Soil & Tillage Research 213 (2021) 105116

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Soil & Tillage Research
journal homepage: www.elsevier.com/locate/still

Evaluating the effects of biodegradable and plastic film mulching on soil
temperature in a drip-irrigated field
Ning Chen a, Xianyue Li a, b, *, Jirí Šimůnek c, Haibin Shi a, b, Qi Hu a, Yuehong Zhang aaCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China
Research and Development of Efficient Water-saving Technology and Equipment and Research Engineering Center of Soil and Water Environment Effect in Arid Area of
Inner Mongolia Autonomous Region, Hohhot, 010018, Chinac
Department of Environmental Sciences, University of California Riverside, Riverside, CA, 92521, USAb

A R T I C L E I N F O

A B S T R A C T

Keywords:
Drip irrigation
Biodegradable film
Irrigation depth
Accumulative soil temperature
Fluctuation of soil temperature
HYDRUSThe use of plastic film mulching (PM) has steadily increased in the past few decades due to many advantages
compared to no film mulching (NM). However, PM also has many drawbacks, such as producing plastic film
residues and causing high temperatures at later crop growth stages. Thus, biodegradable film mulching (BM) has
recently been used as an excellent alternative solution. In this study, the effects of three mulching types,
including PM, BM, and NM, on soil temperatures (Ts) are evaluated using field experiments. Three mulchingtypes with an irrigation depth of 22.5 mm (i.e., PM22.5, BM22.5, and NM22.5) and three irrigation depths of 15,
22.5, and 30 mm with BM (i.e., BM15, BM22.5, and BM30, respectively) were compared. Additionally, the Ts
fluctuations and distributions during different crop growth stages were simulated using HYDRUS (2D/3D). The
results showed that HYDRUS (2D/3D) successfully simulated Ts with RMSE of 2.11–4.00 ◦ C, EF of 0.63− 0.85,
and MRE of 8.1 %–11.6 % during the validation period. There were large differences in Ts among PM22.5, BM22.5,
and NM22.5 in different crop growth stages. In the elongation and tasseling stages, Ts under PM22.5 and BM22.5
was not significantly different but markedly improved compared with NM22.5. In the filling and maturation
stages, higher variability of Ts was observed under BM22.5 compared with PM22.5. The standard deviation (SD),the deviation variance (DV), and the kurtosis coefficient (K) under BM22.5 were by 6.7 %, 32.6 %, and 19.3 %higher than under PM22.5, while accumulated soil temperature (AT) and the ratio of effective accumulated soil
temperature (AET, ≥10 ◦ C) to AT (RT) decreased by 3.8 % and 4.0 %, respectively. Additionally, apparent
differences in Ts between BM22.5 and PM22.5 appeared mainly in the soil surface layer (0− 10 cm). The area with
“optimal Ts” (i.e., corn growth is optimal in the Ts range of 20− 24 ◦ C) in the 0− 30 cm soil layer increased by 33.5
% under BM22.5 compared with PM22.5. Moreover, Ts decreased with an increase in the irrigation depth from
BM15 to BM22.5, and BM30, with the maximum size of the “optimal Ts” area under BM22.5. Generally, BM has moreadvantages in terms of heat preservation and preventing high temperatures compared with NM and PM,
respectively. Therefore, the biodegradable film can be recommended as an alternative material to replace thetraditional polyethylene film.

1. Introduction
The use of plastic film mulching (PM) in agriculture has been steadily
increasing around the world, including in Germany (Nader et al., 2019),
Spain (Marí et al., 2019), and China (Ma et al., 2020). Its objective is topreserve soil water (Lamptey et al., 2019; Ibrahim et al., 2020), improvesoil temperature (Ts) (Lee and Park, 2020; Gu et al., 2019), and decrease
unproductive water consumption (Borrowman et al., 2020). The tech­
nology can also significantly improve the seed emergence rate (Lianget al., 2018) and enhance the root physiological activity (Sekhon et al.,2019; Yin et al., 2020), crop yield, and field productivity (Majumder
et al., 2018; MacAlister et al., 2020; Yin et al., 2020). However, since theplastic film is mainly made of non-degradable polyethylene materials, its
use results in large amounts of plastic film residues in the field, which
incur a series of negative impacts on the soil environment and agricul­
tural production (Briassoulis et al., 2015; Li et al., 2020; Hu et al., 2020).
Additionally, during later crop growth stages, PM often results in hightemperatures, restricting crop growth and yield due to heat stress (Hou* Corresponding author at: College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, 010018, China.
E-mail address: lixianyue80@126.com (X. Li).
https://doi.org/10.1016/j.still.2021.105116
Received 7 October 2020; Received in revised form 28 May 2021; Accepted 10 June 2021
0167-1987/© 2021 Elsevier B.V. All rights reserved.

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Soil & Tillage Research 213 (2021) 105116

et al., 2010; Gu et al., 2017). Compared with the polyethylene film, thebiodegradable film made of cellulose and starch can self-degrade by
assimilating soil microbes under a suitable C/N ratio (Chiellini et al.,2006) and does not cause any environmental pollution. Moreover,biodegradable film mulching (BM) can also resolve adverse effects ofPM, such as poor soil aeration and excessive temperatures during latercrop growth stages as a result of its larger disintegration area (Gu et al.,2017; Chen et al., 2019, 2020). For example, Hou et al. (2010) showed asmall positive mulching effect when the PM duration was more than 60days, mainly due to excessive temperatures. Therefore, BM is a prom­ising agricultural technology to replace PM (Souza et al., 2020; Sintim
et al., 2020; Borrowman et al., 2020).
Soil heat dynamics under different mulching treatments have beenstudied in some previous studies. For example, Lee et al. (2018) reported
that PM increased mean soil water contents and Ts by 15–22 % and1.2–2.7 ◦ C compared with NM, respectively. Gu et al. (2017) analyzed
and compared PM and BM’s effects on Ts and found out that Ts was
significantly lower under BM than PM 150 days after sowing. Addi­
tionally, several previous studies have explored the Ts characteristics
under different BM treatments. For instance, Yin et al. (2019) attempted
to identify a biodegradable film’s optimal degradation rate, demon­
strating that Ts for the fast and moderate degradation rates wasapproximately 1.3–2.0 ◦ C lower than for the slow degradation rate.
Braunack et al. (2020) studied differences in Ts under a sprayablebiodegradable polymer membrane and oxo-degradable plastic film
mulching, showing similar heat phenomena for both materials, closely
related to the mulching area.
However, most of these studies focused on field experiments, which
are very time-consuming and costly. Therefore, the generalization ofthese results using a numerical model, as an alternative and low-cost
approach, would be highly welcomed. Moreover, numerical models
can provide additional details about soil temperature characteristics.
Currently, only soil water and soil nitrogen dynamics under BM havebeen studied using numerical models (e.g., Chen et al., 2019, 2020,
respectively). The soil heat transport under BM, as related to surface
latent and sensible heat fluxes, especially as a function of the dis­
integrated area of the biodegradable film, has not yet been studied using
numerical models.
In the past decades, several types of numerical models, such as RZSHAW (Flerchinger et al., 2000), DNDC (Gilhespy et al., 2014), andHYDRUS (Šimůnek et al., 2016), have been used to assess the pattern of
Ts in the tillage layer (0− 30 cm). However, these models vary widely interms of statistical accuracy, model efficiency, and modeling parame­
ters. For example, although RZ-SHAW can simulate Ts in the soil
boundary layer, Ts was overpredicted during an early growing season(Gillette et al., 2017). Poor simulations of Ts were found for the mulchedfield using DNDC, since the simulated downward heat flux was reducedby neglecting downward longwave radiation reflected from the plastic
film (Zhou et al., 2020). Compared with these models, HYDRUS (2D/3D)
considers more processes and factors when modeling Ts. It can capture
variations in the soil surface heat flux, Ts gradients, and soil thermal
properties to improve simulation accuracy (Saito et al., 2006). HYDRUS(2D/3D) has been widely used to simulate soil heat dynamics under PM
in a drip-irrigated field. For example, Zhao et al. (2018) studied soil heatflow in the ridge cultivation using HYDRUS (2D/3D), illustrating that Ts
under PM was similar to under straw mulching, although daily tem­
perature fluctuations significantly increased. Zhang et al. (2018) eval­uated soil water and heat transport for different wetted soil surface
areas, finding that Ts were similar for soil surfaces wetted between 35 %and 75 %. However, similar research on soil heat dynamics under abiodegradable film using HYDRUS (2D/3D) is still lacking, especiallyconcerning the Ts distribution in the soil profile and Ts fluctuations
during different crop growth stages.

The main objectives of this study thus are 1) to calibrate and validate
the HYDRUS (2D/3D) under PM, BM, and NM using measured soil watercontents and Ts, 2) to evaluate Ts under PM, BM, and NM during
different crop growth stages, 3) to compare fluctuations of Ts during
different crop growth stages under PM, BM, and NM, and 4) to analyze
differences in Ts distributions in the tillage layer under PM, BM, and NM.
2. Materials and methods
2.1. Field experiment
The experiment was conducted at the Jiuzhuang Water Saving
Comprehensive Station, Inner Mongolia, China (40◦ 41′ N, 107◦ 18′ E).
The soil texture at the site was sandy loam. The mean annual precipi­
tation, mean air temperature, and the annual sunshine duration were138.8 mm, 6.8 ◦ C, and 3230 h, respectively. These factors were classified
as a typical warm temperature climate. The soil had in the tillage layer(0− 30 cm) a pH of 7.6, the organic matter content of 1.2 %, total ni­
trogen of 0.093 %, total phosphorous of 0.07 %, total potassium of 1.60%. Average soil bulk density and field capacity were 1.42 g cm− 3 and0.41 cm3 cm− 3 within the 0− 100 cm soil layer, respectively.
Corn seed was sown on May 1 and 4 and harvested on September 14
and 20 in 2018 and 2019, respectively. The crop rows, crop spacing, andseed rate were 50 cm, 30 cm, and 66,700 viable seeds ha− 1, respectively.
A conventional flat planning system was adopted in all experimental
plots. The experiment was a completely random design, comprising
three replicates of five treatments, i.e., 15 field plots. Each plot was 20 m
wide and 4 m long, separated by a 1 m wide bar. There were three typesof mulching treatments, including plastic film mulching (PM22.5, madeof polyethylene), biodegradable film mulching (BM22.5, made of corn
starch, polycaprolactone, and masterbatch in a 30:65:5 ratio), and nofilm mulching (NM22.5), with a local recommended irrigation depth of
22.5 mm (80 % of field capacity). The width and thickness of the plastic
film (manufactured by Linhe Tianbao Environmental Protection Tech­
nology Co., Ltd.) and biodegradable film (manufactured by Shandong
Tianzhuang Environmental Protection Technology Co., Ltd.) were 80 cm
and 0.008 mm, respectively. Additionally, the local recommended irri­
gation depth was either increased or decreased by 7.5 mm (85 % or 75 %of field capacity) for BM, leading to the BM30 (30 mm) and BM15 (15mm) scenarios, respectively. Irrigation was applied to each plot when
the soil water content was less than 65 % of field capacity (0.27 cm3
cm− 3), and 10 and 9 irrigation events were used in 2018 and 2019,respectively. Surface water with an average temperature of 21.6 ◦ C wasused for irrigation during the crop growing season. One drip line with a
30 cm emitter spacing and an irrigation rate of 2.4 L h− 1 was placed in
the middle of two cornrows using an automatic sowing-mulchingfertilization machine. Before sowing, each plot was fertilized with 50
kg ha− 1 of urea, 100 kg ha− 1 of (NH4)2HPO4, and 100 kg ha− 1 of K2O as
basal fertilizer. Moreover, 210 kg ha− 1 of the Carbamide solution (CO(NH2)2, N ≥ 32 %) as topdressing was mixed with irrigation water andapplied to each plot in the elongation stage (63 kg ha− 1), the tasselingstage (84 kg ha− 1), and the filling stage (63 kg ha− 1). Sowing, mulching,
and basal-fertilizer application were carried using an automatic sowingmulching-fertilization machine.
2.2. Measurements and methods
2.2.1. Meteorological data
Daily precipitation, solar radiation, air temperatures, and wind speed
were measured in the experimental field using the automatic meteoro­
logical station (Onset Computer Inc.; U30, Hobo, USA) at a one-hourinterval, and the 24 -h statistics (averages) were computed (Fig. 1).

2

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Soil & Tillage Research 213 (2021) 105116

Fig. 1. Precipitations, groundwater table depths, and relative humidities at the experimental site during the crop growth seasons of 2018 (left) and 2019 (right).

2.2.2. Soil water content and soil temperature
Two TDR probes were installed in each plot in the middle of twocornrows and under the bare area for measuring soil water contents(SWC). Horizontal distances between TDR probes in the mulched area
and the crop row, drip line, and mulching boundary were about 24 cm, 1
cm, and 39 cm, respectively, while corresponding distances in the barearea were 25 cm, 50 cm, and 10 cm, respectively. SWCs were taken once
every 5–7 days at soil depths of 0− 20, 20− 40, 40–60, 60–80, and80− 100 cm, and these data were verified by gravimetric measurements
using a soil auger (Beijing New Landmark Soil Equipment Co., Ltd.,
0301, XDB, CHN). Soil temperatures (Ts) were measured in the tillage
layer (0− 30 cm) using thermocouples (Beijing Huize Agriculture
Technologies Inc., HZR-8 T, CHN) every 2 h at soil depths of 5, 15, and25 cm. The horizontal position of thermocouple probes was consistent
with TDR probes. Additionally, soil temperatures were averaged every
24 h.

Table 1
Measured radiation properties of the plastic film, biodegradable film, and baresoil for wavelengths between 0.3 and 50 μm.
Property

Reflectivity

Transmissivity
Emissivity

Radiation

Short wave
(0.3− 2.5 μm)
Long wave (2.5–50
μm)
Short wave
(0.3− 2.5 μm)
Long wave (2.5–50
μm)

Plastic
film

Biodegradable
film

Bare
soil

0.28

0.25

0.15
(wet)
0.26
(dry)

0.02

0.01

0.95

0.91

0.81

0.76

0.97

0.96

1

determined using a spectrophotometer (PerkinElmer model 402, USA)at normal incidence (Liakatas et al., 1986). The mulch emissivities forthermal radiation were measured according to Fuchs and Tanner(1966). Radiative properties of the plastic film, biodegradable film, andbare soil are summarized in Table 1.

2.2.3. Soil evaporation
Since plastic film mulching can entirely cut off water vapor flow
between the soil surface and atmosphere, soil evaporation from the soil
under plastic film mulching was neglected in this study, similarly as inmany other studies (e.g., Li et al., 2013; Saglam et al., 2017). Soilevaporation from the soil under biodegradable film mulching and baresoil was determined using cylindrical micro-lysimeters with and withouta biodegradable film, respectively. Micro-lysimeters with the biode­gradable film had a similar disintegrated area as in the field (Wu et al.,2017). The installed micro-lysimeters had a diameter of 11 cm and aheight of 20 cm. Micro-lysimeters were weighed twice daily at 8:00 and
17:00 using an electronic scale with a precision of 0.01 g.
Micro-lysimeters were reinstalled after irrigation or precipitation toensure measurement precision

2.2.7. Groundwater table and its temperature at the experimental site
A pressure transducer (Onset Computer Inc.; U20, Hobo, USA),installed in the observation well 3 m deep with a 5 cm internal diameter,
was used to measure the groundwater table depth and its temperature at
the experimental site. Data were averaged and recorded at one-day in­tervals and stored in a datalogger, from which they were automaticallydownloaded.
2.3. Calculations of soil temperature

2.2.4. Corn leaf area and height
Five plants from each plot were chosen to determine the corn leaf
area and plant height (using a tape with a precision of 0.1 cm) once
every 7–15 days. The leaf area index (LAI) was calculated using the FAO
method (Allen et al., 1998).

Two indices were used to evaluate differences in Ts fluctuations and“heat preservation” among different mulched fields, i.e., an averageincrease (Tu) and decrease (Td) in daily temperatures (Han et al., 2018).
Tu and Td were used to assess increasing and decreasing trends in soil
temperature in the tillage layer, respectively:

2.2.5. Disintegrated area of the biodegradable film
A digital camera (Canon EOS Rebel T3, Japan) was used to takephotos of the biodegradable film’s disintegrated area under daylightfrom a distance of about 25 cm between the camera and the film’s
surface once every 20 days (Chen et al., 2019). Images were processedusing a geometric correction and a background subtraction, and theaverage disintegrated area was calculated using the Auto CAD 2020
software (Autodesk Inc., USA).

Tu =

n− 1
1 ∑
max(Ti+1 − Ti , 0)m1 i=1

(1)

Td =

n− 1
1 ∑
min(Ti+1 − Ti , 0)m2 i=1(2)

n − 1 = m1 + m2

2.2.6. Radiative properties of the plastic film, biodegradable film, and baresoil
The reflectivity and transmissivity of mulch materials were

(3)

where Ti is the average daily temperature (◦ C), Tu is an average increasein temperature on days with increasing temperature (◦ C), Td is anaverage decrease in temperature on days with decreasing temperature3

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Soil & Tillage Research 213 (2021) 105116

where b1, b2, and b3 are empirical parameters (W cm− 1 ◦ C− 1).

(◦ C), n is the total number of data points, m1 is the total number of days
with increasing temperatures (i.e., positive values of Ti+1-T1), and m2 is
the total number of days with decreasing temperatures (i.e., negativevalues of Ti+1-T1).

2.4.2. Soil hydraulic functions, thermal parameters, and time-variableboundary parameters
The soil profile was divided into three layers (0− 20, 20− 40, and40− 100 cm soil depths). Soil hydraulic parameters for different soil
layers were first estimated using the Rosetta software package (Schaap
et al., 2001) from the soil textural information and the bulk density(Table 2). Selected soil hydraulic parameters (the empirical shape pa­
rameters α and n, and the saturated hydraulic conductivity Ks) were thenadjusted using a Marquart-Levenberg-type parameter optimization al­
gorithm in HYDRUS (2D/3D) (Table 2). The thermal parameters (b1, b2,
and b3) were simultaneously optimized using observed SWCs and Ts fordifferent mulching treatments at different soil depths (5, 10, 15, and 30cm) during the entire crop growth season.
The model requires daily rainfall, potential soil evaporation (Ep),potential crop transpiration (Tp), and emitter fluxes as inputs to define
the upper boundary condition. Daily precipitation data measured at the
automatic meteorological station was used. Potential evapotranspira­tion (ETp) was calculated using the Penman-Monteith equation (Allenet al., 1998). Ep and Tp can be obtained as a fraction of ETp (Campbell
and Norman, 1989):

2.4. Numerical simulation
2.4.1. Soil water flow and heat transport
Soil water contents and soil temperatures under BM, PM, and NM
during both years were simulated using HYDRUS (2D/3D) (Šimůnek
et al., 2016). The model is a multi-purpose finite-element model
developed to simulate the movement of water, solutes, and heat invariably-saturated porous media under various irregular and complex
boundary conditions. A modified form of the Richards equation wasused in HYDRUS (2D/3D) as follows:∂θ∂∂h= [K (h) + Kiz ] − S(h)∂t ∂xi ij ∂xj(4)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 cm3 day-1), x is the xaxis, and z is the vertical coordinate. The root water uptake term, S, isaffected by the potential uptake rate, Tp, and the water stress factor, α(Feddes et al., 1978):(5)

S(h) = α(h)⋅b(x, z)⋅L⋅Tp(10)

Ep = exp(− kLAI)ETp(11)

where k is the extinction coefficient of the crop canopy, and LAI is theleaf area index.
Assuming that evaporation (Ep) does not occur from the area with
non-disintegrated biodegradable film, the surface flux (qb, cm d− 1) inthe mulched region can be adjusted depending on the disintegration rateof the biodegradable film as follows:

where α(h) is a dimensionless function of the soil water pressure head, Tp
is the potential transpiration rate (cm day− 1), L is the surface length
associated with transpiration (cm), and b(x,z) is the normalized root
water uptake distribution (cm-2).
The two-dimensional heat transport equation, ignoring the effect ofwater vapor, is as follows:∂C(θ)T∂∂T∂T= [λij (θ) ] − Cw qi
∂xi
∂t
∂xj
∂xi

Tp = [1 − exp(− kLAI)]ETp

where FD is the fraction of the disintegrated area of the biodegradable
film (-), and P is the precipitation rate (cm d− 1).
Since drip irrigation can form a wetted surface area with a diameterof 8− 12 cm on the soil surface for different irrigation depths, the emitter
flux (qe) was applied as a time-variable flux (q) boundary condition on a
10 cm long boundary (in daily intervals) (Chen et al., 2020):

where C(θ) and Cw are the volumetric heat capacities of soil and water (Jcm− 3 ◦ C-1), respectively, λij(θ) is the soil apparent thermal conductivity(W cm-1 ◦ C-1), T is the temperature (◦ C), and qi is the water flux (cm day1). C(θ) was calculated using the following equation (Hillel, 1998):/
C(θ) = (2 × 106 BD 2.65) + 4.2 × 106 θ + 2.5 × 106 f0(7)
where BD is the bulk density (mg cm ), and f0 is the volumetric soilorganic matter fraction (cm3 cm− 3). The soil apparent thermal con­ductivity, λij(θ), was calculated as follows:Q=

1000 × qe te
1(14)

where q is the boundary water flux (cm d− 1), Q is the amount of water
applied by the emitter during one day (cm2 d− 1), L’ is the boundary
width with the time-variable flux boundary condition (cm), qe is theemitter flow rate (L h− 1), te is the irrigation duration (h) (less than 24 h),1000 is a unit conversion constant, and 1 represents the scale trans­
formation factor from three-dimensions to two-dimensions (cm). The
length of the time-variable flux boundary condition was assumed to be
the same for different irrigation depths. The difference between different
irrigation depths was mainly reflected in different boundary water
fluxes (q).

(8)

where λL and λT are the longitudinal and transverse thermal dis­persivities (cm), respectively, δij is the Kronecker delta, and λ0(θ) is thethermal conductivity (W cm− 1 ◦ C− 1) that can be obtained by Chung andHorton (1987):(9)

λ0 (θ) = b1 + b2 + b3 θ0.5

(13)

q = Q/L’

− 3

qj qi
λij (θ) = λT Cw |q|δij + (λL − λT )Cw+ λ0 (θ)δij
|q|

(12)

qb = Ep FD − P(6)Table 2
Soil physical properties (soil particle size distributions and bulk density) and soil hydraulic parameters (the residual water content θr, the saturated water content θs,
the shape parameters α, n, and l, and the saturated hydraulic conductivity Ks) of the 0-20 cm, 20-40 cm, and 40-100 cm soil depths in the experiment field.
Depth

Soil particle size distributions

Bulk density

θr

θs

α

n

Ks

l

(cm)

Clay

Silt

Sand

(g m− 3)

(cm3 cm− 3)(cm3 cm− 3)(cm− 1)(-)(cm day− 1)

(-)

0− 20
20− 4040− 100

4.5%
4.4%
3.1%

88.4 %
88.2 %
89.3 %

7.1 %
7.4 %
7.6 %

1.28
1.60
1.39

0.057
0.053
0.044

0.459
0.429
0.385

0.006
0.006
0.009

1.69
1.65
1.58

69.4
46.5
24.4

0.5
0.5
0.5

4

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Soil & Tillage Research 213 (2021) 105116

Additionally, heat fluxes in the mulched region and the bare area forheat transport simulations were obtained from the energy balance
equations:
Rn − Hm − LEm − Gm = 0(15)

Rn − Hb − LEb − Gb = 0(16)

layer) measured at the beginning of the simulation period were taken as
the initial conditions. The time-variable pressure head boundary con­dition was specified at the bottom of the flow domain (Fig. 2). The noflow boundary condition was prescribed on the left and right sides ofthe domain. Additionally, there are three types of upper boundary
conditions for the BM, PM, and NM treatments. First, the Time-Variable
Flux boundary condition was applied in the mulched area of the BM
treatments to represent biodegradable film’s disintegration. Second, theNo-flow boundary condition was applied in the mulched area of the PM
treatment. Third, the Atmospheric boundary condition was applied in
the bare area of the BM and PM treatments and the entire upperboundary of the NM treatment.
The third-type boundary condition (for heat transport) was used on
the upper boundary for the BM and NM treatments. Additionally, thethird-type boundary condition was also applied in the emitter part andon the bare area for the PM treatment to represent the actual heat flux inthe mulched and bare areas. However, the first-type boundary condition
was applied in the mulched area of the PM scenario since this boundary
had a no-flow boundary condition for water flow.

where Rn is the net radiation received by the soil (W m− 2), Hm and Hb are
the sensible heat flux densities in the mulched region and bare area (Wm− 2), respectively, L is the latent heat of vaporization (equal to 2.45 MJkg-1), Em and Eb are the evaporation rates in the mulched region and barearea (kg m− 2s-1), respectively, which were measured using microlysimeter, and Gm and Gb are the surface heat flux densities in themulched region and bare area (W m− 2), respectively.
Rn can be calculated using the following equation (Liakatas et al.,1986):
Rn = (1 − ρs )τS + L’n(16)

where ρs is the reflection coefficient of the soil, τ is the transmission
coefficient of the mulch, S is the flux density of net solar radiation on ahorizontal surface under the canopy, which was measured using tube net
radiometers mounted 40 cm above the mulch (Biscoe et al., 1974), and
L’n is net thermal radiation received by the soil beneath a mulch, which
can be obtained using the following equation (Liakatas et al., 1986):
L’n = τ’Ld + εm σTm4 − σ Ts4

2.5. Statistical analysis
The model efficiency was evaluated using the root mean square error(RMSE), the modeling efficiency (EF), and the mean relative error(MRE):√̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅̅
n
1∑
(20)
(Si − Oi )2
RMSE =
n i=1(17)

where τ’ is the transmission coefficient of the mulch for thermal radia­tion, Ld is the incident flux of solar radiation (W m− 2) measured using a
LICOR radiometer installed in 40 cm above the mulch (Tripathi andKatiyar, 1984), εm is the emissivity of the mulch, σ is the
Stefan-Boltzmann constant (56.7 × 10-9 Wm− 2 K-4), and Tm and Ts are
the mean temperatures of the mulch and the soil, respectively.
The surface heat flux densities were computed using the following
equation (Rai et al., 2019):
dTm
dZ

(18)

dTb
Gb = λdZ(19)Gm = λn∑i=1
EF = 1 − ∑n(Si − Oi )2(Oi − O)2

(21)

i=1

MRE =

n
1∑
|Si − Oi |× 100%
n i=1
Si

(22)

where S is the simulated value, M is the observed value, i is the obser­
vation data point, and n is the number of measurements.
3. ResultsdTbmwhere dT
dZ and dZ are the temperature gradients in the mulched region
and bare area, respectively, and λ is the thermal conductivity (W cm− 1
◦ − 1
C ).

3.1. Efficiency of HYDRUS (2D/3D) to simulate soil temperature
In this study, the measured SWC and Ts (average daily values) datafrom different treatments and different soil depths in 2018 were used tocalibrate the soil hydraulic and heat transport parameters. The

2.4.3. Initial and boundary conditions
The SWCs (in the 0− 100 cm soil layer) and Ts (in the 0− 30 cm soil

Fig. 2. The modeling domain, boundary conditions, and observation points for biodegradable film mulching (BM) (a), plastic film mulching (PM) (b), and no film
mulching (NM) (c) scenarios.
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Soil & Tillage Research 213 (2021) 105116

Table 3
Statistical results for soil water contents (SWC) in 0-20, 20-40, 40-100 cm and soil temperatures (Ts) at 5, 15, and 25 cm soil depths under plastic film mulching,(PM22.5), biodegradable film mulching (BM22.5), and no film mulching (NM22.5), with an irrigation depth of 22.5 mm, and biodegradable film mulching with anirrigation depth of 30 (BM30) and 15 (BM15) mm during 2018 (calibration) and 2019 (validation). RMSE - root mean square error, EF - modeling efficiency, MRE - mean
relative error.
PM22.5

BM22.5
Year

Depth
(cm)

0− 20
SWCs 20− 40
40− 100
2018
5
Ts
15
25
0− 20
SWCs 20− 40
40− 100
2019
5
Ts
15
25

NM22.5RMSE(cm3
cm− 3)/(◦ C)

EF
(-)

MRE
(%)

RMSE
(cm3cm-3)/(◦ C)

EF
(-)

MRE
(%)

0.02
0.01
0.02
3.07
1.97
2.44
0.02
0.03
0.03
3.44
2.57
2.76

0.88
0.93
0.90
0.82
0.88
0.80
0.81
0.85
0.83
0.73
0.81
0.78

7.6
4.6
7.3
9.3
7.7
8.8
9.1
8.2
8.2
10.4
8.7
9.5

0.02
0.02
0.03
2.73
2.04
1.86
0.02
0.03
0.03
3.34
2.64
2.11

0.85
0.89
0.81
0.83
0.85
0.89
0.78
0.70
0.80
0.63
0.76
0.84

8.1
7.9
8.7
8.4
7.5
7.4
8.4
8.7
9.1
11.3
8.7
8.1

0.02
0.02
0.03
2.73
2.04
1.86
0.02
0.03
0.03
3.34
2.64
2.11

BM30

BM15

RMSE
(cm3cm-3)/(◦ C)

EF
(-)

MRE
(%)

RMSE
(cm3cm-3)/(◦ C)

EF
(-)

MRE
(%)

RMSE
(cm3cm-3)/(◦ C)

EF
(-)

MRE
(%)

0.03
0.03
0.02
3.02
2.57
2.56
0.04
0.03
0.03
4.00
3.72
3.21

0.76
0.79
0.84
0.78
0.84
0.85
0.71
0.72
0.77
0.65
0.68
0.79

10.7
9.5
8.7
8.8
8.4
7.8
13.2
11.3
9.3
11.6
10.2
9.8

0.03
0.02
0.02
4.13
3.64
2.83
0.03
0.03
0.02
3.18
3.28
2.94

0.82
0.87
0.85
0.69
0.73
0.77
0.78
0.76
0.84
0.76
0.72
0.85

8.8
7.8
9.5
12.6
9.8
8.1
9.3
11.7
9.6
9.2
10.5
9.1

0.03
0.03
0.02
2.59
2.48
2.63
0.03
0.03
0.03
3.74
2.82
2.99

0.86
0.84
0.80
0.73
0.70
0.79
0.81
0.82
0.81
0.65
0.80
0.81

7.9
8.3
9.8
8.4
8.3
8.8
11.2
9.2
10.3
10.4
8.9
9.3

Fig. 3. Simulated (line) and observed (dots) daily soil temperatures in the 5 (top), 15 (middle), and 25 (bottom) cm soil depths under plastic film mulching (PM22.5),
biodegradable film mulching (BM22.5), and no film mulching (NM22.5) with an irrigation depth of 22.5 mm, and biodegradable film mulching with irrigation depthsof 30 (BM30) and 15 (BM15) mm in a) 2018 (calibration) and b) 2019 (validation).
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Soil & Tillage Research 213 (2021) 105116

Fig. 4. Simulated (lines) and observed (dots) soil temperatures after irrigation in the early (DAS 28-30 in 2018 (abc) and DAS 31-33 in 2019 (ghi)) and late (DAS
120-122 in 2018 (def) and DAS 108-110 in 2019 (jkl)) crop growth stages at depths of 5 (top), 15 (middle), and 25 (bottom) cm under plastic film mulching (PM22.5),
biodegradable film mulching (BM22.5), and no film mulching (NM22.5) with an irrigation depth of 22.5 mm, and biodegradable film mulching with irrigation depthsof 30 (BM30) and 15 (BM15) mm.

corresponding 2019 data were used to validate the model (Table 2). The
results showed that the range of RMSE, EF, and MRE values in thecalibration period for BM22.5, PM22.5, NM22.5, BM30, and BM15 were0.01− 0.03 cm3 cm− 3, 0.76− 0.93, and 4.6 %–10.7 %, respectively, for
SWCs, while they were 1.86–4.13 ◦ C, 0.69− 0.89, and 7.4 %–12.6 %,respectively, for Ts (Table 3). In the validation period, the corresponding
statistical parameters were 0.02− 0.04 cm3 cm− 3, 0.70− 0.85, and 8.2%–13.2 %, respectively, for SWCs, while they were 2.11–4.00 ◦ C,
0.63− 0.85, and 8.1 %–11.6 %, respectively, for Ts. Among different
mulching treatments, the PM22.5 scenario had the highest simulation
accuracy with RMSE of 0.02− 0.03 cm3 cm− 3 (the range of values refers
to multiple depths), EF of 0.70− 0.89, and MRE of 7.9 %–9.1 % for SWCs,
and RMSE of 1.86–3.34 ◦ C, EF of 0.63− 0.89, and MRE of 7.4 %–11.3 %for Ts. Additionally, the visual inspection was used to assess the corre­
spondence between simulated and measured daily Ts values for different
mulching and irrigation treatments (Figs. 3 and 4). The correspondence
between simulated and measured values significantly improved withincreasing soil depth. Generally, HYDRUS (2D/3D) could well capture
the soil heat flux dynamics.

downward parabola shape during the crop growing season with the
maximum values during DAS 60− 100. However, in 2019 (a dry year),the Ts variations showed a logarithmic, linear tendency, i.e., Ts was highduring early crop growth stages while it was low during late crop growthstages.
To further capture diurnal fluctuations of Ts, three consecutive days
after irrigation in the early (DAS 28–30 in 2018 and DAS 31–33 in 2019)and late (DAS 120–122 in 2018 and DAS 108–110 in 2019) crop growthstages were chosen (Fig. 4). In the early crop growth stages, diurnal Ts
fluctuations at different soil depths under BM and PM were very similar.
In the late crop growth stages, significant differences in diurnal Ts
fluctuations occurred under BM and PM, especially at the 5 cm soil
depth. Ts at nighttime under BM was 2.8 % and 2.1 % lower than under
PM in 2018 and 2019, respectively, but it was similar in the daytime.
The largest variations of diurnal Ts among different mulching treatments
occurred in the NM treatment. During the daytime, average soil tem­
peratures Ts at the 5 cm soil depth under NM were 4.8 % and 5.3 %higher than under BM and PM, respectively, while they were 37.0 % and38.7 % lower during nighttime. Additionally, differences in diurnal Ts
fluctuations among NM, BM, and PM decreased as the soil depth
increased. Diurnal Ts fluctuations were almost the same for different
irrigation depth treatments (Fig. 4), i.e., the highest Ts value occurred at
2:00− 3:00 pm while the lowest Ts value occurred at 5:00− 6:00 am.

3.2. Daily and diurnal fluctuations of soil temperatures under PM, BM,
and NMA significant difference was found in surface Ts (5 cm) between thePM, BM, and NM treatments with different mulching areas. In general,the lowest seasonal average surface Ts of 30.5 and 26.6 ◦ C occurred in
NM22.5 in 2018 and 2019, respectively, which was 2.2 and 4.7 ◦ C lower
than in PM22.5 and 2.5 and 4.2 ◦ C lower than in BM22.5, respectively. The
lowest average Ts of 25.6 ◦ C appeared in BM30 during the entire crop
growth season (Fig. 3), decreasing by 0.4 and 1.6 ◦ C compared with theBM22.5 and BM15 treatments, respectively. Additionally, there weresignificant spatio-temporal differences in Ts for different treatments indifferent hydrological years. In 2018 (a wet year), the Ts variation had a

3.3. Soil temperatures under PM, BM, and NM
Interactions between the soil surface and atmosphere are different
for different types of mulches, resulting in different vapor transport and
SWCs. Furthermore, the soil thermal properties, such as C(θ) and λ(θ),
will also be different due to variations in SWCs during the crop growing
season. During the elongation and tasseling stages, temperatures Ts
under two film mulching treatments (FM) (i.e., PM22.5 and BM22.5) were
not significantly different, but markedly improved and stabilized
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Soil & Tillage Research 213 (2021) 105116

Table 4
Soil temperatures (Ts) and the Ts difference analysis during the elongation, tasseling, filling, and maturation stages in 2018 and 2019 under plastic film mulching(PM22.5), biodegradable film mulching (BM22.5), and no film mulching (NM22.5) with an irrigation depth of 22.5 mm, and biodegradable film mulching with irrigation
depths of 30 (BM30) and 15 (BM15) mm. AT - accumulated soil temperature, AET - effective accumulated soil temperature, Tmax - the maximum value of Ts, Tmin - theminimum value of Ts, Tavg - the average Ts, RT - the ratio of AET to AT, SD - the standard deviation, DV - the deviation variance, K – the kurtosis coefficient.
Year

Crop stages

Elongation(May 1- June 14, 45 days)

Tasseling(Jun 15- July 19, 35 days)
2018
Filling(July 20- August 24, 36 days)

Maturation(August 25-September 14, 21 days)

Elongation(May 4- June 22, 50 days)

Tasseling(Jun 23- July 22, 30 days)
2019
Filling(July 23- August 24, 33 days)

Maturation(August 25-September 20, 27 days)

Treatments
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15
BM22.5PM22.5
NM22.5BM30
BM15Soil temperature

Difference analysis

AT

AET

TMax

TMin

Tavg

RT

SD

DV

K

1155.21139.51166.21143.71120.6
1000.81026.11003.31024.21034.01045.11052.81083.51094.31091.8
556.9
603.3
507.4
567.8
575.6
1303.31408.1
1443.81399.91461.7
845.5
902.5
876.3
868.3
921.8
843.5
873.9
812.9
851.1
886.1
526.2
554.2
463.2
538.4
529.0

689.5
705.2
656.2
693.7
670.6
626.1
650.8
603.3
674.2
684.0
692.8
685.1
623.5
734.3
731.8
332.3
340.1
250.2
347.8
355.6
908.1
993.3
943.8
899.9
961.7
602.5
645.5
576.3
568.3
621.8
543.9
533.5
482.9
521.1
556.1
284.2
256.2
193.2
268.4
259.0

30.0
31.4
32.8
29.9
30.1
33.1
34.4
33.9
33.9
33.2
31.6
32.4
32.7
32.8
32.6
28.8
29.5
29.8
29.5
29.2
29.3
32.2
36.3
31.2
32.2
30.6
32.7
33.0
31.2
33.3
29.1
30.0
30.0
28.8
30.5
23.8
26.3
21.4
24.9
24.5

19.1
18.9
19.0
20.5
20.0
24.0
24.7
24.0
24.5
25.0
26.2
25.6
26.4
27.3
27.5
22.8
21.5
21.0
22.8
22.8
19.6
21.1
20.4
21.8
23.3
24.2
26.7
23.3
26.4
27.3
22.1
24.1
20.8
23.6
23.4
16.6
15.6
14.1
16.3
16.0

25.7
25.3
24.9
25.4
24.9
28.6
29.3
28.2
27.3
29.5
29.0
29.2
30.1
28.4
30.3
25.5
25.1
25.9
24.8
26.2
28.1
28.2
25.9
26.0
29.2
29.2
30.1
28.2
28.9
30.7
25.6
26.5
24.6
25.8
26.9
19.5
20.5
17.2
17.9
19.6

0.60
0.62
0.56
0.61
0.60
0.63
0.63
0.60
0.66
0.66
0.66
0.65
0.58
0.67
0.67
0.60
0.56
0.49
0.61
0.62
0.70
0.71
0.65
0.64
0.66
0.71
0.72
0.66
0.65
0.67
0.64
0.61
0.59
0.61
0.63
0.54
0.46
0.42
0.50
0.49

2.62
2.87
3.09
2.46
2.49
2.45
2.40
2.60
2.40
2.01
1.37
1.68
1.60
1.41
1.23
1.57
1.93
2.02
1.66
1.63
2.28
2.53
4.11
2.09
2.00
1.57
1.51
2.94
1.15
1.47
2.00
1.78
2.37
1.61
2.11
2.23
3.32
1.95
2.52
2.48

5.26
5.74
6.18
4.92
4.98
4.91
4.81
5.21
4.82
4.03
2.76
3.37
3.20
2.82
2.47
3.13
3.85
4.04
3.32
3.28
5.37
6.57
17.61
4.49
4.11
2.49
2.33
9.31
1.36
2.28
4.11
3.20
6.03
2.61
4.46
6.14
11.07
3.93
6.37
6.19

− 0.40− 0.03− 0.36− 0.58− 0.68− 0.52− 0.66− 0.80− 0.67− 0.35− 0.33− 0.290.12− 0.30− 0.29− 0.17
0.18
2.24
0.91
0.42
0.44
0.16
− 0.67
0.53
0.71
0.75
− 0.22− 1.090.02
0.26− 1.12− 1.000.38− 1.10− 1.09− 0.84− 0.942.19− 0.67− 0.67compared to the NM22.5 treatment (Table 4). The average Ts (Tavg) underBM22.5 and PM22.5 were 27.9 and 28.2 ◦ C, respectively, increasing by
1.09 and 1.43 ◦ C compared with NM22.5. Moreover, the standard devi­
ation (SD) and deviation variance (DV) under BM22.5 were 2.23 and
4.51, respectively, decreasing by 30.0 % and 52.9 % compared with
NM22.5; the corresponding parameters (i.e., SD and DV) under PM22.5
were 2.33 and 4.86, respectively, which was 27.0 % and 49.2 % lower
than under NM22.5. The maximum temperature range Trange (i.e., thedifference between the maximum and minimum values) of 12.3 ◦ Coccurred in NM22.5, with the kurtosis coefficient (K) of -0.73. During thefilling and maturation stages, BM22.5 resulted in higher variability of Ts
values than in PM22.5. The SD, DV, and K values for BM22.5 were 6.7 %,32.6 %, and 19.3 % higher than for PM22.5, respectively, while accu­
mulated soil temperature (AT) and the ratio of effective accumulated
soil temperature (AET, Ts≥10 ◦ C) to AT (RT) decreased by 3.8 % and 4.0%, respectively. Compared with FM, AT, AET, and Tavg under NM22.5
decreased by 7.6 %, 28.1 %, and 3.6 %, respectively, and Trange
increased by 0.1–1.4 ◦ C. However, there are apparent differences in Tavg
during the filling and maturation stages in both years due to different air

relative humidities. Tavg under NM22.5 in 2018 increased by 0.8 ◦ C
compared with FM, while Tavg under NM22.5 in 2019 was 2.1 ◦ C lower
than under FM. The high relative humidity increased heat losses forNM22.5 in 2019 (Fig. 1).
There is an inverse relationship between Ts and the irrigation depth
under the same mulching treatment. When the irrigation depth was 30
mm (BM30), higher by 7.5 mm than 22.5 mm (BM22.5), the AT, AET, andTavg values decreased by 17.3 ◦ C, 9.0 ◦ C, and 0.81 ◦ C, respectively.
Meanwhile, SD and DV increased by 1.4 % and 2.2 % compared with
BM22.5, respectively, but RT and K were not significantly different. Whenthe irrigation depth was 15 mm (BM15), lower by 7.5 mm than 22.5 mm(BM22.5), the AT, AET, and Tavg values increased by 43.0 ◦ C, 20.2 ◦ C, and0.78 ◦ C, respectively. SD, DV, and K decreased by 1.4 %, 7.4 %, and 2.2%, respectively, and RT was about the same.
3.4. Seasonal fluctuations of soil temperatures under PM, BM, and NM
To capture differences in soil temperatures Ts among the PM, BM,
and NM treatments in the tillage layer, the two indices (see Section 2.3)

8

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Soil & Tillage Research 213 (2021) 105116

Fig. 5. Tu and Td in the 5 (top), 15(middle), and 25 (bottom) cm soil
depths during the elongation, tasseling,filling, and maturation stages in 2018
(left) and 2019 (right) under plastic film
mulching (PM22.5), biodegradable film
mulching (BM22.5), and no film mulch­ing (NM22.5) with an irrigation depth of
22.5 mm, and biodegradable film
mulching with an irrigation depth of 30(BM30) and 15 (BM15) mm. Tu - anaverage temperature increase on days
with increasing temperature, Td - anaverage temperature decrease on days
with decreasing temperature.

were adopted in this study., i.e., an average temperature increase ondays with increasing temperature (Tu) and an average temperature
decrease on days with decreasing temperature (Td). The largest differ­ence in Ts between BM22.5 and PM22.5 occurred in the soil surface layer(5 cm), especially in the later crop growth stages (Fig. 5). Tu in BM22.5
was 0.53 ◦ C lower than in PM22.5, while Td increased by 0.12 ◦ Ccompared with PM22.5. Seasonal fluctuations of Ts decreased with anincrease in the soil depth for FM. In the 15 cm soil depth, Tu was higher
by 0.13 ◦ C under BM22.5 compared with PM22.5, but Td was lower by
0.14 ◦ C. In the 25 cm soil depth, Tu increased by 0.10 ◦ C under BM22.5
compared with PM22.5, while Td decreased 0.04 ◦ C, respectively. Sea­
sonal fluctuations of Ts under NM22.5 were more intensive since they
were easily affected by air temperature and humidity. On the other
hand, significant differences in Ts fluctuations between BM22.5 andPM22.5 appeared only in the soil surface layer and during later crop
growth stages.
The soil temperature Ts in the surface soil was also markedly affected
by SWC. When the irrigation depth was increased to 30 mm (BM30), andTu and Td increased by 0.03 ◦ C and 0.10 ◦ C compared with BM22.5,
respectively. Moreover, Tu and Td decreased by 0.13 ◦ C and 0.05 ◦ C,
respectively, for BM15 (an irrigation depth of 15 mm) compared with
BM22.5. However, there were no obvious differences in Ts fluctuations
among treatments with different irrigation depths in the 15 and 25 cm
soil depths.

3.5. Two-dimensional Ts distributions under PM, BM, and NM
Two-dimensional daily average Ts values in the tillage layer under
different mulching and irrigation scenarios were compared on DAS 38(one day before irrigation), DAS 40 (one day after irrigation), DAS 118(one day before irrigation), and DAS 120 (one day after irrigation) in2018 (Fig. 6). The two-dimensional Ts distributions were similar forBM22.5 and PM22.5 on DAS 38 and DAS 40, but the “optimal Ts” (i.e.,20− 24 ◦ C) (Yan and Tu, 2003) area under FM was markedly larger
compared with NM22.5. Differences in Ts distributions for different
mulching scenarios occurred mainly in the 0− 10 cm soil layer andincreased with time. On DAS 118, the “optimal Ts” areas under NM22.5
and BM22.5 were 256.08 and 66.48 cm2, respectively, which represented
an increase of 82.7 % and 33.5 % compared with PM22.5, respectively.
However, the areas with “relatively high Ts” (i.e., Ts≥25 ◦ C) were 46.5 %and 4.9 % lower for NM22.5 and BM22.5, respectively, than for PM22.5. On
the other hand, the areas with “relatively low Ts” (i.e., Ts ≤19 ◦ C) were
the same (all were zero). After irrigation (DAS 120), the Ts distribution
in the 0− 10 cm soil layer was visibly uneven regardless of the treatment.
The areas with “optimal Ts” under BM22.5, PM22.5, and NM22.5 accounted
for 14.0 %, 10.9 %, and 28.8 % of the tillage layer, respectively.
Generally, BM effectively regulated soil temperature in an optimal range
for crop growth, and the biodegradable film can thus be recommended
as an alternative material to replace the traditional polyethylene film.

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Soil & Tillage Research 213 (2021) 105116

Fig. 6. Simulated two-dimensional soil temperature distributions in the tillage layer (0-30 cm) on (from top down) DAS 38 (1 day before irrigation), DAS 40 (1 day
after irrigation), DAS 118 (1 day before irrigation), and DAS 120 (1 day after irrigation, bottom row) in 2018 under (from left to right) plastic film mulching (PM22.5),
biodegradable film mulching (BM22.5), and no film mulching (NM22.5) with an irrigation depth of 22.5 mm, and biodegradable film mulching with irrigation depthsof 30 (BM30) and 15 (BM15) mm.

When the irrigation depth was increased to 30 mm, the “relatively
low Ts” area increased by 53.5 %, while the “optimal Ts” area decreasedby 47.2 %. The “relatively high Ts” areas remained the same for all
scenarios. Additionally, when the irrigation depth decreased to 15 mm,
the areas with “relatively low Ts” and “optimal Ts” decreased by 70.1 %and 16.3 %, respectively, while the area with “relatively high Ts”
increased by 37.9 %.

with low gas permeability, especially for impermeable plastic film
mulching. For example, Zhao et al. (2018) estimated Ts variations under
PM using HYDRUS (2D/3D), obtaining a very low RMSE for Ts of only
0.032− 0.055 ◦ C. Zhang et al. (2018) also obtained good modeling ac­
curacy (RMSE = 1.0–4.2 ◦ C) by evaluating differences in Ts at different
soil depths and locations in a drip-irrigated field. In this study, similar
results were obtained for the PM22.5 treatment with RMSE of 1.86–3.34◦
C. Additionally, this study further found that the simulation accuracy of
HYDRUS (2D/3D) was sufficiently high for BM, with RMSEs as low as
1.97 ◦ C. Differences between the model and experimental data can be
explained by the simplification of surface heat fluxes in the mulchedregion.

4. Discussions
4.1. Model evaluation
The HYDRUS model has been widely used in agricultural sciences
due to its flexible boundary conditions, high simulation accuracy, anduser-friendly interface (Sahaar and Niemann, 2020; Fishkis et al., 2020;
Fernandez-Bou et al., 2020) to simulate soil water contents (Elliott andprice, 2019), soil salinities (Phogat et al., 2020), and soil nitrogen (Chenet al., 2020). Much less research has been published, in which HYDRUS
was used to simulate soil temperatures Ts. HYDRUS can solve the partial
differential equation proposed by Philip and de Vries (1957) to simulate
soil heat fluxes while considering soil surface latent heat fluxes, sensible
heat fluxes, water fluxes, and thermal properties and their dependence
on soil water contents (Šimůnek et al., 2016). HYDRUS-1D also con­siders the subsurface movement of liquid water and water vapor driven
by pressure head and temperature gradients (Saito et al., 2006). Thisupdated model was applied in a special scenario with high gas perme­ability materials, e.g., straw mulching (Dahiya et al., 2007). Not all ofthese processes (e.g., vapor flow or thermal liquid flow) are currently
considered by HYDRUS (2D/3D). However, HYDRUS (2D/3D) can
provide good simulation accuracy for soil temperatures under mulching

4.2. Effects of mulching treatments on soil temperature fluctuations
Different Ts fluctuations under different mulching treatments
occurred mainly in the mulching area. The field with a larger mulchingarea can effectively decrease the near-ground wind speed, reduce water
vapor losses (Shahzad et al., 2019), and regulate Ts (Ma et al., 2020;
Hwang et al., 2019). On the other hand, the field with a small mulchingarea can produce increased soil surface temperature fluctuations due tohigh radiation reflection and intense near-ground wind speed (Kaderet al., 2020). For example, in this study, average Ts for PM was 1.12 ◦ Chigher than for NM in 2018 and 2019, while related SD and DV increasedby 27.0 % and 49.2 %, respectively, for NM compared with PM. Lee andPark (2020) found similar results when comparing Ts in the root zone
under different mulching treatments, with Ts under PM 0.5–1.8 ◦ C higher
than under NM. Díaz-Pérez and Batal (2002) further illustrated that NM
had higher Ts fluctuations than PM, mainly due to NM’s low heat pres­ervation, especially the significantly decreased soil heat flux at night.
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Soil & Tillage Research 213 (2021) 105116

Compared with PM and NM, BM has more advantages in heat pres­ervation and heat stress prevention. For example, Ts increased by about
1.1 ◦ C in the BM treatment compared with NM during early crop growthstages, which was similar to that of PM (Shen et al., 2019; Yin et al.,2019). However, during later crop growth stages, BM could effectively
overcome the shortcomings of PM, such as root lignifications and ac­
tivity decline (Lincoln and Eduardo, 2010), by regulating Ts within an
optimal range (20− 24 ◦ C suggested by Yan and Tu (2003)) due to its
oxidation and microbial degradation (Borrowman et al., 2020; Sintim
et al., 2020; Braunack et al., 2020). The result of this study showed that
Ts under BM mostly remained in the 20− 24 ◦ C interval during the latecrop growth stage (Fig. 3). However, Ts under PM increased on averageby 0.4 ◦ C compared with BM, causing heat stress on some days. Gu et al.
(2017) evaluated differences in Ts under PM and BM, finding that Ts
under BM was lower than under PM after DAS 150. Moreover, Sun et al.
(2018) also similarly reported that Ts under BM decreased by 0.4–1.4 ◦ Ccompared with PM after DAS 60.

The SD, DV, and K under BM22.5 were 6.7 %, 32.6 %, and 19.3 % higher
than under PM22.5.
Additionally, the apparent difference in Ts values between BM22.5
and PM22.5 mainly occurred in the soil surface layer (5 cm), and the areawith “optimal Ts” under BM22.5 increased by 33.5 % compared with
PM22.5. The order of Ts for different irrigation treatments was BM15,
BM22.5, and BM30, while the maximum size of the “optimal Ts” area
occurred in BM22.5. Generally, BM effectively regulated soil temperature
within a suitable range for crop growth. The biodegradable film can thus
be recommended as an alternative material to replace the traditional
polyethylene film.

4.3. Effect of irrigation levels on soil temperature in the tillage layerThis research was jointly supported by the National Natural Science
Foundation of China (52079064, 51969024, and 51469022), the Local
Science and Technology Development Fund Projects Guided by theCentral Government (2020ZY0023), the Major science and technology
projects of Inner Mongolia (zdzx2018059), Inner Mongolia autonomous
region graduate education innovation plan subsidize project(S20191167Z). Additionally, we are sincerely appreciating the careful
and precise reviews by the anonymous reviewers, editors.

Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgments

In general, Ts fluctuations and distributions in the tillage layer areclosely related to SWCs (Philip and de Vries, 1957; Saito et al., 2006).
For example, low Ts usually occurred in high SWC regions. In this study,
Ts in the treatment with a high irrigation depth (i.e., the BM30 treatment)
was generally lower than in other irrigation treatments, but the Ts
fluctuations significantly increased (Fig. 5 and Table 4). The reason isthat the specific heat capacity of soil water is higher than that of soil
particles. Romić et al. (2020) evaluated the effects of the extreme
meteorological conditions on grape yield and anthocyanin content,
finding that the adverse impact of long-lasting high-temperature events
could be partially avoided by applying irrigation. Additionally,
two-dimensional Ts distributions under different irrigation levels varied
widely due to the different sizes of the wetted area (Fig. 6). For example,
the maximum depth of the area with “relatively low Ts” under BM30
reached 9.8 cm, increasing by 42.9 % and 79.6 % compared with BM22.5
and BM15, respectively. The corresponding maximum width under BM30
reached 13.2 cm, which was 59.3 % and 75.0 % higher than underBM22.5 and BM15, respectively. Generally, a high irrigation depth
treatment results in a significant increase of the area with “relatively low
Ts” and a decrease of the area with “optimal Ts”. Compared with the highirrigation depth treatment, the low irrigation depth treatment can
reduce the area with “relatively low Ts” and increase the area with“relative high Ts”. The results showed that only the medium irrigation
depth treatment, among different treatments considered in this study,
provided the maximum size of the area with “optimal Ts”. Therefore, we
recommend the medium irrigation depth treatment (22.5 mm) as the
optimal irrigation strategy. However, by observing the Ts distribution
under different irrigation depths, Ren et al. (2019) found the maximum
area with “optimal Ts” for a 46.9 mm irrigation depth treatment. Theirresults were very different from the recommended value in our study.
The main reason may be the differences in precipitation and ground­water table depths at different experimental sites.

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5. Conclusions
This study evaluated the effects of different mulching and different
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