Geoderma 423 (2022) 115969

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Evaluating soil salts dynamics under biodegradable film mulching withdifferent disintegration rates in an arid region with shallow and saline
groundwater: Experimental and modeling study
Ning Chen a, c, Xianyue Li a, c, *, Jiří Šimůnek b, Yuehong Zhang a, Haibin Shi a, Qi Hu a,
Maoxin Xin aaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China
Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USAc
Collaborative Innovation Center for Integrated Management of Water Resources and Water Environment in the Inner Mongolia Reaches of the Yellow River, Hohhot
010018, Chinab

A R T I C L E I N F O

A B S T R A C T

Handling Editor: Matthew Tighe

Soil salinization caused by shallow, saline groundwater represents a serious threat to field productivity, espe­
cially in arid regions with intense soil evaporation. Plastic film mulching (PM) has been increasingly applied toreduce soil evaporation and alleviate soil salinity stress. However, PM introduces into the soil a significant
amount of plastic residues. Although biodegradable film mulching (BM) is an ideal alternative to PM due to thedegradability of these films, unreasonably high disintegration rates may reduce the benefits of the proposedsolution. Understanding the effects of these factors on soil salinity is essential for designing management options
for improving water productivity. A two-year cornfield experiment was therefore carried out during 2019–2020
to evaluate differences in soil salt dynamics among treatments with BMs with low, medium, and high disinte­
gration rates (BML, BMM, BMH), one polyethylene film mulching (PM), and no mulching (NM). Additionally, the
HYDRUS-2D model was used to evaluate the electrical conductivity of the saturation paste extract (ECe), soil salt
fluxes, salt distributions, and salt mass balances in two-dimensional soil profiles under BML, BMM, BMH, PM, and
NM. The results showed that calibrated HYDRUS-2D could precisely simulate soil salinity under different
mulching treatments. There were large differences between various treatments in the middle and late crop
growth stages (Days After Sowing [DAS] 61–140). The highest ECe among different BM treatments occurred in
BMH. Additionally, the two-dimensional distribution of soil salinity under BM was affected by irrigation events.
The high soil salinity stress area (ECe > 3.80 dS m− 1) occurred one day after irrigation (DAS 108) only under
BMH among different BM treatments. Meanwhile, root water uptake (RWU) and crop yield (CY) under BMH weresignificantly reduced due to excessive accumulation of soil salinity in the root zone under intensive soil evap­oration conditions. Compared with BMH and BMM, BML increased CY and the leaching ratio of soil salts from theroot zone due to its good performance in water conservation. Thus, BM with a low disintegration rate is more
efficient in controlling soil salinization in soils with a shallow groundwater table than BMs with higher disin­tegration rates due to lower soil evaporation. The findings of this study improve the understanding of themechanisms of salt dynamics under biodegradable film mulching with different disintegration rates. The study
also recommends to the farmers and government a suitable disintegration rate of the biodegradable film that canbe adopted to promote field productivity.

Keywords:
Soil salinity
Biodegradable film
Disintegration rate
Groundwater
Brackish water
HYDRUS-2D

1. Introduction
Soil salinity stress is the main factor limiting field productivity ofsalinized farmland, especially in arid regions with intense soil

evaporation and shallow groundwater tables. An intense exchange ofwater between groundwater and soil surface aggravates salt stress.
Agricultural production systems involving plastic film mulching (PM)have been increasingly used worldwide to reduce soil evaporation,* Corresponding author.
E-mail address: lixianyue80@126.com (X. Li).
https://doi.org/10.1016/j.geoderma.2022.115969
Received 7 March 2022; Received in revised form 26 April 2022; Accepted 29 May 2022
0016-7061/© 2022 Elsevier B.V. All rights reserved.

N. Chen et al.

Geoderma 423 (2022) 115969

alleviate soil salinity stress, and increase crop yield (Abed Gatea AlShammary et al., 2020; Kader et al., 2021; Mendonca et al., 2021).
The cause of this phenomenon is that PM can cut off water vapor ex­change between the surface soil and atmosphere, and maintain high soil
moisture by decreasing soil evaporation (Fang et al., 2022). Meanwhile,a reduction in the upward capillary rise and upward migration of soluble
salts occurred due to a small soil water potential difference between thesurface soil and deep soil layers under PM. However, traditional plastic
films are mainly composed of non-degradable low-density polyethylene(Brodhagen et al., 2017; Picuno et al., 2012). The long-term use ofpolyethylene films introduces a significant amount of plastic residues
into the soil, seriously damaging agriculture ecosystems (Beriot et al.,
2021;
Kumar
and
Sheela,2020).
Biodegradable
films,
environment-friendly materials, can be directly degraded to CO2 andH2O and retain advantages and overcome shortcomings of plastic films(Filipović et al., 2020; Gu et al. 2017; Sintim et al., 2019). Therefore, it isincreasingly common to use biodegradable films to reduce plastic resi­
dues in the soil and soil salinization of the root zone while supporting
high crop yields (Saglam et al., 2017; Sintim et al., 2021; Yin et al.,2019).
The evaluation of biodegradable film mulching (BM) has so far been
mainly focused on soil water dynamics, solute transformations, soil
temperature variations, and crop yield (Caruso et al., 2019; Filipović
et al., 2020; Kasirajan and Ngouajio, 2012; Serrano-Ruiz et al., 2020;
Sintim et al., 2021). For instance, Saglam et al. (2017) reported thatwater conservation due to BM is similar to polyethylene film mulching(PM), but the former improved rainfall use efficiency after its disinte­
gration. Caruso et al. (2019) evaluated the effects of different mulchingstrategies on crop yield and soil temperature, revealing that soil tem­
perature under BM was 0.7 ◦ C lower than under PM.
Although solute dynamics under BM have been studied in the liter­
ature (Chen et al., 2020), only soil nitrate transformations and move­
ment have been explored in most cases. There are significant differencesin the effects of BM on soil salt and soil nitrate dynamics due to theirdifferent origins and behavior. The main source of soil nitrate in the rootzone is surface-applied nitrogen or irrigation water (Geza et al., 2021).
On the other hand, the origin of soil salinity in the root zone may beeither saline groundwater or irrigation water (Gebrehiwet et al., 2021),
i.e., root zone soil salinity can come both from above or from below. The
research on soil salt dynamics under BM is limited. In particular, soil salt
dynamics under BM in arid regions with shallow and saline groundwater
have not yet been studied.
Soil salinity significantly affects soil physicochemical properties andplays a negative role in agricultural production (Adeyemo et al., 2022;
Casterad et al., 2018; Kakeh et al., 2021). Root water uptake (RWU) may
become limited because the water potential inside the root cells may not
be low enough to extract water from soils with high soil salinity(Devatha et al., 2016). For example, Babazadeh et al. (2017) assessed
the effects of four irrigation water salinities on RWU and found thatRWU for high salt treatment (8 dS m− 1) was reduced by 48.1%
compared to low salt treatment (1.18 dS m− 1). Soil salinity needs to be
regulated to limit the effects of salt stress on crop growth and agricul­
tural production (Flagella et al., 2004; Gopalakrishnan and Kumar,
2021; Sharma et al., 2016). Successful regulation of soil salinity caneffectively preserve potential crop productivity, avoid secondary sali­nization, and improve crop quality (Bayoumi et al., 2021; Feizi et al.,2007). A complete understanding of soil salt dynamics is thus crucial to
improving agricultural production and farmland environmental
protection.
Due to a common significant shortage of freshwater for irrigatedfarmlands, brackish groundwater is increasingly being used worldwide
for irrigation (Li et al., 2019; Selim et al., 2012). In China, the total
volume of brackish water used for irrigation reached 13 billion cubic
meters, while the volume of brackish water used for irrigation in the
Hetao Irrigation District accounts for nearly 70% of the total volume.
Currently, brackish water has been increasingly used in the Hetao

Irrigation Distract. For example, Zhang et al. (2021) optimized the drip
irrigation strategy with alternate use of fresh and brackish water, andthey found that the “two irrigations with brackish water and one withfreshwater” scenario is the optimal irrigation strategy. Althoughbrackish water has great potential for irrigated agriculture, especiallyafter its treatment to lower salinity to acceptable levels, its unreasonable
use may cause further salinization (Gebrehiwet et al., 2021; Navada
et al., 2020).
Different groundwater table depths can also significantly affect soil
salt distributions in the root zone. Soil salinity may decrease in responseto an increase in groundwater table depth since the upward movementof salts from groundwater is reduced by a decrease in capillary rise. For
example, Xu et al. (2013) explored the response of soil salinity togroundwater table depths using the SWAP model, concluding thatlowering the groundwater table could positively contribute to reducing
salts accumulation in the root zone already affected by soil salinization.
Nosetto et al. (2013) studied the spatial variability of groundwatersalinity and soil salts accumulation in a sub-humid landscape withshallow groundwater, indicating that soil salinity of unsaturated soils
increased as groundwater became shallower. Gholami et al. (2010)
similarly found that root zone soil salinity decreased by 7.2% when the
groundwater table depth was lowered from 8.35 to 14.7 m for the samegroundwater salinity. On the other hand, soil salinity may decrease in
response to increased irrigation frequency. For example, Askri et al.
(2014) reported that a high irrigation frequency and shallow ground­water are needed to preserve high soil water contents and low salinity of
the root zone in a saline region. This phenomenon was caused by asignificant increase in drainage and salt leaching with increasing irri­
gation frequency.
However, the effects of different groundwater table depths under BM
on soil salt dynamics are still unknown. Also, the uneven disintegrationof biodegradable films may cause uneven soil salt redistributions in thesoil profile. It is thus imperative to evaluate the soil salts distribution infields drip-irrigated with brackish water under BM and quantify soil
salinity variations as a function of the disintegration of the biodegrad­able film and groundwater table depth. While Sintim et al. (2019)analyzed soil salinity variations under BM, they only focused on sea­sonal differences before and after the crop growth season. Temporalvariations of soil salinity under BM, PM, and NM during different crop
growth stages, its spatial variations in a two-dimensional soil profile,and the effects of different degradable rates on soil salinity distributionsin the root zone have not yet been studied. Finally, the impact of varying
groundwater table depths on the soil salinity of the root zone under BM
needs to be further explored.
Numerous field experiments conducted to study soil salt dynamics,
usually time-consuming and costly endeavors, have been reported in theliterature. It is currently challenging to monitor soil salinity’s spatiotemporal characteristics in field experiments continuously. As an alter­
native, mathematical models can simulate soil environmental varia­
tions, thereby providing further details on the soil salts dynamics.
Widely used mathematical models include the SWAP (van Dam et al.,1997), DSSAT (Hoogenboom et al., 2019), DNDC (Li et al., 1992), andHYDRUS models (Šimůnek et al., 2016). HYDRUS-2D, among thesemodels, has been widely used due to its flexibility in accommodating
different types of boundary conditions (Azad et al., 2019; Gohardoust
et al., 2021; Hlaváčiková et al., 2016) to capture soil solute dynamics.
For example, Karandish and Šimůnek (2018) used the HYDRUS-2D
model to assess various scenarios with different irrigation and salinity
levels and indicated that irrigation levels need to be considerably
reduced when irrigation water salinity exceeds 5 dS m− 1. However, few
modeling studies focus on soil salinity variations under different disin­tegration rates of the BM and for different groundwater table depths.
The main objectives of this study were: 1) to calibrate and validate
the HYDRUS-2D model using observed experimental data, 2) to assess
temporal differences in root zone soil salinities under different BMs, 3)
to quantify the soil salt fluxes into the root zone under BM with different
2

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Geoderma 423 (2022) 115969

degradation rates, 4) to analyze two-dimensional spatial distributions ofroot zone soil salinity, 5) to evaluate soil water and salt balances under
different mulching treatments, and 6) to analyze soil salinity variations
under different disintegration rates of the biodegradable film andvarious groundwater table depths by scenario simulations using HYD­
RUS-2D.

Table 2The specific crop stages for corn in the early (DAS 0–60), middle (DAS 61–120),and late (DAS121-140) crop growth stages.

2. Materials and methods

Crop growth stages

Crop stages for corn

The early crop growth stage (DAS 0–60)
The middle crop growth stage (DAS 61–120)
The late crop growth stage (DAS 121–140)

The seedling and elongation stages
The tasseling and filling stages
The maturation stage(25% of total topdressing, 56 kg ha− 1) stages.

2.1. Experimental details

2.2. Observations and calculations

The experiment was carried out in 2019 and 2020 near the Yellow
River in the Hetao region (40◦ 41′ N, 107◦ 18′ E), which is one of the threelarge-scale irrigation regions in China. An arid climate characterized thisstudy area. Soil texture at the site is sandy loam with a bulk density of
1.42 g cm− 3, field capacity of 0.29 cm3 cm− 3, and a wilting point of 0.12
cm3 cm− 3 within the top 0–100 cm soil layer (Table 1). The groundwatertable depth was between 1.28 and 2.38 m during 2019–2020,.
Corn (Zea mays L.) was sown on May 4 and 10 in 2019 and 2020,
respectively, with a crop spacing of 30 cm, a crop row distance of 50 cm,
and a plant density of 60,030 seeds ha− 1. Harvesting was conducted on
September 20 and 26 in 2019 and 2020, respectively. Corn growth was
divided into three stages, i.e., the early (DAS 0–60), middle (DAS
61–120), and late (DAS121-140) crop growth stages (Table 2). Becauseof the cold winter, there was no cropping rotation between the firstyear’s harvest and the second year’s sowing. The experimental treat­ments involved two crop cycles (2019 and 2020), four mulching types,
and a non-mulched control. Four mulching types included the lowdensity polyethylene film (PM) and the biodegradable films with low(BML), medium (BMM), and high (BMH) disintegration rates. The start
time of disintegration for BML, BMM, and BMH is about 30, 60, and 90
days after sowing (DAS), respectively. The experimental design was acompletely random design with three replicates (Fig. 1). The four films’
thickness (0.008 mm) and width (80 cm) were the same. BML, BMM, andBMH were made of corn starch, polycaprolactone, and masterbatch inratios of 30:67:3, 30:65:5, and 30:62:8, respectively (Yin et al., 2019).
PM was made of polyethylene by a polymerization reaction. Percentagesof breaking elongation of BML, BMM, and BMH were 213.3, 149.0, and58.7%, respectively. The maximum loads of BML, BMM, and BMH were
0.84, 0.58, and 0.02 N, respectively. Additionally, the tensile strengths
of BML, BMM, and BMH were 20.9, 14.5, and 3.2 MPa, respectively. The
percentage of breaking elongation, the maximum load, and the tensile
strength of PM were 363.8%, 0.97 N, and 24.1 MPa, respectively.
Corn was irrigated using a drip system with 2.4 L h− 1 drippers spaced
30 cm apart and aligned with corn rows. Groundwater used as an irri­
gation source had average salinity of 2.55 g L-1 during the study period.
The irrigation depth of 22.5 mm (a locally recommended value) was
adopted in all plots every 7–15 days. A total of nine and seven irrigation
events were performed throughout the growing seasons in 2019 and2020, respectively. Before sowing, 56 kg ha− 1 of urea, 120 kg ha− 1 ofphospham, and 120 kg ha− 1 of potassium were applied into the tillage
layer when the soil was deep-tilled and hoed using tractors. Further­more, 224 kg ha− 1 of urea solution, as a total topdressing, was applied toeach plot during the crop elongation (37.5% of total topdressing, 84 kg
ha− 1), tasseling (37.5% of total topdressing, 84 kg ha− 1), and filling

Meteorological data, including rainfall, air temperature, relative
humidity, solar radiation, and wind speed, were collected at a one-hourinterval using an automated meteorological station located at theexperimental site (Onset Computer Inc., U30, Hobo, USA). ET0 (mm)was computed using the Penman-Monteith equation described by Allenet al. (1998). ET0 in 2019 and 2020 was 572.6 and 636.4 mm, respec­tively, while total rainfall was 87.9 and 151 mm. Potential transpiration
Tp (mm) and potential evaporation Ep (mm) were further obtained bymultiplying ET0 by the crop coefficient (Kc) using the dual Kc method(Rosa et al., 2012a):
Tp = Kcb ⋅ET0(1)

Ep = Ke ⋅ET0(2)

where Ke is the soil evaporation coefficient and Kcb is the basal crop
coefficient, which was estimated as follows:( )0.3h
Kcb = kcb (stand) + [0.04(u2 − 2) − 0.004(RHmin − 45)](3)3
where Kcb (stand) is the basal crop coefficient under a standard
climate [i.e., a minimum relative humidity (RHmin) of 45% and a windspeed at 2 m of 2.0 m s− 1, as recommended by FAO-56], u2 is the windspeed at 2 m (m s− 1), RHmin is the mean daily minimum relative hu­
midity (%), and h is the mean plant height (m).
Ke was calculated using the following equation:(4)

Ke = Kr (Kcmax − Kcb )⩽few Kcmax

where Kr is a dimensionless evaporation reduction coefficient, Kc max
is the maximum value of Kc following rain or irrigation, and few is thefraction of exposed and wetted soil. Kc max represents an upper limit
placed on E and T from the cropped surface and was estimated asfollows:h
Kcmax = max({1.2 + [0.04(u2 − 2) − 0.004(RHmin − 45)]( )0.3 }, Kcb + 0.05)
3(5)
Variations in Kr were divided into two stages, i.e., a constant Kr
during the first stage and a variable Kr during the second stage, as
follows:⎧⎨ TEW − De, j - 1 De, j - 1 > REW
TEW − REW
Kr =
(6)
⎩
1 De, j - 1 ⩽REW

Table 1
Soil texture, bulk density, pH, field capacity, wilting point, soil particle size distributions, and soil fertility (total nitrogen, total phosphorus, total potassium) of the
0–20, 20–40, and 40–100 cm soil depths at the experimental site.
Depth
(cm)

Soil texture

Bulk density(g m− 3)pH(-)

Field capacity(cm3 cm− 3)

Wilting point(cm3 cm− 3)

Soil particle size
distributions (%)
Clay
Silt
Sand

Soil fertility (g kg− 1)
Total nitrogen

Total phosphorus

Total potassium

0–20
20–40
40–100

Sandy loam
Sandy loam
Sandy loam

1.28
1.6
1.39

7.81
7.68
7.26

0.30
0.30
0.27

0.13
0.13
0.11

4.4
4.4
3.1

1.05
0.93
0.81

0.94
0.65
0.52

17.3
16.7
14.2

3

88.4
88.2
89.3

7.1
7.4
7.7

N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 1. Schematic of the five experimental treatments with three replicates (15 plots), locations of TIME-TDR probes, and the field cropping pattern.

where TEW is the maximum depth of water subject to evaporationfrom the surface soil layer when this layer is completely saturated (mm),
REW is readily evaporable water (mm), and De, j-1 represents cumulative
depletion of moisture from the soil surface layer at the end of day j − 1.
{min(1 − fc , fw ) for PM and BM
few =
(7)
min[1 − fc , (1 − 0.67fc )⋅fw ] for NM
Kcb − Kc min (1+0.5h)
fc = ()
Kc max − Kc min(8)

fw = max[1 − (1 − τ)fm , 0.3 ](9)Additionally, a soil auger (Beijing New Landmark Soil Equipment Co.,
Ltd., 0301, XDB, CHN) was used to collect undisturbed soil samples tomeasure SWCs using the gravimetric method. The probes were further
verified using the gravimetric method at periodic intervals.
Sampling locations and intervals for electrical conductivities of thesaturation paste extract (ECe) were the same as for SWCs. 2850 soil
samples were collected for the ECe analysis during the entire crop
growing season. The saturated paste method was used to determine ECe(Gharaibeh et al., 2021; Rhoades, 1993). ECe was measured using astandard conductance meter (Shanghai Youke Instrument and Meter
Co., ltd.; DDS-307A, CHN).
The leaching solution below the root zone was collected using
ceramic cups installed at a depth of 100 cm once every 7–15 days (Liet al., 2015). The corresponding vertical water fluxes were monitored
using a zero-tension lysimeter (Li et al., 2014). Each device consisted ofan open cylinder connected to a glass bottle. Leached water wascollected in the cylinder, from which it freely flowed into the outside
glass bottle through a flexible tube. Once the leaching solution was
obtained, laboratory chemical analyses were carried out to measureconcentrations of individual ions, i.e., Na+, Ca2+, Mg2+, K+,−
2−−Cl-,SO2−
4 ,HCO3 ,CO3 , and NO3 (Rhoades, 1982). The soil salt flux wasdetermined by multiplying the water flux and the salt concentration of
the leaching solution.
The salt mass balance during the entire crop growing season was
obtained by adding salt balances for each sampling interval:

where Kc min is the minimum value of Kc for dry bare soil, fw is thefraction of the surface soil wetted by irrigation or precipitation, fc is thefraction of the surface soil effectively covered by vegetation, fm is thefraction of the mulched area (approximately 0.80), τ is the fraction of thedisintegrated area of a biodegradable film, which was obtained byexperimental measurements (Chen et al., 2022), and 0.3 is the value
recommended by FAO-56 to represent the drip irrigation condition(Allen et al. 1998). More details about the dual Kc method can be foundin Allen et al. (1998) and Rosa et al. (2012a, 2012b). The related pa­
rameters for the dual Kc method have been summarized in Table 3.
Soil water contents (SWCs) in the mulched and bare areas weremonitored at soil depths of 10, 30, 50, 70, and 90 cm using two TIMETDR (IMKO GmbH Inc.; IPH, TRIME-PICO, GER), once every 7–15
days. Each plot has nine TIME-TDR probes. Moreover, three replicateswere carried out to ensure data accuracy, i.e., 15 plots in total. Thus,
there are 135 TIME-TDR probes used in this experiment (Fig. 1).

(10)

SR = SI + SA + Sra − SL
where SI is the initial soil salts storage (t ha− 1), SA is the mass of salts

Table 3
The adjusted basal crop coefficient (Kcb), the fraction of the surface soil wetted by irrigation or precipitation (fw), the total available water (TAW), readily available
water (RAW), the maximum depth of water subject to evaporation from the surface soil layer when this layer is completely saturated (TEW), readily evaporable water(REW), evaporable depth (Ze), and root depth (Zr) for polyethylene film mulching (PM), biodegradable film mulching with low (BML), medium (BMM), and high (BMH)
disintegration rates, and no mulching (NM).
Treatments

Kcb ini

Kcb mid

Kcb latefw

TAW (mm)

RAW (mm)

TEW (mm)

REW (mm)

Ze (m)

Zr (m)

PM
BML
BMM
BMH
NM

0.15
0.15
0.15
0.15
0.15

1.21
1.19
1.15
1.08
1.05

0.55
0.55
0.53
0.50
0.50

0.30
0.31
0.34
0.38
0.40

170
170
170
170
170

94
94
94
94
94

22
22
22
22
22

8
8
8
8
8

0.15
0.15
0.15
0.15
0.15

1.0
1.0
1.0
1.0
1.0

4

N. Chen et al.

Geoderma 423 (2022) 115969

added by irrigation water (t ha− 1), Sra is the mass of salts migrating fromgroundwater (t ha− 1) determined from the mass balance, SL is the massof soil salts leached below the 100 cm soil depth (t ha− 1), and SR is theresidual mass of salts after harvest (t ha− 1) determined by a product of
the salt concentration and soil water content. To determine the salts
concentration, a common approximation between ECe and salt con­centration was adopted in this study (i.e., ECe (dS m− 1) = 0.64 mg salt
cm− 3) (Phogat et al., 2020; Rhoades, 1996; Roberts et al., 2008; Siyal
et al., 2013; Waller and Yitayew, 2016).
The leaching ratio of soil salts (LR) from the root zone was deter­
mined using the following equation (Phogat et al., 2020):
LR =SL
SA + Sra

Hoffman, 1977):
Where α(h,hψ ) is a dimensionless stress response function for waterand osmotic stress (-), hϕ is the osmotic head (cm), b(x,z,t) is thenormalized root water uptake distribution function (cm− 2), and LT is thelength of the soil surface associated with transpiration (cm).
It was assumed that there was no root salt uptake. The twodimensional advection–dispersion equation was adopted to describe
salt transport:
(
)
(
)
(
)
(
) (
∂θc ∂
∂c
∂
∂c
∂
∂c
∂
∂c
∂qx c
=
θDxx
+
θDxz
+
θDzx
+
θDzz
−
∂x
∂x
∂z
∂z
∂t
∂x
∂z
∂x
∂z
∂x
)
∂qz c
+
∂z
(16)

(11)

The ratio of the mass of salts migrating from groundwater and thetotal migration mass of salts in the root zone (AR) was obtained using thefollowing equation:Sra
AR =SA + Sra

where c is the solute concentration (mg cm− 3), Dxx, Dxz, Dzx, and Dzz
are the components of the effective dispersion tensor (cm2 d-1), and qx
and qz are the components of the volumetric flux density (cm d-1).

(12)

The average soil salt flux during the crop growth stage was calculatedusing the following equation:
S=|S1 | + |S2 | + ... + |Sn |n(15)

S(h, hφ ) = α(h, hφ )⋅b(x, z, t)⋅Tp LT

3.2. Modeling domain, initial values, and boundary conditions
A rectangular domain was constructed in HYDRUS-2D with a verticaldepth of 100 cm and a horizontal width of 50 cm. The measured SWCs
and ECe of each soil layer at the beginning of the simulation period weretaken as the initial conditions in the model. Since it is common toconsider the electrical conductivity of soil water (ECsw) when simulating
soil salinity with HYDRUS-2D (Šimůnek et al., 2016), ECsw was deter­
mined based on the approximate relationship between ECe and ECsw (i.
e., ECsw = 2ECe) (Ayers and Westcot, 1976). Note that measured ECe,
rather than ECsw, was used to calibrate and validate modelingparameters.
Four boundaries were defined in HYDRUS-2D, i.e., the upperboundary, the bottom boundary, and two lateral boundaries (Fig. 2). In
the PM scenario, the upper boundary was divided into three sections
with the time-variable flux, no-flow, and atmospheric boundary condi­
tions representing the wetted area below the dripper, the mulched re­gion, and the bare area, respectively. Rainfall, evaporation, andtranspiration fluxes were provided for the “Atmospheric” boundary
condition.
In the BM scenarios (BML, BMM, and BMH), the mulched soil surface(0–40 cm from the dripper) was assigned a “Variable Flux” boundary
condition (Chen et al., 2019) to represent the effect of the fraction of themulched area on soil evaporation. The surface flux (i.e., the difference
between soil evaporation and rainfall) in the mulched area in the BM
scenarios was computed depending on the fraction of the disintegrated
area of the biodegradable film as follows (Chen et al., 2019):(13)

where S is the average soil salt flux during the crop growth stage (mgcm− 2 day− 1), S is the soil salt flux (mg cm− 2 day− 1), and n is the numberof days.
The disintegrated area of the biodegradable film (i.e., the bare areain the mulched region) was measured using the method described byChen et al. (2019). The details of measurement and calculation can befound in Appendix.
Five corn plants from each row of the experimental plot were used todetermine the leaf area and plant height every 7–15 days. The leaf area
was determined using a leaf area meter (Li-3000, LI − COR, USA). The
plant height was measured after washing out the roots using tape withan accuracy of 0.1 cm. Crop yield was determined by randomly har­vesting ten plants from each plot in the harvesting area of 20 m2 at theend of the crop growing season. The spatial distribution of corn roots
was measured using root samples collected from a soil transect during
each crop growth stage. Root samples were scanned using a root systemscan (Reagent Instru.; Perfection 4870photo, Epson, Japan) with the
450-dpi resolution.
3. Modeling3.1. Main equations for water flow and solute transport in HYDRUS-2D
The HYDRUS-2D model was used to simulate soil water and salt
dynamics under different mulching treatments. The model is a multipurpose finite-element model developed to simulate the movement ofwater, heat, and solutes in variably-saturated porous media of various
irregular geometries and with complex boundary conditions. It solves
the Richards equation for variably-saturated water flow and advec­
tion–dispersion equations for solute transport (Šimůnek et al., 2016).
The governing two-dimensional water flow equation is defined asfollows (Šimůnek et al., 2016):
[
]
[
(
)]
∂θ ∂
∂h
∂
∂h
(14)
=
K(h)
+
K(h)
+1
− S(h, hφ )
∂z
∂t ∂x
∂x
∂z

(17)

Ed = Ep × τ − R-1where Ed is the surface flux (mm d ), Ep is potential evaporation(mm d-1), and R is the rainfall rate (mm d-1).
The bare area of the soil surface (i.e., 40–50 cm from the dripper) in
the BM and PM scenarios was assigned an “Atmospheric” boundary
condition. The entire soil surface was assigned an “Atmospheric”
boundary condition in the NM scenario. The time-variable pressure headboundary condition was specified at the bottom of the flow domain torepresent measured groundwater table depths. In addition, the no-flow
boundary condition was prescribed on the left and right sides of thedomain.
The third-type Cauchy boundary condition was used for salt trans­
port at the upper and bottom boundaries. The emitter flux, potential
transpiration, and potential evaporation on the upper boundary were
determined using the flux equation (Skaggs et al., 2004) and the dual
crop coefficient method (Allen et al., 1998).

where θ is the volumetric water content (cm3 cm− 3), h is the pressure
head (cm), K is the unsaturated hydraulic conductivity (cm day− 1), t is
time (day), S is the root water uptake term (cm3 cm− 3 day− 1), x is thehorizontal coordinate (cm), and z is the vertical coordinate (cm).
Root water uptake under water and salinity stress conditions wascomputed using a multiplication model (Feddes et al., 1978; Mass and5

N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 2. The modeling domain, boundary conditions, and observation points for the biodegradable film mulching (BM) (a), plastic film mulching (PM) (b), and no
mulching (NM) (c) scenarios.

3.3. Modeling parameters3.5. Statistical analysis

The modeling domain was divided into three layers (0–20, 20–40,
and 40–100 cm). The soil hydraulic parameters for different layers were
initially estimated using the neural network method (Schaap et al.,2001) from the soil textural information and the bulk density. These
parameters were then manually adjusted by comparing simulated andobserved SWC and ECe values until a good accuracy was achieved. Soil
hydraulic properties were described using the van Genuchten (1980)
model (Table 4).
Soil longitudinal (DL) and transverse dispersivities (DT) are needed todetermine the components of the dispersion tensor. A wide range of DL
can be found in the literature. For example, Wang et al. (2014) recom­
mended DL of 20 cm in the 0–20, 20–60, and 60–100 cm soil layers.
Ramos et al. (2012) set DL to 25.8, 25.8, and 12.2 cm in the 0–30, 30–75,
and 75–100 cm soil layers. In this study, DL was set to values between 20
and 50 cm in the 0–100 cm soil layer (Table 4). The transverse dis­persivity (DT) was further taken as one-tenth of DL (Hanson et al., 2006;
Ramos et al., 2012). The salinity threshold and slope for corn were set to
1.7 dS m− 1 and 12%, respectively (Ayers and Westcot, 1976; Karandish
and Šimůnek, 2018; Katerji et al., 2003; Maas, 1990).

The mean relative error (MRE) (%), the root mean square error(RMSE) (dS m− 1), the index of agreement (IA) (-), and the Taylor coef­
ficient (TIC) (-) were used to evaluate the model performance (Qiu et al.,2022). Note that MRE and RMSE are close to zero, and IA and TIC are
close to one when a good estimation accuracy occurs:⃒n ⃒⃒Si − Oi ⃒1∑⃒
⃒ × 100%
MRE =
(18)
⃒
n i=1
Oi ⃒
RMSE =√̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
n1∑(Si − Oi )2
n i=1
∑n

IA = 1 − ∑ni=1 (Si −i=1 (|Si −

(19)

Oi )2

(20)

O| + |Oi − O|)2√̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
n∑1(Si − Oi )2ni=1̅̅ √̅̅̅̅̅̅̅̅̅̅̅̅̅̅
TIC = √̅̅̅̅̅̅̅̅̅̅̅̅̅
n
n
∑
∑
1
S2i + 1n
O2i
n
i=1

(21)

i=1

where Si and Oi are the simulated and observed values, respectively,
S and O are the mean values of simulated and observed values, respec­tively, i is the observation point, and n is the number of observation
points.

3.4. Scenario simulation
Numerical simulations with HYDRUS-2D were further carried out toexplore the effects of the disintegrated area and groundwater table
depth on salts distribution (Fig. 6). Ten different disintegration rates(DS) that resulted in 0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%,90%, and 100% disintegration of the biodegradable film on the last dayof the crop growth season (DAS 140) were considered. To explore theeffects of the groundwater table depth on soil salinity, eleven different
groundwater table depths (0.5, 0.8, 1.1, 1.4, 1.7, 2.0, 2.3, 2.6, 2.9, 3.2,
and 3.5 m) were considered in HYDRUS simulations for the BML treat­ment during the entire crop growth season.

4. Results and discussion
4.1. Evaluation of HYDRUS-2D
Modeling parameters were calibrated and validated using theobserved SWC and ECe data in 2019 and 2020, respectively. The results
showed that HYDRUS-2D simulated well SWC and ECe under different

Table 4
Soil hydraulic parameters of the van Genuchten (1980) model (the residual water content, θr, the saturated water content, θs, the shape parameters, α, n, and l, and thesaturated hydraulic conductivity, Ks), solute transport parameters (the longitudinal dispersivity, DL, and the transverse dispersivity, DT), and salinity stress parameters
for corn (the salinity threshold ST and slope) of the 0–20 cm, 20–40 cm, and 40–100 cm soil depths in the experiment field.
Depth (cm)Soil hydraulic parametersθrθs(cm3 cm− 3)(cm3 cm-3)

α (cm− 1)

n
(-)

Ks
(cm day− 1)l (-)

Solute transport parameters
DT (cm)DL (cm)Salinity stress parameters for corn
ST (dS m-1)
Slope (%)

0–20
20–40
40–100

0.055
0.051
0.045

0.006
0.07
0.09

1.65
1.64
1.59

69.1
48.2
21.4

0.5
0.5
0.5

50
20
21

1.7

0.456
0.419
0.383

6

5.0
2.0
2.1

12

N. Chen et al.

Geoderma 423 (2022) 115969

mulching treatments. In the calibration period, the range of MRE, RMSE,
IA, and TIC were 5.5–9.8%, 0.02–0.04 cm3 cm− 3, 0.86–0.99, and
0.02–0.05, respectively, for SWC, while they were 6.0–12.6%, 0.11–0.36
dS m− 1, 0.89–0.99, and 0.06–0.12, respectively, for ECe (Table 5). The
corresponding accuracy measures in the validation period were
5.5–11.1%, 0.02–0.04 cm3 cm− 3, 0.88–0.98, and 0.03–0.05, respec­tively, for SWC, while they were 7.5–13.7%, 0.09–0.38 dS m− 1,
0.93–0.99, and 0.05–0.11, respectively, for ECe. The highest simulation
accuracy among the PM, BM, and NM scenarios was obtained for the PM
scenario, with average MRE, RMSE, IA, and TIC of 6.1%, 0.02 cm3 cm− 3,
0.97, and 0.04, respectively, for SWC, and average MRE, RMSE, IA, and
TIC of 8.9%, 0.22 dS m− 1, 0.98, and 0.07, respectively, for ECe. The
estimation accuracy for the BM scenario was slightly lower than for PM,
with average MRE, RMSE, IA, and TIC of 6.6%, 0.02 cm3 cm− 3, 0.94, and0.04, respectively, for SWC, and average MRE, RMSE, IA, and TIC of
9.4%, 0.21 dS m− 1, 0.96, and 0.08, respectively, for ECe. The lowest
accuracy was obtained for the NM scenario since external environmental
conditions greatly affected its surface soil salinity. In general, the
HYDRUS-2D simulation accuracy for SWC and ECe meets the accuracy
requirement for all PM, BM, and NM scenarios. Additionally, a visualverification was used further to verify the agreement between observed
and simulated values, indicating that HYDRUS-2D can be used to eval­uate soil salt dynamics under different mulching treatments (Fig. 3). The
calibrated model can then provide a more detailed and quantitativedescription of evaluated processes than experimental data.

increased surface soil evaporation due to reduced mulched area (Chenet al., 2019). Upward water flow (i.e., capillary rise) and corresponding
solute transport increased due to increased water potential difference
between surface soil and deep soil layers, particularly in arid regionswith shallow and saline groundwater. Therefore, the BM treatment’s
surface soil salinity (0–20 cm) was higher than in PM and lower than in
NM treatments. During the middle crop growth stage (DAS 61–120), thehighest ECe (among different BM treatments) occurred in the BMH
treatment, about 36.6% higher than in PM. However, ECe under BML
and BMM were close to PM, higher by 21.1% and 12.3%, respectively.
Meanwhile, ECe in the BML, BMM, and BMH treatments were 29.5, 21.6,
and 2.9% lower than for NM, respectively. The above results showedthat soil evaporation mostly drove an increase in ECe. Similar results
have been reported in other studies. For example, Sintim et al. (2019)indicated that ECe under BM markedly increased by 0.25 dS m− 1
compared with PM. Zribi et al. (2017) further reported that ECe in theroot zone under PM was 42% lower than under NM.
During the late crop growth stage (DAS 121–140), ECe in the BM
treatments visibly increased in response to a decrease in SWC because of
an increase in the disintegration area of the biodegradable film, espe­
cially for BMH (Fig. 3). The average ECe for BML, BMM, and BMH were7.0, 23.1, and 34.9% higher than for PM, respectively, while they were39.5, 26.8, and 13.7% lower than for NM, respectively. Moreover, weobserved an increase in soil salinity in response to the rise in thedisintegration rate of the biodegradable film. For instance, the averageECe in both years for BMH was 25.0% and 11.1% higher than for BML
and BMM, respectively. However, soil salinity does not directly affect thedisintegrated rate of the biodegradable film because of halotolerant
bacteria, e.g., Bacillus. Earlier studies have shown that Bacillus caneffectively disintegrate biodegradable film (Bonifer et al., 2019; Kimet al., 2017; Tchakounté et al., 2020). For example, Meyer-Cifuentes
et al. (2020) reported that while Actinomycetes and Bacteroides weremore abundant in the free community than in the membrane commu­
nity, Bacillus was more abundant in the membrane community.
Differences in soil salinities among BM, PM, and NM decreased indeeper soil layers (in the 20–40 cm and 40–100 cm soil depths)
compared with the surface soil layer (0–20 cm soil depth). In the 20–40

4.2. Soil salt dynamics under different biodegradable film mulching
Differences in soil salinities among different mulching treatments
varied during different crop growth stages (Fig. 3). During the early crop
growth stage (DAS 0–60), there were no noticeable differences in ECe
under PM, BM, and NM due to low crop water consumption. The averageECe in both years for BM (i.e., BML, BMM, and BMH) was 1.37 dS m− 1,
6.6% higher than for PM, and 6.2% lower than for NM. The movement ofsoil salts is primarily driven by soil water flow (e.g., Hillel, 1971; Leiet al., 1988; Šimůnek et al., 2016). In general, larger disintegration areas
occur in the BM treatments than in PM, resulting in significantly

Table 5
Statistical performance of HYDRUS-2D for soil water contents (SWC) and electrical conductivities (ECe) in the 0–20, 20–40, and 40–100 cm soil layers during cali­
bration (2019) and validation (2020) for polyethylene film mulching (PM), biodegradable film mulching with low (BML), medium (BMM), and high (BMH) disinte­
gration rates, and no mulching (NM). MRE, RMSE, IA, and TIC are the mean relative error, the root mean square error, the index of agreement, and the Taylor
coefficient, respectively.
Variable

Soil depth (cm)

Index

2019
PM

BML

BMM

BMH

NM

2020
PM

BML

BMM

BMH

NM

SWC

0–20

MRE (%)RMSE (cm3cm− 3)
IA (-)TIC (-)MRE (%)RMSE (cm3cm− 3)
IA (-)TIC (-)MRE (%)RMSE (cm3cm− 3)
IA (-)TIC (-)MRE (%)RMSE (dS m− 1)
IA (-)TIC (-)MRE (%)RMSE (cm3cm− 3)
IA (-)TIC (-)MRE (%)RMSE (cm3cm− 3)
IA (-)TIC (-)

6.1
0.02
0.98
0.04
6.1
0.02
0.98
0.03
5.5
0.02
0.99
0.03
10.8
0.29
0.99
0.08
8.9
0.26
0.98
0.09
6.5
0.13
0.95
0.07

6.9
0.03
0.97
0.04
5.7
0.02
0.93
0.03
5.6
0.02
0.96
0.03
7.5
0.21
0.99
0.07
10.9
0.23
0.96
0.10
7.1
0.13
0.93
0.07

7.4
0.03
0.95
0.04
6.3
0.02
0.98
0.03
5.5
0.02
0.91
0.03
12.6
0.36
0.97
0.12
9.0
0.22
0.98
0.08
8.1
0.14
0.93
0.08

6.8
0.03
0.98
0.03
5.8
0.02
0.93
0.02
5.6
0.02
0.99
0.03
10.9
0.33
0.99
0.09
7.0
0.19
0.99
0.07
6.1
0.11
0.95
0.06

9.8
0.04
0.96
0.05
9.2
0.02
0.88
0.03
5.6
0.02
0.86
0.03
12.1
0.33
0.95
0.12
9.8
0.25
0.95
0.11
9.3
0.18
0.89
0.10

7.5
0.03
0.96
0.05
5.7
0.02
0.92
0.04
6.0
0.02
0.98
0.03
11.1
0.38
0.99
0.10
8.6
0.19
0.99
0.06
7.5
0.09
0.98
0.05

8.2
0.03
0.98
0.04
6.5
0.02
0.94
0.04
6.6
0.02
0.94
0.03
8.1
0.20
0.99
0.08
11.3
0.24
0.97
0.10
9.0
0.12
0.94
0.08

8.1
0.03
0.92
0.04
6.3
0.02
0.88
0.04
6.8
0.02
0.92
0.03
13.7
0.34
0.98
0.11
8.7
0.24
0.99
0.08
8.3
0.12
0.94
0.08

8.4
0.03
0.91
0.04
6.7
0.03
0.88
0.03
5.5
0.02
0.90
0.03
11.1
0.29
0.99
0.08
10.8
0.19
0.96
0.09
9.6
0.13
0.93
0.09

11.1
0.04
0.88
0.05
7.3
0.03
0.93
0.04
5.7
0.02
0.94
0.03
12.7
0.28
0.96
0.11
11.7
0.20
0.98
0.09
9.0
0.11
0.94
0.07

20–40

40–100

ECe

0–20

20–40

40–1007

N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 3. Simulated (lines) and observed (dots) electrical conductivities (ECe) in the 0–20 (top), 20–40 (middle), and 40–100 (bottom) cm soil layers under poly­
ethylene film mulching (PM), biodegradable film mulching with low (BML), medium (BMM), and high (BMH) disintegration rates, and no mulching (NM) in 2019(left) and 2020 (right). Irrigation and rainfall are shown in the top figure; the groundwater table depth is shown in the bottom figure. Note that the colored area (lightblue) refers to the ECe variation range under biodegradable film mulching (BML, BMM, and BMH).

cm soil layer, the average ECe during the entire crop growth season
increased by 7.1, 15.9, and 26.9% in the BML, BMM, and BMH treatments
compared with PM, respectively, and decreased by 27.6, 20.0, and 8.0%
compared with NM, respectively. In the deep soil layer (40–100 cm),
ECe under different mulching treatments shows no noticeable differ­ences. The average ECe in both years were 1.32, 1.36, 1.37, 1.41, 1.47
1.37 dS m− 1 for the PM, BML, BMM, BMH, and NM treatment, respec­tively. The average ECe in the root zone under different mulchingtreatments was higher due to less rainfall and more frequent irrigationsin 2019 than in 2020, especially in the 0–20 cm soil layer. The averageECe in the 0–20 cm soil layer under different mulching treatments in2019 increased by 5.3% compared with 2020.

respectively. Additionally, cumulative salt fluxes during the entire crop
growth season for BML, BMM, BMH were 0.9, 2.4, and 3.6 times larger
than for PM, respectively.
However, differences in the soil salt fluxes between BM and PM
decreased in the 40 cm soil depth compared with the 20 cm soil depth(Fig. 4). The average soil salt fluxes under BML, BMM, and BMH were36.6, 61.1, and 121.8% higher than under PM during the entire crop
growing season, respectively. The corresponding cumulative salt fluxes
in the 40 cm soil depth under BML, BMM, and BMH were 0.8, 2.1, and 3.1
times larger, respectively, than under PM.
Differences in the soil salt fluxes between BM and PM further
decreased in the 100 cm soil depth compared with the 40 cm soil depth
due to the relatively high soil salt storage in the 40–100 cm soil layer.
The cumulative salt fluxes in the 100 cm soil depth under BML, BMM, andBMH were 0.7, 1.6, and 2.6 times larger than under PM, respectively.

4.3. Soil salt fluxes in the root zone under biodegradable film mulching
In general, soil salt fluxes decreased with depth, and mulchingaffected mainly surface soil salt dynamics (Fig. 4). Additionally, spa­tial–temporal differences in surface soil salt fluxes (20 cm soil depth)
were found for different mulching treatments. There were no noticeable
differences in soil salt fluxes among PM, BM, and NM during early crop
growth. In both years, the average soil salt fluxes were 0.37, 0.37, 0.36,
0.36, and 0.38 mg cm− 2 d-1 in the PM, BML, BMM, BMH, and NM sce­narios, respectively. However, differences in soil surface salt fluxes in
the PM, BM, and NM treatments significantly increased (20 cm soil
depth) during the middle and late crop growth stages (Fig. 4). The soil
salt flux in the NM scenario was markedly higher than in mulchingtreatments, with an average increase of 59.9% in both years. Among
different mulching treatments, the average soil salt fluxes for BML, BMM,
and BMH increased by 57.0, 87.1, and 143.6% compared with PM,

4.4. Two-dimensional distribution of soil water and salt
Four days in 2019, i.e., one day before irrigation (DAS 106), one day
after irrigation (DAS 108), three days after irrigation (DAS 110), and thelast day of the crop growth season (DAS 140), were selected to assess theeffects of irrigation events and evaporation on temporal and spatial soil
salt distributions under different mulching treatments. On DAS 106, thesurface SWC (in the 0–20 cm soil layer) was relatively low, especially inthe mulched area (0–40 cm in the horizontal direction). Soil salts dis­played the opposite trend to the soil water content distribution. Soilsalinity gradually decreased horizontally from the dripper towards thebare area.
Soil salinity in the mulched area was usually lower than in the bare8

N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 4. Simulated actual (a, c; left) and cumulative (b, d; right) salt fluxes (upward fluxes are positive) in the 20, 40, and 100 cm soil depths under polyethylene film
mulching (PM), biodegradable film mulching with low (BML), medium (BMM), and high (BMH) disintegration rates, and no mulching (NM) in 2019 (a, b; top) and2020 (c, d; bottom).

layer. Additionally, high soil salinity stress areas (ECe > 3.80 dS m− 1)
developed only under the BMH and NM treatments (19.1 cm2 and 153.7
cm2, respectively).
There is a difference in soil salt distributions under PM, BM, and NM
three days after irrigation (DAS 110). The soil salt distributions in thehorizontal direction were more uniform under PM, BML, and BMM than
BMH and NM. Soil salinity under BMH and NM first decreased and thenincreased from the dripper to the bare area. On the last day of the crop
growing season (DAS 140), the distributions of SWCs and soil salts werevisibly different under different BM treatments (Fig. 5). The lowest SWC
occurred under the BMH treatment, 8.2% and 3.6% lower than under
BML and BMM, respectively. However, BMH had the largest soil salinity
stress area of 545.2 cm2, 4.7 and 1.7 times larger than BML and BMM,
respectively.

area (i.e., the middle of two mulched areas) (Liu et al., 2020; Zribi et al.,2017). However, we found that soil salinity in the mulched area washigher than in the bare area for all mulching treatments (Fig. 5). The
reason may be higher root water uptake (about 350 mm on average) in
the mulched area than soil evaporation (about 110 mm on average) inthe bare area. Furthermore, deficit irrigation was adopted in this study(the total irrigation depth was only 157.5–202.5 mm). Therefore, since
the total irrigation depth was smaller than root water uptake, soil waterand groundwater migrated into the root zone below the mulched sur­face, while soluble salts were transported into and accumulated in theroot zone.
In the vertical direction, soil salinity decreased with soil depth. There
are many reasons for this. For example, the surface soil layer is theprimary water source for soil evaporation (Allen et al., 1998). Mulching
thus alters soil salts distributions by limiting the water vapor transport
between the surface soil layer and the atmosphere (Wu et al., 2017).
Also, drip irrigation with high emitter flow and short irrigation duration
was adopted in this study, resulting in surface soil salinity being
significantly affected by the expansion of the wetted soil after irrigation.
In general, soil salinity under BM, and especially under NM, washigher than under PM. The salt stress area (ECe > 1.70 dS m− 1) in the
0–40 cm soil layer under NM increased by 60.0% compared with PM. On
DAS 108, the SWC in the mulched area increased by 8.0% comparedwith the bare area, while the surface SWC was 10.6% higher than in the
deeper soil layer. Due to solute convection, soil salinity near the dripper
visibly decreased after irrigation (Fig. 5). The soil salinity gradually
increased from the dripper to the bare area in the horizontal direction. In
the vertical direction, soil salinity first increased and then decreased
with soil depth. The highest salts mass accumulated in the 20–30 cm soil

4.5. Soil water and salt balance under different mulching treatments
There were large differences in soil water balances under BM, PM,
and NM, especially with respect to soil evaporation (E). Average E inboth years under BML, BMM, and BMH increased by 49.0, 70.2, and80.0%, respectively, compared with PM, while it decreased by 69.2,
47.3, and 22.8% compared with NM. Differences in E further resulted indifferences in soil water fluxes at the bottom of the root zone (i.e.,drainage or capillary rise) under different mulching treatments. There
was a capillary rise from shallow groundwater under BM, except for
BML. On the other hand, drainage occurred under PM. Among BM
treatments, root water uptake (RWU) under BMH and BMM was signifi­
cantly constrained due to excessive E and SR in the root zone. RWU for
BMH and BMM were 30.7% and 13.9% lower compared with PM,
9N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 5. Simulated two-dimensional SWCs and electrical conductivities of the saturation extract (ECe) in the root zone (0–100 cm) one day before irrigation (DAS 106;
left), one day after irrigation (DAS 108), three days after irrigation (DAS 110), and on the last day of the crop growing season (DAS 140; right) in 2019 underpolyethylene film mulching (PM; top), biodegradable film mulching with low (BML), medium (BMM), and high (BMH) disintegration rates, and no mulching (NM;bottom). The small graphs on the top and right of the figures represent simulated SWC profiles in horizontal and vertical directions. The blue dashed line refers to theobserved zone of SWC variations in the horizontal direction, and the red dashed line refers to the observed zone of SWC variations in the vertical direction.

10

N. Chen et al.

Geoderma 423 (2022) 115969

Fig. 6. Simulated electrical conductivities of the saturation extract (ECe) in the 0–20, 20–40, and 40–100 cm soil layers as a function of a) different disintegration
rates of the biodegradable film (0%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%) and b) simulated soil salinity in the 0–20, 20–40, and 40–100 cm soil
layers as a function of different groundwater table depths (0.5, 0.8, 1.1, 1.4, 1.7, 2.0, 2.3, 2.6, 3.0, 3.2, 3.5 m). Please note that disintegration rates refers to the last
day of the crop growing season (DAS 140), and different groundwater table depths were for biodegradable film mulching with a low disintegration rate (BML).

respectively. The highest RWU among BM treatments occurred under
BML and only decreased by 8.4% compared with PM. Additionally, there
were no noticeable differences in the soil water storage (△W) under BM
and PM (Table 6).
Substantial differences in soil salt balance components were foundbetween the PM, BM, and NM treatments. In general, soil salinity
decreased with the mulching area (Phogat et al., 2020; Qi et al., 2018).
For example, the average mass of salts migrating from groundwater (Sra)in both years under BM was 4.1 t ha− 1, which was a decrease of 27.8%
compared with NM, and an increase of 32.0% compared with PM(Table 6). Similar results were also presented in previous studies, such as
in Bezborodov et al. (2010), who indicated that soil salinity under straw
mulching was 20% lower than under NM. Abd El-Mageed et al. (2016)
further found that farmyard manure mulching, straw mulching, and PM
can effectively reduce salt accumulation in the root zone.
Soil salts accumulated in the soil profile mainly in response to asignificant decrease in the mulching area of the biodegradable film. The
largest Sra (27.4% and 12.6% larger than for BML and BMM, respectively)
occurred in the BMH treatment among different BM treatments. The
ratio of the mass of salts migrating from groundwater and the total
migration mass of salts in the root zone (AR) in the BMH treatment was
15.5% and 6.6% higher than for BML and BMM, respectively. Leachingsoil salts in different mulching treatments showed an opposite trend
than soil salts accumulation. The average amount of soil salts leached
below the depth of 100 cm (SL) in both years was 3.4 t ha− 1 for BM,
15.8% higher than for PM, and 40.3% lower than for NM. This phe­nomenon may be associated with differences in soil water potentials.
Soil evaporation under mulching treatments can be effectively reduced

by restraining water vapor transport and maintaining a high soil water
potential in the surface soil layer (Domagala-Swiatkiewicz and Siwek,
2013; Selim et al., 2013). Especially after irrigation, the surface soil
water potential was significantly higher than in the deep soil layer. The
mulching treatment thus promoted soil salt leaching while restraining
soil salt accumulation in the root zone (Selim et al., 2013).
The largest SL among different BM treatments occurred in the BML
treatment, with an increase of 9.2% and 25.0% compared with BMM and
BMH, respectively. The corresponding leaching ratio of soil salts (LR) for
BML was 16.5% and 35.3% higher than for BMM and BMH, respectively.
The order of the residual soil salt mass after harvest (SR) for different
mulching treatments was similar to Sra (Table 6). The average SR for BM
was 19.4% higher than for PM and 17.5% lower than for NM. Further­more, soil salts accumulation in the root zone increased due to faster
degradation rates of the biodegradable film.
In general, the degradation rate of biodegradable films is a doubleedged sword for agricultural ecosystems. On the one hand, the biode­gradable film with a slow degradation rate may cause excessive soil
temperatures in some arid regions (Chen et al., 2021). On the other
hand, the biodegradable film with a fast degradation rate can signifi­
cantly increase soil evaporation, leading to excessive soil salts accu­
mulation and eventually limited crop growth. It is thus crucial toreasonably control the degradation rate of biodegradable films todecrease soil salinity and increase crop yield.
Among BM treatments, crop yield (CY) for BMH and BMM weresignificantly constrained due to excessive SR in the root zone. CY for
BMH and BMM was 23.9% and 11.9% lower, respectively, comparedwith PM (P < 0.05). Restrained crop growth in 2019 due to higher soil

Table 6The simulated soil water balance, salt mass balance, leaching ratio of soil salts (LR), the ratio of the mass of salts migrating from groundwater and the total migration
mass of salts in the root zone (AR), and observed crop yield (CY) for the polyethylene film mulching (PM), biodegradable film mulching with low (BML), medium(BMM), and high (BMH) disintegration rates, and no mulching (NM) treatments. SI is the initial soil salt storage, SA is the mass of salts added by irrigation water, Sra is
the mass of salts migrating from groundwater into the root zone, SL is the mass of salts leached below the 100 cm soil depth, SR is the residual mass of salts after harvest,
I is the irrigation depth, R is rainfall, D is drainage (positive value) or capillary rise (negative value), Es is soil evaporation, and △W is the change in soil water storage.
Year
2019

2020

Treatments
PM
BML
BMM
BMH
NM
PM
BML
BMM
BMH
NM

Soil water balance (mm)
I
R
D

RWU

Es

△W

Salt mass balance (t ha− 1)
SI
SA
Sra
SL

SR

202.5
202.5
202.5
202.5
202.5
157.5
157.5
157.5
157.5
157.5

358.4
324.6
296.6
237.3
212.0
438.5
405.3
389.3
315.3
247.2

53.1
105.0
189.1
265.9
324.5
51.1
99.2
160.6
246.5
339.3

− 186.0− 187.3− 189.9− 191.0− 193.2− 226.8− 227.5− 230.8− 234.4− 236.7

7.5
7.5
7.5
7.5
7.5
5.9
5.9
5.9
5.9
5.9

11.0
12.0
13.1
14.6
15.9
9.1
9.8
10.8
11.7
13.2

87.9
87.9
87.9
87.9
87.9
151.0
151.0
151.0
151.0
151.0

64.9
48.1
− 5.4
− 21.8− 52.945.7
31.5− 10.6− 18.9− 41.3

11

5.1
5.1
5.1
5.1
5.1
4.0
4.0
4.0
4.0
4.0

2.5
3.3
4.0
4.9
5.8
3.1
3.6
4.3
4.6
5.6

4.1
3.9
3.5
2.9
2.5
3.9
3.7
3.4
2.8
2.3

LR

AR

CY
(kg ha− 1)

0.54
0.46
0.38
0.29
0.23
0.55
0.49
0.41
0.33
0.24

0.33
0.39
0.44
0.49
0.53
0.44
0.47
0.52
0.53
0.58

9878.2bc
9554.6c8590.1d7365.7e6543.4f
11826.8a11668.4a10526.7b9156.8 cd
7368.8e

N. Chen et al.

Geoderma 423 (2022) 115969

salinity compared to 2020 resulted in a decrease in CY in 2019. The
average CY under different mulching treatments in 2019 was 17.0%
lower than in 2020. The most optimal soil salinity conditions among
various BM treatments occurred in BML. Meanwhile, BML had thehighest CY compared with other BM treatments (Table 6). The average
CY in the BML treatment was only 2.2% lower than in PM, while it was
42.4% higher than in NM (P < 0.05). Therefore, BML can be recom­
mended as the optimal mulching treatment in this region. However, theincreased cost of BML will limit large-scale field applications of biode­gradable film technologies. Reducing production costs or providing
government subsidies may be required for biodegradable film technol­ogies to be widely adopted (Nampitch and Magaraphan, 2011).

depths. However, Xu et al. (2013) suggested that a target groundwatertable depth is between 1.0 and 1.5 m. The main reason for this difference
may be different irrigated crop and drainage conditions. While Xu et al.
(2013) studied wheat, we evaluated the effects of the groundwater table
depth on corn growth. Since water consumption of corn was lower thanthat of wheat, the target groundwater table depth in the corn fields was
lower than in the wheat fields. Overall, a target groundwater table depth
between 1.70 and 2.0 m is suggested.
To alleviate waterlogging and salinity, it is necessary to lower the
groundwater table depth using proper irrigation strategies and hydraulicengineering. For example, soil salts can be leached from the root zone by
applying a large irrigation depth before winter or installing subsurface
drainage systems. Several researchers have reported that subsurface
drainage can effectively control the groundwater table depth andimprove soil structure (Ben Aissa et al., 2013; Ghumman et al., 2012;
Ghorbani et al., 2015). For example, Islam et al. (2022) found that soil
salinity decreased by 31–52% in the field with subsurface drainage.
Therefore, subsurface drainage should be recommended for local
farmland to control the target groundwater table depth.

4.6. Soil salinity variations under different scenario simulations
4.6.1. Different disintegration rates of the biodegradable film
The results showed that ECe increased in response to an increase in
the disintegration rate, especially in the 0–20 cm soil layer. ECe
increased by 5.8% for a 10% increase in the disintegration rate (Fig. 6a).
Interestingly, the 20% DS scenario resulted in the lowest ECe, with only
4.31 dS m− 1 in the 0–20 cm soil layer. The reason may be that rainfall
infiltration after the film disintegration was lower than soil evaporation.
The causes of the disintegration of biodegradable films are various.
Usually, the oxidative and biotic degradation rates are controlled mainly
by soil conditions and the exudates of crop roots (Bikiaris et al., 1997;
Chiellini et al., 2007; Kapanen et al., 2008). For example, high soil watercontents may reduce the disintegrated rate of biodegradable films. First,
a decrease in the oxygen content in soil pores restrains oxidative
degradation. Second, a reduction of soil temperature, resulting from theloss of soil water absorbed heat, impedes biotic degradation by soil
microorganisms. Furthermore, root exudates also affect the disintegra­
tion rate of biodegradable films, especially in the middle and late stagesof crop growth. The high activity of decomposition bacteria triggered bycorn root exudates promotes the disintegration rate of biodegradable
films (Hu et al., 2021).

5. Conclusions
Differences in ECe were observed among different mulching treat­ments and crop growth stages. During the early crop growth stage (DAS0–60), there were only minor differences in ECe between different
mulching treatments. However, during the middle and late crop growthstages (DAS 61–140), differences in ECe significantly increased. The
largest SL and LR among different BM treatments occurred in the BML
treatment. Meanwhile, BML had the highest CY compared with other BM
treatments.
The HYDRUS-2D model can successfully and precisely simulate soil
salinity under different mulching treatments and provide additional
quantitative information compared to experimental data. The simulated
results showed that surface soil salt fluxes (20 cm soil depth) signifi­
cantly increased in response to an increase in the disintegration rate of
the biodegradable film. Also, scenario simulations showed that ECe
increased by 5.8% for a 10% increase in the disintegration rate, whilesoil salinity increased by 9.6% for a groundwater table depth decrease of
0.3 m.
BM with a low disintegration rate is more efficient in controlling soil
salinization than BMs with higher disintegration rates for conditions
with a shallow groundwater table. BML can thus be recommended forfarmlands threatened by salinization for maintaining high field
productivity.

4.6.2. Different groundwater table depths
Usually, soil salinity increases in response to a decrease in the
groundwater table depth because more soluble salts migrate upward bya capillary rise from groundwater into the crop root zone, especially inarid regions with shallow and saline groundwater. For example, thisstudy found that the highest soil salinity of 1.92 mg cm− 3 was reachedwhen the groundwater table was 0.5 m deep, while the lowest soil
salinity of 0.69 mg cm− 3 occurred when the groundwater table was 3.5
m deep (Fig. 6b). A negative linear relationship between soil salinity andgroundwater table depth was found (y = -0.45x + 2.2, R2 = 0.99). An
average 9.6% increase in soil salinity was achieved for a groundwatertable depth decrease of 0.3 m. This is in line with earlier results that soil
salinity decreases with an increase in the groundwater table depth(Gholami et al., 2010; Nosetto et al., 2013). However, a significant
decline in the groundwater table will increase the osmotic stress in thecrop root zone, especially when considering reduced irrigation depths.
Thus, the groundwater table depth needs to be controlled to develop
sustainable agriculture.
Dai (2021) evaluated the effects of different groundwater table
depths on soil salinity and corn growth and similarly reported that the
groundwater table depth in the Hetao irrigation district should be>1.75
m. In this study, the most significant reduction in soil salinity occurredfor groundwater table depths from 1.7 to 2.0 m, which indicated that soil
salts could be effectively leached for this range of groundwater table

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.
Acknowledgments
This research was jointly supported by the Local Science and Tech­
nology Development Fund Projects Guided by the Central Government(2020ZY0023), the National Natural Science Foundation of China(52079064, 51969024, and 51469022), the Trans formation Projects of
Scientific and Technological Achievements of Inner Mongolia(2021CG0022 and 2022YFHH0039), and the Inner Mongolia Autono­
mous Region Graduate Education Innovation Plan Subsidize Project.

12

N. Chen et al.

Geoderma 423 (2022) 115969

Appendix:
Measurements and calculations of the disintegration rate of the biodegradable film
A high-definition digital camera (Canon EOS Rebel T3, Japan) was installed at a vertical height of about 25 cm above the biodegradable film
surface to take images under daylight conditions once every 20 days. These images were then reprocessed using geometric corrections, backgroundsubtraction, and gray processing. The disintegrated area of the biodegradable film was obtained using the image software (Auto CAD 2018).
Since the fraction of the disintegrated area of the biodegradable film varied in the direction perpendicular to the drip tape, the mulching region was
divided into three parts R1, R2, and R3. The region around the dripper (R1, 0-10 cm) had the maximum disintegration, while the region furthest fromthe dripper (R3, 25-40 cm) had the least disintegration. The disintegration rate of the biodegradable film (τi) for three different regions was calculatedusing the following equation:
′

τ1 =

A1
× 100%
A1

τ2 =A2× 100%
A2

τ3 =A3× 100%
A3

(1)

′

(2)

′

(3)

where A1, A2, and A3 are total areas of film mulching in different regions (cm2), and A1 , A2 , and A3 are total areas of the disintegrated biodegradable
film in different regions (cm2). Since the widths of three different regions are different, the average fraction of the disintegrated area of the biode­gradable film (τ) is calculated using the weighted average as follows:
′

τ=

n
1∑
τi × wi
L i=1

′

′

(4)

where L is the width of the mulching area (cm) (set to be 40 cm), and wi is the width of different regions, which were 10, 15, and 15 cm for R1, R2,
and R3, respectively.

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