modelling of nitrogen leaching from experimental onion field under drip fertigation
TRANSCRIPT
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8
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Modelling of nitrogen leaching from experimental onionfield under drip fertigation
Khalil Ajdary a, D.K. Singh b,*, A.K. Singh b, Manoj Khanna b
a Shahrood University of Technology, IranbWater Technology Centre, Indian Agricultural Research Centre, New Delhi 110012, India
a r t i c l e i n f o
Article history:
Accepted 10 December 2006
Published on line 5 February 2007
Keywords:
Drip fertigation
Fertigation strategies
Nitrogen leaching
Modelling
a b s t r a c t
Instances of groundwater pollution from use of nitrogenous fertilizer are at increase in
recent years. With increase in area under cultivation and regular use of fertilizer in irrigated
agriculture, groundwater pollution from agricultural activities is becoming a major concern
in India. This requires appropriate water and nutrient management to minimize ground-
water pollution and, maximize the nutrient use efficiency and production. Drip fertigation is
an alternative, which improves water and nutrient use efficiency with higher production
and minimum effect on groundwater quality. Appropriate design of drip fertigation system
requires detailed knowledge of water and nutrient distribution pattern and nutrient avail-
ability in root zone and, nutrient leaching below root zone in different types of soils under
varying emitter discharge rates and fertigation strategies. Design and operation of drip
fertigation system requires more understanding of nutrient leaching behaviour in case of
shallow rooted crops like onion, which cannot extract nutrient from lower soil profile
leaving more scope for nitrogen leaching. Present study was undertaken to asses the
nitrogen leaching from onion field under drip fertigation system. The study involved field
experimentation for 2 years on onion crop under drip fertigation. Field data were collected
on spatial and temporal distribution of water and available nitrogen in the growing season
to calibrate and validate the solute transport model. A two-dimensional solute transport
model HYDRUS-2D was applied to simulate the nitrogen leaching from various soils for
varying emitter discharge rates and fertigation strategies. It was found that more permeable
soils like sandy loam is prone to nitrogen leaching compared to less permeable soils.
Nitrogen leaching from loam and sandy loam soils was negligible. Effect of soil type on
nitrogen leaching was more than the emitter discharge rates. Fertigation strategies did not
affect the nitrogen leaching as commonly perceived. Increased emitter discharge rates did
not affect the nitrogen leaching except in coarse textured soils like sandy loam. Outward
spreading of nitrogen was more in fine textured silt clay loam and silt soils. In all the
scenarios, adequate nitrogen availability was maintained in the root zone. Based on the
results, it is reported that with selection of appropriate emitter discharge, irrigation duration
and irrigation interval, and nitrogen leaching even from fields under shallow rooted crops
# 2007 Elsevier B.V. All rights reserved.
can be minimized.
* Corresponding author. Tel.: +91 1125846790.E-mail address: [email protected] (D.K. Singh).
0378-3774/$ – see front matter # 2007 Elsevier B.V. All rights reserved.doi:10.1016/j.agwat.2006.12.014
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 816
1. Introduction
Nitrogen (N) is an essential plant nutrient, which is taken up by
the crops throughout the growing season. Most common
forms of nitrogen found in the soils are organic N, ammonium
(NH4+), nitrate (NO3
2�), and gaseous nitrogen (NH3, N2).
Mineralization and nitrification processes convert the organic
N and NH4+ into NH4
+ and NO32�, respectively which are
absorbed and utilized by crops and termed as available
nitrogen. Nitrate is highly mobile and leachable. It has been
established that excessive application of nitrogen leads to
nitrate pollution of groundwater and surface water (Hayens,
1985; Waskom, 1994). Studies conducted in India, suggest that
groundwater pollution due to nitrate leaching is becoming a
serious problem particularly in agriculturally developed states
such as Punjab, Haryana, Andhra Pradesh, Maharashtra,
where fertilizer applications are high (Singh et al., 1994;
Agrawal et al., 1999). Nitrate leaching potential depends on soil
properties, crops and crop rotation, irrigation methods,
management practices and climatic parameters. This neces-
sitates the development of appropriate water and fertilizer
application strategies so as to maximize their application
efficiency and minimize fertilizer losses through leaching.
Fertigation is the process of application of soluble fertilizer
along with irrigation. When fertilizer is applied through drip
irrigation system, it is referred to as drip fertigation. Applica-
tion of water and fertilizer through drip irrigation improves
water and nutrient use efficiency and aims at maximizing
farmer’s income and minimizing pollution. Drip fertigation
offers various advantages such as: easy application of amount
and concentration of nutrients suited to the crop according to
its stage of development and climatic conditions; reduces the
salinization and groundwater pollution; decreases fluctuation
in nutrient concentration in soil during the crop growing
season; permits easy use of soluble solid as well as balanced
liquid fertilizer and micronutrients (Bar-Yosef, 1999). It
prevents wetting of crop foliage thus controls the attack of
pathogens (Yarwood, 1978).
Wetting pattern in the soil and the spatial distribution of
soil water, matric potentials, and nitrate concentrations
depend on soil hydraulic properties, emitter discharge rates,
spacing, and their placement, irrigation amount and fre-
quency, crop water uptake rates and root distribution patterns
(Gardenas et al., 2005). A better understanding of the
interactions of irrigation method, soil type, crop root distribu-
tion, and uptake patterns and rates of water and nutrients
provides improved means for proper and efficient micro-
irrigation water management practices (Hopmans and Bris-
tow, 2002). A properly designed drip fertigation systems
delivers water and nutrients at a rate, duration and frequency,
so as to maximize crop water and nutrient uptake, while
minimizing leaching of nutrients and chemicals from the root
zone of agricultural fields (Gardenas et al., 2005).
Appropriate design of drip fertigation system requires
detailed knowledge of water and nutrient distribution pattern
in the root zone, nutrient availability in the vicinity of roots
and nutrient leaching below the root zone which is the
function of discharge of emitter and soil hydraulic and
physical properties. Though, some guidelines are available
to install, maintain and operate drip irrigation systems
(Hanson et al., 1996), there are no clear guidelines for design
and managing drip irrigation systems that account for
differences in soil hydraulic properties (Cote et al., 2003).
Conducting field experiments in large number of soils with
varying emitter discharge rates to investigate water and
nutrient distribution for evolving appropriate design and
management option is a costly and time consuming affair. A
properly calibrated and validated flow and solute transport
model can reduce time and cost required for studying the
water and nutrient dynamics under drip irrigation system.
Models provide an understanding of the relationship amongst
the amount and timing of water and nutrient application, the
crop root uptake, yield and soil hazard and groundwater
pollution (Antonopoulos, 2001). However, selection of an
appropriate model is very important. Several models have
been developed to simulate water flow, nutrient transport,
heat flux, crop water and nutrient uptake and biological
transformation of nutrients in the soil (Bergstrom et al., 1991;
Huston and Wagenet, 1991; Jarvis, 1995; Gabriella and Kenjeni,
1996; Breve et al., 1997; Lafolie et al., 1997). Most of these
models describe the early stage of infiltration and provide an
estimate of water content behind the wetting front (Clothier
and Scotter, 1982). Although they are easy to implement, they
deal mainly with design considerations of the drip source
(Cote et al., 2003). Analytical solutions of transient axi-
symmetrical infiltration (Warrick, 1974; Revol et al., 1997)
can simulate the dynamic condition associated with the drip
irrigation but their application was limited in simulation of
water and nutrient movement under drip fertigation system
under simple boundary conditions. An appropriate fertigation
guideline can be developed using modeling approaches. There
are few soil and crop specific guidelines for designing and
managing irrigation/fertigation systems that minimize nitrate
leaching, considering typical non-uniform distributions of soil
solution nitrate and crop uptake but few have investigated the
effect of fertigation management/irrigation management on
the spatial distribution and crop availability of supplied
nitrogen (Gardenas et al., 2005).
Cote et al. (2003) used a two-dimensional solute transport
model HYDRUS-2D to analyze the soil wetting and solute
transport in subsurface trickle irrigation under various
irrigation and fertigation strategies. They demonstrated that
fertigation at the beginning of the irrigation cycle might reduce
nitrate leaching under specific conditions. However, in their
study, they did not consider the nutrient uptake by plant.
Gardenas et al. (2005) investigated nitrate leaching from
citrus, grape, tomato and strawberry fields for various fertiga-
tion scenarios under micro-irrigation including surface drip
fertigation using HYDRUS-2D. In case of drip fertigation,
simulation was done for grape crop with the root depth of
2.0 m. Irrigation time and interval were 1.5 and 3.5 days,
respectively. They reported that seasonal leaching was the
highest for coarse-textured soils and that fertigation at the
beginning of the irrigation cycle increased seasonal nitrate
leaching in contrast to fertigation at the end of the irrigation
cycle, which reduced the potential for nitrate leaching in all
types of soils except surface drip and tapesystem inclayey soils.
The present study was conducted to model the nitrogen
leaching from onion field under surface drip fertigation. Onion
(Allium cepa L.) is an important crop in India. Area under onion
Fig. 1 – Layout of drip irrigation plot.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 17
cultivation in India increased from 0.21 to 0.45 million ha
during the period of 1978–1979 to 2000–2001 with increase in
total production from 2.20 to 4.80 million mt (Ministry of
Agriculture, Government of India, 2003). In India, onion is
cultivated under irrigated condition with adequate applica-
tion of fertilizer. Majority of the onion cultivator use flood or
basin irrigation method with top dressing or band applica-
tion of fertilizer. Recommended dose of fertilizer for onion in
India is 120 kg N, 50 kg P and 70 kg K/ha. Considerable
portion of the applied nitrogen is lost through leaching due
to frequent irrigation. Though, there is no estimate of
nitrogen losses from onion field at country level, considering
the large area under onion cultivation, the nitrogen losses
from the onion field could be substantial. Leaching losses of
nitrogen can be minimized if fertilizer is applied through
drip fertigation. Improper fertigation strategies might lead to
loss of nitrogen fertilizer in form of leaching resulting in
groundwater pollution. It has been reported (Gardenas et al.,
2005) that even if the rate of water application is equal or less
than the evapotranspiration rate, water and nitrate leaching
might occur. Onion is a shallow rooted crop with most of the
roots confined within 30 cm depth of soil. This facilitates the
loss of mobile nutrient such as nitrogen and sulphur by
excessive irrigation compared to the deep-rooted crops.
Therefore, water and nitrogen management in onion is very
important from production and nitrogen losses view points.
The main objective of the study was to determine the
nitrogen leaching below root zone from various types of soils
for various irrigation and fertigation strategies using a solute
transport model HYDRUS-2D. The study involved field
experiment and modeling of nitrogen leaching. Field data
were used to calibrate and validate the solute transport
model. The results of the study could be of great help to
onion cultivators in selecting appropriate irrigation and
fertigation strategies to minimize the nitrogen leaching and
obtain a higher yield.
2. Materials and methods
2.1. Field experiment
Experiments were carried out in the years 2003 and 2004. The
growing season was from third week of January to last week of
May in both the years. The field experiments consisted of design
and installation of drip fertigation system, field observations
and samplings and analysis of soil samples. Drip laterals were
placed in the middle of the rows and spaced at 0.60 m to cover
the two rows of the crop. Row to row spacing was 30 cm.
Distance of the plant from emitter was 15 cm. Drip emitters
were placed on the lateral line at a spacing of 50 cm (Fig. 1).
2.1.1. Experimental siteThe experiment was conducted at the Indian Agricultural
Research Institute (IARI) Farm, New Delhi located between the
latitudes of 2883702200N and 388390N and longitudes of 778804500E
and 7781002400E at an average elevation of 230 m above mean
sea level.
Climate of Delhi is categorized as semi-arid, subtropical
with hot dry summer and cold winter. The mean annual
temperature is 24 8C. May and June are the hottest months
with 30 years normal maximum temperature of 39.7 8C.
January is the coldest month with a mean temperature of
14 8C however, the minimum temperature dips to as low as
1 8C. The mean annual rainfall is 710 mm of which as much as
75% is received during monsoon season (June to September).
Some winter showers are also received during December and
March. Frost occurs occasionally during the months of
December–January. Weather parameters recorded during
the period of experiment at the IARI are given in Table 1.
Soil samples were collected from different layers from
surface till the depth of 1.2 m and analyzed to determine
physical and chemical properties. Values of the physical
properties namely particle size distribution, bulk density, field
capacity, permanent wilting point and hydraulic conductivity
are presented in Table 2. Upper layer (0–15 cm) of soils was
classified as sandy loam. Lower layers (15–120 m) were sandy
clay loam. Chemical properties like pH, EC, organic carbon,
available nitrogen, phosphorous, and potassium are presented
in Table 3.
2.1.2. Irrigation and fertigation scheduleWater requirement of onion crop was estimated using the pan
evaporation data. Five years average daily pan evaporation
values were multiplied with the pan and crop coefficients to
estimate the daily crop water requirements. Irrigation
requirement was estimated by subtracting corresponding
effective rainfall. Irrigation was applied on alternate days
during the crop growing period (till 16th week), based on crop
water demand. Irrigation water was applied at the rate of 2.5 L/
h through drip emitters placed on the lateral line. Irrigation
was stopped 2 weeks before harvesting to allow the crop to
mature. Amount of water applied during each irrigation varied
with the water requirement of the onion and was regulated by
Table 1 – Weather parameters recorded during the period of experimentation
Year and month Temperature (8C) Relativehumidity (%)
Rainfall(mm)
Average dailyevaporation (mm)
Minimum Maximum
2003
January 5.7 16.3 82.0 41.6 1.6
February 9.7 21.7 95.0 28.4 2.7
March 13.8 28.1 58.0 24.6 4.8
April 20.2 37.2 42.0 0.0 7.8
May 24.0 39.4 40.0 7.4 9.8
2004
January 7.3 17.4 79.0 14.1 1.7
February 9.3 24.0 64.0 0.0 7.3
March 15.6 32.5 52.0 0.0 5.9
April 21.4 37.5 47.0 19.6 9.1
May 25.7 39.1 47.0 24.8 8.9
Table 2 – Physical properties of soil of the experimental field
Depth (cm) Mineral content % mass Textural class Hydraulicconductivity (cm/h)
Bulk density(g/cm3)
FC(vol.%)
PWP(vol.%)
Clay Silt Sand
0–15 16 12 72 Sandy loam 1.22 1.56 20.67 6.48
15–30 21 10 69 Sandy clay loam 1.39 1.63 26.17 8.10
30–45 24 20 56 Sandy clay loam 0.70 1.57 27.11 10.27
45–60 22 26 52 Sandy clay loam 1.09 1.56 26.36 10.84
60–75 19 26 55 Sandy clay loam 1.01 1.63 28.12 11.78
75–90 19 22 59 Sandy loam 1.21 1.63 28.89 10.81
90–120 17 26 57 Sandy clay loam 1.14 1.67 27.43 10.70
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 818
increasing or decreasing the duration of irrigation. Irrigation
interval was 48 h. Duration of irrigation during each irrigation
varied from 0.33 to 2.5 h. Total amount of water applied in the
entire growing period was 4630 m3/ha. Nitrogen fertilizer in
the form of urea was applied on weekly basis at the rate of
96 kg/ha through drip fertigation in a split doses in the first 12
weeks during growing period. During each fertigation,
fertilizer was applied in the beginning of irrigation for
0.166 h. The amount of nitrogen fertilizer applied per week
varied from 10 to 26 kg/ha depending on the growth stages and
requirement. Along with it, recommended doses of P (50 kg/
ha) and K (70 kg/ha) were given 10 times and 7 times,
respectively on weekly basis. However, analysis was done
only for N. Irrigation and fertigation schedule adopted in this
study were typical representative of the farmers practices for
cultivation of onion in India under drip fertigation.
2.1.3. Observations and analysisSoil samples were collected from different depths (0–0.15, 0.15–
0.30, 0.30–0.45, 0.45–0.60 m) and vertical planes located at
emitter and at 15 and 22.5 cm away from emitter periodically
Table 3 – Chemical properties of soil of the experimental field
Depth (cm) pH EC (ds/m) Organic carbon (%) NO3�N
0–15 7.2 0.17 0.27 31
15–30 7.2 0.13 0.22 43
30–45 7.2 0.11 0.13 28
45–60 7.1 0.11 0.13 34
(before fertigation, 2, 4, 24, 48, 52 and 72 h after fertigation) using
tube auger from the experimental area to determine spatial and
temporal distribution of water and, available nitrogen in the
growing season. These were analyzed to determine the
gravimetric moisture content and, ammonium and nitrate
forms of the available nitrogen. Kjeldahl method (Page et al.,
1982) was used to estimate the ammonium and nitrate forms of
the available nitrogen. In this method, distillation procedures
for determination of NH4+ and NO3
� involve steam distillation
with MgO and Devarda alloy. Soil sample was shaken with 2 M
KCl (10 mg/g of soil) for 1 h, and the extract from this was
analyzed by steam distillation. NH3 form of nitrogen liberated
by steam distillation was collected in H3BO3� indicator solution
and determined by titration with standard (0.005N) H2SO4.
2.2. Water and nutrient transport modeling
The modelling of nitrogen leaching from the onion field under
drip fertigation was carried out using the computer simulation
model, HYDRUS-2D (Simunek et al., 1999). It simulates
three-dimensional axially symmetric water flow; solute
(kg/ha) NH4�N (kg/ha) Available
N (kg/ha) P (kg/ha) K (kg/ha)
.36 47.04 78.40 20 170
.90 28.22 75.58 12 125
.22 26.65 71.08 4 110
.49 15.68 59.06 4 110
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 19
transport and root water and nutrient uptake based on finite-
element numerical solutions of the flow equations. The model
can implement a wide range of boundary conditions, irregular
boundaries, and soil heterogeneities.
Two-dimensional soil water flow in variably saturated,
rigid, isotropic porous medium under surface drip irrigation is
described by the modified form of Richards’ equation. The
equation is given by
@u
@t¼ @
@rKr
@h
@r
� �þ @
@zKz
@h
@z
� �� @K
@z�WUðh; r; zÞ (1)
where u is the volumetric water content [L3L�3], h the soil water
pressure head [L], t the time [T], r the radial coordinate [L], z the
vertical coordinate taken positive upwards [L], K the unsatu-
rated hydraulic conductivity function [LT�1] and WU(h,r,z)
defines root water uptake [T�1]. The axi-symmetrical form
of Eq. (1) is used in this study to simulate water flow under
surface drip emitter system. This equation was solved with
the HYDRUS-2D model using Galerkin finite element method.
The hydraulic relationships defined by van Genuchten (1980)
were used in this study.
The root water uptake WU in Eq. (1) was computed from
WUðh; r; zÞ ¼ gðhÞRDFðr; zÞWTpot (2)
where g(h) is the soil water stress function (dimensionless) of
Feddes et al. (1978). RDF is the normalized root water uptake
distribution [T�1], Tpot the potential transpiration rate [LT�1],
and W is the radius of the soil surface [L], associated with the
transpiration process. For the present study, the root distribu-
tion was assumed as uniform in time.
Solute transport in soil under surface drip fertigation
system is controlled by physical transport. Solute flow is
considered to be influenced mainly by soil properties and drip
emitter discharge rates. In this study, chemical and biological
interactions were not considered. The governing equation for
the simulation of the transport of a single non-reactive ion in
homogeneous medium in three dimensional axi-symmetrical
with polar coordinate system, in advection-dispersion form as
given by Bear (1972) and modified by (Simunek et al., 1999) by
adding nutrient uptake parameter, is as follows:
@uC
@t¼ @
@ruDrr
@C
@rþ uDrz
@C
@z
� �þ 1
ruDrr
@C
@rþ uDrz
@C
@z
� �þ @
@zuDzz
@C
@zþ uDrz
@C
@r
� �� �� @qrC
@rþ qrC
rþ @qzC
@z
� ��NUðC; r; z; tÞ (3)
where C [ML�3] is solute concentration in the soil water, qr and
qz [LT�1] are the components of the volumetric flux density,
Drr, Dzz and Drz [L2T�1] are the components of the dispersion
tensor. These components are given by Bear (1972). First term
on the right side is solute flux due to dispersion, the second
term is solute flux due to convection with flowing water and
third term is nutrient uptake by root:
uDrr ¼ eLq2r
jqj þ eTq2z
jqj þ utD0 (4)
q2z q2
r
uDzz ¼ eL jqj þ eT jqj þ utD0 (5)uDrz ¼ ðeL � eTÞqrqzjqj (6)
where jqj [LT�1] is the absolute value of the volumetric flux
density, eL and eT [L] are the longitudinal and transversal
dispersivities. D0 [L2T�1] is the molecular diffusion coefficient
of the solute in free water, and t is the tortuosity factor. The NU
term defines the local passive nitrate uptake [ML�3T�1] by
plant roots, which is function of space and time and is com-
puted from water uptake value using
NUðr; z; tÞ ¼ cðr; z; tÞWUðr; z; tÞ (7)
In present study, mineralization gains and denitrification
losses were neglected.
2.2.1. Calibration and validationModel was calibrated for hydraulic conductivity and disper-
sivity values for the soil of experimental area with the values
of water and nitrogen at various points, observed in the root
zone with respect to the emitter, at 4, 24, 48, 52 and 72 h after
fertigation. Model was run by giving the required input
parameters. The various parameters namely saturated water
content, residual water content, empirical factors and
saturated hydraulic conductivity, for loam, silty clay loam
and silt soils were taken from the HYDRUS-2D soil catalogue.
For sandy clay loam and sandy loam soils, Neural Network
prediction model available in HYDRUS-2D was used to
estimate these parameters except saturated hydraulic con-
ductivity by giving the exact values of clay, silt and sand
percentage. Saturated hydraulic conductivity of these soils
was obtained from the field experiment.
Modelpredictedvalueswerecomparedwithobservedvalues
and the values of the calibrated parameters were selected from
the runwhen predicted and observed values were close enough.
After calibration, model was validated with the seasonal data to
examine its predictability. To validate the model, simulation
was done for whole crop growing period of 125 days to predict
water and nitrogen distribution and leaching.
2.2.2. System geometryDue to the symmetry of the emitter layout, and assuming that
each emitter discharges water at the same flow rate, entire
field was subdivided into identical volume elements with a
emitter placed at the surface on the plane of symmetry. Water
and nitrogen patterns in the entire field can be described by
analyzing the flow in this single volume element irrigated by
single emitter. Because of the axial symmetry around the
vertical axis, the infiltration process can be viewed as an axi-
symmetrical flow with the radius r [L] and the depth z [L] as key
variables. In the present study, radius r was taken as 30 cm
(half of the lateral to lateral spacing) and depth z as 60 cm. This
was done because onion is a shallow rooted crop and nutrient
leaching below 60 cm depth will not be available to the plant.
The flux radius was taken equal to the wetted radius
Fig. 2 – Conceptual diagram of simulated area.
Fig. 3 – Relative root distribution of onion.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 820
considering emitter in centre. Surface area for irrigation
resulting from a single emitter without causing ponding was
determined from the flux radius and flux per unit area. Fig. 2
shows the conceptual diagram of simulated area.
2.2.3. Initial and boundary conditionsInitial condition for water was given as initial water content in
different soil layers within the flow domain, as observed in the
experimental field. Initial available nitrogen concentration as
observed in various soil layers within the flow domain was
given as initial condition for solute concentration. For all
simulations, on the sides of the flow domain, it was assumed
that no flow of water and nitrogen took place and hence no-
flux boundary condition was chosen, which in HYDRUS-2D is
specified for impermeable boundaries where the flux is zero
perpendicular to the boundary. In the present study, water
table was situated far below the domain of interest and
therefore free drainage boundary condition at the base of the
soil profile was considered. Bottom boundary was considered
as free drainage boundary. The system was conceptually
divided into four layers based on the variability of the soil
physical properties. The whole simulated region was divided
into the element of size 1 cm � 3.16 cm. To account the emitter
discharge during the irrigation, a flux type boundary condition
with constant volumetric application rate of emitter for
irrigation duration was considered. During no irrigation
period, flux was kept as zero. Time variable boundary
condition option in HYDRUS-2D was used to manage the flux
boundary during irrigation and no irrigation period. This was
done to take into account the irrigation and no irrigation
periods and temporal changes in duration of irrigation in the
growing period. A constant flux was estimated by dividing
emitter discharge with wetted surface area. Solute was applied
with irrigation water and a third-type Cauchy boundary
condition was used to prescribe the concentration flux along
flux radius at the top boundary. Concentration of incoming
water was specified in mg/mL. In case of drip fertigation,
solute flux is the product of water infiltration and dissolved
nitrate concentration. Cumulative nitrogen leaching below
the root zone, i.e. lower boundary of flow domen is controlled
by nitrate concentration at depth and the corresponding
water flux.
Potential root water uptake may be distributed non-
uniformly over a root zone. The maximum root water uptake
distribution is time independent (scaled to a potential ET rate
of unity and assuming no water or salinity stress). However,
the root water uptake rate itself may be time dependent. The
maximum root water uptake distribution reflects the distribu-
tion in the root zone of roots that are actively involved in water
uptake. Distribution of roots in the root zone in relative term
with onion plant in the middle is shown in Fig. 3. The root zone
having maximum root density was assigned the value of 1.
Root distribution was assumed to be constant through out the
growing season. Simulation depth and maximum root depth
was taken as 60 and 30 cm, respectively.
For all simulated scenarios, the crop evapotranspiration
was computed from the product of reference evapotranspira-
tion (using weather data) and crop coefficient. This was
bifurcated into evaporation and transpiration as required by
HYDRUS-2D from the procedure described by Supit and Van
der Goot (2003). In this procedure, evaporation from soil is
estimated as a function of leaf area index (Ritchie, 1971, 1972;
Goudriaan, 1977)
2.2.4. Input parametersFor the various input parameters required in HYDRUS-2D
namely saturated water content (us), residual water content (ur)
and empirical factors (a, n) (except saturated hydraulic
conductivity Ks) for sandy clay loam soil, Neural Network
Prediction option available in HYDRUS-2D was used by
assigning the values of clay, silt and sand percentage.
Saturated hydraulic conductivity of sandy clay loam was
obtained from field experiment. Soils considered for simula-
Table 4 – Soil hydraulic parameters for sand clay loam soil of experimental site
Soil layer Qr (ur) (cm3/cm3) Qs (us) (cm3/cm3) Alpha (a) (cm�1) n Ks (cm/h)
1 0.0404 0.3741 0.0079 1.4202 1.09
2 0.0395 0.3749 0.0059 1.4736 0.7
3 0.0337 0.3606 0.0048 1.5252 1.39
4 0.0262 0.3681 0.0142 1.3874 1.22
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 21
tion were isotropic. Values of longitudinal and transverse
dispersivity were taken as 0.3 and 0.03 cm, respectively. This
was confirmed through calibration process. Molecular diffu-
sion was neglected. The l value was set to 0.5. Values of the
hydraulic parameters of the sandy clay loam soil is presented
in Table 4. During calibration runs, simulation period was kept
to 168 h, which included one fertigation (for 0.166 h in the
beginning of irrigation) and two irrigation events (for 0.33 h at
the interval of 48 h). Water flux during each irrigation event
was equal to 1.27 cm/h and duration of irrigation varied (from
0.33 to 2.5 h) to meet crop water requirement. During
fertigation events, duration of nitrogen application was kept
equal to 0.166 h however, concentration of solute flux varied
0.253–1.35 mg/mL depending on the nitrogen applied at
various crop growth stages. In validation, simulation period
was kept to 3000 h equal to growing period of onion. Other
input parameters were selected in the same way as in case of
calibration. van Genuchten (1980) analytical model without
hysteresis was used for the soil hydraulic properties. Galerkin
finite element method was adopted to solve the water flow
equation. Feddes’ root water uptake model with no solute
stress was adopted and parameters were selected from
Feddes’ Parameters (1978) available in the HYDRUS crop
database. In this study, initial nitrogen concentration in the
soil was given as the total available nitrogen, which was
considered as sum of NH4+ and NO3
� forms of nitrogen. This
was done with the expectation that most of the applied
ammonium would be transformed to nitrate within 2–3 weeks
at soil temperature of 25–30 8C (Rolston et al., 1979). Though
the process of nitrification is reduced in saturated zone
immediately below the emitter but nitrification occurs in the
unsaturated zone around the emitter (Laher and Avnimelech,
1980). Urea was applied as the source of nitrogen which is
relatively mobile and is not strongly adsorbed by soil colloids.
In soil, urea is hydrolyzed to the ammonium ion and
subsequently undergoes to nitrification. Leaching of nitrogen
occurs mostly in the nitrate form, which is predicted by model.
Therefore, in this paper, predicted nitrogen distribution within
the root zone and cumulative nitrogen going below root zone
are reported as available nitrogen and amount of nitrogen
leached.
2.3. Simulation of nitrogen leaching and distributionunder different scenarios
After calibration and validation, model was used to predict the
nitrogen distribution and leaching below the root zone. A total
of 45 scenarios which included different emitter discharge
rates and fertigation strategies were considered for simulation
to evaluate the nitrogen distribution and nitrogen leaching
from five soils namely, sandy clay loam, sandy loam, loam,
silty clay loam and silt. The basic simulation parameters were
same in all the scenarios except the soil hydraulic parameters,
emitter discharge rates and fertigation strategies. Saturated
water content (us), residual water content (ur), empirical factors
(a, n) and saturated hydraulic conductivity (Ks), for loam, silty
clay loam and silt soils were taken from the HYDRUS-2D soil
catalogue. For sandy clay loam and sandy loam soils, Neural
Network prediction model available in HYDRUS-2D was used
to assign these parameters (except Saturated hydraulic
conductivity Ks) by giving the values of clay, silt and sand
percentage. Saturated hydraulic conductivity of these soils
was obtained from field experiment. Various scenarios
considered in the study are given below:
1. E
mitter discharge rates (L/h): 1, 2.5 and 42. S
oil type:sandy clay loam
sandy loam
loam
silty clay loam
silt
3. F
ertigation strategies:(i) ADI-WF: alternate day irrigation, weekly fertigation,
fertigation for 10 min after beginning of irrigation.
(ii) ADI-WF: alternate day irrigation, weekly fertigation,
fertigation for 10 min before irrigation cutoff.
(iii) DI-WF: daily irrigation, weekly fertigation, fertigation
for 10 min before irrigation cutoff.
As mentioned earlier, duration of fertilizer application and rate
of water application were constant (amount of fertilizer applied
during eachfertigationand durationofwater application during
each irrigation were varied to match the requirement).
However, total amount of water and fertilizer applied in all
the scenarios were same. Scenarios considered in the simula-
tion were seen as irrigation and fertigation strategies alter-
natives available to the onion cultivators in India.
2.4. Results and discussion
2.4.1. Calibration and validationResults of the calibration for water and N distribution at the
end of first month after planting are presented through Figs. 4
and 5. Figures were plotted using the output files obtained
from the model. Model gives spatial and temporal distribution
of water content and N concentration in simulated layers at
pre-decided time steps. Since, field observations for water
content and N concentration in the soil were taken at 4, 24, 48,
52 (4 h after next irrigation) and 72 h (24 h after next irrigation)
after fertigation, simulated values of water and N concentra-
tion at 4, 24, 48, 52 and 72 h after fertigation were used to
compare with observed values. However, due to limitation of
space the results are presented for 4, 48 and 52 h only.
Fig. 4 – Simulated and observed water content at the end of
first month after transplanting at (a) at emitter, (b) at 15 cm
from emitter and (c) at 22.5 cm from emitter.
Fig. 5 – Simulated and observed nitrogen content at the end
of first month after transplanting at (a) at emitter, (b) at
15 cm from emitter and (c) at 22.5 cm from emitter.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 822
Figures show that simulated and observed water contents
follow a similar trend without much difference. Values of
simulated and observed water content at the end of 4 h varied
from26to30% and 23to29%, respectively (Fig.4(a)). At the endof
48 h (completion of one irrigation cycle), these values were in
the range of 22–28% and 21–26% (Fig. 4(b)). In both cases, even
the lowest moisture content is near the field capacity of soil. Fig
4(c) shows water content at the end of 52 h, i.e. 4 h after the next
irrigation. Due to application of irrigation, water content in the
soil has increased which is reflected by observed and simulated
values shown at 52 h. This indicated that model is able to
simulate time varying boundary flux as there is not much
difference between observed and simulated values. Correlation
coefficient between observed and simulated water contents
varied from 0.93 to0.99. Rootmean squareerror (RMSE) between
simulated and observed values was also estimated to examine
the predictability of the model.RMSE values varied from 0.015 to
0.017. This indicates that HYDRUS-2D can be used to simulate
the water distribution with very good accuracy.
Fig. 5(a)–(c) shows the simulated and observed N concen-
tration at various depths at 4, 48 and 52 h after fertigation.
These figures reveal that simulated and observed N distribu-
tions also follow similar trends and N concentration decreases
with increasing depth. These figures also reveal that con-
centration of N at various points decreases with elapsed time
after fertigation. For example, simulated and observed N
concentrations below the emitter 4 h after fertigation were
0.42 and 0.44 mg/mL in the first layer and the same was 0.28
and 0.32 mg/mL after 48 h. Similar trends were observed in all
layers. Simulated and observed N concentrations in the soil
layers in one irrigation cycle show decrease in N concentration
with increase in horizontal distance. For example, average N
concentration at emitter, at 15 cm from emitter and at 22.5 cm
from emitter in the first layer was 0.43, 42 and 0.41 mg/mL,
respectively.
Correlation coefficient between observed and simulated N
concentration were also determined to find out the closeness
between them. Higher values of R2 (varying from 0.95 to 0.99)
indicated that simulated and observed values are highly
correlated. RMSE values for N concentration at 4 h after
fertigation varied from 0.018 to 0.04 h indicating the high
accuracy of selected model for simulating the N concentration.
Fig. 6 – Simulated and observed available nitrogen at the
end of simulation period of 125 days, i.e. at the time of
harvesting: (a) at emitter; (b) 15 cm from emitter; (c)
22.5 cm from emitter.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 23
To examine the predictability of the model on seasonal
basis, simulation was carried out to predict the N distribution
at the end of growing season (taking the simulation period of
125 days). The results of simulation in the form of N
concentration are shown in Fig. 6. This figure reveals that
simulated and observed values of N follow similar trend with
not much difference. This figure also reveals that at the time of
harvesting, N concentration is higher in the second layer.
Simulated and observed N concentrations in the soil at the
time of harvesting varied from 0.14 to 0.19 and 0.14 to 0.22,
respectively. Correlation coefficient between simulated and
observed N concentration varied from 0.83 to 0.96. Root mean
square error between simulated and observed varied from
0.011 to 0.017. This also indicates that there is not much
difference between simulated and observed N concentrations.
The above discussion implies that HYDRUS-2D can be used to
predict the N concentration in the soil under drip fertigation
on seasonal basis also with very good predictability. After
calibration and validation, model was used to predict the
nitrogen distribution and leaching from onion field under drip
fertigation system for various scenarios.
2.4.2. Nitrogen distribution at the time of harvestTo examine the seasonal leaching potential, N distribution at
the time of harvesting in the simulated zone can be used as an
indicator. This has been shown using spectral maps obtained
as output of the model (Fig. 7). Due to the limitation of
software, spectrum scale is different for each soil. For the
convenience, scale of spectrum associated with each simula-
tion is shown with each figure. These types of figures were
drawn for all scenarios, however, to save space, results have
been presented with selected figures only. Closer look at the
color spectrum (Fig. 7) reveals that N concentration in the last
layer in case of sandy clay loam; loam and silt soil is nearly
same. The highest and lowest N concentration in this layer
was observed for sandy loam and silt soils, respectively. This
implies that more permeable soils are prone to leaching
compared to the less permeable soils. Lateral spreading of N in
second layer is more for silt clay loam and silt soils. This might
have been caused due to poor intake rate and increased
ponding time. However, it may be mentioned that N
concentration in active root zone is adequate in all soils
considered in the study.
Simulated N distributions in the vertical direction under
various soils at the end of simulation period can be explained
with Fig. 8(a)–(e). Figures reveal that difference in N concen-
tration is more at the depth of 10–15 cm, which is classified as
active root zone. N concentration increased with depth up to
10–15 cm thereafter decreased and became almost constant in
all soils except sandy loam. In case of sandy loam soil, it was
still showing decreasing trend. For all soils, concentration of N
was more at the vertical plane located at 15 cm from emitter. It
may be mentioned that plant is located at 15 cm from the
emitter. As discussed earlier, this would also mean adequate N
availability near the plant roots.
The effect of discharge on N concentration at the time of
harvest for each type of soil was also investigated. N
concentration at the time of harvesting indicated that effect
of emitter discharge was more in the vicinity of emitter in the
upper layer (Fig. 8(b)–(e)). Fig. 8(a) shows that emitter discharge
rate did not affect the N distribution in sandy clay loam soil.
Similarly in loam soil also, emitter discharge did not affect the
nitrogen distribution (Fig. 8(c)). It influenced N concentration
in middle and lower layers for sandy loam, silty clay loam and
silt soils. In sandy loam soil, higher N concentration in active
root zone was observed for the emitter discharge of 2.5 L/h
(Fig. 8(b)). However, in case of 1 and 4 L/h, N concentration in
the active root zone (middle layer) is comparatively smaller.
Though, N concentrations for 1 and 4 L/h in the middle layer
(in active root zone) are adequate, leaching percentages of N
below 60 cm would be more for the discharge of 4 L/h. This
may be due to the fact that higher emitter discharge may have
pushed the N below the 60 cm.
In silty clay loam soil, there was not much difference in N
concentration between the emitter discharge of 1 and 2.5 L/h
(Fig. 8(d)). However, in case of 4 L/h discharge, the concentra-
tion of N increased in outward direction within the depth of
20 cm. This could be attributed to the lower intake rate of this
soil than the flux created by 4 L/h emitter discharge. This could
have caused more outward movement of N than the down-
ward movement. The N concentration in the last layer was
found to be nearly the same to the initial N concentration
(0.133 mg/mL) for 1 and 2.5 L/h. For 4 L/h, N concentration in
the last layer was little more than the initial level. This
indicated that leaching potential of N in silty clay loam soil is
almost negligible. In silt soil, result was slightly different than
Table 5 – Free drainage below 60 cm in different soils forvarious emitter discharges
Soil type Free drainage (cm3)
Emitter discharge
1.0 2.5 4.0
Sandy clay loam 440 (0.23) 441 (0.23) 459 (0.24)
Sandy loam 1520 (0.79) 1528 (0.80) 1597 (0.84)
Loam 357 (0.19) 359 (0.19) 377 (0.19)
Silt 5 5 5
Silty clay loam Neg. Neg. Neg.
Note: values in parentheses represent free drainage as a percentage
of applied water.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 824
others (Fig. 8(e)). Concentrations of N at the depth of 20 and
60 cm for 1 and 4 L/h discharge rates are about 0.25 and
0.15 mg/mL, respectively. However, at 2.5 L/h, N concentra-
tions at the corresponding depths were 0.22 and 0.14 mg/mL,
respectively. Also, the concentration in outward direction in
the upper first and second layers was more than in the bottom
layers. This was more pronounced in 1 and 4 L/h. This may be
due to the fact that in case of 1 L/h, duration of irrigation was
more than that for the 2.5 L/h. However, volume of water
applied was the same in all cases. This means that the flux
created with 1 L/h discharge would have been nearly same to
the intake rate of the soil and with increased duration of
irrigation, more water and N moved outward and downward.
Similar observations were made in case of 4 L/h with only
difference that higher discharge rate facilitated more water
and N movement in outward and downward directions.
2.4.3. Free drainage and nitrogen leachingThe amount of water percolating below the root zone depth (in
this case the simulated depth of 60 cm) was obtained from the
model output file. Cumulative free drainage for each soil type
was divided with the amount of applied water to determine
the free drainage as a percentage of applied water (Table 5). It
can be seen from the table that the free drainage was negligible
in case of silt and silty clay loam soils followed by loam, sandy
clay loam and sandy loam soils. Effect of emitter discharge on
free drainage component is negligible in case of silty clay loam
and silt soils. In case, emitter discharge is increased from 1 to
4 L/h, free drainage increased from 440 to 549, 1120 to 1597 and
357 to 377 cm3 for sandy clay loam, sandy loam and loam soils,
respectively. The increases in free drainage with emitter
Fig. 7 – Simulated nitrogen concentration (mg/mL) contours in d
(x-axis represents distance from emitter and y-axis represents
discharge are more in sandy loam soil than the sandy clay
loam and loam soils. Above results reveal that effect of emitter
discharge on free drainage component is negligible in case of
less permeable soils like silt and silty clay loam. This implies
that the soil hydraulic properties play major role in controlling
the free drainage component, which is very important in
design and operation of drip fertigation system. Very low
percentage of free drainage could be due to the high
evaporation and transpiration components and, low water
application rate and less duration of irrigation. It may be
mentioned that maximum temperature during major portion
of growing season was above 30 8C.
To find out the leaching potential of each soil under various
emitter discharge rates, amount of N going below 60 cm depth
were determined. N leaching percentage was taken as ratio of
cumulative N going below 60 cm depth and applied N. N
ifferent type of soil with the emitter discharge of 2.5 L/h
depth in cm).
Fig. 8 – Simulated nitrogen concentration (mg/mL) contours after 125 days, i.e. at the time of harvesting (a) in sandy clay
loam soil, (b) in sandy loam soil, (c) in loam soil, (d) in silty clay loam soil and (e) in silt soil (x-axis represents distance from
emitter and y-axis represents depth in cm).
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 25
Fig. 8. (Continued).
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 826
leaching was estimated from the solute going below 60 cm
depth as this would not be available to onion crop and leach
down during rainy season, which starts about 3 weeks after
harvesting of the crop. Table 6 reveals that N leaching was
highest from sandy loam soil and negligible from silty clay
loam soil. Lower intake rate of fine textured soil facilitates
more lateral movement of N and minimizes the leaching
losses. In silt soil, a very small percentage of N leached below
the root zone depth. In loam and sandy clay loam soils, N
leaching percentage was higher than in the loam and lower
than in the sandy loam soil. There was no effect of fertigation
strategies and emitter discharge rates on N leaching in silt and
silt clay loam soils. N leaching increased with increase in
discharge rate under sandy loam soil. In sandy clay loam and
loam soils, effect of emitter discharge rate was visible at 4 L/h.
For sandy loam soil, highest N leaching was observed for ADI-
WF with 4 L/h emitter discharge and fertigation for 0.166 h in
the beginning of irrigation. In sandy loam soil, for 1 L/h
discharge, N leaching was highest in Fertigation strategy (ii).
For the same soil with 2.5 L/h emitter discharge, the N leaching
was highest in case of alternate day irrigation-weekly
fertigation (ADI-WF) given 10 min before irrigation cut off
(strategy ii). However, at 4 L/h, N leaching was highest in case
of alternate day irrigation-weekly fertigation (ADI-WF) given
0.166 h after beginning of the irrigation (strategy i). This
implies that in case of permeable soils like sandy loam,
fertigation strategies play role in N leaching. From foregoing
discussions, it is clear that the effects of soils on N leaching is
higher than the fertigation strategy. N leaching is more in
coarse textured soils. For all other soils, leaching potential was
very small. Except for sandy loam soils, fertigation strategy did
not affect N leaching. Even in sandy loam soil, effect of
fertigation strategies on N leaching was very small. Qualita-
tively, these results are in agreement with Gardenas et al.
(2005) who gave similar conclusions. However, percentage of N
leaching reported by them was higher than this study. This
may be due to large irrigation and fertigation duration in their
case (1.5 day and 2 h). In this study, duration of irrigation
Table 6 – Percentage of applied nitrogen leached below the 60 cm depth in the growing period of onion in treatment
Soil types Fertigation strategies Amount of N leached below the root zone
Emitter discharge (L/h)
1 2.5 4
mg % mg % mg %
Sandy loam A 202.54 5.27 206.32 5.37 212.87 5.54
B 208.03 5.31 208.07 5.41 207.65 5.40
C 206.35 5.37 206.97 5.38 210.03 5.46
Sandy clay loam A 58.68 1.53 58.84 1.53 61.35 1.59
B 59.36 1.54 59.27 1.54 59.14 1.54
C 58.78 1.53 58.91 1.53 59.73 1.56
Loam A 47.67 1.24 47.96 1.25 50.36 1.30
B 48.44 1.26 48.43 1.26 48.28 1.26
C 47.83 1.24 48.10 1.25 48.84 1.27
Silt A 0.64 0.02 0.64 0.02 0.65 0.02
B 0.64 0.02 0.64 0.02 0.64 0.02
C 0.64 0.02 0.64 0.02 0.64 0.02
Silt clay loam A Neg. Neg. Neg. Neg. Neg. Neg.
B Neg. Neg. Neg. Neg. Neg. Neg.
C Neg. Neg. Neg. Neg. Neg. Neg.
a g r i c u l t u r a l w a t e r m a n a g e m e n t 8 9 ( 2 0 0 7 ) 1 5 – 2 8 27
varied from 0.33 to 2.5 h and duration of fertigation was
constant to 10 min in accordance to the requirement of water
and fertilizer by onion.
The results presented here may slightly differ if miner-
alization gains and denitrification losses are considered.
However, result presented in this paper give reasonably good
information about nitrogen distribution and leaching under
various irrigation and fertigation strategies for different types
of soils which can be useful for design and operation of drip
fertigation systems for shallow rooted crops such as onion.
3. Conclusions
Results presented in this paper describe the effect of drip
fertigation strategies, nitrogen distribution and leaching from
onion field. Calibration and validation results showed that
HYDRUS-2D can be used for simulation of water and nitrogen
distribution and leaching. Results revealed that emitter
discharge rate did not affect the nitrogen distribution in
sandy clay loam and loam soils. There was some effect of
emitter discharge rate in sandy loam, silt clay loam and silt
soils. In coarse textured sand loam soil, nitrogen tends to
move downward. In fine textured silt clay loam and silt soils,
nitrogen moved outward in top two layers.
Seasonal nitrogen leaching was highest from coarse
textured sandy loam soil followed by sandy clay loam, loam
and silt soils. Silt clay loam soil did not result in nitrogen
leaching. Effect of emitter discharge rates was observed more
in sandy clay loam. There was not much effect of emitter
discharge in silt and silt clay loam soils. In general fertigation
strategies like fertigation in the beginning of irrigation,
fertigation at the end of irrigation and irrigation on daily
basis did not affect the nitrogen leaching much as commonly
perceived. There was some effect of fertigation strategies on
nitrogen leaching in coarse textured sandy loam soil.
More nitrogen leaching was observed with alternate day
irrigation-weekly fertigation with 4 L/h emitter discharge rate
and fertigation for 0.166 h in the beginning of irrigation. In
sandy loam soils, nitrogen leaching varied from 5.27 to 5.54%.
Acknowledgement
We acknowledge the Indian Council of Cultural Relation,
Government of India for providing the scholarship to first
author during the study period. On several occasions during
the study period, we interacted with Prof. J. Simunek of
University of California Riverside on the issues related to
simulation with HYDRUS-2D through email. We are thankful
to him for his valuable suggestions.
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