water
ArticleModeling of Soil Water Regime and Water Balance
in a Transplanted Rice Field Experiment with
Reduced Irrigation
Yong Li 1,2, *, Jirka Šimůnek 3 , Shuang Wang 2 , Jiahui Yuan 2 and Weiwei Zhang 2
1
2
3

*

Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on
Shallow Lakes, Hohai University, Nanjing 210098, China
College of Environment, Hohai University, Nanjing 210098, China; sswwhhu@163.com (S.W.);
riverbasin@163.com (J.Y.); zwwhhu@163.com (W.Z.)
Department of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA;jsimunek@ucr.edu
Correspondence: liyonghh@hhu.edu.cn; Tel.: +86-25-83787145

Academic Editor: Tim Hess
Received: 26 February 2017; Accepted: 28 March 2017; Published: 1 April 2017

Abstract: Available water resources for agricultural irrigation have decreased worldwide in recent
decades, prompting advances in water saving methods. In this study, soil water regime and waterbalance in a transplanted rice field with reduced irrigation (multiple shallow depth irrigations) in the
Taihu Lake Basin of East China were observed and then evaluated using Hydrus-1D model during
two consecutive growing seasons. During the 2008 season, irrigation water accounted for 48% of thetotal water input (TWI, 94.6 cm), but only 20% of TWI (120.4 cm) during the 2009 season. Due to heavy
rainfalls during the wet 2009 season, surface runoff accounted for about 6.4% of the TWI, whereas
during the much drier 2008 season with higher controlled irrigation inputs, no surface runoff occurred.
Simulated evapotranspiration during the 2008 and 2009 seasons accounted for 67.4% and 54.9% of
TWIs, respectively. Measured and simulated results indicate that water percolation (approximately
32.5% and 37.6% of TWIs during the 2008 and 2009 seasons, respectively) was the main path of water
losses from the transplanted rice fields, suggesting that long and high standing water during the2009 season increased water percolation. Water productivities evaluated from total irrigations and
TWIs were 2.08 and 0.99 kg·m−3 during the 2008 season and 3.85 and 0.77 kg·m−3 during the 2009season, respectively, and were 1.47 and 1.40 kg·m−3 , respectively, when evaluated from modeled
evapotranspiration fluxes. The cultivation method with multiple shallow depth irrigation efficiently
used rainfall water and reduced the losses due to water percolation and surface runoff by stabilizing
rice yields.
Keywords: soil water regime; water productivity; multiple-shallow irrigation; transplanted rice;Hydrus-1D model; Taihu Lake Basin

1. Introduction
The traditional transplanting method for rice cultivation worldwide has ensured a stable rice
yield during the long history of humankind [1,2]. Although several new cultivation methods (e.g.,
direct-seeded and seedling-thrown) have been developed in recent years to adapt to different climatesor to save labor [1,3], cultivation of transplanted rice (TPR) remains popular in many regions. However,in most regions, the traditional TPR cultivation still involves continuous flood irrigation (e.g., with awater depth of 5–10 cm), which has drawn attention due to the excessive associated losses of waterand nutrients [4,5]. Increasingly scarce water resources for agricultural irrigation and deteriorating

Water 2017, 9, 248; doi:10.3390/w9040248

www.mdpi.com/journal/water

Water 2017, 9, 248

2 of 14water environments necessitate improvements and optimization of water and fertilizer managements
for TPR [6–9].
Therefore, various water-saving irrigation strategies have been developed in different rice growing
regions to maintain acceptable rice yields [10,11]. For example, a combination of a shallow water depthwith wetting and drying [12,13], alternate wetting and drying [14,15], semi-drying [16], aerobic rice
cropping [10,17], partial rootzone drying [18], moistening, and non-flooded mulching [19] cultivations
are popular techniques that have been adopted around the world. Among these, the alternate
wetting and drying (AWD, also referred to as “alternately submerged-nonsubmerged” or “intermittent
irrigation”) irrigation techniques have been frequently reported for different climates and different local
water resource conditions in recent years [5,6,20]. Ye et al. [15] reported that AWD irrigation during the
TPR paddy field experiments in the Taihu Lake Basin (China) required less frequent irrigations (reducedby five and three in 2010 and 2011, respectively) and reduced the amount of irrigation water used (saved
41.9% and 28.0% in 2010 and 2011, respectively). AWD irrigation techniques not only save water resources,
but also increase rice yields compared to traditional flood irrigation [6,8,13]. However, Bouman andTuong [20] reported that although alternately submerged-nonsubmerged conditions reduced water inputs,
yields usually declined when the soil water potential in the root zone dropped below −10 to −30 kPa.
Compared to the traditional rice cultivation with flood irrigation, AWD provides a different
growth environment, particularly different vertical soil water content profiles and corresponding
nutrient transport and transformations [2,21]. Tan et al. [5] reported that AWD irrigation during
the 2007 and 2008 growing seasons produced a decrease in percolation by 27.8% and 19.0% andin nitrogen leaching by 5.0%–11.2% and 3.0%–23.5%, respectively, compared to continuous flood
irrigation. The AWD cultivation produces less water percolation due to lower vertical pressure headgradients during most of the growing season [20]. Due to complex soil water flow conditions in rice
fields under water-saving irrigation conditions, many scientists increasingly use computer models
to study water movement and water balance in the soil and to develop management and planningguidance [22–24]. The Hydrus-1D model [25] has been used by many researchers to simulate waterflow in agricultural fields with different crops and various irrigation schemes, including in TPR
fields [5,6,23]. However, the use of Hydrus-1D for simulating water flow conditions and water balancein TPR fields under water-saving irrigation has been limited.
In the Taihu Lake Basin of East China, various water-saving irrigation methods for transplanted
rice have been increasingly adopted to decrease the loss of water and associated nutrients and to better
protect surface and groundwater environments [7,21,26]. Multiple-shallow irrigation (MSI) is a type of
the AWD irrigation method that irrigates rice fields multiple times at shallow depths (e.g., 1–3 cm),
depending on soil conditions and weather predictions.
In this study, to exploit rainfall and decrease water losses, the MSI cultivation method wasused in TPR field experiments in the Taihu Lake Basin during two consecutive rice-growing seasons(2008–2009). Water flow in the TPR field under MSI conditions was observed and then evaluated using
Hydrus-1D to improve our understanding of the main characteristics of the soil water regime andthe overall water balance. The water balance, water percolation, and crop water productivities in the
MSI TPR field, during the two seasons (2008–2009) with significantly different rainfall distributions,are discussed and compared in this study. Furthermore, the soil water regimes and water balances in
the MSI TPR field are compared with the direct-seeded rice management approach in the same field(in different sub-plots) during the two consecutive seasons.
2. Materials and Methods
2.1. Field Experimental Data
2.1.1. Study Site Description
The Taihu Lake Basin of East China has a very intensive production of rice crops, regularly rotatingwith either wheat or rape. The basin area is approximately 36,900 km2 , with rice fields accounting forWater 2017, 9, 248

3 of 14

about 34.8%. This region has a subtropical monsoon climate with average annual rainfall of 1181 mm,
60% of which occurs from May through September. The annual pan evaporation from the water surface
is approximately 822 mm, and the average annual air temperature is 15–17 ◦ C. Our experimental site isin the Dangyang region (31◦ 560 N, 119◦ 430 E), upstream of the Taihu Lake (the third largest fresh waterlake in China). Different cultivations of rice are currently grown in this region, including transplanted
rice, direct-seeded rice, and seedling-thrown rice. The dominant soil type in this region is classified asa hydromorphic paddy soil, and the parent material is a lacustrine deposit. The physical properties ofthe soil at the study site are listed in Table 1.
Table 1. Physical properties and calibrated van Genuchten hydraulic parameters of the tested paddy
soil in the Taihu Lake Basin.
Depth
(cm)
0–20
20–40
40–60
60–80
80–100
100–120

Soil Particle Size Distribution (%)
Sand(>0.05 mm)
7.01
0.02
18.53
14.44
14.25
11.32

Silt
Clay
(0.002–0.05 mm) (<0.002 mm)
73.70
81.01
72.83
81.64
81.59
80.30

19.29
18.97
8.64
3.91
4.16
8.38

Bulk
Density(g·cm−3 )
1.42
1.56
1.51
1.43
1.43
1.43

θr
θS
(cm3 ·cm−3 ) (cm3 ·cm−3 )
0.125
0.073
0.075
0.046
0.081
0.052

0.510
0.441
0.489
0.500
0.521
0.512

α (cm)

nKs(cm·Day−1 )0.00920.01300.00400.00510.00210.0039

1.420
1.100
1.853
1.326
1.811
1.436

0.758
0.533
0.724
1.159
0.702
0.714

2.1.2. Experimental Design
Only the experimental design for the MSI TPR field is described here. Three 150 m2 sub-plots
were selected to plant Wuxiangjing 14 (lowland rice), a variety predominantly cultivated in this region.
The rice seeds were soaked in a 100 mg·kg−1 uniconazole solution prior to their sowing in a seedlingbed. The paddy field (with about a 5-cm water depth) was prepared by machine on 19 June 2008 and
14 June 2009, respectively, and basal fertilizer was evenly applied by hand. The mean age of the riceseedlings at transplanting was approximately 1 month. Rice seedlings were mechanically transplanted
at a rate of about four seedlings per hill two days after the basal fertilizer application (i.e., 21 June 2008
and 16 June 2009, respectively). The harvest dates were 25 October 2008 and 20 October 2009, therefore
the total growing periods for TPR during these two seasons were each 128 days. The direct-seeded rice
(Wuxiangjing 14) was directly sowed on 8 June in 2008 and 11 June in 2009, respectively, and harvested
on 1 November in 2008 (a growing season of 147 days) and 5 November in 2009 (a growing season of
149 days), respectively [27].
Water-saving irrigation implemented in the TPR experiment involved multiple irrigations at
a shallow water depth (multiple-shallow irrigation, MSI) in order to minimize losses of water andassociated nutrients. During the first 10 days after transplanting, a shallow water depth (0–5 cm)
was maintained to facilitate seedling recovery and greening. When a deeper water depth (>6 cm)
developed due to precipitation, it was partially drained to protect seedlings. After this stage, eachregular irrigation depth was generally controlled at about 2–3 cm of water, but at about 4–5 cm ofwater when fertilizer and/or pesticide were applied. In addition, the rainfall forecast was consideredin the water management. When rainfall supplied water for the crop, irrigation was reduced or eveneliminated [11]. For example, when rain was predicted for the next day, no irrigation was applied, even
if the irrigation demand was reached. When rain was predicted after two days, an irrigation depth ofabout 2 cm was applied. If no rainfall was predicted, an irrigation depth of 3 cm was applied. The soil
drying stages in the 2008 and 2009 seasons were between 23 and 27 July and between 16 and 20 July,
respectively. Additionally, all floodwater was drained from the field about 2 weeks before harvest.
Rainfall and irrigation were significantly different during the 2008 and 2009 seasons (Figure 1).
During the 2008 season, total rainfall was 49.6 cm and total irrigation was 45.0 cm (15 irrigations).
During the 2009 season, total rainfall and irrigation were 96.4 and 24.0 cm (only seven irrigations),
respectively. The irrigation water depths under MSI conditions in the TPR fields were substantiallylower than those in the direct-seeded rice (DSR) fields (72 and 46 cm during the 2008 and 2009 seasons,Water 2017, 9, 248

4 of 14

Water 2017, 9, 4

4 of 14respectively; each irrigation was about 5–6 cm). The fertilizer management in the MSI TPR field,−1 ) during the two
includingtotal application
rate andrate
application
times, wasthesame·hakg∙ha−1) during
field, theincludingthe total application
and application
times,wasthe (220
samekg(220
seasons.
The seasons.
total application
were thesame
andwere times
different
the two
The total rates
application
rates
were
theapplication
same and times
application
werecompareddifferent with
the DSR
fields with(for details
DSR
fieldsrefer[27]).
comparedthe DSRfor
fields(fordetails
for toDSR
fields refer to [27]).
0

1.5

1.0

Ep
Tp

5

Precipitation

10

Irrigation

15

0.5

20

0.0

Precipitation/Irrigation (cm)Potential Ep , and Tp (cm)

2.0

25
0

15

30

45

60
75
DAB (days)

90

105

120

(a)
Potential Ep , and Tp (cm)

5

Ep
Tp
Precipitation
Irrigation

1.5

1.0

10
15

0.5

20

Precipitation/Irrigation (cm)

0

2.0

25

0.0
0

15

30

45

60
75
DAB (days)

90

105

120

(b)
Figure 1. Potential evaporation, EP, potential transpiration, TP, precipitation and irrigation
Figure 1. Potential evaporation, EP , potential transpiration, TP , precipitation and irrigation during theduring the (a) 2008 and (b) 2009 seasons in the Taihu Lake Basin (DAB—days after basal fertilization).
(a) 2008 and (b) 2009 seasons in the Taihu Lake Basin (DAB—days after basal fertilization).
2.1.3. Measurements and Analysis

2.1.3. Measurements and Analysis

Daily climate data were obtained from an adjacent agro‐meteorological station in the Dangyang

Daily
data
were
obtainedfroman adjacentagro-meteorologicalstation in
the depth
Dangyangregion.climate
Irrigation
water
was
measuredby using
flow metersat inlets, and the flooding
water
wasIrrigation
recorded every
days
at five random
pointsin meters
each sub‐plot.
Self‐madeflux
lysimeters
weredepth
region.
watertwowasmeasuredby usingflow
at inlets,
and theflooding
water
installed atevery
a depthof days
60 cmatbelow
soil surface
measurevertical water
fluxes every
two weeks. were
was recorded
two
five therandompointstoineach sub-plot.
Self-madeflux lysimeters
Piezoelectric
tubeoftensiometers(0–100.00
weretoinstalled
at fiveobservation
points in
the field
installed
at a depth
60 cm below
the soilkPa)
surfacemeasureverticalwater fluxes
every
twoto
weeks.
measure pressure heads, which were installed at depths of 20, 40, and 60 cm below the soil surface,
Piezoelectric tube tensiometers (0–100.00 kPa) were installed at five observation points in the field torespectively. The pressure heads were recorded every two days. The groundwater table wasmeasure pressure heads, which were installed at depths of 20, 40, and 60 cm below the soil surface,observed once a week at an observation point near the experimental field, which slightly fluctuatedrespectively.
The pressure
wererecorded
every
days.
The groundwater table was observed
but remained
around a heads
depth of120 cmbelow thesoiltwosurface[27].
once a weekatanobservation
point
near
the
experimental
field,
which
butwaterremainedThree measures of water productivity (WP, kg of grain per m3 ofslightly
water): fluctuatedthe irrigation
arounda depth of(WP
120I),cm
below
theratiosoil surface
productivity
whichis theof grain [27].
yield to the amount of irrigation water; the input
3 of water):water productivity
IR), whichis the ratioof grainto perthe mamountof irrigationwater pluswaterThreemeasures of(WP
water
productivity(WP,
kg ofyieldgrain
the irrigation
rainfall; andET
waterproductivity
(WP
ET
),
which
is
the
ratio
of
grain
yield
to
crop
ET,
werewater
productivity(WPthe
),
which
is
the
ratio
of
grain
yield
to
the
amountofirrigationwater;
theinput
I
calculatedtocompare
the
water
use
efficiencies[28–30].
productivity (WPIR ), which is the ratio of grain yield to the amount of irrigation water plus rainfall;
and the ET water productivity (WPET ), which is the ratio of grain yield to crop ET, were calculated to
2.2. Hydrus‐1D Modelcompare the water use efficiencies [28–30].
The one‐dimensional Hydrus‐1D software [25] was used to simulate water movement in theexperimental
field. Detailed descriptions of the model can be found in Šimůnek et al. [25] and2.2. Hydrus-1D
Model
Li et al. [27]. The van Genuchten soil hydraulic parameters (Table 1), θr, θS, α, and n, were directly

The one-dimensional Hydrus-1D software [25] was used to simulate water movement in theexperimental field. Detailed descriptions of the model can be found in Šimůnek et al. [25] andLi et al. [27]. The van Genuchten soil hydraulic parameters (Table 1), θ r , θ S , α, and n, were directlyWater 2017, 9, 248

5 of 14

adopted from Li et al. [27]. The pore connectivity parameter (l) was assumed equal to an average valueof 0.5 [31].
The Penman–Monteith equation was used for calculating the reference crop evapotranspiration(ET0 ) from available climatic, crop, and soil parameters [32,33]. The reference evapotranspiration, ET0 ,and the crop coefficient, KC , were used to determine the potential crop evapotranspiration ETC undernormal conditions as [32,34]:
ETC = ET0 × KC ,(1)
For the crop, which only partly covered the soil surface, ETP was divided into potential
evaporation, EP , and potential transpiration, TP . This partitioning was achieved using the cropleaf area index (LAI) as given by Belmans et al. [35], which is a function of the crop development stage:
EP = ETC × e−Kgr × LAI ,(2)

TP = ETC − EP ,(3)

here Kgr is an extinction coefficient for global solar radiation; its value was taken as 0.3 for the rice
crop [29]. Values of LAI of the MSI transplanted rice at various growth stages during two seasons were
measured (Table 2), and estimated values of potential evaporation (EP ) and potential transpiration (TP )(Figure 1) were then used as input variables in the Hydrus-1D simulations.
Table 2. Leaf Area Index (LAI) of transplanted rice at various growth stages during the 2008 and 2009seasons (DAB—days after the basal fertilizer application).

Season
2008
2009

DAB
2

30

60

90

128

3.1 ± 0.5
3.0 ± 0.6

4.4 ± 1.1
4.6 ± 1.0

6.3 ± 1.3
6.4 ± 1.1

7.3 ± 1.7
7.3 ± 1.9

4.9 ± 1.1
4.8 ± 0.9

The initial conditions were defined using the measured pressure head distributions. The soil
surface was subjected to the atmosphere boundary condition (BC) with specified daily values ofprecipitation, irrigation, and evaporation. During the soil drying stage and the last 2 weeks before theharvest, the upper boundary condition was set equal to an "Atmospheric BC with Surface Runoff”.
During the rest of the season, the upper boundary condition was set equal to an “Atmospheric BC
with a Surface Layer”, with maximum water depths of 6 cm during the first 10 days after transplanting
and 10 cm during remaining growth stages, respectively. Potential values of EP , TP , irrigation, andrainfall were used to represent the atmospheric boundary condition. The bottom boundary was set toa time-variable pressure head based on observed groundwater table data.
2.3. Model Evaluation
Simulated values of the pressure heads and percolation water fluxes were compared with theobserved data from the experimental paddy field during the 2008 and 2009 seasons. The correspondence
between simulated and observed data was evaluated using the coefficient of determination (R2 ) andthe root mean square error (RMSE), calculated as:
R2 = 1 −

SSerr
,
SStot

(4)
1

2
1 n
RMSE = [ ∑ (Si − Mi )2 ] ,
n 1

(5)

Water 2017, 9, 248

6 of 14

where
SSerr is9,thesum of squared differences between simulated and observed values, SS
tot14is theWater 2017,46 of
sum of squared differences between observed values and the mean of observed values, Si and Mi arewhereandSSerrmeasured
is the sumvalues,of squared
differences
betweenandobserved values.
values, SS
simulated
respectively,andn is thesimulated
number ofcompared
AntotRis2 thevalue ofsum of squared
differences
betweenobserved
valuesand themean of observed
1.0 indicatesa “perfect”
fit to theobserved
data,
whereasan optimalvalue of values,
RMSE Sisi and
0. Mi aresimulated and measured values, respectively, and n is the number of compared values. An R2 valueof 1.0 indicates a “perfect” fit to the observed data, whereas an optimal value of RMSE is 0.
3. Results
3. Results
3.1. Model
Assessment

Simulatedpressure heads at depths of 20, 40, and 60 cm matched well with observed data during
3.1.
Model Assessment
the 2008 (n = 164, R2 = 0.97, RMSE = 4.25 cm) and 2009 (n = 154, R2 = 0.97, RMSE = 3.88 cm) seasons,
Simulated pressure heads at depths of 20, 40, and 60 cm matched well with observed data
and responded
well to the water input events (i.e., rainfall and irrigation) (Figure 2). In contrast
during the 2008 (n = 164, R2 = 0.97, RMSE = 4.25 cm) and 2009 (n = 154, R2 = 0.97, RMSE = 3.88 cm)
to theseasons,
2008 season(Figure 2a),
to waterfrequent
continuous
rainfall,most pressure
and responded
well dueto theinputandevents(i.e., rainfall
and irrigation)(Figureheads
2). In at 20cm remained
positiveduring
the
first
half
of
the
2009
season(Figure2b).
Duringthelate2008 andcontrast to the 2008 season (Figure 2a), due to frequent and continuous rainfall, most pressure heads
2009 atseasons,
multiple-shallow
irrigations
producedmorevariations
betweenwettinganddrying20 cm remained positive during the first half of the 2009 season (Figure 2b). During the late 2008
and 2009
seasons,
multiple‐shallow
producedmore values
variations
betweenwetting
conditionsin thesoil. Pressure
heads atirrigations
20 cm reachedminimumof −130.0 cmand −and
112.0 cmdryingconditions
the soil.
Pressureheads
at seasons,
20 cm reachedminimum
values headsof −130.0
cmcm
andduringthe soildrying instagesof the2008 and2009
respectively.
Pressure
at 60
during−112.0cm
duringthesoildryingstages
of
the
2008
and
2009
seasons,
respectively.
Pressure
heads
atthe two seasons were mostly between 0 and −63.0 cm, and their peaks lagged about 1–2 days behindthose60atcm
20during
cm. the two seasons were mostly between 0 and −63.0 cm, and their peaks lagged about 1–2
days behind those at 20 cm.
Simulated total percolation flux at 60 cm before the soil drying stage in the 2008 season was
Simulated total percolation flux at 60 cm before the soil drying stage in the 2008 season was
14.6 cm,
agreedwellwellwithwiththe theobserved
value
of of
15.2
cm.
For
14.6 which
cm, whichagreedobserved
value
15.2
cm.
Forthetheentire
entiregrowing
growingseason
season ofof 2008,
simulated
total
percolation
at
60
cm
was
29.7
cm,
and
the
observed
value
was
31.8
cm.
By
comparison,
2008, simulated total percolation at 60 cm was 29.7 cm, and the observed value was 31.8 cm. By
duringthe entireduring
2009 season,
simulatedandobserved
water fluxes
60 cm
comparison,
the entirethe2009season, thesimulatedandcumulative
observed cumulative
wateratfluxes
at were44.4 cm
and46.144.4
cm,cm
respectively.
correspondence
between observed
and simulated
percolation
60 cm
were
and 46.1 cm, The
respectively.
The correspondence
between observed
and simulated
percolation
boththroughout
early on andthe
throughout
growing
periods
fluxesboth earlyfluxes
on andgrowingthe
periods
wasgood.was good.
0

15

30

45

DAB (days)
60
75

90

105

120

Pressure head (cm)

20
-100

15
20cm
40cm
60cm

-200

Precipitation
Irrigation

10
5

-300

Precipitation/Irrigation (cm)

25
0

0

(a)
0

15

30

DAB (days)
45
60
75

90

105

120

Pressure head (cm)

20
-100

15

20cm
40cm
60cm

Precipitation
Irrigation

-200

10
5

-300

Precipitation/Irrigation (cm)

25
0

0

(b)
Figure 2. Simulated (lines) and observed (points) pressure heads at 20, 40, and 60 cm depths, andFigure 2. Simulated (lines) and observed (points) pressure heads at 20, 40, and 60 cm depths, andprecipitation and irrigation water depths (vertical lines) during the (a) 2008 and (b) 2009 seasons.
precipitation and irrigation water depths (vertical lines) during the (a) 2008 and (b) 2009 seasons.
Positive pressure heads were not observed by tensiometers.
Positive pressure heads were not observed by tensiometers.

Water 2017, 9, 248

7 of 14

Water 2017,Water9, 4
3.2. Flooding
Depths and Surface Runoff

7 of 14

Rainfall,irrigation,
and andrunoffcausedthe surface water to suddenly rise and fall in paddy fields.
3.2.
Flooding
Water Depths
Surface
RunoffDaily field water levels showed more frequent fluctuations in the 2008 season than in the 2009 season
Rainfall, irrigation, and runoff caused the surface water to suddenly rise and fall in paddy(Figure3). Changes in the surface water depth between observed and simulated values were closely
fields. Daily field water levels showed more frequent fluctuations in the 2008 season than in the 2009
matchedduringthe3).2008(n = 34,
R2 surface= 0.96, RMSE
= 0.9 betweencm) andobserved
2009 (n =and38, simulated
R2 = 0.95, values
RMSEwere= 1.1 cm)
season(FigureChangesin thewater depth22seasons.
The
maximum
standing
water
depth
(8.1
cm)
duringthe2008
seasonappearedon
30= DABclosely matched during the 2008 (n = 34, R = 0.96, RMSE = 0.9 cm) and 2009 (n = 38, R = 0.95, RMSE
(days1.1
afterbasal The
fertilizer
application),whendeptha heavy(10.1thecm)
occurred.
During thecm)theseasons.
maximum
standing water(8.1rainfallcm) during
2008
season appearedon 200830 DAB(days
afterdepth
the basal
when a heavy
rainfall depth(10.1 cm)
occurred.
season,surfacewater
wasfertilizer
alwaysapplication),
below the maximum
controlled
becausethe During
water input
the 2008 determinedseason, surface
depth
was always(Figure
below thedepth because
theheavy
was mainly
bywatershallow
irrigations
3a).maximum
During controlled
the 2009 season,
several
water
input
was
mainlydeterminedbyshallow
irrigations(Figure3a).
Duringthe2009season,rainfall events resulted in the water depths exceeding or approaching 10 cm (Figure 3b), which wasseveral heavy rainfall events resulted in the water depths exceeding or approaching 10 cm (Figure
specified as a maximum water depth in the simulation.
3b), which was specified as a maximum water depth in the simulation.
During the 2008 season, no surface runoff was observed in the field. Due to a few heavy rainfall
During the 2008 season, no surface runoff was observed in the field. Due to a few heavy rainfall
eventsduringthe 2009
season,
some
water
was
lostlost
fromthethefieldsasassurface
eventsduringthe 2009
season,
some
water
was
from
fieldssurfacerunoff
runoffduring
during two
two mainsurfacerunoffevents
on
43
and
45
DAB.
Simulatedandobserved
total
surfacerunoffsduringthe 2009
main surface runoff events on 43 and 45 DAB. Simulated and observed total surface runoffs duringseason7.7 andwere
6.5 cm,respectively.
thewere2009 season
7.7 and6.5 cm, respectively.
0
5

12Sim. Obs.
water depth
precipitation
irrigation

9
Soil drying
stage

6

10
15
20

3

Precipitation/Irrigation (cm)

Flooding Water Depth (cm)

15

25

0
0

15

30

45

60
75
DAB (days)

90

105 120

(a)
0
5

12
Sim. Obs.
Soil drying
stage

9

water depth
precipitation
irrigation

6

10
15
20

3

Precipitation/Irrigation (cm)

Flooding Water Depth (cm)

15

25

0
0

15

30

45

60
75
DAB (days)

90

105 120(b)
Figure 3. Observed (points) and simulated (lines) flooding water depths during the 2008 (a) and 2009

Figure 3. Observed (points) and simulated (lines) flooding water depths during the 2008 (a) and 2009(b) seasons.
(b) seasons.

3.3. EvapoTranspiration
3.3. EvapoTranspiration

Reflecting general crop growth, simulated root water uptake during the 2008 and 2009 seasons
gradually
after growth,transplanting
and reachedmaximum
between
30 andand 2009
60 DAB
Reflectingincreased
general crop
simulatedroot water
uptakevalues
duringthe 2008
seasons−1 on around(Figure4).
Themaximum
daily
rate
of
root
water
uptakewasapproximately
0.7
cm∙daygradually increased after transplanting and reached maximum values between 30 and 60 DAB−1 on around45 4).
DAB.
the later
cropwater
growth,dailywasroot
water uptake 0.7
gradually(FigureTheDuring
maximum
dailystages
rate ofofroot
uptakeapproximately
cm·daydeclined.
Cumulative root water uptake slowly increased during the initial 30 days, then quickly increased
45 DAB. During the later stages of crop growth, daily root water uptake gradually declined. Cumulative
and ultimately reached 49.8 and 51.6 cm over the entire growing seasons of 2008 and 2009,
root water uptake slowly increased during the initial 30 days, then quickly increased and ultimately
respectively. Simulated cumulative evaporations in the MSI TPR field were 14.0 and 14.5 cm during
reached49.8 and 51.6 cm over the entire growing seasons of 2008 and 2009, respectively. Simulated
the 2008 and 2009 seasons, respectively. The total ET amounts in MSI TPR field throughout the 2008

cumulative evaporations in the MSI TPR field were 14.0 and 14.5 cm during the 2008 and 2009 seasons,Water 2017, 9, 248

8 of 14

Water 2017, 9, 4

8 of 14respectively.
The total
ET63.8amounts
in MSIofTPR
field throughout
the(an2008
andof2009seasons−1) and 66.1 cm−1), wereand 2009 seasons
were
cm (an average
0.50 cm∙day
average0.52 cm∙day−1 ) and 66.1 cm (an average of 0.52 cm·day−1 ), respectively.
63.8 cm(anaverage
of
0.50
cm
·
day
respectively.
60

2008
2009

Cum. Water Uptake (cm)

Water Uptake Rate (cm/day)

0.8
Water 2017, 9, 4

8 of 140.6cm (an average of 0.50 cm∙day−1) and 66.1 cm (an45 average of 0.52 cm∙day−1),
and 2009 seasons were 63.8
respectively.
0.4

30
60

2008
2009

0.2

15

0.6

45

0.0

0.4

0

15

30

Cum. Water Uptake (cm)

Water Uptake Rate (cm/day)

0.8

45

60
75
DAB (days)

90

0
120 30

105

0.2

15

Figure 4. Simulated actual daily water uptake rate and cumulative root water uptake during the 2008
Figure4. Simulated actual daily water uptake rate and cumulative root water uptake during the 2008
and 2009 seasons.
and 2009 seasons.
0.0
03.4. Soil Water Content Changes

0

15

30

45

3.4. Soil Water Content Changes

60
75
DAB (days)

90

105

120

Simulatedsoil wateractual
contents(Figureroot5) at
the uptake
soil surface
in the root
Figure 4. Simulated
daily andwaterwater
uptakesaturations
rate and cumulativewater
duringandthe 2008

0.8

1.0

1.0

0.6

0.8

0.8

0.4

Effective saturation

0.6

0.4
WC at surface
Se at surface
WC at rootzone
Se atatrootzone
W
surface

0.6

0.2
Soil drying stage

0.4

0.0
0.20

15

0.2
0.4

C
0.0
at surface
60 75 Se90
105 120 0.2
Soil drying stage
W at rootzone
DAB (days) C

30

45

Se at rootzone

0.0
0

0.6

15

30

45

(a) 7560

90

DAB (days)(a)Figure 5. Cont.

105 120

0.0

Effective saturation

0.8

W ater content (cm 3 cm -3)

W ater content (cm 3 cm -3)

andsimilar
2009
Simulatedsoilseasons.
water
contents
water saturations
5) atthetosoil
surfacein the rootzone had
distributions
asand
the pressure
heads and (Figure
responded
well
rainfallandandirrigation
Surfacesoil water ascontents
variedheads
quickly
0.318–0.505
cm3∙cm−3and(average
0.479
zone events.
had similar
distributions
the pressureandbetween
responded
well to rainfall
irrigation
events.
3.4.
Water0.325–0.505
Content Changes
3∙cmSoil−3) and3∙cm−3 (average 0.484 cm3∙cm−3) during
3
−
3
3
cm
cm
the
2008
and
2009
seasons,
Surface soil water contents varied quickly between 0.318–0.505 cm ·cm (average 0.479 cm ·cm−3 )3 ·soil
3 (average
3 ·saturations−3 ) duringrespectively,
compared
to contents
smaller0.484
andwatermore
gradualchanges
deeperdepths.
Asin thedepth
Simulatedwater
and(Figure5) atat thesoil surface
andtherespectively,
root
and 0.325–0.505
cm
cm−
cm
cm
the
2008
and
2009
seasons,increased,variations
in soil waterascontents
gradually
but wereapparently
influenced
zone hadsimilar distributions
the pressure
headsdecreased,
and responded
well stillto rainfall
and irrigationcompared to smaller and more gradual changes at deeper depths. As the depth
increased, variations
3∙cm−3 (average 0.479
Surfacewater events
contents
varied1).
quickly
betweencmduring
by events.
the rainfall
and soil
irrigation(FigureContrary
to the0.318–0.505
2008 season,
most days of thein soil water
gradually
decreased,
but0.484
werecmstill
apparently
influenced
by therainfall and3∙cmcontents−3) and 0.325–0.505−3 (average
3∙cm
cmseason,
cm3∙cmat) during
the 2008
and 2009
seasons,2009
the soil water content
the soil surface
andin−3theroot zone
remained
mostlyclose toirrigation
events(Figure1).
Contrary
to
the
2008
season,during
most
days
of
the
2009
season, therespectively,
comparedsmaller andevents.
more Several
gradual smallchanges
at deeper
As only
the depth
saturation
due tofrequent toprecipitation
rainfalls(e.g., depths.
<1 cm) had
a slight
soil watercontent
atcontents
the soilandin thezone
remained
mostlyclose
to surface
saturation
due toincreased,variations
in soilwater
contents
gradually
decreased,
but were
still
influenced
effecton waterinsurface
the
root
zone,
butroota moresubstantial
effectonapparently
the soilwater
byprecipitation
theSimulation
rainfall andevents.
irrigation
events (Figure
1).
Contrary
to theseason,duringdays
thefrequent
Severalsmall<12008cm)
hadonly
a mostslighteffecton watercontent.
results
indicatedthat
therainfalls
soil
water(e.g.,storage
in
the
upper
60 cm
of thesoilofprofile
2009
season,soilseason
water
at theandthesoilrootthezone
remained
close
to by
contents
in theroot
zone,
but acontent
more substantial
oninthesurfacewater mostly
content.
Simulation
throughout
thethe2008
decreasedby soil
3.9 surface
cm,effect
whereasduring2009
season,it decreased
saturation due to frequent precipitation events. Several small rainfalls (e.g., <1 cm) had only a slightabout
4.2 cm; theirdifferenceswerein4.1theandupper4.5 cm,60
respectively.
results
indicatedthat observed
the soil water
storagecm of the soil profile throughout theeffect on water contents in the root zone, but a more substantial effect on the soil surface water
Duringthe 2008by
and2009
seasons,theeffective
saturation(Se) [25]values at thesurfaceranged2008 season
decreased
3.9
cm,
whereasduringthe2009season,decreased
bythe
about
4.2
cm; their
content. Simulation results indicated that the soil water storage in theitupper
60 cm ofsoil profile
between
0.500
and
1.00
(an
averageof
0.929)
andbetween
0.517
and
1.00
(an
averageof
0.943),
observeddifferences
4.1 and
4.5 cm,by
respectively.
throughout
the were2008 season
decreased
3.9 cm, whereas during the 2009 season, it decreased byrespectively (Figure 5). In the root zone, these values ranged during the 2008 and 2009 seasons
about the4.2 cm;theirobserveddifferenceswere
4.1 andsaturation
4.5 cm, respectively.
During2008
and2009 seasons,theeffective(Se ) [25] values at the surface ranged
betweenDuring0.621 theand2008
1.00and(an2009
averageof the0.943)
and between
0.642
andvalues
1.00 at(an averageof0.953),
seasons,
effectivee) [25] andsurfacerangedbetween 0.500
and 1.00(an averageof 0.929)
and saturation
between (S
0.517
1.00the(anaverageof 0.943),
respectively.
However,
the
soil
at
both
40
and
60
cm
depthsremained
unsaturated
throughout
both
between 0.500 and 1.00 (an average of 0.929) and between 0.517 and 1.00 (an average of 0.943),
respectively(Figure5).
In the2),root
zone,
these
valuessoil
rangedduring2008
andsaturated.
2009 seasons between
growingseasons(Figurewhen
the surface
and
the
soil
atthe
20the
cm2008
wererespectively(Figure5). Ineven
the rootzone,
these values
rangedduringand 2009 seasons
0.621 and 1.00 (an average of 0.943) and between 0.642 and 1.00 (an average of 0.953), respectively.
between 0.621 and 1.00 (an average of 0.943) and between 0.642 and 1.00 (an average of 0.953),
However,the soil atHowever,both 40 and
60 cm
depthsremained
unsaturated
both growing
1.0
respectively.
the1.0soil
at both
40 and60 cm depths
remained throughout
unsaturated
throughout
bothseasons(Figure growing2), evenseasons
when thesurfacesoilwhenandthethesurface
soil atsoil
20andcm thewere(Figure2), evensoilsaturated.
at 20 cm were saturated.

Water 2017, 9, 248

9 of 14

Water 2017, 9, 4

9 of 14

Water 2017, 9, 4

9 of 14

1.0

0.8

0.8

Effective saturation

1.0

W ater content (cm cm -3)

W ater content (cm 3 cm3-3)

1.0

0.8

0.8

0.6

0.6

0.6

0.6

0.4

0.4
WC at surface
Se at surface
WCC atatrootzone
surfaceWatrootzone
surfaceSSee at

0.4

0.2
Soil drying stage

0.2

0.0
0

Soil drying stage

15

30

45

15

30

45

0.0
0

WC at rootzone
75 90 105 120
Se at rootzone

0.4

0.2

0.2

0.0

60
DAB (days)

60 75
DAB(b)(days)

90

Effective saturation

1.0

0.0

105 120

Figure 5. Simulated water contents (WC) and effective(Se) at the soil surface and in the root(b) saturation
Figure 5. Simulated water contents (W C ) and effective
saturation (Se ) at the soil surface and in the rootzone during the 2008 (a) and 2009 (b) seasons.
zone Figureduring5.the2008 (a)waterand contents
2009 (b)(Wseasons.
SimulatedC) and effective saturation (Se) at the soil surface and in the rootzone
duringthe 2008 (a) and 2009 (b) seasons.
3.5.
Water
Percolation

3.5. Water Percolation
Downward water percolation (Figure 6) closely corresponded with precipitation and irrigation
3.5. Water Percolation

events (Figure 1). Intensive rainfalls during the early 2009 season (before 65 DAB) resulted in

Downward water percolation (Figure 6) closely correspondedwith precipitation and irrigation
relatively
continuous
high percolation
rates
0.51 cm∙day−1) at
a depthof 60 cm.and
Duringthe
Downward
water percolation(Figure6)(averageclosely corresponded
withprecipitation
irrigation
events (Figure
1).
Intensive
rainfalls
during
the
early
2009
season(before65 DAB)
resultedrelatively
entire(Figure
2009 season,
the average
percolation
ratethewasearly
about20090.34 season
cm∙day−1(before(varying
0.01inandevents1). Intensive
rainfalls
during65between
DAB) resultedin−1 ) at a depth of 60 cm. During thecontinuous
highpercolation
rates(average
0.51
cm
·
day
−1
−1) at a depth
0.76 cm∙day), whichwassubstantiallythanthecm∙daycorresponding
valueofofcm∙day−1theentire
relatively
continuous
highpercolation
rateshigher(average
0.51
60 0.24cm. During−1) during
2009 entire
season,averagepercolation
rate was
about
0.34
cm
·percolationday−−11(varying(varying
0.01(0.01–0.69cm∙daythepercolation
2008 season.
Thewascumulative
water
fluxesbetween
atbetween
60 cm 0.01
in the2009theseason,theaverage
rate
about
0.34
cm∙dayand and−1
TPR),field
were was29.7
and44.4 cm during
the 2008
andthe2009corresponding
seasons, respectively,
which−1which0.76 cm·day
substantiallyhigherthanthecorresponding
value
0.24
cm·−1day−1
0.76MSIcm∙day), whichwassubstantiallyhigher
than
value
of of
0.24matchedcm∙day
well
with
the
valuesof 31.5
and 46.1
cm.
−1observed(0.01–0.69cm∙day) during
the20082008
season.
The
cumulativewater
percolation
fluxes
at 60atcm
thein the(0.01–0.69cm·day) −1during
theseason.
The
cumulativewater
percolation
fluxes60incm
MSI
TPR
field
were
29.7
and
44.4
cm
during
the
2008
and
2009
seasons,
respectively,
which
matchedMSI TPR field were 29.7 and 44.4 cm during the2008 and 2009 seasons, respectively, which matched
DAB (days)
well withthe observed
values
and
46.1
cm.
15
3046.145 cm.
60
75
90 105 120
0 31.5well withthe observed
values
of of
31.5
and
30

90

105

120 -30
0
-60

-3.0
-4.5

-3.0

0 cm

Cum. flux at 0 cm

-90

60 cm

Cum. flux at 60 cm
Observed Cum. flux at 60 cm-60

Soil drying
stage

-6.0

-4.5

0 cm
60 cm

-6.0 0-30

Soil drying
stage

-1.5

15

30

Water Flux (cm/day)

-90

Cum.
flux at 60 cm
DAB (days)
at 60
45 Observed
60
75Cum.
90 flux
105
120cm
0

15

30

45

DAB (days)
60
75

-30

90

105

120
0

0.0

Water Flux (cm/day)

-120

(a)

0.0
-1.50

-120

Cum.
(a)flux at 0 cm

-60

-3.0
Soil drying
stage

-1.5

-4.5

0 cm
60 cm

-3.0
-6.0
-4.5

-30
Cum. flux at 0 cm
Cum. flux at 60 cm
Observed Cum. flux at 60 cm

Soil drying
stage

0 cm

Cum. Water Flux (cm)

Water Flux (cm/day)

0.0

Cum. Water Flux (cm)

15

-1.5

(b)

Cum. flux at 0 cm

-90

-60
-120

-90

Cum. Water Flux (cm)

Water Flux (cm/day)0

DAB (days)
45
60
75

Cum. Water Flux (cm)

0

0.0

60 cm
Figure 6. Observed (points) and simulated(lines)water
fluxesCum. flux
at 60
cm at the soil surface and at a depth of
60 cm during the 2008 (a)
and
2009
(b)
seasons.
Observed
Cum.
flux
at 60 cm -120
-6.0

(b)
Figure 6. Observed (points) and simulated (lines) water fluxes at the soil surface and at a depth of

Figure 6. Observed (points) and simulated (lines) water fluxes at the soil surface and at a depth of
60 cm during the 2008 (a) and 2009 (b) seasons.
60 cm during the 2008 (a) and 2009 (b) seasons.

Water 2017, 9, 248

10 of 14

4. Discussion
Generally, rice is a typical water consuming crop. Water contents in the soil root zone are critical
for the growth and yield of rice. In this study, the average grain yields of TPR under the MSI conditionsin the 2008 and 2009 seasons were 9380 and 9250 kg·ha−1 , respectively, approaching the averagevalue of about 9500 kg·ha−1 for TPR in this region [36,37]. They were markedly higher than thosefor DSR in the same field (8980 and 8530 kg·ha−1 ) [27]. The DSR yield during the 2009 season was
influenced by two typhoons, which resulted in significant DSR lodging. Contrary to DSR, TPR could
better persist during the bad weather due to relatively deeper root systems and stronger straw [37,38].
Maqsood et al. [39] reported for Faisalabad (Pakistan) that transplanted rice had 19.18% higher yieldthan DSR. In the MSI TPR field, pressure heads in the root zone were higher than −100 cm during
most days of the two seasons, which also agrees well with the water stress thresholds for a high andstable rice yield [20].
The total water inputs (TWIs) in the MSI TPR field during the 2008 and 2009 seasons were
94.6 and 120.4 cm, respectively (Table 3). Irrigation water in the MSI TPR field was substantiallylower compared to those in the DSR fields (72.0 and 46.0 cm during the 2008 and 2009 seasons,respectively) [27]. Liang et al. [12] reported that a similar irrigation method (“thin-shallow-wet-dry”)
used in South China, at the middle nitrogen level, led to a decrease in the total water consumption by
21.7%–23.5% and an increase in the rice water use efficiency by 17.8%–27.2%.
Surface runoffs (Table 3) from the MSI TPR field are substantially lower than those (5.8 and24.4 cm during the 2008 and 2009 seasons, respectively) from the DSR field [27], where most surface
runoff was lost during the germination period (the first 2 weeks). This indicates that different water
managements between multiple-shallow irrigated TPR and regular irrigated DSR fields led to different
surface runoff volumes. Ye et al. [15] reported for this region that in 2010, surface runoff was 4.2 cm
for continuous flood irrigation (CF) and 1.8 cm for AWD irrigation; surface runoff in 2011 was 8.0 cm
for CF and 6.4 cm for AWD irrigation. In another TPR field experiment in this region, Zhao et al. [40]reported that by controlling most flooding water depths below 3–5 cm, surface runoff reached 47.0,
15.4, and 88.2 cm during the 2007, 2008, and 2009 seasons, respectively.
Table 3. Simulated (using Hydrus-1D) components of water balance (cm) in the upper 60 cm of the soil
profile, and water productivities (WP) (kg·m−3 ) for the transplanted rice crop in the Taihu Lake Basin.

Season2008-TPR
2009-TPR
2008-DSR
2009-DSR

Input

OutputWater Productivity

R

I

SR

ET

SS

P

49.6
96.4
54.3
97.4

45.0
24.0
72.0
46.0

0
−7.7
−5.8
−24.4

−63.8
−66.1
−68.9
−64.0

−3.9
−4.2
−1.2
−2.3

−29.7
−44.4
−53.9
−50.1

δ

−2.8
−2.0
−3.5
2.7

WPI

WPIR

WPET

2.08
3.85
1.25
1.85

0.99
0.77
0.71
0.59

1.47
1.40
1.30
1.33

Note: R—rainfall, I—irrigation, SR—surface runoff, ET—evapotranspiration, SS—soil storage, P—percolation,
δ—total water balance error, WPI —the ratio of grain yield to the amount of irrigation water, WPIR —the ratio of
grain yield to the amount of irrigation water plus rainfall, WPET —the ratio of grain yield to crop ET.

Estimated evapotranspiration volumes in the MSI TPR field (Figure 4 and Table 3) are slightly
lower than those (17.4 and 15.8 cm during the 2008 and 2009 seasons, respectively) in the DSR fields [27]due to relatively shorter growing periods. Studies have demonstrated that excessive irrigation withlarge depths of standing water in paddy fields would lead to high water losses by evaporation [13,41].
In this study, simulated ETs during the 2008 and 2009 seasons accounted for 67.4% and 54.9% ofcorresponding volumes of TWIs, respectively. Compared to the 2008 season, a slight increase in
ET during the 2009 season did not produce a corresponding increase in the rice yield. Jia et al. [7]reported that average ET in the Taihu Lake Basin during the 2010 and 2011 TPR seasons was 44.1 cm(an average of 0.40 cm·day−1 ) under controlled flooding water depth conditions, and it declined
by about 22.6% compared to traditional continuous flooding irrigation (average 0.54 cm·day−1 ).
Jiang et al. [8] reported that, in an experimental field in Shanghai (China) during the 2012 season, ET

Water 2017, 9, 248

11 of 14from TPR fields with intermittent and moistening irrigation was 70.8 cm (an average of 0.52 cm·day−1 )and 73.9 cm (an average of 0.54 cm·day−1 ), respectively, lower by 5.9% and 1.8%, respectively, thanfrom traditionally flooded TPR fields.
Excessive water inputs with large depths of surface water lead to excessively highpercolation [10,14]. Lian et al. [42] reported that water percolation rates in this region were between
0.49 and 0.56 cm·day−1 under the traditional flooding irrigation method. In this study, waterpercolation at a depth of 60 cm accounted for approximately 31.4% and 36.9% of TWIs, respectively;
and the average water percolation rates from the MSI TPR field were 0.24 cm·day−1 during the 2008
season and 0.34 cm·day−1 during the 2009 season. In the DSR fields, the average water percolation
rates were 0.37 cm·day−1 and 0.34 cm·day−1 during the 2008 and 2009 seasons, respectively [27].
These differences from the same paddy field indicated that the water management significantly
affected water percolation by altering the duration of surface flooding and corresponding pressure
head gradients and consequent water fluxes. Jiang et al. [8] reported that, compared to traditional flood
irrigation, the intermittent and moistening irrigation techniques in the Shanghai (China) experimental
TPR fields during the 2012 season resulted in a significant reduction of water percolation by 2.0%
and 17.3%, respectively. Similar to the DSR field [27], downward percolation (Table 3) was the main
component of water losses in the MSI TPR field. However, downward percolation and surface runoff
in the MSI TPR field were significantly reduced as compared to the DSR field [27].
Usually, the water productivity can be used to evaluate the water use efficiency in a paddy fieldand compared with other conditions. The irrigation water productivity (WPI ) and water input waterproductivity (WPIR ) for TPR under MSI conditions were 2.08 and 0.99 kg·m−3 during the 2008 season
and 3.85 and 0.77 kg·m−3 during the 2009 season, respectively (Table 3). These were higher thanthe corresponding values for the DSR [27]. Both rice yields and water use efficiencies were thus
higher in the MSI TPR field than in the DSR field. In the same region, Ye et al. [15] reported the WPIvalues for AWD and continuously flood irrigated TPR fields during the 2010 and 2011 seasons to be
1.56–3.45 kg·m−3 and 1.05–2.02 kg·m−3 under different fertilizer treatments, respectively, and the WPIR
values to be 0.48–1.06 kg·m−3 and 0.41–0.82 kg·m−3 , respectively. Bouman et al. [10] reported that the
average WPIR for TPR under water-saving irrigation conditions was 0.8 kg·m−3 (0.6–0.97 kg·m−3 ) innorthern China during the 2002 season. However, Cabangon et al. [1] reported for Malaysia that TPR
had similar TWI with DSR (dry-seeded), but had significantly more irrigation water and lower WPI
values than DSR (dry-seeded). This was attributed to the ability of DSR to capture more early rainfall
after crop establishment.
Using ET as the water use term enables a better comparison between sites, cultivars, seasons,and management options [43]. The WPET values in our simulations (Table 3) fall in the rangeof globally measured values for rice (0.6–1.6 kg·m−3 ) [6] and are higher than the average value(1.09 kg·m−3 ) [44]. Singh et al. [43] reported an average WPET of 0.94 kg·m−3 for TPR in the Sirsa
district (India). Belder et al. [6] reported that the WPET in a TPR field experiment (Hubei, China) undersubmerged-nonsubmerged conditions was 4%–20% higher than that under continuous submerged
conditions with the same fertilizer management. Due to relatively higher yields and similar ETs, theWET values in the MSI TPR field were slightly higher than those (1.30 kg·m−3 in 2008 and 1.33 kg·m−3
in 2009) in the DSR field [27]. Cabangon et al. [1] also reported for Malaysia that, due to relative higher
yield and lower ET, the TPR had higher WET values compared to DSR.
In general, in dry or semi-dry areas where water is the most limiting factor, maximizing WP may
be economically more profitable for the farmer than maximizing yields [11,45]. While in the Taihu
Lake basin, water is not a limiting factor for the agricultural production, a worsening quality of surface
waters and groundwater, due to increasing nitrogen and phosphorus surface runoff and leaching fromagricultural lands [21,26], has become a serious problem. Increasing the WP by adopting the MSI
method can reduce water and nutrient losses from TPR fields, compared to DSR fields. However,
the effects of the MSI method in the TPR fields on reducing nutrient losses needs to be studied andcompared with the DSR cultivation method.

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5. Conclusions
Soil water regimes and water balance were monitored in an MSI (multiple-shallow irrigation)
TPR field in the Taihu Lake Basin of East China, and then evaluated using the Hydrus-1Dmodel. The Hydrus-1D can simulate well soil water flow in the TPR field under MSI conditions.
Evapotranspiration under the MSI conditions was not affected by water management, and percolation
substantially increased with increasing water inputs and flooding days. Percolation was the main pathof water losses, independent of whether the water input was mainly by irrigation or precipitation.
The MSI cultivation of TPR substantially reduced water losses by percolation and surface runoff,and correspondingly increased water use productivities, while sustaining relatively high rice yields
compared to the regular cultivation of DSR in the same field. Water productivities showed that the MSI
TPR cultivation, which considers both soil conditions and rainfall forecast when scheduling irrigation,
efficiently used rainfall water and reduced water losses from paddy fields. Water savings can berealized by adopting MSI without reducing rice yield. Additionally, it needs to be emphasized that
because most water savings resulted from reduced percolation rates, adoption of this approach will
reduce groundwater recharge and associated nutrient percolation.
Acknowledgments: The work described in this publication was supported by the National Natural Science
Foundation of China (Nos: 51579074 and 51079048), the National Science and Technology Ministry of China(No. 2015BAB07B02), the Fundamental Research Funds for the Central Universities (No. 2009B16914), the Priority
Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and the China ScholarshipCouncil. The authors would like to thank two anonymous reviewers for providing thoughtful comments that
helped us to improve the manuscript significantly and the editors for their careful and responsible work.
Author Contributions: Yong Li conceived and designed the experiments; Shuang Wang, Jiahui Yuan, andWeiwei Zhang performed the experiments; Shuang Wang, Jiahui Yuan, and Weiwei Zhang analyzed the data;
Yong Li and Jirka Šimůnek contributed reagents/materials/analysis tools; Yong Li and Jirka Šimůnek wrote
the paper.
Conflicts of Interest: The authors declare no conflict of interest.

Summary of Abbreviations
TPR
DSR
MSI
AWD
CF
TWI
WP
WPI
WPIR
WPET
ET
EP
TP
ETP
WC
Se
DAB
LAI

Transplanted rice
Direct-seeded rice
Multiple-shallow irrigation
Alternate wetting and drying
Continuous flood
Total water input
Water productivity
Irrigation water productivity
Input water productivity
Evapotranspiration water productivity
Evapotranspiration
Potential evaporation
Potential transpiration
Potential evapotranspiration
Water content
Effective saturation
Days after basal fertilization
Leaf area index

References
1.
2.

Cabangon, R.J.; Tuong, T.P.; Abdullah, N.B. Comparing water input and water productivity of transplantedand direct-seeded rice production systems. Agric. Water Manag. 2002, 57, 11–31. [CrossRef]
Chen, S.; Cai, S.G.; Chen, X.; Zhang, G.P. Genotypic differences in growth and physiological responses totransplanting and direct seeding cultivation in rice. Rice Sci. 2009, 16, 143–150. [CrossRef]

Water 2017, 9, 248

3.
4.
5.
6.
7.
8.
9.
10.

11.
12.
13.

14.
15.

16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.

13 of 14

Farooq, M.; Siddique, K.H.M.; Rehman, H.; Aziz, T.; Lee, D.; Wahid, A. Rice direct seeding: Experiences,challenges and opportunities. Soil Till. Res. 2011, 111, 87–98. [CrossRef]
Liu, Y.; Yu, X.; He, Y. The research progress of water-saving irrigation in China since 2000. Adv. Mater. Res.
2014, 955–959, 3206–3210. [CrossRef]
Tan, X.; Shao, D.; Gu, W.; Liu, H. Field analysis of water and nitrogen fate in lowland paddy fields under
different water managements using HYDRUS-1D. Agric. Water Manag. 2015, 150, 67–80. [CrossRef]
Belder, P.; Spiertz, J.H.J.; Bouman, B.A.M.; Lu, G.; Tuong, T.P. Nitrogen economy and water productivity oflowland rice under water-saving irrigation. Field Crops Res. 2005, 93, 169–185. [CrossRef]
Jia, G.; Yan, Z.; Wang, Y.; Zhu, F. Field test and research on agricultural water-saving irrigation and pollution
reduction in Taihu Lake Basin. Yangtze River 2013, 44, 81–84.
Jiang, P.; Yuan, Y.; Zhu, R.; Dai, Y.; Shen, Y.; Zhao, Z.; Yue, Y.; Zhao, Q.; Cao, L. Study on the nitrogen loss
from paddy fields on different water management. Chin. J. Agro-Environ. Sci. 2013, 32, 1592–1596.
Waraich, E.A.; Ahmad, R.; Ashraf, M.Y.; Saifullah; Ahmad, M. Improving agricultural water use efficiency
by nutrient management in crop plants. Acta Agric. Scand. Sect. B Soil Plant Sci. 2011, 61, 291–304. [CrossRef]
Bouman, B.A.M.; Feng, L.; Tuong, T.P.; Lu, G.; Wang, H.; Feng, Y. Exploring options to grow rice using lesswater in northern China using a modelling approach II. Quantifying yield, water balance components, andwater productivity. Agric. Water Manag. 2007, 88, 23–33. [CrossRef]
Geerts, S.; Raes, D. Deficit irrigation as an on-farm strategy to maximize crop water productivity in dry areas.
Agric. Water Manag. 2009, 96, 1275–1284. [CrossRef]
Liang, Y.; Li, F.; Nong, M.; Luo, H.; Zhang, J. Microbial activity in paddy soil and water use efficiency of riceas affected by irrigation method and nitrogen level. Commun. Soil Sci. Plant Anal. 2015, 47, 19–31. [CrossRef]
Mao, Z. Water Efficient Irrigation and environmentally Sustainable Irrigated Rice Production in China.
International Commission on Irrigation and Drainage, 2001. Available online: http://www.icid.org/wat_mao.pdf (accessed on 23 December 2013).
Tan, X.; Shao, D.; Liu, H.; Yang, F.; Xiao, C.; Yang, H. Effects of alternate wetting and drying irrigation on
percolation and nitrogen leaching in paddy fields. Paddy Water Environ. 2013, 11, 381–395. [CrossRef]
Ye, Y.; Liang, X.; Chen, Y.; Liu, J.; Gu, J.; Guo, R.; Li, L. Alternate wetting and drying irrigation andcontrolled-release nitrogen fertilizer in late-season rice. Effects on dry matter accumulation, yield, water andnitrogen use. Field Crops Res. 2013, 144, 212–224. [CrossRef]
Prathapar, S.A.; Qureshi, A.S. Modelling the effects of deficit irrigation on soil salinity, depth to water table
and transpiration in semi-arid zones with monsoonal rains. Water Resour. Dev. 1999, 15, 141–159. [CrossRef]
Kato, Y.; Okami, M. Root morphology, hydraulic conductivity and plant water relations of high-yielding rice
grown under aerobic conditions. Ann. Bot. 2011, 108, 575–583. [CrossRef] [PubMed]
El-Sadek, A. Water use optimisation based on the concept of partial rootzone drying. Ain Shams Eng. J. 2014,
5, 55–62. [CrossRef]
Zhang, Z.; Zhang, S.; Yang, J.; Zhang, J. Yield, grain quality and water use efficiency of rice under non-flooded
mulching cultivation. Field Crops Res. 2008, 108, 71–81. [CrossRef]
Bouman, B.A.M.; Tuong, T.P. Field water management to save water and increase its productivity in irrigatedlowland rice. Agric. Water Manag. 2001, 49, 11–30. [CrossRef]
Peng, S.; Yang, S.; Xu, J.; Luo, Y.; Hou, H. Nitrogen and phosphorus leaching losses from paddy fields withdifferent water and nitrogen managements. Paddy Water Environ. 2011, 9, 333–342. [CrossRef]
Garg, K.K.; Das, B.S.; Safeeq, M.; Bhadoria, P.B.S. Measurement and modeling of soil water regime ina lowland paddy field showing preferential transport. Agric. Water Manag. 2009, 96, 1705–1714. [CrossRef]
Tan, X.; Shao, D.; Liu, H. Simulating soil water regime in lowland paddy fields under different water
managements using HYDRUS-1D. Agric. Water Manag. 2014, 132, 69–78. [CrossRef]
Tsubo, M.; Fukai, S.; Tuong, T.P.; Ouk, M. A water balance model for rainfed lowland rice fields emphasisinglateral water movement within a toposequence. Ecol. Model. 2007, 204, 503–515. [CrossRef]Šimůnek, J.; van Genuchten, M.T.; Šejna, M. Development and applications of the HYDRUS and STANMOD
software packages, and related codes. Vadose Zone J. 2008, 7, 587–600. [CrossRef]
Yang, S.; Peng, S.; Xu, J.; Hou, H.; Gao, X. Nitrogen Loss from paddy field with different water and nitrogen
managements in Taihu lake region of China. Commun. Soil Sci. Plant Anal. 2013, 44, 2393–2407. [CrossRef]
Li, Y.; Šimůnek, J.; Jing, L.; Zhang, Z.; Ni, L. Evaluation of water movement and water losses ina direct-seeded-rice field experiment using Hydrus-1D. Agric. Water Manag. 2014, 142, 38–46. [CrossRef]

Water 2017, 9, 248

28.

29.

30.
31.
32.
33.
34.
35.
36.
37.
38.

39.
40.
41.

42.
43.
44.
45.

14 of 14

Molden, D. A water-productivity framework for understanding and action. In Water Productivity inAgriculture: Limits and Opportunities for Improvement; Kijne, J.W., Barker, R., Molden, D., Eds.; International
Water Management Institute: Colombo, Sri Lanka, 2003; pp. 1–18.
Phogat, V.; Yadav, A.K.; Malik, R.S.; Kumar, S.; Cox, J. Simulation of salt and water movement and estimationof water productivity of rice crop irrigated with saline water. Paddy Water Environ. 2010, 8, 333–346.
[CrossRef]
Humphreys, E.; Kukal, S.S.; Gill, G.; Rangarajan, R. Effect of water management on dry seeded and puddled
transplanted rice Part 2: Water balance and water productivity. Field Crops Res. 2011, 120, 123–132.
Van Genuchten, M.T. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils.
Soil Sci. Soc. Am. J. 1980, 44, 892–898. [CrossRef]
Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration-Guidelines for Computing Crop Water
Requirements. Irrigation and Drain; Paper No. 56; FAO: Rome, Italy, 1998.
Feddes, R.A.; Kowalik, P.J.; Zaradny, H. (Eds.) Simulation of Field Water Use and Crop Yield; John Wiley & Sons:
New York, NY, USA, 1978.
Arif, C.; Setiawan, B.I.; Sofiyuddin, H.A.; Martief, L.M.; Mizoguchi, M.; Doi, R. Estimating Crop Coefficientin Intermittent Irrigation Paddy Fields Using Excel Solver. Rice Sci. 2012, 19, 143–152. [CrossRef]
Belmans, C.; Wesseling, J.G.; Feddes, R.A. Simulation model of the water balance of a cropped soil: SWATRE.
J. Hydrol. 1983, 63, 271–286. [CrossRef]
Xu, Q.; Yang, L.; Dong, Y. Rice Field Ecosystem in China; Chinese Agricultural Press: Beijing, China, 1998.
(In Chinese)
Zhang, H.C.; Li, J.; Yao, Y.; Huo, Z.Y.; Dai, Q.G.; Xu, K.; Yang, B.; Zhao, P.H.; Wei, H.Y. Scientific Issues of
Direct Seeding Rice Cultivation; Chinese Agricultural Science Press: Beijing, China, 2009. (In Chinese)Ünan, R.; Sezer, İ.; ŞAhin, M.; Mur, L.A.J. Control of lodging and reduction in plant length in rice
(Oryza sativa, L.) with the treatment of trinexapac-ethyl and sowing density. Turk. J. Agric. For. 2013,37, 257–264. [CrossRef]
Maqsood, M.; Shehzad, M.A.; Ali, S.N.A.; Iqbal, M. Rice cultures and nitrogen rate effects on yield andquality of rice (Oryza sativa, L.). Turk. J. Agric. For. 2013, 37, 665–673. [CrossRef]
Zhao, X.; Zhou, Y.; Min, J.; Wang, S.; Shi, W.; Xing, G. Nitrogen runoff dominates water nitrogen pollution
from rice-wheat rotation in the Taihu Lake region of China. Agric. Ecosyst. Environ. 2012, 156, 1–11. [CrossRef]
Tuong, T.P.; Bouman, B.A.M. Rice production in water-scarce environments. In Water Productivity inAgriculture: Limits and Opportunities for Improvement; Kijne, J.W., Barker, R., Molden, D., Eds.; CABI Publishing:
Wallingford, UK, 2003; pp. 53–67.
Lian, G.; Wang, D.; Lin, J.; Yan, D. Characteristics of nutrient leaching from paddy field in Taihu Lake area.
Chin. J. Appl. Ecol. 2003, 14, 1879–1883.
Singh, R.; van Dam, J.C.; Feddes, R.A. Water productivity analysis of irrigated crops in Sirsa district, India.
Agric. Water Manag. 2006, 82, 253–278. [CrossRef]
Zwart, S.J.; Bastiaanssen, W.G.M. Review of measured crop water productivity values for irrigated wheat,rice, cotton and maize. Agric. Water Manag. 2004, 69, 115–133. [CrossRef]
English, M. Deficit irrigation. I. Analytical framework. J. Irrig. Drain. Eng. ASCE 1990, 116, 399–412.
[CrossRef]© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).