sustainability
ArticlePerformance of Spring and Summer-Sown Maize underDifferent Irrigation Strategies in Pakistan
Abdul Ghaffar Khan 1,2,3 , Muhammad Imran 1,4,5, * , Anwar-ul-Hassan Khan 1 , Ali Fares 3 , Jiří Šimůnek 5 ,Tanveer Ul-Haq 4 , Abdulaziz Abdullah Alsahli 6 , Mohammed Nasser Alyemeni 6 and Shafaqat Ali 7,8, *
1

2

3

4

5

6

7
8



Citation: Khan, A.G.; Imran, M.;
Khan, A.-u.-H.; Fares, A.; Šimůnek, J.;
Ul-Haq, T.; Alsahli, A.A.; Alyemeni,
M.N.; Ali, S. Performance of Spring
and Summer-Sown Maize underDifferent Irrigation Strategies inPakistan. Sustainability 2021, 13, 2757.
https://doi.org/10.3390/su13052757
Academic Editors:
Mohammad Valipour and José
Manuel Mirás-Avalos
Received: 8 December 2020
Accepted: 23 February 2021
Published: 4 March 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional affiliations.

*

Institute of Soil & Environmental Sciences, University of Agriculture, Faisalabad 03802, Pakistan;ghaffarniazi@gmail.com (A.G.K.); drauhkhan@yahoo.com (A.-u.-H.K.)
Senior Scientist (Soil Science) Directorate of Rapid Soil Fertility Survey & Soil Testing Institute Punjab, Lahore
54000, Pakistan
College of Agriculture and Human Sciences, Prairie View A&M University, Prairie View, TX 77446, USA;
alfares@pvamu.edu
Department Soil and Environmental Sciences, MNS-University of Agriculture, Multan 60000, Pakistan;tanveer.ulhaq@mnsuam.edu.pk
Department Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA;jiri.simunek@ucr.edu
Department of Botany and Microbiology, College of Science, King Saud University,
Riyadh 11451, Saudi Arabia; aalshenaifi@ksu.edu.sa (A.A.A.); mnyemeni@ksu.edu.sa (M.N.A.)
Department of Environmental Sciences, Government College University, Faisalabad 38000, Pakistan
Department of Biological Sciences and Technology, China Medical University, Taichung 40402, Taiwan
Correspondence: m.imran@mnsuam.edu.pk (M.I.); shafaqataligill@gcuf.edu.pk (S.A.)

Abstract: Pakistan is facing severe water shortages, so using the available water efficiently is essential
for maximizing crop production. This can be achieved through efficient irrigation practices. Field
studies were carried out to determine the dynamics of soil water and the efficiency of water utilization
for maize grown under five irrigation techniques (flood-irrigated flatbed, furrow-irrigated ridge,
furrow-irrigated raised bed, furrow-irrigated raised bed with plastic mulch, and sprinkler-irrigatedflatbed). Spring and summer maize was grown for two years. The Irrigation Management System(IManSys) was used to estimate the irrigation requirements, evapotranspiration, and other waterbalance components for this study’s different experimental treatments based on site-specific crop,
soil, and weather parameters. The results showed that the flood irrigation flatbed (FIF) treatment
produced the highest evapotranspiration, leaf area index (LAI), and biomass yield compared toother treatments. However, this treatment did not produce the highest grain yield and had thelowest water use efficiency (WUE) and irrigation water use efficiency (WUEi ) compared to thefurrow-irrigated raised-bed treatment. The furrow-irrigated raised bed with plastic mulch (FIRBM)
treatment improved grain yield, WUE, WUEi , and harvest index compared to the flood irrigation
flatbed (FIF) treatment. The results showed a strong correlation between measured and estimatednet irrigation requirements and evapotranspiration, with high r2 values (0.93, 0.99, 0.98, and 0.98) for
the spring- and summer-sown maize. It was concluded that the FIRBM treatments improved thegrain yield, WUE, and WUEi, which ultimately enhanced sustainable crop production. The growing
of summer-sown maize in Pakistan has the potential for sustainable maize production under thesemiarid and arid climate.
Keywords: sprinkler irrigation; furrow-irrigated raised bed; irrigation management software; evapotranspiration; water use efficiency

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
In recent decades, increasing water shortages have begun threatening food security
for millions of people because more than 80% of freshwater is used by agriculture [1]. According to the International Water Management Institute (IWMI), one-third of developing

Sustainability 2021, 13, 2757. https://doi.org/10.3390/su13052757

https://www.mdpi.com/journal/sustainability

Sustainability 2021, 13, 2757

2 of 13countries’ population lives in regions where water supplies are inadequate to meet theiragricultural, domestic, and industrial needs [2]. With over 220 million people, if sufficientwater supplies are not available for crop production, Pakistan cannot meet its demand forfood. The per capita water supply decreased from 5600 m3 in 1947 to only about 1000 m3
in 2004 [3]. With the rising demand for irrigation water for agriculture, the world is now
facing the challenge of producing more food with less water. Realistically, this goal can beachieved only when irrigation water utilization is more efficient. Moreover, water scarcity
can be managed through optimal planning [4]. The highest (55.5 USD m−3 ) agriculture
water use efficiency in the world was reported in the Netherlands, whereas in Pakistan, it
was only 0.2 USD m−3 [5].
Water and its movement across the soil–plant–atmosphere continuum are some of themost important core factors influencing crop productivity [6]. Efficient irrigation technologies and water management practices moderate the negative impacts of higher water use
on farm incomes and environmental effects on soils and groundwater tables [7]. Many
agricultural management practices have been used to increase agricultural production formany years [8]. Irrigation scheduled at different growth stages can significantly improvewater use efficiency [9]. Similarly, Ref. [10] also reported that grain yield and water use
efficiency (WUE) were strongly affected by soil water contents and irrigation scheduling. Furrow-irrigated raised-bed planting, furrow-irrigated raised bed with plastic mulch
planting, and sprinkler irrigation have been proposed as three of the most significant
strategies to minimize the cost of cultivation, improve WUE, and maximize crop yield.
In bed sowing, 24% [11] and 34% [12] of water was saved compared to flat sowing. The
sprinkler irrigation method has a higher potential for application efficiency than flood
irrigation [13]. In the Indian subcontinent, sprinkler irrigation has increased on-farmirrigation efficiencies by up to 80% under the prevailing climatic conditions [14]. It wasalso found that water savings with sprinkler irrigation were 30% higher than with flatbed
sowing [15]. The pivot central sprinkler irrigation practice also improved the water use
efficiency, ranging from 1.07 kg m−3 to 2.2 kg m−3 [16]. There were also reports that thewater use efficiency decreased when irrigation systems ignored soil variability and applied
water uniformly [16].
Soil covers, such as different mulching materials, can significantly reduce evaporationand improve soil temperature and crop yield. The cost of plastic mulch is lower comparedto gravel or sand, and it is easily managed. Thus, it has been widely reported that bothgrain yield and WUE can be increased under mulches [17,18]. It was observed that the soil
and water conservation techniques played a significant role in decreasing water losses andincreasing water infiltration [18]. It was also reported that the high moisture content wasrecorded in areas where conservation practices have been adapted compared to other areas
where farmers ignore these practices. It was also reported that soil and water conservation
practices improved soil health by increasing soil organic matter, ultimately improving
water conservation [19]. These practices also improved the crop yield.
To forecast environmental parameters of interest [20], simulation models usually
integrate theoretical principles, scientific information, computational algorithms, andstatistical considerations. The Irrigation Management System (IManSys) [21,22] was used
to estimate the irrigation requirements for this study’s different experimental treatments
based on site-specific crop, soil, and weather parameters.
Maize is the third most important cereal crop in Pakistan after wheat and rice, andits production increased by 6% during 2019–2020. Its contribution in value addition ofagriculture is 2.9%, and it contributes 0.6% to the gross domestic production (GDP) of
Pakistan. The increase in production was mainly due to the increase in cultivated area,
which increases the water demand in the agriculture sector [23]. Thus, it is vital to improve
the water use efficiency of maize in order to reduce agriculture’s water requirement.
This study has two objectives. The first objective is to evaluate the effects of different
irrigation techniques and growing seasons (spring and summer) on water use efficiency,
crop yield, evapotranspiration, and soil water dynamics within and below the root zone inSustainability 2021, 13, x FOR PEER REVIEW

3 of 13

Sustainability 2021, 13, 2757

3 of 13crop yield, evapotranspiration, and soil water dynamics within and below the root zone
inPakistan.
The
secondobjective
is evaluate
to evaluate
performanceof IMaySys
in estimating
Pakistan.
The
secondobjective
is tothetheperformanceof IMaySys
in estimatingthetheirrigation
requirements,
evapotranspiration,
and
the
rest
of
the
water
budgetcompoirrigation requirements, evapotranspiration, and the rest of the water budget components
nents
this study
site-specificweather
conditionsof Pakistan.
of thisofstudy
using usingsite-specificweather
conditionsof Pakistan.
2.
2. Materials
Materials andand Methods
Methods
2.1. Experimental
Experimental Site
Site andand Setup
Setup
2.1.
The field
field experimentexperiment waswas conductedconducted at the experimental
experimental farm of the Institute of Soil
The
andEnvironmental
Sciences,
UniversityofAgriculture,
Faisalabad, Pakistan
Pakistan (latitude,(latitude,and Environmental Sciences, University of Agriculture, Faisalabad,◦ 260 N and 73◦ 060 E, 184 m ASL) during the spring and summer growing seasons of
31
31°26′ N and 73°06′ E, 184 m ASL) during the spring and summer growing seasons of 201120112012.
and 2012.
The study
climateis semi-subtropical,ofand
The study
area’sarea’s
climateis semi-subtropical,
arid,arid,
withwith
moremorethanthan
70%70%of thethe annual
rainfalloccurringto September.
automatedweatherstationannualrainfalloccurring
fromfrom
JuneJuneto September.
An An
automatedweatherstationwaswasininstalledabout
m awayfromthe experimental
Reference
evapotranspiration
stalledabout
500500m awayfromthe experimental
field.field.
Reference
evapotranspiration(ET0)(ET0calculated) was calculated
the Penman–Monteithequationfrom meteorologicalvariables
wasusing using
the Penman–Monteithequationfrom meteorologicalvariables(Fig(Figure1).
ure 1).

10

Rainfall

100

ET0

90

9

80
70

7

60

6

50

5

40
30

4

Rain fall (mm)ET0 (mm)

8

20

3

10

2

0
0

10 20 30 40 50 60 70 80 90
DAS
(a)

0

10 20 30 40 50 60 70 80 90
DAS(b)

FigureFigure 1.
1. Daily
Daily reference
reference evapotranspiration
evapotranspiration (ET(ET00))andandrainfall
rainfallduring
duringthethe(a)(a)spring
spring(average(averageof
of25
25February
Februaryto
to29
29May,
May,2011
to 77 November,
November, 2011
2011 andand 2012)
2012) seasons.
seasons. DASDAS stands
stands forfor daysdays after
after sowing.
sowing.
2011 andand 2012)
2012) (b)(b) summer
summer (27(27 July
July to

The
The experimental
experimental site’ssite’s soil
soil type
type isis well-drained
well-drained Hafizabad
Hafizabad loam,
loam, mixed,
mixed, semiactive,
semiactive,
isohyperthermic
isohyperthermic Typic
Typic Calciargids
Calciargids (Table(Table 1).
1). The
The three
three composite
composite soil
soil samples
samples were
were colcollected
lected fromfrom each
each soil
soil layer
layer andand thenthen analyzed
analyzed forfor soil
soil texture
texture [24],[24], soil
soil organicorganic mattermatter [25],
[25],
and
and waterwater retention
retention curves [26]. The
The soil
soil bulk
bulk density
density was
was also
also determined
determined using the core
methodforeacheachmajor
majorsoil
soil
layer
three
randomly
selectedlocations.
Atsamethe samemethod [27] for
layer
at at
three
randomly
selectedlocations.
At thetime,
the saturated
hydraulicconductivity(Kfs ) wasat threerandomly
selectedtime,
the saturated
hydraulicconductivity(Kfs) also
was measured
also measured
at threerandomly
sesites using
Guelphpermeameter
method(Model(Model
2800 KI)[27].
lectedsites theusing
the Guelph
permeameter
method2800KI) [27].
Table 1. Measured soil physical and hydraulic parameters of the four main horizons at the experimental site.

Depth
(cm)
0–20
20–40

Particle Fractions (%)
B.D.
SOC
θs
θFC
θPWP
θAWC
Kfs
−3
3
−3
−1
Sand
Silt
Clay
(Mg m )-----cm cm ----cm Day(%)
40.07 ±
37.41 ± 0.13 22.52 ± 0.10 1.45 ± 0.10 0.44 ± 0.03 0.29 ± 0.01 0.13 ± 0.01 0.16 ± 0.01 28.31 ± 1.55 0.50 ± 0.37
0.12
43.47 ±
34.08 ± 0.12 22.45 ± 0.14 1.48 ± 0.03 0.44 ± 0.02 0.27 ± 0.01 0.12 ± 0.01 0.15 ± 0.01 27.27 ± 3.01 0.34 ± 0.45
0.15

Sustainability 2021, 13, 2757

4 of 13

Table 1. Measured soil physical and hydraulic parameters of the four main horizons at the experimental site.
Depth
(cm)

Particle Fractions (%)

B.D.

θs

θFC

θPWP

θAWC

Kfs

SOC

cm
Day−1

(%)

Sand

Silt

Clay

(Mg
m−3 )

0–20

40.07 ±
0.12

37.41 ±
0.13

22.52 ±
0.10

1.45 ±
0.10

0.44 ±
0.03

0.29 ±
0.01

0.13 ±
0.01

0.16 ±
0.01

28.31 ±
1.55

0.50 ±
0.37

20–40

43.47 ±
0.15

34.08 ±
0.12

22.45 ±
0.14

1.48 ±
0.03

0.44 ±
0.02

0.27 ±
0.01

0.12 ±
0.01

0.15 ±
0.01

27.27 ±
3.01

0.34 ±
0.45

40–60

45.24 ±
0.22

32.30 ±
0.23

22.46 ±
0.12

1.55 ±
0.02

0.43 ±
0.02

0.27 ±
0.01

0.12 ±
0.01

0.15 ±
0.01

19.52 ±
4.25

0.28 ±
0.18

60–10046.38 ±
0.19

31.21 ±
0.14

22.41 ±
0.14

1.59 ±
0.02

0.42 ±
0.01

0.27 ±
0.013

0.12 ±
0.01

0.15 ±
0.01

20.00 ±
2.35

0.22 ±
0.28—–cm3 cm−3 —–B.D = soil bulk density, θ s = saturated water content, θ FC = water content at field capacity, θ PWP = water content at the permanent wilting
point, θ AWC = available water content, Kfs = field-saturated hydraulic conductivity, SOC = soil organic carbon, n = 3.

2.2. Experimental Treatments
The experimental design was a randomized complete block design with four replications, with irrigation techniques as the main treatments. Plot sizes were 4 m2 each,separated by a 1 m crop-free buffer strip. The local high-yielding maize hybrid (DK 919)
was planted. The spring sowing time was on 27 February, 2011, and 25 February, 2012.
However, the summer sowing was on 27 July, 2011, and 29 July, 2012. The seeding rate was
25 kg ha−1 , with a 65 cm row spacing and a 22.5 cm plant to plant distance. Fields were
irrigated uniformly (101.6 mm) before sowing to ensure optimum germination. Urea wasapplied at a rate of 250 kg N ha−1 in two splits. Phosphorous and potassium were appliedat sowing at 150 kg ha−1 of single super phosphate and 105 kg ha−1 of potassium sulfate.
The spring-sown maize was harvested on 29 May, 2011, and 27 May, 2012, whereas thesummer-sown maize was harvested on 5 November, 2011, and 7 November, 2012.
The individual experimental treatments consisted of five different irrigation techniques(i.e., flood-irrigated flatbed (FIF), furrow-irrigated ridge (FIR), furrow-irrigated raised bed(FIRB), furrow-irrigated raised bed with plastic mulch (FIRBM), and sprinkler-irrigatedflat sowing (SIF)). Readily available water (RAW) was maintained at adequate levels in all
irrigation techniques so that there were no water stresses in either growing season.
2.3. Plant Measurements
From a harvested area of 1 m2 at the center of each plot, the total aboveground biomass
and grain yield were recorded. The ratio of grain yield to total biomass was calculated
as the harvest index. A digital leaf area meter (YMG-A/YMG-B; https://www.hinotek.
com/lab/ymj-aymj-b-portable-leaf-area-meter (accessed on 1 February 2021)) was used
to calculate the leaf area (LA) from the three randomly selected leaves (top, middle, andbottom leaves) from three randomly selected plants per replication per treatment. After the
LA meter calibration, the Leaf Area Index (LAI) was calculated by dividing the total leaf
area by the land area. However, in the absence of the leaf area meter, LA was calculatedusing the following formula [28]:Leaf area = L × W × A(1)

where L is the leaf length (m), W (m) is the greatest leaf width, and A is a factor, which has
a value of 0.75 for maize. Leaf area index was measured 7, 15, 30, 60, 75, and 90 days aftersowing (DAS) and at harvest.

Sustainability 2021, 13, 2757

5 of 132.4. Soil Water Content and Actual Evapotranspiration
Based on weekly measured water content readings, the amount of irrigation water
needed to sustain the soil water status at RAW (mm) was determined and applied whenrequired. Readily available water (RAW) was determined according to the formula below:
RAW = pTAW

(2)where the “threshold value for readily available water” (TAW) for maize (p = 0.55) was
taken from the FAO Irrigation and Drainage Paper No. 33 and adjusted using the following
formula [29]:p adj = 0.55 + 0.04(5 − ETc )(3)
where padj is the adjusted fraction of the total available water depleted from the root zone
before any moisture stress, and ETc is the crop evapotranspiration in mm/day.
The soil water content in the top 100 cm of the soil profile was measured weekly using
the Time Domain Reflectometry (Triaxial Cables Manufacturer MODEL 6050X3) form at
the following soil profile sections: 0–20, 20–40, 40–60, 60–100 cm depth. The soil watercontent monitoring sensor was calibrated before starting the experiment using gravimetricreference samples from the corresponding depths [30]. Water contents at field capacity
and a permanent wilting point (Table 1) were determined for each depth with a pressure
plate apparatus at pressures of −33 and −1500 kPa, respectively [30]. Based on soil watermeasurements, actual evapotranspiration was calculated using the water balance equation:
ETa = ( I + P) − ∆S(4)where ETa is actual evapotranspiration (mm), I (mm) is irrigation, P (mm) is rainfall, and ∆S(mm) is the change in the root zone water storage. Drainage was assumed to be negligible
because irrigation amounts were adequately delivered to replace depleted water based on
measured soil water contents in the root zone and the optimum water-holding capacity ofthe soil.
2.5. Water Use Efficiency and Irrigation Water Use Efficiency
The water use efficiency (WUE) is defined as follows [31]:
WUE =

GY
ETa

(5)

where WUE (kg ha−1 mm−1 ) is the water use efficiency for grain yield (kg ha−1 ), GY is thegrain yield (kg ha−1 ), and ETa (mm) is the actual evapotranspiration.
Irrigation water use efficiency (WUEi ) is calculated as follows:
WUEi =

GY
I(6)

where I (mm) is the applied irrigation depth.
2.6. IManSys Model Simulation
The Irrigation Management System (IManSys) software was used to calculate irrigation requirements for maize, based on the site-specific data [32]. IManSys solves thefollowing water balance equation:
STO = RAIN + NIR − DRAIN − RUNOFF − CANOPY INTERCEPTION − ETa(7)where STO is the change in the soil water storage (mm), RAIN is rainfall (mm), NIR is
the net irrigation requirement (mm), DRAIN is the drainage below the root zone (mm),RUNOFF is surface runoff (mm), the CANOPY INTERCEPTION is the rainfall interception
by the crop (mm), and ETa is the actual evapotranspiration (mm).

Sustainability 2021, 13, 2757

6 of 13Equation (7) is rearranged, and then the gross irrigation requirements are calculated
as follows:
NIR = (STO − NET RAIN + DRAIN + ETa )/f(8)
where f is the irrigation system efficiency accounting for irrigation losses (f < 1). The
input data for IManSys are meteorological data (rainfall, maximum and minimum airtemperatures, wind speed, and solar radiation), crop data (the initial and maximum
crop root zone depths, and the initial, mid-season, and end-season crop coefficients),
and the soil water-holding capacity for each soil layer. The output data include net
irrigation requirement (NIR), effective rainfall, potential evapotranspiration (ET0 ), actual
evapotranspiration (ETa ), and runoff. More details about IManSys can be found in [32].
The model uses the measured gross rainfall to determine net rainfall/effective rainfall
based on the crop’s LAI and plant height.
2.7. Model Performance
IManSys model was calibrated for the net irrigation requirement (NIR) and ETa using
a data set of the 1st year of all treatments for both seasons. Soil physical and hydraulicparameters (Table 1), climatic data, rooting depth of crop, and LAI were used for calibrationto achieve a goodness of fit between predicted and observed values of the water balancecomponent. The model was then validated with the data of the second year of all treatments
for both seasons. Model efficiency was calculated using the Nash and Sutcliffe method [33]:NSE = 1 −∑in = 1 (Oi − Pi )∑in = 1 (Oi − O)

2

2

(9)

Here an EF value of 1 indicates that the model predicted and observed values are an
exact match, and an EF value of 0 indicates that the mean of observed data would be asimilarly accurate prediction of observed data as the model predicted values. EF value
from −∞ to 0 occurred when observed means were a better predictor than the model.
2.8. Statistical Analysis
The collected data were subjected to normality and homogeneity tests and statisticallyanalyzed using the analysis of variance (ANOVA) techniques according to the randomized
complete block design (RCBD) for both field trials. The mean values were comparedusing the LSD (a least-significant difference) test at p ≤ 0.05 [34]. The software package
STATISTIX 8.1 [35] was used for the statistical analysis.
3. Results and Discussion
3.1. Soil Water Dynamics
The water content in the top 20 cm (0–20 cm) showed clear differences between
different treatments (Figures 2 and 3) in both growing seasons. In contrast, the watercontents in lower layers showed insignificant variations due to more upward movement
and negligible drainage. The water content in the upper 20 cm soil layer was highest in the
FIRBM treatment than the other treatments during both growing seasons. The extent of
measured water contents was as follows: FIRBM > FIRB > FIR > FIF > SIF. Both evaporationand transpiration affected the upper 20 cm soil layer. A high proportion of root water
absorption normally occurs in the near-surface layers due to higher root densities near
the plant base [36]. Earlier researchers reported that the plastic mulch conserved morewater than other mulch materials [37]. Similarly, the highest soil water storage and low
evaporation were recorded for the plastic mulch with furrow irrigation [38].

Sustainability
2021, 13,275713, x FOR PEER REVIEW
Sustainability
2021,
Sustainability 2021, 13, x FOR PEER REVIEW

22

22

Water content(%)

20

20

Water content(%)

7 of 13 7 of 13
7 of 13

18

18

16

16

14

14

12

12

FIF

10

10

FIF

FIR

FIR

FIRB

FIRB

FIRBM
FIRBM

SIF

SIF

8

8

20

20

30

30

40

40

50

50

60
60 DAS70
DAS

70

80

80

90

90

96

96

Figure 2. Measured
soil water contents
in thetop 20cm soil during
layer during
the spring season.
FigureFigure2.2.Measured
Measuredsoil
soilwaterwatercontents
contentsininthe
thetoptop20
20cm
cmsoilsoillayer
layer duringthe
thespring
springseason.
season.

Water Content(%)

Water Content(%)

30
25
20
15
10

30
25
20
15
FIF

10
20

20

30

FIF
30

FIR
40

40

FIR
50

FIRB
50

FIRB

60
60 DAS 70
DAS

FIRBM
FIRBM
70

80

80

SIF
90

90

SIF
96

96

Figure 3. Measured soil water contents in the top 20 cm soil layer during the summer season.
Figure3.3.Measured
Measuredsoil
soilwaterwatercontents
contentsininthe
thetoptop20
20cm
cmsoilsoillayer
layerduring
duringthe
thesummer
summerseason.
season.
Figure3.2. Seasonal
Water
Balanceamong
Different
Irrigation
Practices
3.2.
Water
Balanceamong
Different
Irrigation
Practices
3.2.Seasonal
Seasonal
Water
Balanceamong
Different
Irrigation
Practices
The highest(420–410.5
and lowest(340–290.5
NIR
amounts
recordedThe(420–410.5mm)
and(340–290.5
mm)
NIR
were
recorded
Thehighest
highest(420–410.5mm)mm)
andlowest
lowest(340–290.5mm)mm)NIRamounts
amounts
werewererecorded
for
the
FIF
and
SIF
treatments
duringthespringandsummergrowingseasons(TableforforthetheFIF
FIFandandSIF
SIFtreatments
treatmentsduring
duringthethespring
springandandsummer
summer growing
growing seasonsseasons (Table(Table2).
2). 2).
The
highestseasonal
evapotranspiration(475–407.5mm)
wasrecorded
for
the
FIF
The
Thehighest
highestseasonalseasonalevapotranspiration
evapotranspiration (475–407.5(475–407.5 mm)mm) waswas recorded
recorded forforthetheFIF
FIFtreattreat-treatment,
whereasthelowestseasonal
evapotranspiration(390.2–280mm)
wasrecordedment,
ment,whereas
whereasthe
thelowest
lowestseasonalseasonalevapotranspiration
evapotranspiration(390.2–280(390.2–280mm)mm)waswasrecorded
recordedfor
for forthetreatment
SIF treatment
duringthe springandsummergrowingseasons(Table2). Theretheduringtheandgrowingseasons(Table2).
isisaa is a
theSIF
SIF
treatment
duringthespring
springandsummer
summergrowingseasons(Table2).ThereThere
reasonable
correlation
betweenseasonal
water
evapotranspiration
andtheamountof netreasonable
correlation
betweenseasonal
water
evapotranspiration
andtheamountofreasonable correlation between seasonal water evapotranspiration and the amount ofnet
net
irrigation
requirement(NIR)(Figure4).
However,
the
ET
a
of
the
springseasonwasslightlyirrigation
requirement(NIR)(Figure4).
However,
the
ET
of
the
springseasonwasslightlya a of the spring season was slightly
irrigation requirement (NIR) (Figure 4). However, the ET
higherthan
that
ofsummerthe summer
seasonacrossall treatments.
This
might
be attributed
higherthanseasonacrossallThisbetoto tohigherthanthatthatofofthe
thesummerseasonacrossalltreatments.
treatments.
Thismight
might
beattributed
attributed
differencesinclimatic
conditions,changes
in
soil
water
storage,
and
a
total
growingdifferenceschanges
in in
soil
water
storage,andanda totalgrowingseasondifferencesininclimatic
climaticconditions,conditions,changessoil
water
storage,a totalgrowingsea- season irrigation
depth.
irrigation
depth.
son irrigation
depth.

Treatments
Treatments

2. Comparisonof measured
and simulated
water balancecomponents
NIR(net amountof irrigation(irrigation(I)
Table Table
2. Comparisonof measured
and simulated
water balancecomponents
NIR (net
amountof irrigation(irrigation(I) +Table 2. Comparison of measured and simulated water balance components NIR (net amount of irrigation (irrigation (I)+ (RF))),
rainfallET(RF))),ETevapotranspiration),a (actual evapotranspiration),and ΔSin(change
in storage
soil water
storagewithintheduringroot zone)
during therainfall(actualand∆S(changesoil
water
within
the
root
zone)
the
springa+ rainfall (RF))), ETa (actual evapotranspiration), and ΔS (change in soil water storage within the root zone) during thespring andsummer seasons.
andsummerseasons.
springand summer
seasons.

SpringSummerSpringSummerSpringSummerEstimated (mm)Measured (mm)
Estimated (mm)Measured
Estimated
Measured
Estimated
Measured(mm)(mm)
Estimated(mm)(mm)
Measured(mm)(mm)
Estimated(mm)(mm)
NIR
ETa
∆S
NIR
ETa
∆S
NIR
ETa
∆S
NIR
ETa
∆S
NIR
ET
a
ΔS
NIR
ET
a
ΔS
NIR
ET
a
ΔS
NIR
ET
a
ΔS
* FIF
−55 d
428 a
480 aa−52 c410.5 a
407.5
415 a
2.7 d
NIR
ETa475 a
ΔS
NIR
ET
ΔS
NIR
ET
aa
ΔS3.0 d
NIR
ET412.3a a
ΔS
420 a ++
420
d 428
a 374.2407.5
a 11.3d3.0
d415395.5
a 386.4
412.3
FIR * FIFb ac414.5 b428 a 460 b 480 a−55.5 d −52 c 385.5410.5bcbb 2.7 d+b a475 457.5* FIF
420 a410
a475−55−47.5
d−55
a
480 a
−52 c 410.5 ba 407.5
a 3.0
a415
412.3
a b a2.79.1d
FIRB FIR
390.8
c b
437.8 c−47.0
bc
395.5414.5c
442 c 460 b−46.5 −55.5
bc
345.5
c
332.7
c
12.811.3
b
350.3
c
340 c
10.3 a9.1 b
410
457.5
b
−47.5
c
b
d
385.5
b
374.2
b
c
395.5
b
386.4
b
FIR
410370.8
b d 457.5405.3
b d −47.5
c
414.5
b
460
b −55.5
d 385.5b 374.2
b 11.316.3ca 395.5325bd 386.4315bd 9.1
b
FIRBM
34.5 a
372 d
410 d
a
d
d
10.0 aFIRB
c 437.8
c −−47.0
bc
395.5 c442
442−46.5
c −38−46.5
bc327.5345.5
c 311.2332.7
c 12.8b 350.3
c c340 c10.3
10.3 aFIRB
390.8390.8
437.8
c e −47.0
bc
395.5
332.7
12.8
350.3
ce 340
SIF
340cd
390.2
−50.2
b
347.5 d c
392 e c−44.5 bbc 345.5
290.5 ec
280 e c10.5bc300.2
292.2 e8.0 ca
FIRBM
370.8
d
405.3
d
−34.5
a
372
d
410
d
−38
a
327.5
d
311.2
d
16.3
a
325
d
315
d
FIRBM
370.8 d 405.3
d −34.5 afarmer372
d FIR
410
d
−38 a 327.5
d 311.2
d 16.3 a raised
325bed;d FIRBM
315=dfurrow10.0 10.0
a a
* FIF = flood-irrigatedflat (conventional
practice);= furrow-irrigatedridge; FIRB
= furrow-irrigated+
SIF 340dwith390.2
−50.2
347.5
e −44.5
bsharing
290.5
e samee 10.5c column
300.2
e not
292.2
e8.0 c8.0 c
irrigated
raisedbed
mulch;= sprinkler-irrigated
Values
the
do
SIF
d340
390.2
eplastice−50.2
b SIFb347.5
d d392 e392flat.
−44.5
b 290.5e the280
e280letter(s)10.5
c in 300.2
e 292.2
e differ
Treatments

Measured (mm)significantly
p < 0.05 according
to (conventional
the least-significancedifference(LSD)* FIF =atflood-irrigatedflat
farmerpractice);
FIRtest.
= furrow-irrigated ridge; FIRB = furrow-irrigated raised bed;

* FIF = flood-irrigated flat (conventional farmer practice); FIR = furrow-irrigated ridge; FIRB =+ furrow-irrigated raised bed;
FIRBM = furrow-irrigated raised bed with plastic mulch; SIF = sprinkler-irrigated flat. Values sharing the same letter(s)FIRBM = furrow-irrigated raised bed with plastic mulch; SIF = sprinkler-irrigated flat. + Values sharing the same letter(s)in the column do not differ significantly at p < 0.05 according to the least-significance difference (LSD) test.
in the column do not differ significantly at p < 0.05 according to the least-significance difference (LSD) test.

treatments impacted the crop’s evapotranspiration during the growing season. Maximum
soil water storage values were recorded for the furrow-irrigated raised bed with plastic
mulch treatment (FIRBM) during the summer growing season. A plastic film may reducesurface water evaporation and improve soil temperatures and increase yield [39,40]. Ad8 of 13
ditionally, its cost is lower than that of gravel and sand, and its operation is more straightforward. Consequently, the plastic-mulching technique is widely adopted.

Sustainability 2021, 13, 2757

450

ETa (mm)

ETa (mm)500

450
y = 1.0797x + 16.035
R² = 0.96

400

400
350
y = 1.0634x − 33.099
R² = 0.99

300
250

350
330

350

370

390

410

280

430

330

380

NIR (mm)

NIR (mm)

(a)

(b)

430

Figure4.4.Correlation
Correlationbetween
betweenETETa aand
andNIR
NIRduring
duringthethe(a)(a)spring
springandand(b)(b)summer
summergrowing
growingseasons.
seasons.
Figure3.3. Crop
Growthofand
Yielddepletion followed the following order FIF > SIF > FIR > FIRB
The extent
water> FIRBMduringthespringseason.
Soil water
storagedepletion
variations
Crop growth andyield growing
varied among
different
irrigation
treatments
andgrowingacrosstreatments
impacted
evapotranspiration
during thegrowingseason.
seasons(Table 3). Grain
yieldthewascrop’s
the highest
in the furrow-irrigatedraisedbed with
plasMaximum
soil watertreatment.
storage values
were recorded
theby
furrow-irrigatedraisedbed withtic mulch (FIRBM)
An increasein grainforyield
11.5 and 8.9% for
the FIRB
withplastic
mulch
treatment(FIRBM)duringthesummergrowingseason.
Aplastic
film
mayplastic mulch was observed over FIF during the two growing seasons. This increase was
reducesurfacewater evaporationand improvesoil temperaturesand increase
yield [39,40].
likely due
to higher
water use efficiencies
in thistreatment during
the two growing
seaAdditionally,
its
cost
is
lower
than
that
of
gravel
and
sand,
and
its
operationis moresons. This treatment reduces evaporation from the soil surface due to the minimum
soilstraightforward.
Consequently,
plastic-mulching
adopted.
exposure to direct
sunlight. Antheincreasein yield wastechniquelikely dueistowidelyreduceddrainage from

Treatments
FIF
FIR
FIRB
FIRBM
SIF
LSD (p ≤ 0.05)

furrows and enhanced lateral water movement. These results concur with those reported
3.3. Crop Growth and Yieldby [41]. The key contributing factors of mulch in increasing grain yield include improved
growthand yieldproperties
varied among
different irrigation
treatments
growingsoil Cropphysicaland chemicaland enhanced
soil biologicalactivityand[42].
Our reseasons(Table
3).
Grain
yield
was
the
highestinthefurrow-irrigatedraisedbed
sults agree with [43], who reported that furrow irrigation significantly increased the withgrain
plastic mulch (FIRBM) treatment. An increase in grain yield by 11.5 and 8.9% for the FIRB
yield of maize. The raised-bed treatment saved water and increased yield in the wheat–with plastic mulch was observed over FIF during the two growing seasons. This increasemaize rotation compared to the flood-irrigated flat field [37].
was likely due to higher water use efficiencies in this treatment during the two growing
seasons.
This plant
treatment
reduces
evaporation
fromsoil surface
Table
3. Measured
parameters
duringthe spring
and thesummerseasons.due to the minimum soil
exposure to direct sunlight. An increase in yield was likely due to reduced drainage fromfurrows andSpringenhanced lateral water movement. These resultsSummer
concur with those reportedby [41]. TheBiomass
key contributing factors of mulch
in increasing
grain
yield include improved
Grain Yield
Grain
Yield
Biomass
Harvest Index
Harvest Index−1) physical−1)−1) biological
soil
andha
chemicalproperties and enhanced(Mg ha(Mg(Mg hasoil(Mg activityha−1) [42]. Our resultsthat furrow
irrigation
increased
the grain
5.67 agreec + with [43],14.2whoa reported 0.39
c6.04 bcsignificantly
16.1
a0.37 cyieldofmaize.
The
raised-bed
treatment
saved
water
and
increased
yield
in
the
wheat–maize
6.06 abc
13.6 abc
0.44 b
6.16 bc
15.1 bc
0.40 brotation compared to the flood-irrigated flat field [37].
6.16 ab13.9 ab
0.44 b
6.26 ab15.3 ab
0.40 b
6.32
a
12.8
c
0.45
a
6.58
a
14.8
bc
0.44 aTable 3. Measured plant parameters during the spring and summer seasons.
5.80 bc
13.1 bc
0.44 b5.87 c14.3 c0.40 b
SpringSummer
0.48
1.10
0.01
0.37
0.91
0.01

Treatments
Grainflat
Yield
Biomass
Grain Yield
FIF = flood-irrigated(conventional
farmer practice); FIR = furrow-irrigatedridge; FIRB = Biomass
furrow-irrigated raised bed;
Harvest Index
Harvest Index
1)+ Values(Mg ha−1 )raised bed(Mg
ha−plastic(Mg ha−1flat.
)(Mgsharingha−1 ) the same letter(s)FIRBM = furrow-irrigatedwithmulch; SIF = sprinkler-irrigatedinFIF
the column do notatap < 0.05 according(LSD)
5.67differ
c + significantly
14.2
0.39 cto the least-significant
6.04 bc difference 16.1
a test.
0.37 cFIR

6.06 abc

13.6 abc

0.44 b

6.16 bc

15.1 bc

0.40 b

FIRB

6.16 ab13.9 ab

0.44 b

6.26 ab15.3 ab

0.40 b

FIRBM

6.32 a12.8 c0.45 a6.58 a14.8 bc

0.44 aSIF

5.80 bc

13.1 bc

0.44 b5.87 c14.3 c0.40 bLSD (p ≤ 0.05)

0.48

1.10

0.01

0.37

0.91

0.01

FIF = flood-irrigated flat (conventional farmer practice); FIR = furrow-irrigated ridge; FIRB = furrow-irrigated raised bed; FIRBM = furrowirrigated raised bed with plastic mulch; SIF = sprinkler-irrigated flat. + Values sharing the same letter(s) in the column do not differ
significantly at p < 0.05 according to the least-significant difference (LSD) test.

Sustainability 2021, 13, x FOR PEER REVIEW
Sustainability 2021, 13, 2757

9 of 13
9 of 13

The biomass (grain + straw) under different irrigation practices varied between 13.1
+ straw)
under different
irrigation
varied between
13.1
and The14.2 biomass
Mg ha−1(grainin springand between
14.3 and16.1 Mgpractices
ha−1 in summer.
The higher−1
and
14.2 Mg
hafloodin spring
andtreatment
between (Table
14.3 and16.1 achieved
Mg ha−1 duein summer.
higherbiomassin theirrigation
3) wasto higherThevegetative
biomass
in athefloodofirrigation
treatment(Table 3)The
wasplant
achieveddue
to vegetative
higher vegetative
growth as
resulthigher water
applications.
heightandgrowth
growthasaresultofhigherwater
applications.
The
plant
heightandvegetative
growthincreased with higher water applications, which ultimately increased the biomass. Our
increased
withwithhigherwater
applications,whichbiomass.
results agree[17,37],
who
reported thatthe ultimately
plastic filmincreased
enhancedthecropyield byOur
21–
results
agree with
[17,37],
who reported
the plastic
crop
yield byirrigation
21–92%.
92%. Similar
to ourobservations,
Sun etthatal. [39]
studiedfilm
theenhanced
relationshipbetween
Similarto andour concluded
observations,
et al. [39]studiedthe relationshipbetweenirrigationand yield
thatSunincreased
irrigation
increased
ETc and soil
evaporation
and,andyield and theconcluded
increased
irrigation
increased
evaporationc andconsequently,
biomass.that
However,
excessive
irrigation
wasET
not
cost soil
effectiveand deand,consequently,
the [41].
biomass.
However,
excessive
irrigationwasnot costwas
effective
creasedthe grain yield
The highest
harvestindex forthe FIRBM
treatment
likelyanddecreased
the
grain
yield
[41].
The
highestharvest
index
for
the
FIRBM
treatment
due to the higher total dry matter and higher grain yield in this treatment. The polythenewaslikelydue tohighertotal dry matter andand better
higherretention
grain yieldin thistreatment.
mulch
resultedin thea bettermicroenvironmentof soilmoisture,
ultiThepolythene
mulch
resultedinabettermicroenvironment
andbetterretentionof soilmately leading to a higher grain yield and harvest index (HI). Similar results wereobmoisture,
leading tothat
a highergrain planting
yield andenhanced
harvest index(HI). Similar
tained byultimately[42], who reported
raised-bed
the harvest
index results
signifiwere
obtained[42], who
reported
that raised-bed
plantingenhancedthe harvest
cantlydue to bylessened
weed
infestationand lodging.
The highest
harvestindex index
in thesignificantly
duetolessened
weed
infestation
andlodging.
Thehighestharvestindex acin
FIRBM treatment could be due to the better germination rate, higher total dry matter
the
FIRBM
treatment
could
be
due
to
the
bettergermination
rate,highertotal
drymattercumulation, and grain yield. The lowest harvest index for flood irrigation was likely due
accumulation,
grainandyield.
The lowest
index
flood irrigation
wasresearcher’s
likely due
to higher plantand
heightbiomass.
Theseharvest
findings
are forvalidatedby anothertohigherplant
heightandbiomass.
These
findings
arevalidatedbyanother
researcher’sobservations, who also recorded the maximum HI for the raised-bed treatment [40].
observations,maximumfor theirrigation
raised-bed
treatment[40].
The leaf whoarea also
indexrecorded(LAI) is theinfluenced
by HI
different
practicesandgrowing
The leaf area index (LAI) is influenced by different irrigation practices and growing
seasons (Figure 5) after 45, 60, 75, and 90 days of sowing. Crop grown under the floodseasons (Figure 5) after 45, 60, 75, and 90 days of sowing. Crop grown under the floodirrigated flat sowing treatment during the spring season had a significantly higher leaf
irrigated flat sowing treatment during the spring season had a significantly higher leaf area
area index (i.e., 2.08, 3.94, 4.40, and 4.04 at 45, 60, 75, and 90 DAS, respectively). The lowest
index (i.e., 2.08, 3.94, 4.40, and 4.04 at 45, 60, 75, and 90 DAS, respectively). The lowest LAI
LAI values were obtained for the sprinkler-irrigated flatbed treatment (1.75, 2.97, 3.74, andvalues were obtained for the sprinkler-irrigated flatbed treatment (1.75, 2.97, 3.74, and 3.40
3.40 at 45, 60, 75, and 90 DAS, respectively). A similar trend was observed during theat 45, 60, 75, and 90 DAS, respectively). A similar trend was observed during the summer
summer season (Figure 5b). The high LAI under flood irrigation may be due to the ample
season (Figure 5b). The high LAI under flood irrigation may be due to the ample water
water availability in the root zone. These results concur with the results reported by [44].
availability in the root zone. These results concur with the results reported by [44].
5

5

FIF
FIR
RIRB
FIBRM
SIF

3

4

Leaf Area Index

Leaf Area Index

4

2

3
2

2

2

1

1

0

0
7

15

30

45

60

DAS
(a)

FIF
FIR
FIRB
FIRBM
SIF

75

90

105

7

15

30

45
60
DAS

75

90

105

(b)

Figure5.5.Leaf
Leafarea
areaindex
index(LAI)(LAI)during
duringthethe(a)(a)spring
springandand(b)(b)summer
summerseasonsseasons(DAS—days(DAS—daysafter
aftersowing).
sowing).
Figure3.4. Water Use Efficiency (WUE) and Irrigation Water Use Efficiency (WUEi )The average WUE varied between 11.9 and 15.2 and 14.8 and 21.1 kg ha−1 mm−1
during the spring and summer growing seasons (Table 4), respectively. The water use

Sustainability 2021, 13, 2757

10 of 13efficiency was highest for the FIRBM treatment and lowest for the FIF treatment during
both growing seasons. However, it was statistically similar to SIF, which has an additional
cost of the sprinkler system and is more expensive than plastic mulch in Pakistan. In
general, WUE values decreased with increasing amounts of irrigation water. Reference [45]reported values of WUE of 5.90–7.45 kg m−3 from their experiments with maize in thesame region of Pakistan.
Table 4. Measured water use efficiency (WUE) and irrigation water use efficiency (WUEi ) during thespring and summer seasons.
SpringSummerTreatments

WUE(kg ha−1 mm−1 )WUEi(kg ha−1 mm−1 )WUE(kg ha−1 mm−1 )WUEi(kg ha−1 mm−1 )FIF

11.9 d +13.5 d

14.8 c14.7 cFIR

13.3 c14.7 c16.4 c15.9 b

FIRB

14.0 b

15.7 b

18.8 b

18.1 ab

FIRBM

15.2 a17.2 a21.1 a20.2 aSIF

14.8 ab17 ab

20.9 ab20.0 a

FIF = flood-irrigated flat (conventional farmer practice); FIR = furrow-irrigated ridge; FIRB = furrow-irrigatedraised bed; FIRBM = furrow-irrigated raised bed with plastic mulch; SIF = sprinkler-irrigated flat. + Values
sharing the same letter(s) in the column do not differ significantly at p < 0.05 according to the least-significant
difference (LSD) test.

Similarly, [36] reported WUEs of 1.96–1.99 kg grain m−3 for maize with the FIRB
irrigation practice. One scientist also found that bed planting resulted in 34% watersavings and 32 and 19% higher yields for maize and wheat crops, respectively [12]. The
WUEi in the summer season was higher in all treatments than WUEi in the spring season(Table 4). This could be attributed to water use from the soil water storage due to higher
temperatures, higher wind speeds, and lower relative humidity levels in April and May.
The maximum mean WUEi was observed for the FIRBM treatment (17.2 kg ha−1 mm−1 ),while the minimum WUEi was observed for the FIF treatment (12.1 kg ha−1 mm−1 ) during
spring. The WUEi recorded for all treatments is ranked from high to low: FIRBM >SIF > FIRB > FIR > FIF. During the summer season, the water use efficiency was moresignificant than the irrigation water use efficiency due to the ample supply of water andrainfall (Table 4). The maximum mean WUEI was observed for the FIRBM treatment(20.2 kg ha−1 mm−1 ), and the minimum WUEI for the FIF treatment (14.7 kg ha−1 mm−1 ).
Plastic mulch significantly enhanced WUE due to reduced evaporation water loss andan increase in transpiration. Similar results are noted by [46,47] under arid to semiarid
conditions. Similarly, Reference [36] found that WUEi generally increased with a decline in
irrigation quantity.
3.5. Performance of the IManSys Model
There is a strong linear correlation between measured and estimated ETa for bothgrowing seasons (Figure 6). IManSys-simulated ETa values fitted measured values well,with correlation coefficients of 0.99 in both spring and summer seasons. Similarly, there
were also linear relationships between measured and estimated NIR values (Figure 7).
IManSys fitted the NIR values well, with r2 values of 0.99 and 0.98 in the spring andsummer seasons, respectively. Strong correlations were thus obtained between measured
and estimated values of both NIR and ETa . Our results are in line with a previous study inwhich the model performed well under similar environmental conditions [22].

Sustainability
2021,
13,
Sustainability
2021,
13,2757
x FOR
PEER
REVIEW
Sustainability
2021,
13,
x FOR
PEER
REVIEW

500
500

11
11of
of13
13
11
of 13

ETa Estimated (mm)ETa Estimated (mm)ETa Estimated (mm)ETa Estimated (mm)

450
450
400
400

450
450

350
350

y =y 1.0097x+ 0.0147= 1.0097x+ 0.0147
r²r²= 0.99= 0.99NSE= 0.99NSE= 0.99

400
400

350
350
350
450
500
350 ET400
400
450
500
(mm)
a MeasuredETa Measured (mm)(a)(a)

300
300
250
250
250
250

y =y 0.9805x+ 14.701= 0.9805x+ 14.701
r²r²= 0.99= 0.99NSE= 0.96NSE= 0.96
350
450
350
450
ETET
(mm)
a Measured
Measured(mm)a(b)(b)

FigureCorrelation
betweenmeasuredandsimulated
evapotranspiration(ET(ETa) in inthethe(a)(a)
springand(b)(b)
summerseasons.
Figure6.6. Correlation
betweenmeasuredandsimulated
evapotranspiration(ET(a)
springand(b)summerseasons.
Figure6. Correlation
betweenmeasuredandsimulated
evapotranspiration
springandsummerseasons.
a ) ina)the

450
450

450
450

400
400

400
400
350
350
300
300
300
300

NIR Estimated (mm)NIR Estimated (mm)NIR Estimated (mm)NIR Estimated (mm)

500
500

y =y 1.0538x− 14.48= 1.0538x− 14.48
r²r²= 0.99= 0.99NSE= 0.97NSE= 0.97
350
400
450
350
400
450
NIR
Measured(mm)
NIR Measured (mm)(a)(a)

350
350
300
300

y =y 1.0038x+ 3.9503= 1.0038x+ 3.9503
r²r²= 0.98= 0.98NSE= 0.96NSE= 0.96250250
250
250 300
300 350350 400
400 450450
NIR
Measured(mm)
NIR
Measured(mm)(b)(b)

Figure7. Correlation
betweenmeasuredandsimulated
netnetirrigation
requirements
(NIR)
in in
thethe(a)(a)
springand(b) summer
Figure7. Correlation
betweenmeasuredandsimulated
irrigation
requirements(NIR)
springandFigure7. Correlation
betweenmeasuredandsimulated
net irrigation
requirements(NIR)
in the(a) springand (b)(b) summer
sumseason.
season.
mer season.

4. Conclusions
Conclusions
4.
Conclusions
4.
Most
of of
Pakistan
is aridarid
to semiarid
semiarid
and
faces
water
scarcity.
A limited
limitedsupplyof of
Most
Pakistanisaridtosemiarid
and
faces
water
scarcity.
AlimitedsupplyMostofPakistan
is
to
and
faces
water
scarcity.
A
supplyofirrigation
water
makes
agricultural
production
in
this
regionmore
expensive.
Therefore,
irrigation
water
makes
agricultural
production
thisregionmore
expensive.
Therefore,
irrigation
water
makes
agricultural
production
in in
this
regionmore
expensive.
Therefore,
thethedevelopment
of ofwater-saving
agricultural
practices
is required
required
to to
cope
with
water
development
water-saving
agricultural
practicesisrequired
cope
with
water
the
developmentofwater-saving
agricultural
practices
is
to
cope
with
water
shortages
duringdifferent
growthstages
of
the
maize
crop
in
Pakistan.
It
wasconcluded
shortages
duringdifferent
growthstagesof themaize
crop
in Pakistan.
It wasconcluded
shortages
duringdifferent
growthstagesof themaize
crop
in Pakistan.
It wasconcluded
fromthetheresults
of
this
study
that
inin
Pakistan,thethesowingof ofsummer
maize
is is
more
proffromtheresults
ofof
this
study
that
Pakistan,thesowingofsummersummermaize
is morefromresults
this
study
that
Pakistan,sowingmaize
more
profitablecomparedto tospring-sown
maize.
Experimental
resultsalso
showedthatdifferent
profitablecomparedto spring-sown
spring-sown
maize.
Experimental
resultsalso
showedthatdifferent
itablecomparedmaize.
Experimental
resultsalso
showedthatdifferent
irrigation
techniqueshavesignificantly
affectedthethewateruse
efficiency,
thetheirrigation
irrigation
techniqueshavesignificantly
affected
the
water
use
efficiency,
theirrigation
irrigation
techniqueshavesignificantly
affectedwater
use
efficiency,
irrigation
water
use
efficiency,
the
soil
water
balance,andcropyield.
The
best
results
wereobtainedwater
useuseefficiency,
thethesoilsoilwaterbalance,andandcrop
yield.
TheThebest
results
wereobtainedwater
efficiency,
waterbalance,cropyield.
best
results
wereobtained
forforthethefurrow-irrigatedraisedbed
coveredwithplastic
mulch
treatment.
Results
furtherforthefurrow-irrigatedraisedbed
coveredwithplastic
mulch
treatment.
Results
further
furrow-irrigatedraisedbed
coveredwithplastic
mulch
treatment.
Results
furthershowedthat
thistreatment
also
producedanan
increase
insoilsoil
water
storage.
Ourfindings
showedthat
thistreatment
also
produced
anincreaseinwater
storage.
Ourfindings
showedthat
thistreatment
also
produced
increase
in
soil
water
storage.
Ourfindings
furtherclarifiedthat
theIrrigation
Irrigation
Management
SystemSoftwarecould
beeffectiveananeffective
furtherclarifiedthattheManagement
SystemSoftware
could
be an
tool
furtherclarifiedthat
the
Irrigation
Management
SystemSoftwarecouldbeeffective
tool
for
irrigation
schedulingforsuccessful
cropproduction
inPakistan’s
semiarid
re-reforirrigation
schedulingforsuccessful
cropproduction
inPakistan’s
semiarid
regions.
We
tool for irrigation scheduling for successful crop production in Pakistan’s semiarid
gions.
We
recommendtothefarmersof
thisregiontouse
thissoftwareforirrigation
recommendtothefarmersof
thisregiontouse
thissoftwareforirrigation
scheduling.
gions. We recommend to the farmers of this region to use this software for irrigation
scheduling.
scheduling.

Author Contributions: Conceptualization, A.G.K., A.-u.-H.K., A.F., J.Š., A.A.A., M.N.A. and S.A.;
Data
curation,
A.G.K. andConceptualization,
M.I.;
Formal analysis,
A.G.K.,
M.I. and T.U.-H.;
Fundingacquisition,
A.A.A.
AuthorContributions:
A.G.K.,
A.-u.-H.K.,
A.F.,
J.Š.,
A.A.A.,
M.N.A.
andS.A.;
AuthorContributions:Conceptualization,
A.G.K.,
A.-u.-H.K.,
A.F.,
J.Š.,
A.A.A.,
M.N.A.
and
S.A.;
and
M.N.A.;
Investigation,
M.I.,
A.F.
and
T.U.-H.;
Methodology,
A.G.K.,M.I.
andT.U.-H.;
Project
Data
curation,
A.G.K.
andM.I.;
Formalanalysis,
A.G.K.,M.I.
and
T.-u.-H.;
Fundingacquisition,
Data curation, A.G.K. and M.I.; Formal analysis, A.G.K., M.I. and T.-u.-H.; Funding acquisition,
administration,
J.Š.; Resources,
A.-u.-H.K.,
J.Š.,T.U.-H.,
A.A.A.
and M.N.A.;
Software,A.-u.-H.K.,
A.A.A.
and
M.N.A.;
Investigation,
M.I.,
A.F.
and
T.U.;
Methodology,
A.G.K.,
M.I.
and
T.U.;
Project
A.A.A.
and
M.N.A.;
Investigation,
M.I.,
A.F.
and
T.U.;
Methodology,
A.G.K.,
M.I.
and
T.U.;
Project
A.F.
and
S.A.;
Supervision,
A.-u.-H.K.;
Validation,
A.G.K.
and
M.I.;
Visualization,
M.I.
andT.U.-H.;administration,
J.Š.;Resources,
A.-u.-H.K.,
J.Š.,T.-u.-H.,
A.A.A.
and
M.N.A.;
Software,A.-u.-H.K.,
administration, J.Š.; Resources, A.-u.-H.K., J.Š., T.-u.-H., A.A.A. and M.N.A.; Software, A.-u.-H.K.,
Writing—originaldraft, A.G.K.,
M.I., A.A.A.
and S.A.;
Writing—review& editing,M.I.
A.-u.-H.K.,
A.F.,
A.F.
and
S.A.;
Supervision,
A.-u.-H.K.;
Validation,
A.G.K.
and
M.I.;
Visualization,
andT.-u.-H.;
A.F.
and
S.A.;
Supervision,
A.-u.-H.K.;
Validation,
A.G.K.
and
M.I.;
Visualization,
M.I.
andT.-u.-H.;
Writing—originaldraft,
A.G.K.,M.I.,
A.A.A.
andS.A.;
Writing—review& editing,A.-u.-H.K.,
A.F.,
J.Š.,
M.N.A. and S.A.
All
authors
have
read
and
agreedto Writing—review
the published versionof themanuscript.
Writing—originaldraft,
A.G.K.,M.I.,
A.A.A.
andS.A.;& editing,A.-u.-H.K.,
A.F.,
J.Š.,
M.N.A.
andS.A.
AllAllauthors
have
read
and
agreedto tothethepublishedversionof ofthethemanuscript.
J.Š.,M.N.A.
andS.A.
authors
have
read
and
agreedpublishedversionmanuscript.

Sustainability 2021, 13, 2757

12 of 13

Funding: This research was partially supported by the Higher Education Commission, Pakistan,under IRSPI Program. The authors would like to extend their sincere appreciation to the Researchers
Supporting Project Number (RSP-2020/180), King Saud University, Riyadh, Saudi Arabia.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments: This research was partially supported by the Higher Education Commission of
Pakistan. The authors would like to extend their sincere appreciation to the University of Agriculture,
Faisalabad. The authors would like to extend their sincere appreciation to the Researchers Supporting
Project Number (RSP-2020/180), King Saud University, Riyadh, Saudi Arabia.
Conflicts of Interest: The authors declare no conflict of interest.

References
1.
2.
3.

4.
5.
6.
7.
8.
9.
10.
11.

12.
13.
14.
15.
16.
17.
18.
19.
20.
21.

22.

Wolf, T.A. (Ed.) Conflict Prevention and Resolution in Water Systems; Edward Elgar Publishing Ltd: Cheltenham, UK, 2002.
Seckler, D.; Upali, A.; Molden, D.; de Silva, R.; Barker, R. World Water Demand and Supply, 1990 to 2025: Scenarios and Issues.
Research Report 19; Iwmi: Colombo, Sri Lanka, 1998.
Kahlown, A.; Ashraf, M.; Hussain, M.; Salam, A.; Bhatti, A. Impact Assessment of Sewerage and Industrial Effluents on Water Resources,
Soil, Crops and Human Health in Faisalabad; Pakistan Council of Research in Water Resources (PCRWR), Khyaban-e-Johar, H-8/1:
Islamabad, Pakistan, 2006.
Abdelrahman, M.A.E.; Arafat, S.M. An Approach of Agricultural Courses for Soil Conservation Based on Crop Soil Suitability
Using Geomatics. Earth Syst. Environ. 2020. [CrossRef]
FAO. Progress on Water Use Efficiency—Global Baseline for SDG 6 Indicator 6.4.1 2018; FAO: Rome, Italy, 2018.
Byrne, J.; Quinn, G.; Mpitsos, J.; Lederhendler, I.; Belardetti, F.; Biondi, C. Plant Productivity and Environment. Science 1982, 218,
443–448.
Khan, S.; Abbas, A. Upscaling water savings from farm to irrigation system level using gis-based agro-hydrological modelling.
Irrig. Drain. J. Int. Comm. Irrig. Drain. 2007, 42, 29–42. [CrossRef]
Govaerts, B.; Sayre, K.D.; Deckers, J. Stable high yields with zero tillage and permanent bed planting? Field Crops Res. 2005, 94,
33–42. [CrossRef]
Fang, Q.; Ma, L.; Yu, Q.; Ahuja, L.R.; Malone, R.W.; Hoogenboom, G. Irrigation strategies to improve the water use efficiency ofwheat–maize double cropping systems in North China Plain. Agric. Water Manag. 2010, 97, 1165–1174. [CrossRef]
Kang, S.Z.; Zhang, L.; Liang, Y.L.; Hu, X.T.; Cai, H.J.; Gu, B.J. Effects of limited irrigation on yield and water use efficiency of
winter wheat in the Loess Plateau of China. Agric. Water Manag. 2002, 55, 203–216. [CrossRef]
Sayre, K.D. Effect of tillage, crop residue retention and nitrogen management on the performance of bed planting, furrow irrigatedspring wheat in Northwest Mexico. In Proceedings of the 15th Conference International Soil and Tillage Research Organization,
Fort Worth, TX, USA, 2–7 July 2000.
Hassan, I.; Hussain, Z.; Akbar, G. Effect of permanent raised beds on water productivity for irrigated maize–wheat cropping
system. Eval. Perform. Perm. Rais. Bed Crop. Syst. Asia Aust. Mex. 2005, 121, 59–65.
Jay, L.; Jack, K.; Janet, K.L.; Thomas, B.K. Surface and Agricultural Water; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2005.
Sharma, S.K. Principles and Practices of Irrigation Engineering; Oxford and IBH Publication Co.: New York, NY, USA, 1984.
Haq, N. Evaluation of Modern Irrigation Techniques for Sandy Loam Soil Having Low Slopes. Master’s Thesis, Department of
Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan, 1990.
El Shirbeny, M.A.; Ali, A.M.; Savin, I.; Poddubskiy, A.; Dokukin, P. Agricultural Water Monitoring for Water Management Under
Pivot Irrigation System Using Spatial Techniques. Earth Syst. Environ. 2020. [CrossRef]
Li, X.Y.; Gong, J.D.; Gao, Q.Z.; Li, F.R. Incorporation of ridge and furrow method of rainfall harvesting with mulching for crop
production under semiarid conditions. Agric. Water Manag. 2001, 50, 173–183. [CrossRef]
Li, X.Y.; Gong, J.D. Effects of different ridge:furrow ratios and supplemental irrigation on crop production in ridge and furrow
rainfall harvesting system with mulches. Agric. Water Manag. 2002, 54, 243–254. [CrossRef]
Alewoye Getie, M.; Legesse, S.A.; Mekonnen, M.; Aschalew, A. Soil Properties and Crop Productivity Strategies as a Potential
Climate Variability Adaptation Options in Adefwuha Watershed, Ethiopia. Earth Syst. Environ. 2020, 4, 359–368. [CrossRef]
Sarmah, A.K.; Kookana, R.S.; Alston, A.M. Application of varleach and leachm models to experimental data on leaching of a
non-reactive tracer and three sulfonylurea herbicides. Aust. J. Soil Res. 2001, 39, 1041–1058. [CrossRef]
Fares, A. Water Management Software to Estimate Crop Irrigation Requirements or Consumptive Use Permitting In Hawaii; Departmentof Land and Natural Resources: Honolulu, HI, USA, 2008. Available online: http://treephys.oxfordjournals.org/cgi/reprint/15/9/611 (accessed on 26 December 2020).
Khan, A.G.; Iqbal, M.; Ullah, E. Assessing the performance of different irrigation techniques to enhance the water use efficiency
and yield of maize under deficit water supply The treatments consisted of four irrigation practices. Soil Environ. 2015, 34, 166–179.

Sustainability 2021, 13, 2757

23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.

39.
40.

41.
42.
43.

44.
45.
46.
47.

13 of 13

Finance Disvision, Government of Pakistan. Annonymous Economic Survey of Pakistan. 2018. Available online: http://www.
finance.gov.pk/survey/chapters_19/Economic_Survey_2018_19.pdf (accessed on 26 December 2020).
Bouyoucos, G.J. Hydrometer method improved for making particle size analyses of soils. Agron. J. 1962, 54, 464. [CrossRef]
Ryan, J.; Estefan, G.; Rashid, A. Soil and Plant Analysis Laboratory Manual; ICARDA: Aleppo, Syria, 2001.
Dane, J.H.; Hopmans, J.W. Laboratory Determination of Water Retention; Dane, J.H., Topp, G.C., Eds.; Method.; Soil Science Societyof America, Inc.: Madison, WI, USA, 2002.
Blake, G.R.; Hartge, K.H. Bulk density. In Methods of Soil Analysis, Part 1. Physical and Mineralogical Methods, Agronomy MonographNo. 9, 2nd ed.; Klute, A., Ed.; Wiley Online Library: Madison, WI, USA, 1986; pp. 363–375.
Dwyer, L.M.; Stewart, D.W. Leaf Area Development in Field-Grown Maize. Agron. J. 1986, 78, 334–343. [CrossRef]
Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements; FAO
Irrigation and Drainage Paper 56; Food and Agriculture Organization of the United Nations: Rome, Italy, 1998.
Cassel, D.K.; Nielsen, D.R. Field Capacity and Available Water Capacity; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2018; pp.
901–926.
Hussain, G.; Al-Jaloud, A.A.; AI-Shammary, S.F.; Karimulla, S. Effect of saline irrigation on the biomass yield and the protein,nitrogen, phosphorus and potassium composition of alfalfa in a pot experiment. J. Plant Nutr. 1995, 18, 2389–2408. [CrossRef]
Fares, A.; Fares, S. Irrigation Management System, IMANSYS, a User-Friendly Computer-Based Water Management Software
Package. In Proceedings of the Irrigation Show and Education Conference, Orlando, FL, USA, 2–6 November 2012.
Nash, J.E.; Sutcliffe, J.V. River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol. 1970, 10,282–290. [CrossRef]
Steel, R.G.D.; Torrie, J.H.; Dicky, D.A. Principles and Procedures of Statistics- A Biometrical Approach, 3rd ed.; McGraw Hill Book
International Co.: New York, NY, USA, 1997; pp. 352–358.
StatSoft, Inc. STATISTICA. Data Analysis Software System, Version 8. 2001. Available online: http://www.statsoft.com (accessedon 14 February 2018).
Wang, F.H.; Wang, X.Q.; Sayre, K. Conventional, flood irrigated, flat planting with furrow irrigated, raised bed planting for winterwheat in China. Field Crop Res. 2004, 87, 35–42.
Li, S.X.; Wang, Z.H.; Li, S.Q.; Gao, Y.J.; Tian, X.H. Effect of plastic sheet mulch, wheat straw mulch, and maize growth on water
loss by evaporation in dryland areas of China. Agric. Water Manag. 2013, 116, 39–49. [CrossRef]
Zhou, J.; Wang, C.; Zhang, H.; Dong, F.; Zheng, X.; Gale, W.; Li, S. Effect of water saving management practices and nitrogen
fertilizer rate on crop yield and water use efficiency in a winter wheat-summer maize cropping system. Field Crops Res. 2011, 122,
157–163. [CrossRef]
Sun, H.Y.; Liu, C.M.; Zhang, X.Y.; Shen, Y.J.; Zhang, Y.Q. Effects of irrigation on water balance, yield and WUE of winter wheat in
the North China Plain. Agric. Water Manag. 2006, 85, 211–218. [CrossRef]
Jat, M.L.; Srivastava, A.; Sharma, S.K.; Gupta, R.K.; Zaidi, P.H.; Rai, H.K.; Srinivasan, G. Evaluation of maize-wheat cropping
system under double-no-till practice in indo-gangetic plains of India. In Proceedings of the Asian Regional Maize Workshop,
Beijing, China, 5–9 September 2005.
Deng, X.P.; Shan, L.; Zhang, H.; Turner, N.C. Improving agricultural water use efficiency in arid and semiarid areas of China. In
Agricultural Water Management; Elsevier: Amsterdam, The Netherlands, 2006; Volume 80, pp. 23–40.
Saif, U.; Masood, M.; Farooq, M.; Hussain, S.; Habib, A. Effect of planting patterns and different irrigation levels on yield andyield component of Maize (Zea mays L.). Int. J. Agric. Biol. 2003, 5, 64–66.
Hamilton, G. Refinement and Adoption of Permanent Raised Bed Technology for the Irrigated Maize-Wheat Cropping System in Pakistan;
Australian Centre for International Agricultural Research: Canberra, Australia, 2006. Available online: http://www.aciar.gov.au/
project/LWR/2002/034 (accessed on 26 December 2020).
Hobbs, P.R.; Singh, Y.; Giri, G.S.; Lauren, J.G.; Duxbury, J.M. Direct Seeding and Reduced Tillage Options in the Rice-Wheat Systems of
the Indo-Gangetic Plains of South Asia; IRRI workshop: Bangkok, Thailand, 2000; pp. 25–26.
Abbas, G.; Hussain, A.; Ahmad, A.; Wajid, S.A. Water use efficiency of maize as affected by irrigation schedules and nitrogenrates. J. Agric. Soc. Sci. 2005, 1, 339–342.
Huang, Y.L.; Chen, L.D.; Fu, B.J.; Huang, Z.L.; Gong, J. The wheat yields and water-use efficiency in the Loess Plateau: Straw
mulch and irrigation effects. Agric. Water Manag. 2005, 72, 209–222. [CrossRef]
Zhang, S.L.; Lövdahl, L.; Grip, H.; Tong, Y.A.; Yang, X.Y.; Wang, Q.J. Effects of mulching and catch cropping on soil temperature,soil moisture and wheat yield on the Loess Plateau of China. Soil Tillage Res. 2009, 102, 78–86. [CrossRef]