing
the effects of varying leaf area index (LAI) values about the base-casevalues for simulations in vegetated soil with measured daily precipitation ( Johnson et al., 2007).

Model Sensitivity to Leaf Area Index
Model sensitivity to the LAI, the primary aboveground parameter
constraining simulated plant transpiration, was tested by varying the
LAI base value (i.e., 1.2 × cover) from 0.4 LAI (0.51 × cover) to 1.6
LAI (1.9 × cover). A comparison of root-zone water storage for variations in the LAI is shown in Fig. 12. Relative trends in water storage
were similar for all LAI values; however, the rate and amount of moisture depletion were least for 0.4 LAI (e.g., March–Sept. 2005; Fig. 12).
Despite varying depletion rates, predictions from the base-case and 1.6
LAI simulations reached similar minimum storage values (25 mm)
during September of each year (Fig. 4 and 12, respectively). In contrast,
minimum storage values for the 0.4 LAI simulation typically exceeded
those for other simulations by 1 to 10 mm.
The effects of varying the LAI on the simulated cumulative ETtime series are shown in Fig. 13. The total cumulative ET for the
4.7-yr simulations was 553 mm for 0.4 LAI, 566 mm for the basecase, and 568 mm for 1.6 LAI; precipitation totaled 555 mm. The
large difference between the 0.4 LAI and the base-case LAI reflects
differences in storage and accumulating moisture. As anticipated,the cumulative proportion of ET attributed to transpiration
increased with increasing LAI: the E/T flux ratios were 79:21 for
0.4 LAI, 75:25 for the base case, and 73:27 for 1.6 LAI.
Summary statistics comparing simulated daily ET time series forvarying LAI values indicate that LAI variability had a minimal
affect on the daily ET (Table 3). The mean difference between
the daily simulated ET for the base LAI and sensitivity values
ranged from 0.0007 to −0.0001 mm d−1 for 0.4 LAI and 1.6 LAI,
respectively. The 1.6 LAI value was the most correlated (r = 0.996,
P < 0.0001, Table 3) with the base LAI and showed the lowest
maximum absolute difference (0.048 mm d−1). Variations in LAI
did little to improve comparisons between the simulated and fielddetermined ET shown in Fig. 7.

Fig. 13. Cumulative simulated evapotranspiration showing the effectsof varying leaf area index (LAI) values about the base-case value forsimulations in vegetated soil with heat flow. Inset shows an exampleof the differences in the rate of evapotranspiration increases during
spring and summer.

6 Conclusions
Plant and temperature contributions to dynamic water movement
in desert soils were investigated using a comprehensive modelthat coupled isothermal liquid, isothermal vapor, and nonisothermal liquid and vapor flow. Plant uptake of root-zone (upper 1 m)
moisture triggered an upward driving force for isothermal flow.
Similar to field measurements (Andraski, 1997a), nonisothermal
simulations of large rainfall related increases in pressure head andwater storage within the root zone of vegetated soil were followedby similarly large decreases. Negligible changes in water content
within the underlying coarse gravel indicate that infi ltrating precipitation was effectively removed by ET on an annual basis. For
unvegetated soil, increasing root-zone water storage and pressure
heads within and below the root zone during the 4.7-yr study
indicated long-term moisture accumulation. Continued mois-

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Table 3. Summary statistics for comparisons between simulated daily evapotranspiration for vegetated soil (VS) using the base leaf area index (LAI) and sensitivity values.
Evapotranspiration
Difference†
Simulation

LAI

r2

RMSE

Pearson’s r

MedianMean

Max. absolutewith a capillary break to 35 mm without. In
an environment with similarly stratified soils
and sediments, disturbance of such capillary
breaks could have large implications for longterm drainage.

——————— mm d−1 ——————

Simu lation resu lts provide a g reater
understanding of soil–plant–atmosphereinteractions that control the shallow moisVS with heat 1.6 × LAI 0.993 0.008
0.996 (<0.0001) 0.000−0.0001 0.048
tureflux regime in arid environments. To our† Base LAI minus LAI sensitivity values.
knowledge, this study is the first to delineate
the temporal effects of heat flow on soil water
movement in a vegetated soil. The inclusion
ture accumulation, in turn, created a persistent driving force forof vegetation along with coupled isothermal and nonisothermal
downward isothermal flow.
water flow identified interactions that have potential ecohydrologic
implications for desert environments. In particular, the presence
Similar to previous studies (Fischer, 1992; Andraski, 1997a), therof plants and heat transport were shown to have notable effects in
mal vapor flow in the vegetated soil was the dominant mechanism
limiting downward sub-root-zone water movement and in supplefor water movement in the root zone and upper portion of thementing the delivery of moisture to plant roots during the driest
underlying gravelly layer during warm periods and cool dry periparts of the year.
ods and at all times below this gravelly layer. Exclusion of thermal
Acknowledgments
vapor flow from vegetated soil limited the extent of shallow soil
We gratefully acknowledge Michael J. Fayer, Edwin P. Weeks, and anonymous redrying and reduced pressure head gradients, ultimately restrictviewers for helpful comments on the manuscript. Support for this work was provided through the U.S. Geological Survey’s Toxic Substances Hydrology, National
ing the magnitude of isothermal flow. Total water fluxes predicted
Research, and Groundwater Resources programs.
without heat transport were, on average, an order of magnitudeless than predictions with heat transport in the mid- to lower rootzone and one to three orders of magnitude less below the root zone.
VS with heat

0.4 × LAI

0.990

0.009

0.995 (<0.0001)

0.000

0.0007 0.054

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