Geoderma 241–242 (2015) 306–312

Contents lists available at ScienceDirect

Geodermajournal homepage: www.elsevier.com/locate/geoderma

Inverse estimation of soil hydraulic properties under oil palm trees
Nor Suhada Abd Rashid a, Muhamad Askari b,⁎, Tadashi Tanaka c, Jirka Simunek d, Martinus Th. van Genuchten e,faFaculty of Civil Engineering, Univ. Teknologi Malaysia, 81310 Johor Bahru, Malaysia
Institute of Environmental and Water Resources Management (IPASA), Univ. Teknologi Malaysia, 81310 Johor Bahru, MalaysiacDep. of International Affairs, Univ. of Tsukuba, Ibaraki 305-8577, Japand
Dep. of Environmental Sciences, Univ. of California, Riverside, CA 92521, USAeDep. of Mechanical Engineering, Federal Univ. of Rio de Janeiro, UFRJ, Rio de Janeiro, RJ 21945-970, BrazilfDep. of Earth Sciences, Utrecht Univ., Budapestlaan 4, 3584CD Utrecht, Netherlandsba r t i c l e

i n f oArticle history:
Received 17 August 2014
Received in revised form 29 November 2014
Accepted 4 December 2014
Available online xxxx
Keywords:
Stemﬂow
Tension disc inﬁltrometer
Soil hydraulic properties
Oil palm
HYDRUS-2D/3D

a b s t r a c t
Canopies of forested and agricultural ecosystems can signiﬁcantly alter rainfall patterns into separate stemﬂow
and throughfall areas. These two areas often have also different organic matter contents and soil compaction
properties, and hence also soil hydraulic properties, thus causing further differences in the local inﬁltration
rates close to and away from trees. In this study we analyzed possible differences in the unsaturated soil hydraulicproperties of the stemﬂow and throughfall areas below an oil palm tree. Tension disc inﬁltrometer experiments
were carried out underneath the canopy and in the interspace area of an oil palm tree plantation at successive
tensions of 5, 2, and 0 cm. Soil hydraulic properties were estimated inversely from the measured data using
the HYDRUS-2D/3D software package. Four van Genuchten soil hydraulic parameters (i.e., the residual watercontent, θr, the shape factors α and n, and the saturated hydraulic conductivity, Ks) were optimized. Saturated
water contents, θs, were ﬁxed at their laboratory-measured values. Initial estimates of the optimized parameters
were set according to Wooding's solution, which ensured rapid convergence of the inverse solution. The
stemﬂow and throughfall regions exhibited contrasting hydraulic properties as indicated by the estimatedhydraulic parameters. Values of θs, α, n and Ks for the stemﬂow area were all found to be higher as comparedto those of the throughfall area. The inverse solution using tension disc inﬁltrometer data proved to be very usefulfor rapid characterization of hydraulic properties of soil under the oil palm trees.
© 2014 Elsevier B.V. All rights reserved.

1. Introduction
This study focuses on possible differences in the physical andhydraulic properties of the stemﬂow and throughfall areas of oil palm
trees. Previous studies have shown that stemﬂow can be a major sourceof tree-induced inﬁltration and subsequent ﬂow in and below the soil
root zone, including recharge (Aboal et al., 1999; Gomez et al., 2002;
Liang et al., 2007, 2011; Pressland, 1976; Sansoulet et al., 2008;
Tanaka et al., 1996). Liang et al. (2007) observed that cumulative
stemﬂow per unit inﬁltration area along the downslope side of a tree
trunk was nearly 20 times cumulative open-area rainfall. Sansoulet
et al. (2008) similarly found that stemﬂow caused the inﬁltration
rates around a banana stem to be up to six times higher than in thethroughfall areas. Several other studies observed differences between
stemﬂow and throughfall rates, including for olive trees (Gomez et al.,2002), banana plants (Cattan et al., 2009), tall stewartia (Liang et al.,2009), and ponderosa pine (Guan et al., 2010). While all of the above
studies point to signiﬁcant differences between the stemﬂow and⁎ Corresponding author.
E-mail address: muhaskari@utm.my (M. Askari).

http://dx.doi.org/10.1016/j.geoderma.2014.12.003
0016-7061/© 2014 Elsevier B.V. All rights reserved.

throughfall rainfall rates, noticeably lacking are studies about possible
differences in the soil hydraulic properties of the stemﬂow andthroughfall areas, which should further exacerbate differences in thelocal inﬁltration rates.
The objective of the present study was to estimate the hydraulicproperties characterizing the soil water retention and unsaturated hydraulic conductivity functions of soil underneath the stemﬂow andthroughfall areas of an oil palm tree. Knowledge of these functions is essential to describe the movement of water and solutes in the vadosezone below the trees, including for ecohydrological studies and estimating local recharge rates.
A large number of direct and indirect approaches may be used to estimate the hydraulic properties of unsaturated soils. Neuman (1973)
deﬁned direct methods as those estimating the hydraulic conductivity
and soil water retention directly from laboratory and/or ﬁeld experiments. Numerous direct methods are available for this purpose as summarized well in several texts (Dane et al., 2002; Klute and Dirksen,
1986; van Genuchten et al., 1999). Unfortunately, direct methods haveseveral limitations that restrict their use in practice in that they (i) are
generally time consuming, especially for ﬁeld-drainage experiments,(ii) are often difﬁcult to implement for certain boundary conditions(especially for ﬁeld conditions at relatively large scales), and (iii) often

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

307

require steady-state ﬂow conditions during the experiments. Information
about uncertainty in the estimated hydraulic parameters is often also notreadily derived using direct measurements. For these various reasonsindirect approaches have become more popular recently.
Neuman (1973) deﬁned indirect methods as parameter estimation
methods involving the solution of an inverse problem. Inverse solutions
based on the Richards equation are now increasingly used for estimating the unsaturated soil hydraulic properties. An advantage of thisapproach is that the retention and hydraulic conductivity functions
can be estimated simultaneously from transient ﬂow data, as shownby many past and recent studies (Abbasi et al., 2003; Abbaspour et al.,
1999; Dane and Hruska, 1983; Eching and Hopmans, 1993; Kool andParker, 1987; Lazarovitch et al., 2007; Minasny and Field, 2005; Ritter
et al., 2003; Russo et al., 1991; Schwarzel et al., 2006; Sonnleitneret al., 2003; Zachmann et al., 1981). The soil hydraulic parameters arethen obtained by minimizing an objective function, usually deﬁned
as the sum of squared deviations between observed and predicted transient water ﬂow variables (Hopmans et al., 2002). In our study we usedtension inﬁltration data for evaluating saturated and unsaturated
hydraulic conductivities using the analytical approach of Wooding(1968). Tension disc inﬁltrometry has become a popular method formeasuring in-situ cumulative inﬁltration functions and unsaturated hydraulic conductivities. The method has been used for many different soil
types, climates, and vegetation covers (Ankeny et al., 1991; Kashkuli
and Tangsir, 2011; Moret-Fernández et al., 2012; Schwartz et al.,
2003; Schwen et al., 2011; Ventrella et al., 2005; Wahl et al., 2004). Examples of numerical studies in which tension inﬁltrometer data wereused to inversely estimate the near-saturated soil hydraulic properties
are by Simunek and van Genuchten (1997), Ramos et al. (2006) andCaldwell et al. (2013).
Fig. 1. Layout of the palm trees in the plantation and the measurement locations in thestemﬂow and throughfall areas.

2. Material and methods
2.1. Field experiments
The ﬁeld experiments were carried out at an oil palm plantation inJohor Darul Takzim, Malaysia. The plantation was established approximately 18 years ago. Based on the USDA soil classiﬁcation scheme,
surface soils at the plantation are sandy loams (about 77% sand, 10%
silt, 13% clay). Soils in the area are typical oxisols (Selvaradjou et al.,2005) containing iron-rich parent materials such as serpentinite, basalt,
andesite, schist and ferruginous shale. They are considered quite suitable for rubber and oil palm plantations.
Fig. 1 shows a layout of the palm trees in the measurement area, andthe locations of the hydraulic measurements. The oil palm trees wereplanted using an equilateral triangular arrangement as shown in theﬁgure. Measurements were carried out at four points within thethroughfall area (TA) in the middle between trees, and at three points
within the stemﬂow area (SA). Precise location of the SA points below
the palm tree canopy was important to ensure overlap with the area
where stemﬂow water inﬁltrated into the soil. Tanaka et al. (1991)
found “litter marks” around the tree bases to be useful indicators of
the inﬁltration area of stemﬂow-induced water. The inﬁltration area of
stemﬂow-induced water, Ai, was estimated by the litter marks of oilpalm trees. The area and equivalent radius of the litter marks from thecenter of the oil palm trunks were estimated by tape measurements.
Previous studies (Tanaka, 2011; Tanaka et al., 1991, 1996) found thatthe extent of the litter marks at a given plantation is a function of thediameter of the tree base: the thicker the trunk, the more stemﬂow occurred and the more extensive the SA inﬁltration area. Iida et al. (2005)
quantiﬁed this relationship for Formosa sweet gum and evergreen oak
to obtain:

RL ¼ 23:36 ln ðDÞ−31:53


2
R ¼ 0:753

ð1Þ

where RL is the radius (in cm) of the litter marks from the center of thestem, and D is the diameter of the tree base (in cm). We conducted
several measurements to see if a similar relationship as Eq. (1) would
hold also for our palm tree plantation.
A tension disc inﬁltrometer was used to conduct the ﬁeld inﬁltration
experiments in the stemﬂow (SA) and throughfall (TA) areas to obtain
estimates of the soil hydraulic properties. Three successive tensions of
5, 2, and 0 cm were used for all inﬁltrometer experiments. The discinﬁltrometer had a diameter of 20 cm and consisted of a nylon mesh.
To ensure good contact between the disc and the soil, a thin (approximately 2 mm) layer of sand was placed on top of the soil. The sandlayer was moistened just before placing the disc membrane on the soil
in order to prevent air entry into the disc (Cameira et al., 2003).
Soil samples were collected additionally at depths of 0–10 cm at various measurement locations using a soil ring (height = 5 cm, diameter = 5 cm). In total 14 samples were collected to determine for eachlocation the initial water content, θi, the bulk density, ρb, the organic
matter content, OM, the total porosity, ε, and the residual water content,
θr (the latter simply approximated initially by the wilting point).
2.2. Laboratory measurements
After performing the ﬁeld experiments, laboratory measurements
were carried out using the soil samples from the ﬁeld. The initialwater content was calculated by the loss of weight after oven-drying
the samples at 105 °C for 24 h. Volumetric samples were used to determine the bulk density. The organic matter content was measured fromloss-in-ignition (400 °C). Total porosity was estimated using the measured value of bulk density and a particle density of 2.65 g cm−3 (Postand Kwon, 2000; Rühlmann et al., 2006). Initial estimates of the residual
water content were determined by measuring the water content at apressure head of − 15,000 cm using the pressure plate approach.
Table 1 provides a summary of the laboratory measurements.

308

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

Table 1
Laboratory-measured data of the stemﬂow and throughfall areas of the oil palm plantation.
Location

Point

Initial water content
θi(cm3 cm−3)

Bulk density
ρb(g cm−3)

Total porosityε(%)

Organic matter content
OM(%)

Residual water content
θr(cm3 cm−3)

Stemﬂow area

1
2
3
A
B
C
D

0.350
0.345
0.341
0.418
0.447
0.402
0.376

1.173
1.058
1.275
1.427
1.366
1.386
1.327

55.7
60.1
51.9
46.2
48.4
47.7
49.9

0.492
1.159
0.290
0.100
0.134
0.086
0.087

0.291
0.287
0.288
0.307
0.349
0.285
0.288

Throughfall area

A geometric mean of the actual inﬁltration rates, Qi and Qi + 1, wasused to calculate the average inﬁltration rate, Qi + 1/2:

2.3. Wooding's solution
The solution of Wooding (1968) has been used in many analyses oftension inﬁltration experiments. The solution assumes an exponential
relationship for the hydraulic conductivity function applied to unconﬁned three-dimensional steady-state water inﬁltration (assuming zero
ponding) from a circular source into the soil. The analysis is based on
the following equations2

ð2Þ

K ðhÞdhð3Þ

K ðhÞ ¼ K s expðβhÞð4ÞQ ðho Þ ¼ πr o K ðho Þ þ 4r o ϕðho ÞQ iþ1=2 ¼ exp

ln Q i þ ln Q iþ1
:
2

ð8Þ

Parameter A in Eqs. (5) and (6) for the interval between twoconsecutive tensions is given by
ln Q =Q :A ¼  i iþ1
hi −hiþ1ð9Þ

Zho
ϕðho Þ ¼hl

where Q is the steady-state inﬁltration rate [L3 T−1], ro is the radius of
the disc [L], K is the unsaturated hydraulic conductivity [L T−1] derived
from Gardner's model (Gardner, 1958), ho is the supply wetting pressure head [L], hl some ﬁxed lower limit of the invoked pressure headrange [L], often assumed to be −∞, ϕ(ho) is the matrix ﬂux potential[L2 T−1], Ks is the saturated hydraulic conductivity [L T−1], and β is anempirical shape factor [L−1]. The steady-state ﬂow theory forming thebasis of Eq. (2) and its applications have been discussed previously inmany studies (Clothier and Smettem, 1990; Perroux and White, 1988;
Quadri et al., 1994; Warrick, 1992).
Different approaches may be used to analyze steady-state tension discinﬁltrometer data using Eq. (2). In our study we used the simpliﬁed approach followed by Ankeny et al. (1991) and Reynolds and Elrick(1991). Ankeny et al. (1991) assumed that A = K(h) / ϕ(h) is constantwithin an interval between hi and hi + 1. They then calculated the unsaturated hydraulic conductivity, K(hi) and K(hi + 1), for the steady state
ﬂuxes, Q(hi) and Q(hi + 1), at two different pressure heads, hi and hi + 1,
as follows:

2.4. Inverse solution approach
The numerical inversion approach was based on solution of the
Richards equation for two-dimensional axisymmetric isothermal ﬂow
in a variably-saturated isotropic rigid porous medium (Warrick, 1992):
∂θ 1 ∂
∂h
∂
∂h
þ
¼
rK
K
þK
∂t r ∂r∂r∂z∂zwhere θ is the volumetric soil water content [L3 L−3], h is the pressure
head [L], K is the hydraulic conductivity [L T−1], t is time [T], r is the radial
coordinate [L], and z is the vertical coordinate, positive upward in ourstudy [L].
The initial and boundary conditions under a disc inﬁltrometer having
a radius ro are given by (Simunek et al., 2000; Warrick, 1992):

ð5Þ








4r
2
Q hiþ1 ¼ πro þ o K hiþ1 :A

ðt ¼ 0Þθðz; r; t Þ ¼ θið11aÞhðr; z; t Þ ¼ h0 ðt Þ

ð0brbr 0 ; z ¼ 0Þð11bÞ∂hðr; z; t Þ¼ −1∂zð r Nr0 ; z ¼ 0Þð11cÞhðr; z; t Þ ¼ hi



4r
2
Q ðhi Þ ¼ πr 0 þ o K ðhi Þ
A

ð10Þ



2
2
r þ z →∞ :

ð11dÞThe soil hydraulic functions used in the inversion problem aredescribed using the equations (van Genuchten, 1980):

ð6Þ
Se ðhÞ ¼

θðhÞ−θr¼
θs −θrn −m

1 þ ðαhÞ
1

hb0
h≥0

ð12Þ

hb0

ð13Þ

Reynolds and Elrick (1991) further assumed a piecewise exponentialfunction to estimate the hydraulic conductivity in the middle of two
successively applied tensions, hi + 1/2 = (hi + hi + 1) / 2, by rearranging
Eq. (2) to become:K ðSe Þ ¼

K hiþ1=2 ¼ "where Se is effective saturation [−], θs and θr are the saturated and residual water contents, respectively [L3 L−3], Ks is the saturated hydraulicconductivity [L T−1], and n [−] and α [L−1] are shape parameters, andm = 1 − 1 / n. Eqs. (12) and (13) contain ﬁve unknown soil hydraulics
hydraulic parameters: θs, θr, α, n and Ks, which potentially could all be
estimated inversely from tension inﬁltrometer and related data using

Q iþ1=2
πr 0 2 þ

4r 0
Aiþ1=2#:

ð7Þ

(K s Se

0:5

h


 i
1=m m 21− 1−Se
Ks

h≥0

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

the DISC (Simunek et al., 2000) or HYDRUS-2D/3D (Simunek et al.,2008) software packages.
Simunek and van Genuchten (1996) found that cumulative inﬁltration rates measured with a tension disc inﬁltrometer at only one particular tension did not provide enough information to estimate more than
two soil hydraulic parameters. Additional information, such as thewater content corresponding to the last measured tension under thedisc inﬁltrometer, was needed. They subsequently found that a combination of multiple-tension cumulative inﬁltration data and measured valuesof the initial and ﬁnal water contents yielded unique solutions of the inverse problem (Simunek and van Genuchten, 1997).
The objective function used in our study for the parameter optimization process consisted of cumulative inﬁltration data, the saturated soil
water content (approximated by porosity) and the water content at h =−15,000 cm. Eching et al. (1994) in their study used, in addition to the
cumulative drainage data, also water contents as input for the inversion
in order to optimize the soil water retention and hydraulic conductivity
curves. The initial condition was given by measured initial water contents of both the stemﬂow and throughfall areas.
3. Results and discussion
3.1. Experimental results
We ﬁrst veriﬁed the expected stemﬂow inﬁltration area by correlating observed litter marks around various trees in the oil palm plantation
with measured tree base diameters. Results are shown in Fig. 2. We
ﬁtted an equation similar to Eq. (1) to the data to obtain
RL ¼ 98:25 ln ðDÞ−154:17


2
R ¼ 0:735½14

where, as before, RL is the radius (in cm) of the litter marks from thecenter of the stem, and D is the diameter (in cm) of the tree base.
Eq. (14) has a similar shape as Eq. (1) over the range of measured
data, but with RL values about 2.5 times larger. Differences in the coefﬁcients of Eqs. (1) and (14) are to be expected for different vegetations
having different canopy structures, and for different weather and soil

Fig. 2. Relationship between the diameter of the tree base (D, in cm) and the radius of thelitter marks (RL, in cm) measured from the center of the stem.

309

conditions. Still, Eq. (14) showed that the selected SA measurement
points (160 cm from the center of the tree trunk) were well within
the expected stemﬂow inﬁltration area.
From the ﬁeld tension disc inﬁltration data we obtained cumulative
inﬁltration rates (Q) for all points under the stemﬂow (SA) and throughfall (TA) areas. Fig. 3 shows the measured inﬁltration rates obtained withthree different supply pressure heads (h = −5, −2 and 0 cm). Notice theobvious breaks in the cumulative inﬁltration curves caused by adjusting
the pressure heads at the new time intervals. Also, the slopes of the cumulative inﬁltration curves are different for the inﬁltration measurements atthe three different supply pressure heads. Point 1 in the stemﬂow area
required only approximately 70 min for 800 cm3 of water to inﬁltrate,
whereas Points 2 and 3 required 160 min for 600 cm3 and 200 cm3 ofwater to inﬁltrate, respectively. By comparison, the four points in thethroughfall area showed similar inﬁltration patterns, with Points C andD requiring 160 min to inﬁltrate 400 cm3 and 200 cm3 of water into thesoil. Except for SA Point 2, the cumulative inﬁltration curves indicate overall much higher inﬁltration rates for the stemﬂow area as compared to thethroughfall area.
The laboratory measurements shown in Table 1 indicate that thestemﬂow area had a much higher porosity and higher organic matter
content than the throughfall area. The organic matter contents were
up to 13 times higher in the stemﬂow area. These results agree withmeasurements by Haron et al. (1998) who found that the avenues andweeded circles beneath oil palms had mean organic matter contents
that increased with time after establishing the plantation: 0.82% after
5 years, 1.76% after 10 years and 2.21% after 20 years. A higher soil organic matter content is known to reduce the bulk density (Arvidsson,1998) and soil compaction (Soane, 1990). Soil organic matter producedby trees is also known to improve the friability of otherwise tight soils,
and to enhance soil structural development that will increase the inﬁltration capacity (Franzluebbers, 2002; Martin and Moody, 2001).
3.2. Hydraulic conductivities obtained using Wooding's solution
The inﬁltration rate data for both the stemﬂow and throughfall areas
were used in the equations proposed by Ankeny et al. (1991) andReynolds and Elrick (1991) as discussed earlier, to determine the unsaturated hydraulic conductivity. The approach of Ankeny et al. (1991) wasused to calculate the unsaturated hydraulic conductivity from thesteady state inﬁltration rates at two different tensions, while the approach of Reynolds and Elrick (1991) provided a piecewise exponentialfunction for the hydraulic conductivity to yield estimates midway
between two applied tensions. Fig. 4 shows a plot of the obtained hydraulic conductivity data versus pressure head. Although ﬁeld measurements were carried out at only three pressure heads (− 5, − 2 and0 cm), a relatively complete graph of the near-saturated hydraulic conductivity function, K(h), could be obtained.
The results in Fig. 4 indicate that the saturated hydraulic conductivities (Ks) of the stemﬂow area were approximately six times higher as

Fig. 3. Cumulative inﬁltration rates measured in the ﬁeld and simulated using HYDRUS2D/3D for the stemﬂow (left) and throughfall (right) areas.

310

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

Fig. 4. Hydraulic conductivity data of the stemﬂow (left) and throughfall (right) areas asobtained using Wooding's solution and numerical inversion with HYDRUS-2D/3D.

those of the throughfall area. We next used the measured values of Ks of
the stemﬂow and throughfall areas as initial values in the parameter
estimation approach using HYDRUS-2D/3D.
3.3. Parameter estimation analysis
3.3.1. Optimized cumulative inﬁltration curves
Initial estimates of the saturated hydraulic conductivity were basedon values obtained using Wooding's (1968) analysis. Tables 2a and 2bshow the initial parameter values used in the parameter estimation
analysis with HYDRUS. Of the various hydraulic parameters, saturated
water contents (θs) were determined independently on soil samples
in the laboratory and not optimized, while the initial values of the residual water content (θr) for each point in both areas were set equal to thelaboratory-measured water contents at h = −15,000 cm.
Fig. 3 shows the measured and calculated cumulative inﬁltration
curves when the objective function was deﬁned in terms of the cumulative inﬁltration data. Results indicate excellent agreement between themeasured and optimized inﬁltration curves. Results of the parameter
optimization analyses with HYDRUS-2D/3D for both areas are listed inTables 2a and 2b. The optimized parameter values for α, n and Ks were
mostly very close or only slightly higher than the initial parametervalues we used. The close correspondence of the initial and ﬁnal estimates of Ks lends further credibility to the accuracy of Wooding's(1968) analysis of tension disc inﬁltrometer data, also for the tropicalsoils (oxisols) used in our study.
3.3.2. Hydraulic conductivity curves
Fig. 4 shows the near-saturated hydraulic conductivity curves for the
stemﬂow and throughfall areas obtained with both Wooding's solution
and the numerical inversion option of HYDRUS-2D/3D. Wooding's solution was found to give slightly higher values than the inverse solution,
perhaps because steady-state inﬁltration conditions were not reachedcompletely during the experiments, or the assumption of having an exponential hydraulic conductivity curve between each two pairs ofinﬁltrometer data. Earlier work showed that Wooding's solution will
overestimate the soil hydraulic conductivity if steady-state conditions
are not achieved (Simunek et al., 1999). Also, tension inﬁltration
experiments seldom reach complete saturation (Simunek and van
Genuchten, 1996). The values of Ks for all points in the stemﬂow andthroughfall areas as obtained with HYDRUS were essentially identicalto the values derived using Wooding's solution. In all, relatively good
agreement was obtained between the hydraulic conductivity functions
derived with Wooding (1968) analysis and the numerical inversion
using HYDRUS-2D/3D.
The measured soil physical properties (Table 1) indicate that thebulk density of the throughfall area was higher than that of thestemﬂow area, thus implying more compaction and a lower saturated
conductivity. The higher bulk density is partly due to the much lower
organic matter content of the throughfall area (see Table 1). Hudson(1994) found that soils having higher organic matter contents usually
have a higher water holding capacity and a higher hydraulic conductivity, largely as a result of increased soil aggregation and the associatedbroader pore space distribution. But the higher bulk density of thethroughfall area is in part also due to mechanical compaction by small
pickup trucks used to collect oil palm branches and other material during harvesting. Antille et al. (2013) and Soane et al. (1980) showed thatthe use of agricultural machinery leads to higher bulk densities, andhence generally lower saturated hydraulic conductivities (Assouline,
2006; Dec et al., 2008), mostly because of a smaller volume of relatively
coarse pores.
The higher near-saturated hydraulic conductivities of the stemﬂow
area, along with the higher rates of stemﬂow reaching the soil surface,should combine to produce much higher inﬁltration rates as comparedto the throughfall areas away from the palm trees.
3.3.3. Water retention curves
Fig. 5 shows the estimated soil water retention curves of the stemﬂow
and throughfall areas as obtained with the numerical inversion approach
using HYDRUS-2D/3D, including the laboratory-measured retention dataat saturation and h = −15,000 cm. As expected, the data indicate higher
saturated water contents for the stemﬂow area as compared to thethroughfall area. Saturated water contents were up to 10% higher in thestemﬂow area. Since soil texture and soil type were relatively uniform
across the oil palm plantation, differences in the water contents are due
mostly to differences in the organic matter content (Table 1), and relateddifferences in the bulk density, including those effects caused by wheel
trafﬁcking in the interspace area. Emerson (1995) found that higher soilorganic matter contents strengthen soil aggregation, reduce soil compaction, and increase the water content. Rawls et al. (2003) similarly foundthat an increase in the organic matter content produced an increase inwater retention of sandy soils. In addition, Wall and Heiskanen (2003) observed a signiﬁcant positive correlation between the total porosity andthe log-transformed organic matter content. However, a signiﬁcant negative correlation was found between total porosity and bulk density.
The residual water content, θr, obtained with the inverse solution wasclose to the value of the water content at h = −15,000 cm measured in
the laboratory. Because of the very coarse texture of the soil in our

Table 2aInitial and optimized values of the soil hydraulic parameters of the stemﬂow area.
Hydraulic parameter3−3

θr (cm cm )θs (cm3 cm−3)
α (cm−1)n (−)
Ks (cm min−1)a

Not optimized.

Initial value

Optimized value

Point 1

Point 2

Point 3

Point 1

Point 2

Point 3

0.291
0.566
0.329
1.543
0.1738

0.287
0.565
0.196
1.378
0.0157

0.288
0.525
0.327
1.337
0.05480.291 ± 0.001
0.566a0.508 ± 0.004
2.032 ± 0.064
0.1605 ± 0.0034

0.283 ± 0.02
0.565a0.531 ± 0.012
1.492 ± 0.027
0.0169 ± 0.0004

0.279 ± 0.002
0.525a0.908 ± 0.040
1.340 ± 0.000
0.0549 ± 0.0000

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

311

Table 2b
Initial and optimized values of the soil hydraulic parameters of the throughfall area.
Hydraulic parameterθr (cm3 cm−3)
θs (cm3 cm−3)
α (cm−1)n (−)
Ks (cm min−1)aInitial value

Optimized value

Point A

Point B

Point C

Point D

Point A

Point B

Point C

Point D

0.307
0.485
0.156
1.521
0.0297

0.349
0.534
0.191
1.858
0.0297

0.285
0.496
0.167
1.698
0.0182

0.288
0.490
0.145
1.533
0.01050.306 ± 0.003
0.485a0.214 ± 0.009
1.632 ± 0.098
0.0279 ± 0.0022

0.349 ± 0.001
0.534a0.230 ± 0.003
1.794 ± 0.044
0.0308 ± 0.0010

0.283 ± 0.001
0.496a0.210 ± 0.003
1.556 ± 0.023
0.0189 ± 0.0004

0.287 ± 0.001
0.490a0.272 ± 0.002
1.642 ± 0.022
0.0105 ± 0.0003

Not optimized.

study (77% sand), the water content at the permanent wilting pointshould be a very good estimate of the residual water content (vanGenuchten, 1980). Including this value in the optimization was importantsince most or all of the data used in the optimization were in the wet
range of the hydraulic properties. The water retention measurements at
h = −15,000 cm hence served to ﬁx the dry range of the hydraulic functions (Stephens and Rehfeldt, 1985). Contrary to expectations, the data
indicated lower θr values for the stemﬂow area as compared to thethroughfall area. According to Wall and Heiskanen (2003) and Saxton
and Rawls (2006), the residual water content should increase withincreasing organic matter content and the content of ﬁne particles(especially clay particles). One possible reason may be the type of soil at
our site. The θr values of our oxisol were higher as compared to classaverage pedotransfer estimates obtained by Carsel and Parrish (1988)
for temperate soils, but also higher than the average values obtained byTomasella and Hodnett (1998) and Askari et al. (2008) for tropical soils
in Brazil and Indonesia, respectively.
The optimized values of the α retention parameter (Tables 2a and 2b)
for both areas were relatively large, indicative of the coarse nature of oursoil (Carsel and Parrish, 1988; Fredlund and Xing, 1994). The value of α ofthe stemﬂow area was 2.8 times higher than that of throughfall area,
which again reﬂects the lower bulk density and higher organic matter
content of the stemﬂow area, leading to a more macroporous medium.
By comparison, the values of n of the stemﬂow and throughfall areas
were fairly similar, with the value of n for the stemﬂow area being slightly
lower than for the throughfall area.
4. Conclusions
Our study showed that the saturated soil hydraulic conductivity (Ks)of the stemﬂow area around an oil palm tree was much higher (about 6
times) compared to the throughfall area. The saturated water content(θs) of the stemﬂow area was similarly higher about 10% higher than
the saturated water content of the throughfall area. These results are
signiﬁcant in that they, if combined with the fact that stemﬂow rainfall
rates are much higher than the throughfall rates, cause much higher
local inﬁltration rates near the trees stem areas than in areas awayfrom the trees, including open areas.

Fig. 5. Water retention curves for the stemﬂow (left) and throughfall (right) areas obtainedusing numerical inversion of the ﬁeld-measured tension disc inﬁltrometer data.

Wooding's (1968) analytical solution, implemented here using a
combination of the approaches of Ankeny et al. (1991) and Reynolds
and Elrick (1991), proved to be very effective in estimating unsaturated
hydraulic conductivities. Numerical inversion of the tension discinﬁltrometer data provided a relatively simple, yet reliable alternative
method for determining the water retention and hydraulic conductivity
curves of near saturated soils. Including an independently measured
water content (e.g., at −15,000 cm as done in our study) is important
to better deﬁne the soil hydraulic functions in the dry range. We conclude that the HYDRUS inverse solution approach applied to inﬁltration
data measured with a tension disc inﬁltrometer is a useful technique for
rapid characterization of the unsaturated soil hydraulic properties.
Acknowledgment
The authors want to thank Dr. Rudiyanto from the Department ofCivil and Environmental Engineering, Bogor Agricultural University,
Indonesia, for his help with the numerical inversion methods using
the HYDRUS-2D/3D software. This study was supported by the Ministryof Higher Education, Malaysia (vot number: R.J130000.7822.4F077) andUniversiti Teknologi Malaysia Research University Grant (vot number:
Q.J130000.2609.07J17), as well as by CAPES, Brazil.
References
Abbasi, F., Jacques, D., Simunek, J., Feyen, J., van Genuchten, M.T., 2003. Inverse estimationof soil hydraulic and solute transport parameters from transient ﬁeld experiments:
heterogeneous soil. Trans. ASAE 46 (4), 1097–1111.
Abbaspour, K., Sonnleitner, M., Schulin, R., 1999. Uncertainty in estimation of soil hydraulic parameters by inverse modeling: example lysimeter experiments. Soil Sci. Soc.
Am. J. 63 (3), 501–509.
Aboal, J., Morales, D., Hernandez, M., Jimenez, M., 1999. The measurement and modellingof the variation of stemﬂow in a laurel forest in Tenerife, Canary Islands. J. Hydrol. 221(3), 161–175.
Ankeny, M.D., Ahmed, M., Kaspar, T.C., Horton, R., 1991. Simple ﬁeld method for determining unsaturated hydraulic conductivity. Soil Sci. Soc. Am. J. 55 (2), 467–470.
Antille, D.L., Ansorge, D., Dresser, M.L., Godwin, R.J., 2013. Soil displacement and soil bulk
density changes as affected by tire size. Trans. ASABE 56 (5), 1683–1693.
Arvidsson, J., 1998. Inﬂuence of soil texture and organic matter content on bulk density,
air content, compression index and crop yield in ﬁeld and laboratory compression experiments. Soil Tillage Res. 49 (1–2), 159–170.
Askari, M., Tanaka, T., Setiawan, B.I., Saptomo, S.K., 2008. Inﬁltration characteristics oftropical soil based on water retention data. J. Jpn. Soc. Hydrol. Water Resour. 21,
215–227.
Assouline, S., 2006. Modeling the relationship between soil bulk density and the hydraulicconductivity function. Vadose Zone J. 5, 697–705.
Caldwell, T.G., Wohling, T., Young, M.H., Boyle, D.P., McDonald, E.V., 2013. Characterizing
disturbed desert soils using multiobjective parameter optimization. Vadose Zone J. 12(1).
Cameira, M., Fernando, R., Pereira, L., 2003. Soil macropore dynamics affected by tillage
and irrigation for a silty loam alluvial soil in southern Portugal. Soil Tillage Res. 70(2), 131–140.
Carsel, R.F., Parrish, R.S., 1988. Developing joint probability distributions of soil water retention characteristics. Water Resour. Res. 24 (5), 755–769.
Cattan, P., Ruy, S.M., Cabidoche, Y.M., Findeling, A., Desbois, P., Charlier, J.B., 2009. Effect onrunoff of rainfall redistribution by the impluvium-shaped canopy of banana cultivated on
an andosol with a high inﬁltration rate. J. Hydrol. 368 (1–4), 251–261.
Clothier, B., Smettem, K., 1990. Combining laboratory and ﬁeld measurements to deﬁne
the hydraulic properties of soil. Soil Sci. Soc. Am. J. 54 (2), 299–304.
Dane, J., Hruska, S., 1983. In-situ determination of soil hydraulic properties during drainage.
Soil Sci. Soc. Am. J. 47 (4), 619–624.
Dane, J.H., Topp, C., Campbell, G.S., Horton, R., Jury, W.A., Nielsen, D.R., van Es, H.M.,
Wierenga, P.J., Topp, G.C., 2002. Part 4—Physical Methods. Methods of Soil Analysis.

312

N.S.A. Rashid et al. / Geoderma 241–242 (2015) 306–312

Dec, D., Dörner, J., Becker-Fazekas, O., Horn, R., 2008. Effect of bulk density on hydraulicproperties of homogenized and structured soils. J. Soil Sci. Plant Nutr. 8 (1), 1–13.
Eching, S., Hopmans, J., 1993. Optimization of hydraulic functions from transient outﬂow
and soil water pressure data. Soil Sci. Soc. Am. J. 57 (5), 1167–1175.
Eching, S.O., Hopmans, J.W., Wendroth, O., 1994. Unsaturated hydraulic conductivity fromtransient multistep outﬂow and soil–water pressure data. Soil Sci. Soc. Am. J. 58 (3),687–695.
Emerson, W., 1995. Water-retention, organic-C and soil texture. Soil Res. 33 (2), 241–251.
Franzluebbers, A.J., 2002. Water inﬁltration and soil structure related to organic matterand its stratiﬁcation with depth. Soil Tillage Res. 66 (2), 197–205.
Fredlund, D.G., Xing, A., 1994. Equations for the soil–water characteristics curve. Can.
Geotech. J. 31, 521–532.
Gardner, W., 1958. Some steady-state solutions of the unsaturated moisture ﬂow equation with application to evaporation from a water table. Soil Sci. 85 (4), 228–232.
Gomez, J.A., Vanderlinden, K., Giraldez, J.V., Fereres, E., 2002. Rainfall concentration underolive trees. Agric. Water Manag. 55 (1), 53–70.
Guan, H., Simunek, J., Newman, B.D., Wilson, J.L., 2010. Modelling investigation of waterpartitioning at a semiarid ponderosa pine hillslope. Hydrol. Process. 24 (9),1095–1105.
Haron, K., Brookes, P., Anderson, J., Zakaria, Z., 1998. Microbial biomass and soil organic
matter dynamics in oil palm (Elaeis guineensis Jacq.) plantations, West Malaysia.
Soil Biol. Biochem. 30 (5), 547–552.
Hopmans, J.W., Šimůnek, J., Romano, N., Durner, W., 2002. Inverse methods. In: Dane, J.H.,
Topp, G.C. (Eds.), Methods of Soil Analysis: Part 4 Physical Methods. Soil Science Society of America, Madison, WI, pp. 963–1008.
Hudson, B.D., 1994. Soil organic matter and available water capacity. J. Soil Water
Conserv. 49 (2), 189–194.
Iida, S., Kakubari, J., Tanaka, T., 2005. “Litter marks” indication inﬁltration area of
stemﬂow-induced water. Tsukuba Geoenviron. Sci. 1, 27–31.
Kashkuli, H.A., Tangsir, S., 2011. Comparison of two efﬁcient methods for the estimationof ﬁeld unsaturated hydraulic conductivity from disc permeameter measurements.
World Appl. Sci. J. 14 (7), 1107–1114.
Klute, A., Dirksen, C., 1986. Conductivities and diffusivities of unsaturated soils. Methods
Soil Anal. 1 687–734.
Kool, J., Parker, J., 1987. Development and evaluation of closed‐form expressions for hysteretic soil hydraulic properties. Water Resour. Res. 23 (1), 105–114.
Lazarovitch, N., Ben-Gal, A., Simunek, J., Shani, U., 2007. Uniqueness of soil hydraulic parameters determined by a combined wooding inverse approach. Soil Sci. Soc. Am. J.
71 (3), 860–865.
Liang, W.L., Kosugi, K., Mizuyama, T., 2007. Heterogeneous soil water dynamics around atree growing on a steep hillslope. Vadose Zone J. 6 (4), 879–889.
Liang, W.L., Kosugi, K., Mizuyama, T., 2009. Characteristics of stemﬂow for tall stewartia(Stewartia monadelpha) growing on a hillslope. J. Hydrol. 378 (1–2), 168–178.
Liang, W.L., Kosugi, K., Mizuyama, T., 2011. Soil water dynamics around a tree on a hillslope with or without rainwater supplied by stemﬂow. Water Resour. Res. 47 (2), 18.
Martin, D.A., Moody, J.A., 2001. Comparison of soil inﬁltration rates in burned and unburned mountainous watersheds. Hydrol. Process. 15 (15), 2893–2903.
Minasny, B., Field, D., 2005. Estimating soil hydraulic properties and their uncertainty: theuse of stochastic simulation in the inverse modelling of the evaporation method.
Geoderma 126 (3–4), 277–290.
Moret-Fernández, D., Latorre, B., González-Cebollada, C., 2012. Microﬂowmeter–tension
disc inﬁltrometer: part II—hydraulic properties estimation from transient inﬁltration
rate analysis. J. Hydrol. 466, 159–166.
Neuman, S.P., 1973. Calibration of distributed parameter groundwater ﬂow models
viewed as a multiple‐objective decision process under uncertainty. Water Resour.
Res. 9 (4), 1006–1021.
Perroux, K., White, I., 1988. Designs for disc permeameters. Soil Sci. Soc. Am. J. 52 (5),1205–1215.
Post, W.M., Kwon, K.C., 2000. Soil carbon sequestration and land-use change: processes
and potential. Glob. Chang. Biol. 6 (3), 317–327.
Pressland, A., 1976. Soil moisture redistribution as affected by throughfall and stemﬂow
in an arid zone shrub community. Aust. J. Bot. 24 (5), 641–649.
Quadri, M., Angulo-Jaramillo, R., Vauclin, M., Clothier, B., Green, S., 1994. Axisymmetrictransport of water and solute underneath a disk permeameter: experiments and numerical model. Soil Sci. Soc. Am. J. 58 (3), 696–703.
Ramos, T., Gonçalves, M., Martins, J., van Genuchten, M.T., Pires, F., 2006. Estimation of soil
hydraulic properties from numerical inversion of tension disk inﬁltrometer data. Vadose Zone J. 5 (2), 684–696.
Rawls, W.J., Pachepsky, Y.A., Ritchie, J.C., Sobecki, T.M., Bloodworth, H., 2003. Effect of soilorganic carbon on soil water retention. Geoderma 116 (1–2), 61–76.
Reynolds, W., Elrick, D., 1991. Determination of hydraulic conductivity using a tension
inﬁltrometer. Soil Sci. Soc. Am. J. 55 (3), 633–639.
Ritter, A., Hupet, F., Munoz-Carpena, R., Lambot, S., Vanclooster, M., 2003. Using inverse
methods for estimating soil hydraulic properties from ﬁeld data as an alternative todirect methods. Agric. Water Manag. 59 (2), 77–96.
Rühlmann, J., Körschens, M., Graefe, J., 2006. A new approach to calculate the particle
density of soils considering properties of the soil organic matter and the mineral matrix. Geoderma 130 (3–4), 272–283.

Russo, D., Bresler, E., Shani, U., Parker, J.C., 1991. Analyses of inﬁltration events in relation
to determining soil hydraulic properties by inverse problem methodology. Water
Resour. Res. 27 (6), 1361–1373.
Sansoulet, J., Cabidoche, Y.-M., Cattan, P., Ruy, S., Šimůnek, J., 2008. Spatially distributed
water ﬂuxes in an andisol under banana plants: experiments and threedimensional modeling. Vadose Zone J. 7 (2), 819–829.
Saxton, K.E., Rawls, W.J., 2006. Soil water characteristic estimates by texture and organic
matter for hydrologic solutions. Soil Sci. Soc. Am. J. 70 (5), 1569–1578.
Schwartz, R.C., Evett, S.R., Unger, P.W., 2003. Soil hydraulic properties of cropland compared with reestablished and native grassland. Geoderma 116 (1), 47–60.
Schwarzel, K., Simunek, J., Stoffregen, H., Wessolek, G., van Genuchten, M.T., 2006. Estimation of the unsaturated hydraulic conductivity of peat soils. Vadose Zone J. 5 (2),628–640.
Schwen, A., Bodner, G., Scholl, P., Buchan, G., Loiskandl, W., 2011. Temporal dynamics ofsoil hydraulic properties and the water-conducting porosity under different tillage.
Soil Tillage Res. 113 (2), 89–98.
Selvaradjou, S.K., Montanarella, L., Spaargaren, O., Dent, D., Filippi, N., Dominik, S., 2005.
Metadata of the Soil Maps of Asia. Ofﬁce of the Ofﬁcial Publications of the European
Communities, Luxembourg.
Simunek, J., van Genuchten, M.T., 1996. Estimating unsaturated soil hydraulic properties
from tension disc inﬁltrometer data by numerical inversion. Water Resour. Res. 32(9), 2683–2696.
Simunek, J., van Genuchten, M.T., 1997. Estimating unsaturated soil hydraulic properties
from multiple tension disc inﬁltrometer data. Soil Sci. 162 (6), 383–398.
Simunek, J., Wendroth, O., van Genuchten, M., 1999. Estimating unsaturated soil hydraulicproperties from laboratory tension disc inﬁltrometer experiments. Water Resour. Res.
35 (10), 2965–2979.
Simunek, J., van Genuchten, M.T., Sejna, M., 2000. The DISC computer software for analyzing tension disc inﬁltrometer data by parameter estimation. Version 1.0. U.S. Salinity
Laboratory, Riverside, California.
Simunek, J., van Genuchten, M.T., Sejna, M., 2008. Development and applications of the
HYDRUS and STANMOD software packages and related codes. Vadose Zone J. 7 (2),587–600.
Soane, B.D., 1990. The role of organic matter in soil compactibility: a review of some practical aspects. Soil Tillage Res. 16 (1–2), 179–201.
Soane, B.D., Blackwell, P.S., Dickson, J.W., Painter, D.J., 1980. Compaction by agricultural
vehicles: a review II. Compaction under tyres and other running gear. Soil Tillage
Res. 1, 373–400.
Sonnleitner, M., Abbaspour, K., Schulin, R., 2003. Hydraulic and transport properties of theplant–soil system estimated by inverse modelling. Eur. J. Soil Sci. 54 (1), 127–138.
Stephens, D.B., Rehfeldt, K.R., 1985. Evaluation of closed-form analytical models to calculate conductivity in a ﬁne sand1. Soil Sci. Soc. Am. J. 49 (1), 12–19.
Tanaka, T., 2011. Effects of the canopy hydrologic ﬂux on groundwater. In: Levia, D.F.,
Carlyle-Moses, D., Tanaka, T. (Eds.), Forest Hydrology and Biogeochemistry: Synthesisof Past Research and Future Directions. Springer, pp. 499–518.
Tanaka, T., Tsujimura, M., Taniguchi, M., 1991. Inﬁltration area of stemﬂow-induced
water. Annual Report-Institute of Geoscience 17. University of Tsukuba, pp. 30–32.
Tanaka, T., Taniguchi, M., Tsujimura, M., 1996. Signiﬁcance of stemﬂow in groundwater
recharge. 2. A cylindrical inﬁltration model for evaluating the stemﬂow contribution
to groundwater recharge. Hydrol. Process. 10 (1), 81–88.
Tomasella, J., Hodnett, M.G., 1998. Estimating soil water retention characteristics fromlimited data in Brazilian Amazonia. Soil Sci. 163 (3), 190–202.
van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44 (5), 892–898.
van Genuchten, M.T., Schaap, M., Mohanty, B., Simunek, J., Leij, F., 1999. Modeling Flowand Transport Processes at the Local Scale. Modelling of Transport Process in Soils
at Various Scales in Time and Space. Wageningen Pers, Wageningen, theNetherlands, pp. 23–45.
Ventrella, D., Losavio, N., Vonella, A., Leij, F., 2005. Estimating hydraulic conductivity of aﬁne-textured soil using tension inﬁltrometry. Geoderma 124 (3–4), 267–277.
Wahl, N.A., Bens, O., Buczko, U., Hangen, E., Hüttl, R., 2004. Effects of conventional andconservation tillage on soil hydraulic properties of a silty-loamy soil. Phys. Chem.
Earth A/B/C 29 (11), 821–829.
Wall, A., Heiskanen, J., 2003. Water-retention characteristics and related physical properties of soil on afforested agricultural land in Finland. For. Ecol. Manag. 186 (1–3),
21–32.
Warrick, A.W., 1992. Models for disk inﬁltrometers. Water Resour. Res. 28 (5),1319–1327.
Wooding, R., 1968. Steady inﬁltration from a shallow circular pond. Water Resour. Res. 4(6), 1259–1273.
Zachmann, D.W., Duchateau, P.C., Klute, A., 1981. The calibration of the Richards ﬂow
equation for a draining column by parameter identiﬁcation. Soil Sci. Soc. Am. J. 45,
1012–1015.