Agricultural Water Management 281 (2023) 108250

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Agricultural Water Management
journal homepage: www.elsevier.com/locate/agwat

Effect of water application methods on salinity leaching efficiency indifferent textured soils based on laboratory measurements andmodel simulations
Ting Yang a, b, 1, Setrag Cherchian b, Xinmin Liu c, 2, Hossein Shahrokhnia b, Minghao Mo d,Jirka Šimůnek b, 3, Laosheng Wu b, *, 4aKey Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou Institute of Geography, Guangdong Academy of Sciences,
Guangzhou 510070, Chinab
Department of Environmental Sciences, University of California, Riverside, CA 92512, USAc
Chongqing Key Laboratory of Soil Multi-Scale Interfacial Process, College of Resources and Environment, Southwest University, Chongqing, Chinad
Jiangxi Academy of Water Science and Engineering, Nanchang 330029, China

A R T I C L E I N F O

A B S T R A C T

Keywords:
Leaching efficiency
Irrigation methods
RootzoneHYDRUS-1D/-2D
Agriculture water management

Irrigated agriculture has been in a quandary of sustaining its productivity for centuries while attempting to copewith soil and water salinity issues that continue to devastate crop production. Several of the research gaps
associated with current irrigation practices include how to assess leaching requirement (LR) and efficiency (LE)for different soils, crops, and irrigation regimes. The objective of this study was to test irrigation water appli­
cation methods on salinity leaching efficiency using laboratory soil column experiments and computer model
simulations. Three water application methods (continuous ponding, CP; intermittent ponding, IP; and unsatu­
rated application, UA) were imposed on packed columns of 3 different soils to evaluate salinity leaching effi­
ciency. The HYDRUS-1D model was employed to inversely estimate water and solute transport parameters fromthe column experimental data, while the HYDRUS-2D model was used to simulate water and salinity transport
under flexible (actual field practice) and fixed frequency irrigation (every 7, 5, and 3 days) under the same field
conditions. Our column results showed that water application methods had greater impact on leaching efficiency(LE) in coarse soil than that in fine soil. The soil quality (S index) also changed with water application methods.
Continuous ponding had higher LE for the sandy loam and silt loam, unsaturated application was the best for thesilt loam, while intermittent ponding and unsaturated application were good for both the silt loam and clay.
Model simulations indicated that flexible frequency irrigation resulted in lower salinity in the rootzone than thatof fixed frequency irrigation, while for the fixed frequency irrigation, more frequent application with smaller
amount of water was better for the silt loam. Leaching efficiency under flexible frequency irrigation was 94.2%;
while for the fixed frequency irrigation, the LE values were 87.8%, 95.4%, 98.0%, respectively, for 7-, 5-, and 3d intervals. The findings from this research can help farmers improve water use efficiency by considering water
application methods and soil conditions.

1. Introduction
Increasing water use efficiency in irrigated cropland is critical tosustaining water resources and improving agricultural productivity,

especially in arid and semiarid regions where soils are most affected bysalts. Expansion of irrigated cropland and increased reliance on mar­
ginal water sources, combining with low leaching efficiency (LE, theratio of the drained salt mass to the applied salt mass) and poor soil

* Corresponding author.
E-mail address: laowu@ucr.edu (L. Wu).
10000–0003-1330–5930
2000–0003-3092–096X
30000–0002-0166–6563
40000–0001-6547–8513
https://doi.org/10.1016/j.agwat.2023.108250
Received 16 June 2022; Received in revised form 22 February 2023; Accepted 26 February 2023
0378-3774/© 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

T. Yang et al.

Agricultural Water Management 281 (2023) 108250

internal drainage conditions, can often lead to soil salinization (Kita­
mura et al., 2006; Minhas et al., 2020).
Standard guidelines for managing irrigation and salinity are mostly
designed with the goal of meeting the leaching requirement (LR) to
maintain rootzone salinity at a level that avoids any reduction in crop
growth or yield (Yang et al., 2019). An important aspect for the successof such strategy is the adoption of appropriate irrigation methods for
specific soils and climate conditions. A range of pressurized irrigation
methods (sprinkler, drip) offer alternatives to the traditional surface
irrigation (furrow, basin) in terms of efficiency, environmental impact,
health risks, and more (Barnard et al., 2010). In general, for a water of
specific quality and for a given crop, the impact of an irrigation methodon the rate of salinization will depend on several variables including
vertical and spatial distribution of soil properties, topography, irrigation
management, cultural practices, climatic conditions, and regional hy­
drological conditions (Oster et al., 2012; Nassah et al., 2018; Minhas
et al., 2020).
Different irrigation methods such as flood, furrow, sprinkler or drip
can result in different patterns of saturated and unsaturated water flowin the rootzone. Under continuous ponding (CP), the soil is always
saturated, and the flow is steady during an irrigation event. While underintermittent ponding (IP), it consists of two periods: a water-application
period and a rest period. During the rest period, the soil is saturated at
the beginning, but flow is interrupted for a predetermined period, andno convective transport will occur in this period, i.e., it is assumed thatsolute transfer is only by radial diffusion from the immobile-water re­gion within the spheres to the mobile-water region between them
(Rezaei et al., 2021).
Pressurized drip irrigation can be treated as unsaturated application(UA) (Barnard et al., 2010; Callaghan et al., 2017), which allows enoughtime for solute diffusing to the surface of aggregates so that it can sub­sequently be removed by convective dispersion transport through larger
pores and minimize the effects of bypass flow (Barnard et al., 2010).
The traditional leaching guidelines usually follow the leachingrequirement (LR) concept that is based on steady-state water flow andsalt mass balance. Although true steady-state conditions do not exist in
the real-world irrigated systems, steady-state may become a reasonableapproximation over a sufficiently long period (such as a season or more).
Mathematically, a steady-state flow analysis does not include a time
variable, and thus there are many factors that can violate the steadystate assumption under the field conditions, especially in irrigatedcroplands where alternating wetting and drying conditions are more therule than exception (Letey et al., 2011).
For drip irrigation, the use of conventional LR can result in excessive
leaching (Yang et al., 2019). This further justifies the reassessment of the
traditional one-value LR and adopting a more comprehensive approachto determine leaching requirement by considering the relationships
among water salinity, water application rate, soil texture, and theamount of leaching (Letey et al., 2011; Oster et al., 2012; Minhas et al.,2020). The performances of irrigation methods concerning their effi­
ciency and crop response have been extensively studied, but very little is
known about the impact of water application methods on leaching ef­
ficiency in various textured soils with different hydraulic properties. As
indicated by Hoffman (2009), application rates have effects on soil
salinity leaching efficiency, and the leaching coefficient is approxi­
mately 0.3 for ponding and 0.15 for sprinkler application.
Mathematical models can represent the natural system, and objective
use of models can guide both our future research efforts and current
management practices (Mirbagheri, 2004); while column experiments
are useful tools for constructing models and estimating model parame­ters (Li et al., 2007). The overall objective of this research was to assess
irrigation management practices on salinity leaching efficiency in threesoils of different textures. Specifically, we aimed to (1) conduct labo­
ratory column experiments to evaluate the effect of water application
methods on salinity leaching efficiency in the test soils; (2) use inverse
modeling of column experiment to estimate water and solute transport

Table 1
Particle size distribution and bulk density of the packed soil columns.
Soil sampling
location

Clay

Silt

Sand

(d < 2µm)(2 µm ≤ d ≤63 µm)(d ≥ 63µm)

SC-REC

4.41

45.64

49.95

Kern County
Desert-REC

9.4
72.32

51.99
19.23

38.61
8.45

Soil
textureBulkdensity(g cm-3)

Sandy
loam
Silt loam
Clay

1.56
1.51
1.35

parameters and assess the effect of water application methods on soil
quality (S index); and (3) identify water application methods to achieve
optimal leaching efficiency through a series of simulations under field
conditions by taking into account of soil properties, crop type, irrigationwater quantity and quality, and irrigation methods.
2. Material and methods
2.1. Laboratory leaching experiments
2.1.1. Soil sampling and preparation
Three surface soils (0–25 cm) were collected from three field sites in
California. A sandy loam (Coarse-loamy, mixed, superactive, calcareous,thermic Typic Xerofluvents) was from South Coast Research & Extension
Center (South Coast-REC) in Irvine, CA; a silt loam (Fine-loamy, mixed,
superactive, thermic Durinodic Xeric Haplargids) was from an almondorchard in Kern County, CA; and a clay soil (Fine, smectitic, calcareous,
hyperthermic Vertic Torrifluvents) was from the Desert Research &Extension Center (Desert-REC) in Holtville, CA, respectively. The
collected bulk soils were air-dried, gently crumbled to pass through a 2mm sieve and mixed thoroughly before packing. Particle size analysis
was performed to verify soil texture using a laser particle size analyzer(Beckman-Coulter LS 13–320) (Table 1).
2.1.2. Soil column setup and pretreatments
Plex-glass cylinders (10-cm dia. By 35-cm high) were used for
packing the soil columns. In each column, a cellulose sheet was placed at
the bottom of the column, followed by 1-cm homogeneous grain sized
sand (~1 mm dia.) to facilitate free drainage, and ensure one dimen­
sional water movement. The air-dried soil was then packed in 5-cm in­crements according to the measured field soil bulk density to a totalheight of 30 cm (Table 1). The column experimental treatments included
3 soil types and 3 water application methods, and each treatment was
replicated 3 times, resulting in a total of 27 packed soil columns. Two
additional columns of each soil type were also used for measuring initialsoil salinity distribution after pretreatment of the columns.
Before leaching, each packed soil column was slowly saturated fromthe bottom with a saline solution applied by a Mariotte bottle (Fig. 1a).
The saline solution was created by mixing 0.90 g/L of CaCl2 and 0.48 g/Lof NaCl in distilled water (approximately ECw = 3 dS/m, SAR = 16, andpH = 7.55). After water appeared at the surface for 24 hrs., the soilcolumns were allowed to dry for 3 days to stabilize the soil formation sothat the columns can better mimic field conditions (pretreated columns),
as illustrated in Fig. 1b.
After leaching, two columns from each of the three test soils weresectioned into 3-cm layers to measure vertical salinity distributions in
the columns (Fig. 2). The collected soil samples were air dried andpassed through a 2-mm sieve, then using EC1:5 (1:5 soil to water ratio)
method to extract solution. With measured Ca, Mg, Na, Al, CO23 , HCO3,
2SO4 , EC1:5 was converted to EC1:1 (ECsw) by the Unsatchem model.
2.1.3. Column leaching experiments
Three water application methods: continuous ponding (CP), inter­mittent ponding (IP), and unsaturated application (UA), were imposedon the pretreated columns using tap water [Electrical conductivity (EC)2

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Agricultural Water Management 281 (2023) 108250

Fig. 1. Illustration of different water application methods (a); and schematic of salinity leaching experiments in the laboratory (b).

= 0.4 dS/m, SAR = 5, and pH = 8.2] to leach salts in the soils. An in­dividual Marriott bottle was used to apply water and control the pres­sure head for each column.
For the CP and IP methods, the ponding head for the soil columns
was maintained at 1 cm (Fig. 1b). For the IP, water ponding wasmaintained for about 8–10 hrs in all the columns, then it was turned off
for approximately 4–8 hrs in the sandy loam, 5–8 hrs in the silt loam, and10–30 hrs in the clay soil, respectively, to collect approximately sameamount of drainage water each time after water application was turned
off and before it was resumed for next ponding.
For the UA method, a 2-cm layer of fine-grained glass beads was usedboth at the bottom and the top in each of the packed soil columns. The
air-entry value of the glass beads layer is about − 10 cm, and thus it acts
like a porous plate and allows to control water application undernegative pressure at the top of the column (like a suction permeameter).
A 0.5-cm diameter and 9-cm long plastic tube (closed end) with threesmall holes was attached to the water supply line and buried in the glass
beads to ensure water was evenly distributed at the column surface.
Aluminum foil was used to cover the soil columns to prevent water loss
from evaporation during the entire experimental period.

Fig. 2. Distributions of average soil water electrical conductivity (ECsw) withsoil depth of the pretreated soil columns.

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Agricultural Water Management 281 (2023) 108250

Fig. 3. Initial and boundary conditions for the HYDRUS-2D simulations: a. Almond orchard field irrigation scheme (actual) and ETo; b. Initial ECsw distribution in thesoil profile.

Drainage water (leachate) was collected with a 200-ml flask at aninterval of approximately 100 ml, and EC of the leachate was measured
by an electric conductivity meter (Accumet Research AR50 pH/mV/Ion/
Conductivity Meter, Fisher Scientific, IL).

did not simulate water and solute transport well in the clay columns.
Thus, the dual-porosity version of the HYDRUS-1D was used to simulate
water and solute transport in the clay soil columns where soil water may
exist both in the mobile (θm, moving in inter-aggregate) and immobile(θim, stagnant in intra-aggregate) regions. Under such circumstance, thesoil water content can be expressed as:

2.2. Leaching efficiency simulations in the columns and under field
conditionsθ = θm + θim(2)

The dual-porosity formulation for water flow used in the HYDRUS1D uses the Richards equation to describe water flow in the fractures(macropores) and a mass balance equation to describe moisture dy­
namics in the matrix as follows (Šimůnek et al., 2003):
[
(
)]
∂θm ∂
∂h
(3)
=
k(h)
+1
− Sm − Гw∂z∂t∂z

The HYDRUS-1D model was used to simulate the effects of different
application methods of continuous ponding, unsaturated application,and intermittent ponding methods on leaching efficiencies in the soilcolumns. To mimic the irrigation scheme at the almond orchard field,
the simulations used the fixed frequency methods (every 7, 5 and 3 days)
to evaluate the leaching efficiency. In addition, the HYDRUS-2D model
was used to simulate the effects of fixed/flexible frequency intervals(every 7, 5, and 3 days vs actual scheduling) on leaching efficiency fordrip irrigation in the almond orchard under the field conditions.

∂θim= − Sim + Гw∂t(4)

where Sm and Sim are the sink terms for the two respective regions, and2.2.1. Transport equations
In the HYDRUS-2D model, the Richards equation is numericallysolved to simulate water flow (Šimůnek et al., 2016):
[
]
[
]
∂θ ∂
∂h
∂
∂h
∂K(h)
=
K(h)
+
K(h)
−
− R(h)
(1)
∂z
∂t ∂x
∂x
∂z
∂z

Г w is the transfer rate for water from inter- to the intra-aggregate pores.

The dual-porosity formulation for solute transport in the HYDRUS1D is similarly based on the convection-dispersion and mass balance
equations as follows (Šimůnek et al., 2016):()∂θm cm ∂f ρsm ∂
∂cm
∂qcf
(5)
+
=
θ m Dm−− Фm − Гs
∂z
∂t
∂t
∂z
∂z

where θ is the volumetric water content (cm3 cm-3) as a function of soil
matric pressure head (h, cm H2O), K(h) is the soil hydraulic conductivity(cm h-1) as a function of h, x is the horizontal coordinate (cm), z is thevertical coordinate (cm), and R(h) is the root water uptake term (cm3
cm-3 h-1). θ(h) and K(h) are calculated from the van Genuchten model(van Genuchten, 1980) and Mualem’s (1976) model, respectively.
Our preliminary results showed that the original HYDRUS-1D model∂θim cim ∂(1 − f )ρsim+= − Фim + Гs
∂t
∂t

(6)

where cm and cim are solute concentrations of the mobile and immobile
regions (g cm-3), respectively; f is the fraction of sorption sites in contact
4

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Agricultural Water Management 281 (2023) 108250

Fig. 4. Observed ECdw as a function of pore volume of the three test soils under continuous ponding (CP), intermittent ponding (IP), and unsaturated application(UA): a. sandy loam, b. silt loam, and c. clay soil.

with the mobile water content (dimensionless), ρ is soil bulk density (gcm-3), sm and sim are sorbed solute concentrations of the mobile andimmobile regions (g g-1), respectively; Dm is the dispersion coefficient in
the mobile region (cm2 h-1), q is the volumetric fluid flux density in themobile region (cm h-1), Φm and Φim are sink-source terms that accountfor various zero- and first-order or other reactions in the two respective
regions (g cm-3 h-1), and Г s is the mass transfer term for the solutes
between the mobile and immobile regions (g cm-3 h-1).
The obtained hydraulic parameters for the van Genuchten equation
were further used to calculate slope S (Eq. (7), Dexter, 2004) for each of
the soil columns under different water application method:()− (1+m)
1
S = n(θsat − θr ) 1 +m

2.2.2. Initial and boundary conditions
The initial ECsw distributions in the soil columns are shown in Fig. 2.
The initial soil water condition was expressed as pressure head (cm),which increased linearly from the top (− 30 cm) to the bottom (0 cm).
The upper boundary conditions of water flow in the columns
receiving continuously ponding (CP) and unsaturated water applications(UA) were set to a constant positive pressure (CP, 5 cm) and negative
pressure (UA, − 2 cm), respectively. In the columns receiving intermit­
tent ponding (IP), the upper boundary condition used variable pressure
heads, which was entered as a time series in the model input file. Salt
flux for the upper boundary condition was based on the concentration of
the infiltrating water (3 dS/m).
The lower boundary condition in the columns was imposed as‘seepage face’ on the sandy and silt loams for all the three water
application methods. While in the clay soil columns, a vacuum pressureof − 40 cm at the seepage face was applied to facilitate the collection ofleachate. A zero-concentration gradient was used at the lower boundary
condition for solute transport in all soil columns.
For simulations under field conditions, the initial matric pressure(7)

where, S is used as a soil physical quality index that indicates the extent
to which part of the soil porosity is concentrated into a narrow range ofpore size.

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Agricultural Water Management 281 (2023) 108250

Fig. 5. Total leached salts of the test soils under the three water application methods: a. sandy loam, b. silt loam, and c. clay soil.

head was − 1500 cm, the upper boundary condition was set as variable
flux (field irrigation scheme) and atmosphere boundary conditions forevapotranspiration (ETo) (Fig. 3a). The lower boundary condition was
free drainage for all the treatments. The initial ECsw distribution in the
profile was set to the same for the three water application methods as
measured in the field (Fig. 3b).
Salinity effect on root distribution and root water uptake wasconsidered in the simulations under the field conditions. The maximum
rooting depth of almond was set to 122 cm (4 feet), and the maximum
rooting radius was 152.4 cm (5 feet), and the shape parameters of Pz andPx were 1. The matric-pressure head parameters in the Feddes et al.
(1978) model were: h1 = − 10 cm, h2 = − 25 cm, h3 = − 500 cm, and h4= − 8000 cm. The threshold salinity value was ECe = 3 dS/m and theslope of almond yield function was 19%.
The climate and crop information of the almond orchard in Kern
County, CA was based on the CIMIS station (#5, Shafter, CA) near thefield as well as field measured data. Irrigation water was applied bydouble-line drip irrigation in the orchard and the amount of water
application was calculated based on ETo multiplying the almond crop
coefficients ranged from 0.8 to 1 (Kirr). The changes of daily irrigation
scheme and ETo are showed in Fig. 3a.

2.3. Leaching efficiency evaluation
The total drained salts can be calculated as follows (Yang et al.,2019):
Tsalts = Ddw TDS(8)

where Tsalts is total salts drained per unit area (g/cm2), Ddw is drainage
water depth (cm), TDS is total dissolved solids: TDS (mg/L or ppm)
= ECdw (dS/m) × 640 (ECdw from 0.1 to 5 dS/m); and TDS (mg/L orppm) = ECdw (dS/m) × 800 (ECdw > 5 dS/m), ECdw is EC of drainage
water (dS/m). Leaching (or drain) efficiency is defined as the ratio of thedrained salt mass to the applied salt mass, and can be calculated asfollows (Grismer, 1990; Yang et al., 2019):
LE =DdwECdw
LFw=
DiwECiw
LFEC(9)

where LE is leaching efficiency, LFEC is leaching fraction based on EC(ECiw/ECdw), LFw is leaching fraction based on depth of drainage waterand irrigation water (Ddw/Diw), and Diw and ECiw are depth and EC ofirrigation water, respectively. A lower LE indicates that more salts are
retained (higher salinity) in the rootzone.

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Agricultural Water Management 281 (2023) 108250

Table 2Inversely estimated hydraulic parameters of the three study soils under different water application methods.
Soil Water
application
Sandy loam

Cont.
Inter.
Unsat.
Cont.
Inter.
Unsat.(1st)Unsat.(2nd)Cont.(1st)Cont.(2nd)Inter.(1st)Inter.(2nd)Unsat.

Silt loam

Clay soil

θr
(-)

θs
(-)

Alpha
(cm-1)n(-)

Ks(cm hr-1)

l
(-)

θrim
(-)

θsim
(-)

ω

(hr-1)

S
(-)

0.02
0.02
0.02
0.048
0.048
0.048
0.048
0.068
0.068
0.038
0.038
0.068

0.5
0.5
0.483
0.45
0.45
0.45
0.45
0.38
0.265
0.38
0.38
0.38

0.064
0.064
0.064
0.11
0.11
0.31
0.43
0.008
0.0093
0.05
0.05
0.009

1.4
2.5
1.16
1.17
1.18
1.2
1.27
1.15
1.14
1.2
1.2
1.2

0.225
0.42
2.0
2.71
0.375
0.87
0.022
0.0087
0.05
0.02
0.39
0.0029

0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5

0.002
0.002
0.002
0.002
0.002

0.15
0.15
0.15
0.15
0.15

0.02
0.02
0.01
0.01
0.02

0.097
0.250
0.049
0.044
0.046
0.050
0.062
0.031
0.019
0.042
0.042
0.039

2.4. Data analysis

Table 3Inversely estimated solute transport and reaction parameters of the three study
soils under different water application methods.

Three commonly used evaluation criteria, the coefficient of deter­
mination (R2), the root mean square error (RMSE), and the mean error(ME) of the measured vs calculated values, were used to evaluate theaccuracy of model simulation:∑(oi − pi )2i2
R = 1− ∑(10)(oi − oi )2

Soil Water application

Dispersion(cm)

Fraction(-)ω

Sandy loam

0.189
0.22
0.8
0.15
0.16
1.2
1.2
1.2
0.8
0.079
0.079
5

1
1
1
1
1
1
1
1
1
1
1
1

0
0
0
0
0
0
0
0.01
0.01
0
0
0

Silt loami[
RMSE =∑Ni=1(pi − oi ) N∑|oi − pi |
ME =

i

N

2/

]1/2
(11)

Clay

(12)

Cont.
Inter.
Unsat.
Cont.
Inter.
Unsat.(1st)Unsat.(2nd)Cont.(1st)Cont.(2nd)Inter.(1st)Inter.(2nd)Unsat.

(hr-1)

the sandy loam (Fig. 5a), almost all salts were removed at 1.2 RPV, with
2.42 g and 2.03 g salts, respectively, removed by CP and UA in theirrespective columns, which were slightly higher than that of IP (1.69 g).
As RPV increased from 1 to 2, there was little increase in total salt
removal among the three methods (CP: 2.76 g, IP: 2.08 g, and UA:
2.44 g).
Like the sandy loam, most of the salts were leached out at 2.2 RPV in
the silt loam (Fig. 5b). As RPV increased from 1 to 2, there was only
small increase in salt removal. After 3 RPV, no more salts were removed
under CP (4.79 g) and IP (4.92 g), but salt leaching continued after 3
RPV under UA (3.38 g), indicating that in the silt loam, leaching is more
efficient under CP and IP than that under UA.
In the clay soil, more salts were leached out under CP (11.12 g) andIP (11.4 g) than that under UA (7.8 g) at the same drainage volume of
2.2 RPV. Among the three soils, more salts were leached out from theclay columns than that from the sandy loam (3.2–5.5 times) and the silt
loam (2.3–2.75 times) columns at 2.2 RPV for all the three water
application methods (Fig. 5c). Nevertheless, because the initial salinity
in the clay columns was much higher than that in the sandy loam and silt
loam columns, it requires more water to remove all salts in the clay
columns (about 5 RPV) (Fig. 5c).
Our laboratory results indicate that salt leaching efficiency varies
with soil texture as well as water application methods. In the packed soilcolumns, CP led to saturated soil, steady flow and convective-dispersion
solute transport in the soil. For IP, the soils were saturated at the
beginning, but flow was interrupted for a predetermined period and noconvective transport occurred during this period, which allowed thesoils have more time for salts to diffuse out of the aggregates duringleaching. The experimental data from the columns suggest that leachingefficiency in coarser soils (sandy and silt loam) is higher than that in finesoils (clay) under the three water application methods (CP, IP, and UA).

Where oi is observed data, ōi is the mean of the observed data, and pi isthe predicted data.
3. Results
3.1. Effect of water application methods on salinity leaching in the packed
soil columns
To assess the salinity leaching efficiency, leachate from each of the
27 packed soil columns subjected to different treatments (3 soil texturesand 3 water application methods with 3 replications) was collected andthe EC of the leachate (ECdw) was measured.
On average, the observed ECdw breakthrough curves with respect todimensionless time (relative pore volumes, RPV) differed substantially
under various water application methods (Fig. 4), with most of salts
coming out at approximately 2 RPV. For the sandy loam, the ECdw cameout and reached the plateau earlier (< 1 RPV), and the peak ECdw values
were lower (< 8 dS/m with ECiw = 1 dS/m) under IP and UA than that
under CP (≈ 1RPV, ECdw = 18 dS/m) (Fig. 4a).
In the silt loam, the ECdw reached the plateau (22 dS/m at < 1 RPV)
earlier under IP than that under CP (≈ 1RPV, ECdw = 20 dS/m) and UA(≈ 1RPV, ECdw = 8 dS/m) methods (Fig. 4b). However, all the threewater application methods have very similar breakthrough time (≈ 1
RPV) and peak value (ECdw/ECiw = 14 dS/m) in the clay soil (Fig. 4c).
The above observations indicate that the effect of water application
methods on salinity leaching is more profound in coarse soils (sandy andsilt loam) than that in fine soils (clay), which agrees with the observa­
tions by Russo et al. (2009). For a given irrigation water quality (ECiw),
coarse textured soils have weak capillary force, thus the amount of water(≈ 2 RPV) required to leach out the salts in coarse soils is less than that infine soils, as shown by the ratio of ECdw/ECiw. Besides, most of the salts
were leached out before 2.2 RPV for all the three test soils (Fig. 5a-c). In
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Agricultural Water Management 281 (2023) 108250

Fig. 6. Observed (symbols) and HYDRUS-1D fitted (lines) cumulative drainage water under continuous ponding (CP), intermittent ponding (IP), and unsaturated
application (UA): a. sandy loam, b. silt loam, c. clay soil, and d. stepwise curve fitting.

3.2. Model estimated hydraulic and solute transport parameterssolute transport and reactive parameters (Table 3) that were obtained byinverse modeling through simulating the observed cumulative drainage(Fig. 6) and ECdw of the drainage water (Fig. 7) as a function of time
under CP, IP, and UA, respectively, in the soil columns.

The effects of both soil texture and water application methods on
salinity leaching are reflected in the hydraulic parameters (Table 2), and8

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Agricultural Water Management 281 (2023) 108250

Fig. 7. Observed (symbols) and HYDRUS-1D fitted (lines) ECdw under continuous ponding (CP), intermittent ponding (IP), and unsaturated application (UA): a.
sandy loam, b. silt loam, and c. clay soil.

columns, since the dual-porosity model fitted the experimental data
better for the clay soil.
Using the estimated hydraulic parameters, the HYDRUS-1D simu­
lated cumulative drainage (cm) as a function of time matched theexperimentally measured data well in the sandy loam for all the threewater application methods (Fig. 6a). To better fit the experimental dataof the cumulative drainage depth vs. time for the silt loam and clay soil,
the measured drainage curves were divided into two pieces (first stage
and second stage of leaching) based on the turning point as shown in
Fig. 6b-c. The simulated data at the end of the first period were set as theinitial conditions for the second period. The two-piece model fittings
matched the experimental data much better than those of the simple
linear regression model fittings (Fig. 6d).
The observed ECdw change with time under CP, IP, UA fitted byequilibrium (sandy loam and silt loam) and non-equilibrium (clay soil)models are shown in Fig. 7, and the data error analysis for the three soils
under different treatments are shown in Table 4.
Besides, the obtained hydraulic parameters from inverse modelingwere applied to calculate parameter S, a soil physical quality index thatis related to water transmission properties. The S index varies with soil
structure, total porosity, and water content (Rezaei et al., 2021). When
the S value is greater than 0.050, the soil is considered as very good,
0.050 > S > 0.035 as good, 0.035 > S > 0.020 as poor, and S < 0.020 as

Table 4
Statistical analysis of drainage ECdw between model simulation and samplingsoils under different irrigation treatments.
Soil Water application
Sandy loam
Silt loam

Clay

Cont.
Inter.
Unsat.
Cont.
Inter.
Unsat.(1st)Unsat.(2nd)Cont.(1st)Cont.(2nd)Inter.(1st)Inter.(2nd)Unsat.

R2

RMSE

ME

0.94
0.97
0.96
0.6
0.91
0.74
0.86
0.99
0.88
0.93
0.88
0.99

0.35
0.20
0.80
6.12
0.79
0.69
0.72
0.074
0.18
0.29
0.187
0.12

0.16
0.11
0.05
1.4
0.23
0.24
0.41
0.032
0.056
6.9
3.5
0.11

For the sandy loam and silt loam, the parameters were inversely
estimated based on the van Genuchten hydraulic function (Eq. (1)) andthe equilibrium solute transport model (Eq. (5)), while for the clay soil,
they were obtained based on the dual-porosity (mobile-immobile water)model (Eqs. (2)–(4)) and the physical non-equilibrium model (Eq. (6))
by considering that a suction was applied at the bottom of the soil
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Agricultural Water Management 281 (2023) 108250

Fig. 8. Water flux and water balance under 4 irrigation intervals: a. drainage flux, b. water balance, c. daily and cumulative drained salts (1 m2 area), d. ECsw
distributions in the soil profiles.,.

very poor quality (Dexter, 2004).
Under CP, the S values were 0.097 for the sandy loam, 0.044 for silt
loam, and 0.031 for the first stage of leaching, and 0.019 for the second
stage of leaching in the clay soil, respectively. In terms of S, the qualityof the sandy loam is very good, the silt loam is good, and the clay soil ispoor.
Under IP, the S values were 0.25, 0.046 and 0.042 for the sandy
loam, silt loam and clay soil, respectively. The S values of silt loam
(0.046) and clay soil (0.042) were very close, and they were higher
under IP than those under CP, which implies that compared with CP,
water transmission of the three soils was improved under IP.
Under UA, the S values were 0.049 for the sandy loam, 0.05 and0.062 for the first and second stage of leaching for the silt loam, and0.042 for the clay soil. Different from the S values obtained under CP and
IP, the silt loam had a very high S value under UA, indicating the silt
loam and clay soil quality in terms of water transmission was improved
under UA, while the sandy loam quality declined from very good to goodquality level under UA.
The S index change with water application methods indicates that
this soil quality index (S) can be improved through irrigation manage­
ment. Based on our data, CP and IP were better irrigation methods forthe sandy loam (very good quality) than UA (good quality). For the silt
loam, UA performed better (very good quality) than CP and IP (goodquality); and for the clay soil, IP and UA were substantially better (goodquality) than CP (very poor quality). In other words, continuous ponding
was the best choice for coarser soils to maintain soil quality at very goodlevel. For finer soils, intermittent ponding and unsaturated application
were better water application methods, and unsaturated application was
the best for the silt loam.

3.3. Effect of irrigation frequency on leaching efficiency in the almondorchardSalinity leaching efficiency under different irrigation schemes of 7, 5,
and 3-day intervals versus the actual field irrigation scheme (flexible
frequency) was evaluated for the almond orchard located in Kern
County, CA. Daily drainage flux, water balance, salt flux, and cumulativedrained salts during the growing season, and ECsw distribution in the soil
profiles at the end of the season for the 4 irrigation schemes are shown in
Fig. 8a-d.
Compared with the ET-based actual field irrigation scheme (flexible
frequency, Fig. 8a), the daily drainage fluxes under fixed frequency
irrigation decreased as irrigation frequency increased. The simulated
peak drainage fluxes and cumulative drainage depths decreased grad­ually from the 7- to 3-day irrigation interval (from lower to higher fre­quency) since shorter irrigation interval provided more opportunity forroot water uptake. Compared with fixed irrigation frequency, drainage
flux was reduced and cumulative root water uptake and evapotranspi­
ration increased in the flexible frequency irrigation (the orchard irri­
gation scheme). Thus, we conclude that fixed interval, high frequency
irrigation can help to provide more water for root uptake (Fig. 8b).
The simulated daily salt flux and cumulative drained salts under
flexible frequency irrigation (orchard irrigation scheme) and fixed fre­quency irrigation (3-, 5-, and 7-day intervals) are shown in Fig. 8c. For
the flexible frequency irrigation, the first peak of salt leaching out of therootzone started about 125 days and the second peak started about 225
days after irrigation initiated (see cum. drained salts). After then thesalts drainage rate started declining.
Salinity distributions in the soil profiles at the end of the season10

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Agricultural Water Management 281 (2023) 108250

Fig. 8. (continued).

under different irrigation schemes are shown in Fig. 8d. The salinity inthe rootzone (0–152.4 cm) decreased (from 40 to lower than 5 dS/m).
Salinity near the emitter was lower, but the cumulative drained salts was
less, under flexible frequency irrigation than that under fixed frequency
irrigation of 7-, 5- or 3-day interval. For fixed frequency irrigation, more
frequent irrigation with smaller amount of water is preferable in thealmond orchard soil, which indicates that fixed, higher frequency irri­
gation scheme can reduce the effect of salinity stress on the crop due tolower EC in the rootzone.

4. Discussion
4.1. Dominant factors affecting soil salinity leaching
The effect of both soil texture and irrigation water application
methods on soil salinity leaching can also be observed from the hy­
draulic and solute transport parameters. Salinity leaching is coupledwith water movement thus it depends on the Darcy velocity, which
differs among the water application methods of saturated (CP), semisaturated (IP), or unsaturated (UA) condition (Al-Sibai et al., 1997;
Hoffman, 2009; Chu et al., 2016; Callaghan et al., 2017).
In the silt loam, the model overestimated the cumulative drainage
depths after 200 hrs of leaching under UA due to a decrease in drainage
rate during the leaching experiment (Fig. 6b). There exist large
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Agricultural Water Management 281 (2023) 108250

Table 5
Salts balance and leaching efficiency under different irrigation treatments for fields simulation.
Scenarios
Flexible frequency
Fixed frequency

Actual field schedulingEvery 7 days
Every 5 days
Every 3 days

Cum. Input salts (g)Cum. Drained salts (g)

LFEC

LFw

LE (%)

870
870
870
870

802
749
813
838

0.276
0.279
0.26
0.255

0.26
0.245
0.248
0.25

94.2
87.8
95.4
98.0

differences between the measured and simulated cumulative drainage
depths between CP and IP methods in the clay soil (Fig. 6c). The dis­
crepancies between the simulated and observed data under UA in the silt
loam, and under CP and IP in the clay soil are attributed to the possible
clogging and interaction between ions and soil particles in these soilcolumns, which changed the soil structure and permeability, andconsequently, the drainage rate (van der Zee et al., 2014). Besides, afiner soil has greater specific surface area and porosity, and theiradsorption capacity is generally greater than that of the coarse soils (Liuet al., 2020).
Under different irrigation methods, the inversely estimated hydrau­
lic and solute transport parameters are different (Tables 2 and 3) for thesame soil, which can be attributed to the soil water hysteresis effect.
Structured clay soils benefit mostly from leaching under unsaturated
flow conditions (Tanton et al., 1988; Armstrong et al., 1998) andintermittent water applications (Tagar et al., 2010; Hoffman, O’Connor,
1980). Under saturated conditions, fine soils can retain some of theoriginal soil solution during continuous leaching, whereas drier soils
with intermittent ponding allow a larger fraction of water flowing
through the fine pores and displacing the salts more efficiently (Hoff­man, O’Connor, 1980).
At the same matric pressure, a coarse textured soil has low watercontent and high leaching efficiency under continuous ponding. How­ever, saturated volumetric water content does not affect leaching effi­
ciency among different soils under intermittent ponding (Hoffman,
O’Connor, 1980). Phogat et al. (2012) observed that intermittent water
application pulsing has a smaller impact on leaching fraction and salt
removal in light textured soils.

approximately 100 days after the beginning of irrigation, which is muchearlier than that (~150 days) of flexible frequency irrigation, and thecumulative drained salts at the end of season was 749 g for the 7-day
interval, which is less than that of the flexible frequency irrigation(802 g), but it increased as the irrigation frequency increased (813 g and
838 g, respectively, for the 5- and 3-day interval).
Root water extraction affects not only soil water content and salinity,
but also the movement of water and salts in the rootzone. Plant water
uptake is subjected to osmotic stress effect. The soil water salinity (ECsw)
was lower in the upper layer but higher in the lower layer as irrigation
frequency decreased (longer irrigation intervals) (Fig. 8d), indicatingthat less water uptake under lower frequency irrigation tends to push thesalinity to lower layers.
In terms of salinity leaching, our results indicate that more frequent
application with smaller amount of water (every 3, 5 days) is preferable
to that of less frequent with larger amount of water (every 7 days), as
well as to the flexible frequent irrigation due to its higher LE (Table 5).
Similar results were obtained by Kumar et al. (2007) and Zhou et al.
(2018).
5. Conclusions
In this study, laboratory column study was conducted to evaluatesalinity leaching in three soils of different textures under three irrigation
methods. Our results showed that the test soils responded to water
application methods differently: continuous ponding (CP) was the bestfor the coarse soils (sandy loam) to maintain soil quality at very goodlevel. For the fine soil (clay), intermittent ponding (IP) and unsaturated
application (UA) were better, and UA was the best method for the silt
loam. Using the hydraulic and solute transport parameters estimated by
HYDRUS-1D from the column experiments to calculate the S index, we
found that proper water application methods can improve water trans­mission and salinity leaching.
HYDRUS-2D simulations based on the estimated hydraulic and solutetransport parameters further indicated that irrigation schemes (fixedand flexible frequency) can affect plant water uptake, drainage volume,and salinity leaching under the field conditions of the almond orchard in
Kern County, CA. Salinity leaching efficiency (LE) under flexible fre­quency irrigation is higher than that of 7-day fixed irrigation interval,
but lower than those of 3- and 5-day fixed irrigation intervals. For the
fixed frequency irrigation, the cumulative root water uptake as well as
the salinity leaching efficiency (LE) increased, while the cumulativedrainage decreased as the frequency decreased (longer interval). Hence,
more frequent application with smaller amount of water is recom­
mended to achieve higher leaching efficiency for the almond field.

4.2. Effect of salinity on rootzone water and salt balance
The effect of salinity on transpiration is usually attributed to its effecton water flux from a given soil volume to the plant roots (Carli et al.,2014; Zhou et al., 2018). Under surface drip irrigation, the salt accu­
mulation in a radial pattern above the wetting zone may reduce theeffective soil volume from which water is extracted, thus reduce tran­
spiration (Dudley et al., 2008). At the field scale, large differences insalinity at the end of season in the soil profiles under various irrigation
schemes and plant water uptake are due to disruption of water flux, anddistribution of water and salinity in the rootzone.
Although the same amount of water is applied, the soil moisture andwetting pattern can be different under various irrigation schemes. Rootwater uptake rate under flexible frequency irrigation was lower thanthat under fixed frequency irrigation; while for the fixed frequency
irrigation, water uptake rate was lower under lower frequency irrigation(longer interval) than that under higher frequency irrigation, indicatingthat high-frequency irrigation can improve irrigation water use effi­
ciency (IWUE) and water use efficiency (WUE) of plants (Wang et al.,2006; Kassem, 2008). Kanber et al. (1991) reported that the amount ofirrigation water decreased when IWUE and WUE values increased.
Studies have shown that more frequent irrigation with smaller amountof water increases the yield because ET is higher when irrigation starts at
higher soil water content or matric pressure (Stansell and Smittle, 1989).
For the fixed frequency irrigation schemes, salt leaching appeared atabout 75 days after the beginning of irrigation, but the leaching rate
decreased as irrigation frequency increased. As shown by the cumulativedrained salts (Fig. 8c), salts started to leach out of the rootzone at

Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Data availability
Data will be made available on request.

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Agricultural Water Management 281 (2023) 108250

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We are very thankful to anonymous reviewers and editors for theirvaluable time in reviewing and providing constructive comments on the
manuscript. We also acknowledge the financial support by the Divisionof Agriculture and Natural Resources, University of California Compet­
itive Grants Program, USA; GDAS’ Project of Science and Technology
Development, China (2021GDASYL-20210102008); and Guangdong
Basic
and
AppliedBasic
Research
Foundation,
China(2021A1515110957).
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