Europ. J. Agronomy 83 (2017) 47–56

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European Journal of Agronomy
journal homepage: www.elsevier.com/locate/eja

Spatial distribution of soil water, soil temperature, and plant roots in a
drip-irrigated intercropping ﬁeld with plastic mulch
Xianyue Li a , Jiří Šimůnek b , Haibin Shi a,∗ , Jianwen Yan a , Zunyuan Peng a , Xuewen Gong aabCollege of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Huhhot 010018, China
Department of Environmental Sciences, University of California Riverside, Riverside, CA, 92521, USAa r t i c l e

i n f oArticle history:
Received 27 February 2016
Received in revised form 25 October 2016
Accepted 28 October 2016
Keywords:
Drip irrigation with plastic mulchIntercropping
Soil water
Soil temperature
Root distributiona b s t r a c t
Intercropping and drip irrigation with plastic mulch are two agricultural practices used worldwide. Coupling of these two practices may further increase crop yields and land and water use efﬁciencies when an
optimal spatial distribution of soil water contents (SWC), soil temperatures, and plant roots is achieved.
However, this coupling causes the distribution of SWCs, soil temperatures, and plant roots to be more
complex than when only one of these agricultural practices are used. The objective of this study thus was
to investigate the effects of different irrigation treatments on spatial distributions of SWCs, soil temperatures, and root growth in a drip-irrigated intercropping ﬁeld with plastic mulch. Three ﬁeld experimentswith different irrigation treatments (high T1, moderate T2, and low T3) were conducted to evaluate
the spatial distribution of SWCs, soil temperatures, and plant roots with respect to dripper lines andplant locations. There were signiﬁcant differences (p < 0.05) in SWCs in the 0–40 cm soil layer for different irrigation treatments and between different locations. The maximum SWC was measured under theplant/mulch for the T1 treatment, while the minimum SWC was measured under the bare soil surface
for the T3 treatment. This was mainly due to the location of drippers and mulch. However, no differencesin SWCs were measured in the 60 100 cm soil layer. Signiﬁcant differences in soil temperatures were
measured in the 0 5 cm soil layer between different irrigation treatments and different locations. The soil
temperature in the subsoil (15 25 cm) under mulch was higher than under the bare surface. The overlaps of two plant root systems in an intercropping ﬁeld gradually increased and then decreased during
the growing season. The roots in the 0 30 cm soil layer accounted for about 60% 70% of all roots. Higher
irrigation rates produced higher root length and weight densities in the 0 30 cm soil layer and lower
densities in the 30 100 cm soil layers. Spatial distributions of SWCs, soil temperatures, and plant roots in
the intercropping ﬁeld under drip irrigation were signiﬁcantly inﬂuenced by irrigation treatments andplastic mulch. Collected experimental data may contribute to designing an optimal irrigation programfor a drip-irrigated intercropping ﬁeld with plastic mulch.
© 2016 Elsevier B.V. All rights reserved.

1. Introduction
Intercropping is a very popular agricultural practice used aroundthe world, such as in China (Zhang and Li, 2003), Germany (Munzet al., 2014), Brazil (Crusciol et al., 2014), India (Tanwar et al., 2014),
Pakistan (Asghar Shah et al., 2016). It not only improves the land use
efﬁciency (e.g., Dhima et al., 2007; Tanwar et al., 2014; Wang et al.,2015) and the light and radiation use efﬁciency (Awal et al., 2006),
but also enhances crop yields and farmers’ income(Gou et al., 2016).
However, there are often different water requirements needed by∗ Corresponding author.
E-mail addresses: lixianyue80@126.com (X. Li), Jiri.Simunek@ucr.edu(J. Šimůnek), shi haibin@sohu.com, shb@imau.edu.cn (H. Shi).
http://dx.doi.org/10.1016/j.eja.2016.10.015
1161-0301/© 2016 Elsevier B.V. All rights reserved.

two different crop species during the growing period, which thetraditional ﬂood irrigation, incapable of providing different irrigation amounts in one ﬁeld at the same time, cannot satisfy. This
results in a low water use efﬁciency (WUE) in intercropping ﬁelds(Sampathkumar et al., 2012). On the other hand, drip irrigation withplastic mulch can be an effective practice to increase soil temperatures, the WUE, and crop yields (e.g., Hou et al., 2010; Liu et al.,2012; Yahgi et al., 2013; Wang et al., 2014). Combining drip irrigation with intercropping can increase not only crop yields, butalso the land and water use efﬁciencies. Such a system may provide independent drip irrigation lines for different crop species,
and thus optimize irrigation for every crop species and their different root systems (Sampathkumar et al., 2012). However, such amulti-practice system produces more complex spatial distributions

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X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

Fig. 1. Schematic showing the cropping pattern (with two double rows of tomatoes and one double row of corn), the arrangement of drip tapes, and locations of TDR probes,
geothermometers, surface mulch, and measured root zone.

of soil water contents, soil temperatures, and root growth, whencompared to a single-practice system. It is thus important to investigate variations in soil water contents (SWC), soil temperatures,and root distribution, and to study the competitive mechanisms
in such multi-species systems in order to design optimal irrigation
programs for drip-irrigated intercropping ﬁelds with plastic mulch.
Soil water movement under drip irrigation with different crops
has been studied during the last few decades, both through experimentation (e.g., Yahgi et al., 2013; Badr and Abuarab, 2013) andthe use of simulation models (e.g., Skaggs et al., 2004; Kandelous
et al., 2011; Arbat et al., 2013). For example, the effects of different drip irrigation frequencies (Abou Lila et al., 2013), different drip
patterns (Skaggs et al., 2010), and different irrigation amounts (vanDonk et al., 2013) on soil water movement and crop growth were
all researched in many countries. Results in general show that drip
irrigation produces a higher WUE and lower leaching compared tosurface irrigation (Patel and Rajput, 2008). Additionally, the effectof the drip irrigation on root growth is very complicated. Sharma
et al. (2014) found that while deﬁcit irrigation (50% of ETc ) increased
the root length density of one variety of melon (cv. Mission), it did
not have any impact on another variety (cv. Super Nectar), and it
even decreased the root length density in the third variety (cv. Da
Vinci).
The spatial distribution of roots in an intercropping ﬁeld is different from the distribution in a single crop system. The overlapping
root systems of two crop species lead to the competition for waterand nutrients. For example, an uneven distribution of roots wasmeasured in a maize/cabbage intercropping system (Zhang andHuang, 2003), with the roots of maize extending horizontally togreater distances than those of cabbage. The roots of the two crops
extended into the rhizospheres of each other in the maize/cowpea
intercropping ﬁeld (Adiku et al., 2001), with the roots of maize
being much larger.
Plastic mulch not only increases crop yields, soil temperatures,and the WUE, but it also stabilizes the daily range of soil temperatures (Xing et al., 2012), which can beneﬁt crop growth. Although
the thermal effects of SWC on soil temperature in a soil systemwith plastic mulch have been studied by many scientists (Mahrer
et al., 1984; Hunt et al., 2010), much less similar work has been
done for drip-irrigated intercropping systems with plastic mulch.
Such systems are much more complicated because the spatial distribution of SWCs is affected by the different water consumptionsof two crop species and their overlapping or not overlapping rootsystems, depending on crop species and their particular growing
periods (Gao et al., 2010). The SWCs and root distribution in a dripirrigated intercropping ﬁeld are thus inﬂuenced not only by drip
wetting patterns, but also by the root water uptake competition
between two crops (Gao et al., 2010; Sampathkumar et al., 2012).
The spatial distribution of soil temperature is inﬂuenced not
only by plastic mulch and water contents, but also by the differ-

ent heights of two crops and their shading of the soil surface. All
these factors, i.e., water contents, soil temperatures, and the presence or absence of surface mulch, affect root growth (Ceccon et al.,2011). Understandably, the spatial distributions of SWCs, soil temperatures, and root systems in a drip-irrigated intercropping ﬁeld
with plastic mulch are very complex and difﬁcult to predict.
The main objectives of this study therefore are (i) to analyze theeffects of drip irrigation on SWCs under different drip irrigation
practices in an intercropping ﬁeld, (ii) to evaluate the distribution of soil temperature in a drip-irrigated intercropping ﬁeld withplastic mulch, and (iii) to compare root system distributions under
different irrigation treatments.
2. Materials and methods
2.1. Experimental site
The ﬁeld experiment was conducted at the Dunkou Agroecosystem Experimental Station (40◦ 20 15 N, 107◦ 1 45 E, altitude2004 m), located at the western Hetao Irrigation District, in the
Yellow River basin of Northwest China, during the 2012 and 2013seasons. The main soil texture on the site is sandy clay loam, andthe groundwater table is between 70 and 250 cm deep. The site
is representative of inland arid climate with a long-term average annual rainfall of 198 mm and an average annual potential
evapotranspiration of 2460 mm. Note that average annual potential evapotranspiration is 12.4 times higher than average annual
precipitation, which makes irrigation necessary for crop growth.
2.2. Experimental treatments and procedures
The planting pattern in the intercropping ﬁeld consisted of 4
rows of tomatoes and 2 rows of corn. One drip line was used forboth two crop rows and one mulch strip in order to reduce irrigation costs (Fig. 1). Two rows of crops were irrigated with one
drip line and covered with one white plastic mulch sheet with
80 cm width. Three irrigation treatments, with high T1 (Conventional drip irrigation), moderate T2 (about 75% of T1), and low
T3 (about 50% of T1) irrigation amounts (which were the same ineach irrigation event in a particular year, but different between
treatments) (Table 1), were delivered in three replicates in a completely randomized block design of 9 plots, and the more detailagronomic management can be found in paper of Li et al. (2015).
Different irrigation amounts were adopted for tomato and corn in
one irrigation treatment (Table 1). Two water meters (with a precision of 0.001 m3 ) were used to control irrigation amounts in eachtreatment. Corn was direct-seeded in the ﬁeld (with a 40 cm row
spacing), while tomatoes were transplanted to an intercropping
ﬁeld (with a 40 cm row spacing). After transplanting, all treatments
received a large ﬂood irrigation (about 55 mm) on day of year (DOY)X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56
Table 1
Amounts of irrigation water in a single irrigation event in different irrigation treatments during two years.
Irrigation amount (mm)Treatment

Tomato

Corn

T1
T2
T3

22.5
16.5
10.5

30
22.5
15

49

(Fig. 1). SWC measurements were taken once a week at soil depthsof 0 10, 10 20, 20 40, 40 60, 60 80, and 80 100 cm. Soil temperature
measurements were taken between sowing and harvesting at soil
depths of 5, 10, 15, 20 and 25 cm and at 08:00 h, 10:00 h, 12:00 h,
14:00 h, 16:00 h, 18:00 h and 20:00 h at a 10-day interval. Interday temperature measurements were averaged to give daily soil
temperature.
2.5. Root measurements

132 (2012 season) and 125 (2013 season) for crop survival. Drip irrigation was applied on DOY 167, 175, 190, 196, 199, and 214 to both
crops in the 2012 season, and DOY 141, 156, 171, 188, 198, and 221
in the 2013 season. Corn received two additional irrigations on DOY
222 and 228 in the 2012 season, and one additional irrigation on
DOY 229 in the 2013 season.
2.3. Meteorological measurements
Continuous data were collected for solar radiation (S-LIB-M003),
photosynthetically active radiation (S-LIA-M003), air temperature,
relative humidity (S-THB-M002), air pressure (S-BPA-CM10), windspeed (S-WCA-M003), and precipitation (S-BPA-CM10) at the automatic meteorological station installed about 500 m away from theexperiment ﬁeld. Data were averaged and recorded at one-hourintervals, and stored in a datalogger (H21-001 DT-80), from which
they were automatically downloaded. Reference crop evapotranspiration (ET0 ) rates during the 2012 and 2013 seasons, calculatedusing the Penman–Monteith equation (Allen et al., 1998), are presented in Fig. 2.
2.4. Soil water and soil temperature measurements
TDR probes (TRIME-PICO-IPH, IMKO GmbH, Germany) for measuring SWC and mercury-in-glass geothermometers with bent
stems (Hongxing Thermal Instruments, Wuqiang County, Hebei
Province, China) for measuring soil temperature were installed in
the middle of two rows of tomatoes (P1), two rows of tomato
and corn (P2), and two rows of corn (P3) in each treatment plot

Since measurements of the root spatial distribution are verytime and labor intensive, four measurements of the root distribution were carried out to study root distributions at different growthstages only for the T1 treatment. Measurements were taken on June
6, June 22, July 21, and August 20 in the 2012 season, and on June
5, June 28, July 24, and August 21 in the 2013 season. To study theeffect of the soil water content on root growth, root measurements
for all three treatments (T1, T2, and T3) were taken in July during
both seasons. Horizontal and vertical root distributions of corn andtomato were obtained from a soil transect (Ozier-Lafontaine et al.,
1999; Adiku et al., 2001; Gao et al., 2010), which was dug between
the tomato and corn strips, and which was on one side of the 60 cm
long, 100 cm wide, and 100 cm deep trench (Fig. 1). After the trench
was dug, the working surface of the soil proﬁle was smoothed, theface of the pit was trimmed to be vertical, and then the verticalplane was divided into square, 5 × 5 cm cells, and 5 cm long nails
were driven into it every 5 cm along its length and width.
Soil samples were soaked for 15 min in water and then washedusing a root washing machine (Delta-T, CSIRO, Australia). Washedroot samples were scanned by a root system scanner (Reagent
Instruments Inc.; Perfection 4870photo, Epson, Japan) using the450 dpi resolution. Root length (cm), root volume (cm3 ), and root
surface area (cm2 ) were determined using the WinRHIZO software(ver. 2003b, Reagent Instruments Inc., Quebec, Canada). After the
analysis, root samples were dried at 65◦C for 3 days to measure
the root dry mass (g) (Leskovar and Cantliffe, 1991; Sharma et al.,2014).
2.6. Statistical analysis
All data were analyzed by the analysis of variance (ANOVA)
using the SPSS software (Version 16.0.0). A Duncan’s multiple
range tests were applied to detect differences among the meansof treatments and locations for SWCs, soil temperatures, and root
parameters. Values reported in the tables below and marked withdifferent letters are considered statistically signiﬁcant at a level of
0.05 (the p value) (McCullough and Wilson, 2002).
3. Results
3.1. The effect of irrigation amounts on SWC in a drip-irrigatedintercropping ﬁeld

Fig. 2. Potential evapotranspiration (ET0 ), precipitation (P), and irrigation (I) for
the T1 treatment during the entire growing season 2012 (top) and 2013 (bottom).
There were different irrigation amounts for tomato and corn, while two additional
irrigations were applied to corn on DOY 222 and 228 in the 2012 season, and one
additional irrigation was applied to corn on DOY 229 in the 2013 season.

Movement of soil water directly inﬂuences variations in soil
temperature and migration of crop nutrients, thus affecting crop
growth and crop yield. Average SWCs (Table 2) in the 0 10, 10 20,
20 40, 40 60, and 60 100 cm soil layers were analyzed for all
three irrigation treatments during both seasons (Fig. 3). Results
showed that the average SWC in the 0 40 cm soil layer significantly decreased (p < 0.05) with the reduction of the irrigation
amount, especially between the T1 and T3 treatments. Differences
between different treatments gradually decreased in deeper soil
layers (>40 cm), and virtually disappeared in the 60 100 cm soil
layer (at p > 0.05). Average SWCs in all three treatments (Fig. 3) displayed large ﬂuctuations in the 0 10 and 10 20 cm soil layers during
both seasons due to precipitation and irrigation events, and only

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X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

Fig. 3. A comparison of SWCs at P1 (tomato), P2 (bare), and P3 (corn) locations at depths of 0–10 (top), 10–20, 20–40, 40–60, and 60–100 (bottom) cm during the 2012 (left)
and 2013 (right) seasons.

X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

51

Table 2Average SWCs (cm3 cm−3 ) at different locations (P1, P2, and P3) for different treatments (T1, T2, and T3).
Treatment

0 20 cm

Irrigation(Ir)
T1
T2
T3

2012
0.277a0.256a0.240b2013
0.305a0.296a0.273b20 40 cm
2012
0.278a0.256b
0.236c2013
0.305a0.297ab
0.264b40 60 cm
2012
0.304a0.293b0.300a2013
0.304a0.301a0.294b60 1002012
0.362a0.357a0.354a2013
0.355a0.352a0.348aPosition(P)
P1
P2
P3

0.278a0.228b
0.277a0.315a0.260b0.299ab0.269a0.239b0.261a0.295ab0.274b
0.296a0.307a0.291b
0.296b0.300a0.295b0.305a0.362a0.355a0.356a0.355a0.350a0.351aANOVA
Ir
P
Ir × PP-value
0.010
0.001
0.541

0.023
0.001
0.893

0.001
0.001
0.009

0.001
0.006
0.008

0.039
0.005
0.001

0.121
0.065
0.005

0.238
0.287
0.722

0.276
0.546
0.989

According to the Duncan’s multiple range test, values followed by the same letter within a column are not signiﬁcantly different at p ≤ 0.05.

small ﬂuctuations in the 20 100 cm soil layers. Soil water in the
top soil (0 30 cm) was provided mainly by drip irrigation and average SWCs were 25.7 cm3 cm−3 and 29.0 cm3 cm−3 during the 2012
and 2013 seasons, respectively. On the other hand, soil water inthe subsoil (40 100 cm) was provided not only by irrigation, butalso by groundwater. Consequently, average SWCs reached values of 32.8 cm3 cm−3 and 32.6 cm3 cm−3 during the 2012 and 2013seasons, respectively (Table 2). Average SWCs (over two years) indeeper horizons (60 100 cm) were 35.5 cm3 cm−3 , mainly due to theinﬂuence of the shallow groundwater that was often only about
120 cm below the soil surface during the crop growth period. As
a result, the root system in the region, for conditions with deﬁcit
irrigation, has a tendency both to be deeper, and to reach higher
SWCs in the subsoil.
The largest difference in SWCs, 22.0 cm3 cm−3 , was measured in
the 0 20 cm soil layer between P1 and P3 locations (Table 2). There
were highly signiﬁcant (p < 0.01) differences in SWCs in the 0 40 cm
soil layer among different locations, but these differences decreased
with depth. In the 40 60 cm soil layer, only in the 2012 season were
there signiﬁcant differences (p < 0.05) in SWCs among three locations. Because of small differences between root systems, small
effects of irrigation and precipitation, and a large inﬂuence of shallow groundwater in the 60 100 cm soil layer, no differences in SWCs
were observed among P1, P2, and P3 locations (p = 0.287 in 2012;
p = 0.546 in 2013). The plots of SWCs were practically overlappingat deeper depths at different locations (Fig. 3).
The spatial and temporal distributions of SWCs are very complicated in a drip-irrigated intercropping ﬁeld with plastic mulch.

There were signiﬁcant differences in SWCs in the 0 40 cm soil
layer among different irrigation treatments and different locations(Fig. 3). As expected, irrigation treatments with higher irrigation
amounts produced higher SWCs. SWCs at crop locations P1 and P3
were higher than at the bare location (P2) because of mulch. There
were only small differences in SWCs in the 40 100 cm soil layer, andalmost none in the 60 100 cm soil layer.

3.2. The effect of irrigation amounts on soil temperature in a
drip-irrigated intercropping ﬁeld
Soil temperature data during the mid-season crop growth stages(from mid-July to mid-August) was used because of maximum
differences in SWCs among different locations and maximum differences in crop heights between tomato and corn during this time
period. Two-dimensional soil temperature proﬁles for both seasons and for three treatments are shown in Fig. 4. Fig. 4 shows
distinctive differences in temperatures at different locations. Soil
temperature at the corn location (P1) was clearly higher than at
the tomato location in the top 0 10 cm soil layer, especially in the
topsoil (0 5 cm) (p < 0.05). Soil temperature in the subsoil (15 25 cm)
at the mulch locations (P1 and P3) was signiﬁcantly higher than at
the non-mulch (bare) location (P2) (p < 0.05). Only small differenceswere observed among plots with different irrigation treatments(Fig. 4), although in general, slightly higher soil temperatures wereobserved in plots with the low irrigation treatment because oflower SWCs.

Fig. 4. Comparison of spatial distributions of average soil temperatures of daytime in the 2012 (left) and in 2013 (right) seasons for treatment T1 (top; a, d), T2 (middle; b,e) and T3 (bottom; c, f) from mid-July to mid-August.

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X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

Fig. 5. Two-dimensional root length density distributions at different growth stages.
(left: a, f) Initial stage; (b, g) Development stage; (c, h) Mid-season stage; (right: d, i) Late season stage; in the 2012 (top) and 2013 (bottom) seasons.

3.3. The root system growth during different growth stages in a
drip-irrigated intercropping ﬁeld
To simplify the analysis, the sampled root region was divided
into 3 sections (the dotted lines in Fig. 5) representing the tomato
region, the bare region, and the corn region. The root length density(RLD) and root percentage for the three regions and the different crop growth stages are shown in Table 3. Since the crop roots
were not yet entirely developed during the initial crop growthstage (from seeding to mid-June) and the root lateral distance wasless than 20 cm, there were very few roots and little competitionin the bare region (Table 3; Fig. 5). During the development crop
growth stage (from mid-June to mid-July), the crop roots developed quickly and the roots of the two species extended into thebare region, resulting in an overlap of the two root systems andcompetition for soil resources. The percentage of roots in the bareregion reached 18 25%, compared with only 3 4% during the initial
growth stage (Table 3). However, the rooting depth was still rather
shallow, within the top 30 cm. During the mid-season crop growthstage (from mid-July to mid-August), the root systems were alreadywell developed, with the maximum expansion in both horizontal
and vertical directions. The roots of both plants extended into thebare region, which now contained almost one third of all roots(30 33%). During the late crop growth stage (from mid-August to
mid-September), tomatoes gradually wilted, since no irrigation was
any longer given to the tomato strip, producing more dying roots
than new ones. Additionally, the corn roots grew mainly down-wards, producing more deep roots and fewer in the bare region.
Consequently, there was a reduction in roots overlapping, and thepercentage of roots in the bare region dropped to about 19 27%. The
pattern of roots overlapping in this intercropping ﬁeld thus developed from none to little to full and back to little again from the initial
crop growth stage to the late season stage (Fig. 5), respectively.
Percentages of roots in the bare region developed as follows:
3.06, 18.0, 32.7, and 26.7% in the 2012 season, and 3.62, 24.8, 30.4,
and 19.3% in the 2013 season from the initial crop growth stage tothe late season stage (Table 3), respectively. Average percentages ofroots in the tomato region during the 2012 and 2013 seasons were
32.8 and 36.2%, respectively, and in the corn strip 42.4 and 40.5%,
respectively.
3.4. The effect of irrigation amounts on root growth in a
drip-irrigated intercropping ﬁeld
The largest overlap of the roots of the two species and thelargest SWC variations in an intercropping ﬁeld occurred during
the mid-season crop growth stages. It is thus important to identify
the effects of soil water contents on roots during this crop growth
period. The root length density (RLD), root weight density (RWD),
root volume density (RVD), and root surface area density (RSD) for
every soil layer were averaged and analyzed (Table 4). The results
show that the crop roots were concentrated mainly in the top
0 10 cm soil layer (Fig. 6) and that their content quickly decreased
with depth. More than 50% of roots were in the top 0 20 cm soil

X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

53

Table 3RLD distributions in different soil regions at different growth stages during 2012 and 2013 seasons.
RegionParameter

Year

InitialDevelopment

Mid-season

Late season

TomatoAverage RLD (cm/cm3 )

2012
2013
2012
2013
2012
2013
2012
2013
2012
2013
2012
2013

0.83
0.91
48.46
47.44
0.05
0.07
3.06
3.62
0.83
0.96
48.47
50.02

1.21
2.14
33.95
35.62
0.64
1.49
17.98
24.83
1.71
2.38
48.07
39.56

2.21
3.01
33.71
34.33
2.15
2.66
32.71
30.39
2.20
3.09
33.58
35.29

1.29
2.36
25.55
37.99
1.35
1.20
26.68
19.26
2.42
2.98
47.77
47.97

Root percentage (%)
Bare

Average RLD (cm/cm3 )Root percentage (%)

Corn

Average RLD (cm/cm3 )Root percentage (%)

Table 4
Effects of different irrigation treatments on root distribution.
RLD (cm cm−3 )Treatment
irrigation
0 30

RVD (cm3 cm−3 × 10−3 )RSD (cm2 cm−3 )RWD (g cm−3 × 10−3 )

2012
2.84a
2.54a
2.18b
0.98a
1.16a
1.28a

2013
2.89a
2.68b
2.37c
1.07b
1.15ab
1.30a

2012
8.06a
6.86ab
5.95b
3.07a
3.55a
3.68a

2013
6.36a
6.13a
4.99b
1.59b
1.60b
1.93a

2012
0.64a
0.56a
0.50b
0.25a
0.28a
0.30a

2013
0.48a
0.45a
0.38b
0.14b
0.15b
0.18a

2012
1.74a
1.55ab
1.33b
0.55a
0.63a
0.63a

2013
1.76a
1.68a
1.50a
0.57a
0.64a
0.70a

Depth(cm)
0–10
10 20
20–30
30–40
40–60
60–100

2.75a
2.71a
2.10b
1.71c
0.85d
0.28e

2.88a
2.83a
2.24b
1.66c
1.23d
0.49e

9.33a
6.57b
4.97c
4.41cd
3.54d
1.39e

7.24a
6.00b
4.25c
2.56d
1.71e
0.77f

0.59a
0.60a
0.51b
0.38c
0.26d
0.08e

0.50a
0.46b
0.34c
0.23d
0.15e
0.07f

1.97a
1.55b
1.09c
0.84d
0.53e
0.21f

1.74ab
1.84a
1.36ab0.96b0.66bc
0.21c

ANOVA
Irrigation (0 30)
Irrigation (30 100)
Depth
Irrigation(0 100) × Depth

P-value
0.003
0.145
0.001
0.001

0.001
0.012
0.001
0.001

0.041
0.358
0.001
0.025

0.014
0.070
0.001
0.002

0.019
0.338
0.001
0.009

0.001
0.004
0.001
0.001

0.034
0.580
0.001
0.010

0.133
0.149
0.001
0.985

30 100

T1
T2
T3
T1
T2
T3

According to the Duncan’s multiple range test, values followed by the same letter within a column are not signiﬁcantly different at p ≤ 0.05.

layer, reaching 60 70% in the top 0 30 cm soil layer. The average
RLD and RWD percentages for all three treatments in the 0 30 cm
soil layer were 68.9% and 71.9% in the 2012 season and 69.3% and72.1% in the 2013 season, respectively.
The RLD, RWD, RVD and RSD were divided into two parts of
0 30 cm and 30 100 cm in order to study the effects of soil wateron root growth under drip irrigation (Table 4). The results showedthat there were signiﬁcant differences in all four root measures(p < 0.05) in the 0 30 cm soil layer, except in RWD in the 2013 season. Highly signiﬁcant differences were observed in RLD (p < 0.01)
during the 2012 and 2013 seasons in the top 0 30 cm soil layer.
However, although the overall crop root densities increased fordeﬁcit irrigation in the 30 100 cm soil layer, signiﬁcant differencesin RLD and RSD were observed during the 2013 season. There werehighly signiﬁcant differences in all four root parameters (p < 0.01) inthe vertical direction, and the root densities signiﬁcantly decreased
with soil depth.
4. Discussion
4.1. The effects of irrigation treatments and location on SWCs andsoil temperatures
Since the drip irrigation was used in our study, the wetting front
usually did not travel further than about 30 40 cm below the soil
surface, as was similarly reported in Machado and Oliveira (2005).
Hence, SWCs were affected by the drip irrigation mainly in theregion about 40 cm below the soil surface, and the higher the irriga-

tion amounts, the higher SWCs (Table 2) (Patel and Rajput, 2008).
Capillary rise from shallow groundwater caused higher SWCs atgreater depths, especially in the 60 100 cm soil layer (Table 2; Fig. 3),
as also observed by Ren et al. (2016). Due to capillary rise fromgroundwater, smaller irrigation amounts produced higher WUE, asalso reported by Yahgi et al. (2013) and Ren et al. (2016).
Large observed differences in SWCs between different locationsin an intercropping ﬁeld were due to the presence of plastic mulch.
Since no direct irrigation or mulching was applied in a bare region
between double crop rows (P2), average SWCs were signiﬁcantly
lower in this region as compared to mulched regions (P1 and P3)(Table 2; Fig. 3) (see also Hou et al., 2010; Yahgi et al., 2013). SWCs
were also slightly different between tomato (P1) and corn (P3)locations, because of different root water uptake and different irrigation amounts for the two species in an intercropping ﬁeld (Fig. 3).
Although more irrigation water was applied to corn (P3) than totomato (P1), a higher water requirement and root water uptake ofcorn (P3) resulted in slightly lower SWCs than at the tomato location (P1), as also reported by Allen et al. (1998) and Li et al. (2015).
However, SWCs at both P1 and P3 locations were still higher thanat the bare location (P2) (Fig. 3).
Soil temperatures in an intercropping ﬁeld were not affected
only by soil water contents, but also by crops and location. Soil temperatures were higher at the corn row (P3) than at the tomato row(P1) (Fig. 4). One reason for that was that SWCs at the corn location(P3) were lower than at the tomato location (P1) (Table 2). Since
dry soil has a lower heat capacity than wet soil, there are higher
soil temperatures at lower SWCs during the daytime (as drier soil

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X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

Fig. 6. Vertical distributions of RLD (left: a, c) and RWD (right: b, d) in the mid-season crop growth stage during the 2012 (top: a, b) and 2013 (bottom; c, d) seasons.

warms up more easily) (e.g., Hunt et al., 2010). Another reason
was that tomato leaves spread out to shade the ground surface,
while with corn, the sunlight could more easily reach the soil surface (Awal et al., 2006). The lowest SWCs and the maximum direct
sunlight occurred at the bare location (P2), as compared to otherlocations. As a result, soil temperature of the topsoil was higher
than at the tomato location (P1), but close to that recorded at thecorn location (P3). The lowest soil temperature was observed in the
20 25 cm soil layer under the bare location (P2) (Fig. 4). Heat fromthe subsoil was more easily lost to the atmosphere through the baresoil surface without mulch (Yahgi et al., 2013). Therefore, there
were much higher differences in soil temperatures between the
topsoil (0 5 cm) and the subsoil (20 25 cm), compared to locations
with mulch (P1 and P3) (Fig. 4).
4.2. The effects of irrigation treatments and location on the root
growthRoot distribution plays an important role in the interactions
between species within intercropping ﬁelds. In such ﬁelds, root dis-tributions are different for different species in time and space, andthere is interspecies competition for resources, such as soil water
and/or nutrients, which is very different from monoculture ﬁelds(Mushagalusa et al., 2008). In the corn/tomato intercropping ﬁeld,
the corn root system was more developed than the tomato rootsystem, and also more than that of the cabbage (Zhang and Huang,
2003) and cowpea (Adiku et al., 2001). Especially during the lateseason, the corn root percentages were 9.98% and 22.2% higher
than for the tomato during the 2012 and 2013 seasons, respectively. Based on the percentage of roots in different regions (Table 3)
and the two-dimensional root proﬁle (Fig. 5), the roots developed
ﬁrst both laterally and vertically, and then degenerated. Consequently, the roots of the two crop species ﬁrst displayed no overlap,
then signiﬁcant overlap, and ﬁnally again less overlap during thelate crop growth. The overlap of the two root systems in time andspace in the intercropping ﬁeld may lead to the interspecies competition for soil water and/or nutrients. The less competitive crop
may thus occasionally experience stress due to deﬁciency of soil
water and/or nutrients (Zhang and Huang, 2003; Mushagalusa et al.,2008). When conventional surface irrigation is applied, it is difﬁcult

X. Li et al. / Europ. J. Agronomy 83 (2017) 47–56

to achieve high WUE for both crop species. However, high WUE for
both crop species can be achieved with drip irrigation, which candirectly target different demands by the two crop species at thesame time. Drip irrigation also could easily be adjusted to mainly
wet the soil with roots by changing the irrigation amount, which
could improve the WUE and reduce wasteful evaporation and deep
drainage. This demonstrates the advantage of intercropping ﬁelds(Sampathkumar et al., 2012; Li et al., 2015).
There was a large inﬂuence of SWCs on root growth; RLD and
RWD increased with decreasing irrigation amounts in the top layerand decreased below the 30 cm soil depth. Higher drip irrigation
amounts produced higher SWCs in the 0 30 cm soil layer (wettedby irrigation), producing a well-developed root system in this soil
layer (Fig. 6). Similar observations were made by Sharp and Davies(1985), who also observed increased root growth under a mild
water stress compared to well-watered conditions. Since there wasan insufﬁcient amount of soil water in the upper soil layer during deﬁcit irrigation, while soil water was available in the subsoil,
especially in the 60 100 cm soil layer (Fig. 3), roots tended to growdownward toward these water sources. Consequently, more roots
were often measured in the subsoil for deﬁcit irrigation (Sharma
et al., 2014). For example, the root densities in the T3 treatment in
the 0 30 cm soil layer were lower than in the T1 and T2 treatments,
but the opposite was observed in the 30 100 cm soil layer. However,
the roots in the 0 30 cm soil layer still accounted for a majority ofroots in all treatments. The root densities were higher for the highirrigation treatment than for the low irrigation treatment in theentire root system.

5. Conclusions
SWCs, soil temperatures, and crop root growth were observed
and analyzed for different irrigation treatments and at different
locations in a drip-irrigated intercropping ﬁeld with plastic mulch.
The effects of irrigation amounts on the distribution of SWCs, soil
temperatures, and root growth, and the differences in different
locations (mulch in tomato, corn surface and non-mulch in baresurface) were studied. SWCs for different irrigation treatments andat different locations were signiﬁcantly different in the 0 40 cm soil
layer, with the highest SWC measured at the tomato location andthe lowest SWCs at the bare location. There were much smallerdifferences in SWCs in the 40 100 cm soil layer between different
irrigation treatments and different locations. Almost no differencesin SWCs were observed in the 60 100 cm soil layer.
There were different soil temperatures in the 0 10 cm soil layer,
and especially in the 0 5 cm soil layer, among different irrigation
treatments and different locations. Soil temperature at the mulchedlocations (P1 and P3) was higher than at the non-mulched barelocation (P2) in the subsoil (15 25 cm). The maximum difference intemperatures in the vertical direction was measured at the nonmulched location. The soil temperature at the tomato location (P1)
was lower than at the corn (P3) and bare (P2) locations.
The crop root pattern of “no, little, maximum, and little overlap”
was observed between the initial crop growth stage and the lateseason growth stage. The percentage of roots in the bare region
developed from small, to intermediate, to large, and back to small
during the growth season. The majority of crop roots were in the
top 0 30 cm soil layer (soil wetted by drip irrigation), where about
60 70% of the roots were located. There were signiﬁcant differencesin RLD, RWD, RVD, and RSD among different irrigation treatments.
Higher irrigation amounts produced higher RLD and RWD in the
0 30 cm soil layer, and lower RLD and RWD in the 30 100 cm soil
layer.

55

Acknowledgments
This research was jointly supported by The Innovation Team
Program of Educational Ministry (IRT13069), the National Natural Science Foundation of China (51539005, 51469022, 51109105
and 51669020), the Natural Sciences Foundation of Inner Mongolia(2016JQ06), the State Science and Technology Support Program ofChina (2011BAD29B03) and Science and Technology Program ofInner Mongolia.

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