Download Soil water balance studies in subsurface drip irrigation

Session: CS2: Efficient Water Use in Agriculture
IMPROVING WATER USE EFFICIENCY BY SOIL MOISTURE
MEASUREMENT AND MODELLING
Ms. Neethu. A.
Dr. Santosh G Thampi
Dr. Pramada. S. K.
DEPARTMENT OF CIVIL ENGINEERING
NATIONAL INSTITUTE OF TECHNOLOGY, CALICUT
INTRODUCTION
• Water scarcity is a major concern for water and agricultural authorities around the world
• It is the need of the hour to save water for irrigation by proper control and management,
thereby enhancing water and nutrient use efficiency, maximizing the income of farmers
and minimizing pollution
• An efficient drip irrigation system helps to meet growing irrigation water requirements by
exercising proper control over the application of water, fertilizers and pesticides
• In this study, computation of soil moisture profiles has been performed using HYDRUS-2D
• HYDRUS-2D (Simunek et al., 1998) is a Windows based computer software package and
has been widely used for simulating water, heat, and solute movement in two-dimensional,
variably-saturated porous media
OBJECTIVE
• To study the moisture distribution pattern under a drip irrigated field, to compare results
of HYDRUS-2D simulations of water infiltration and redistribution with field data, and to
assess the utility of using simulation results in the design of drip management practices
• To improve water use efficiency by soil moisture measurement and modelling
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WATER FLOW MODELLING
• The study involves simulation of water flow and water infiltration using the HYDRUS 2D
model (Simunek et al., 1998)
• Soil is assumed to be homogeneous and isotropic
• The governing equation for water flow is the 2D Richards’ equation. The axi-symmetric
form is used in this study to simulate water flow under surface drip emitters
  1  rK h h     K h h   K h  S h
t r r 
r  z 
z  z
where,  = volumetric water content (L3L-3)
t = time (T)
• This equation is solved with the HYDRUS-2D
model – Galerkin finite element method
• The soil hydraulic model describing unsaturated
h = soil water pressure head (L)
r = radial(horizontal)coordinate (L)
z = vertical co-ordinate : positive
upward (L)
K h  = unsaturated hydraulic
conductivity (LT-1)
retention and hydraulic conductivity functions - S h  = sink term representing root
water uptake expressed as volume of
is the van Genuchten-Mualem model
water removed from a unit volume of soil
(van Genuchten, 1980)
per unit time (L3L-3T-1)
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van GANUCHTEN CONSTITUENT RELATIONSHIPS

 r
 (h)  



  s  rn m 
1  h  

 

 

 (h)  s
for h  0
K (h)  K s Sel (1 (1 Se1/ m )m )2
Se     r
 s  r
m  1 1 ; n  1
n
 (h) = volumetric water content (L3L-3)
for h  0
K (h) = unsaturated hydraulic conductivity
at the soil water (LT-1)
h = pressure head (L)
r = residual water content (L3L-3)
 s = saturated water content (L3L-3)
S e = effective water content (L3L-3)
K s = saturated hydraulic conductivity (LT-1)
 = inverse of the air entry pressure
head (L-1)
n
l
= pore size distribution index
(dimensionless)
= pore connectivity parameter = 0.5
(Mualem,1976)
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FIELD STUDY
• Field experiments were carried during 2015-2016 in
the experimental plots at the Kelappaji College of
Agricultural Engineering & Technology, Tavanur,
Malappuram, Kerala
• Consisted of design and installation of drip
irrigation system, field observations and sampling
and analysis of soil samples
• Drip laterals were placed in the middle of rows over
a leveled field and drippers were fixed at 60cm
along the lateral line
• Bed width and emitter spacing = 60cm
• There were 5 laterals, each with 40 emitters of 2lph
capacity each and the flow in each lateral is
controlled by a tap valve
• Soil of the experimental plot - sandy loam texture
and is assumed to be homogenous in nature
Layout of drip irrigated plot
• Irrigation water is applied daily at the rate of 2lph
for a duration of 1 to 1.5h, depending on the crop
water requirement
• Soil samples were collected from different depths
0.1, 0.2, 0.3, 0.4, 0.5 and 0.6m at horizontal
distances of 0, 15, and 30cm from the emitter
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DETAILS OF CROP
• The crop is tomato of Anagha variety - crop period of 90 days
• Crop evapotranspiration  ET  was calculated using CROPWAT – Penman-Monteith equation
c

• CROPWAT requires daily weather parameters - minimum and maximum temperature
humidity, wind speed, sunshine hours for the calculation of reference evapotranspiration
 ET  (Source: Regional Agricultural Research Station, Pattambi)
o


 ET 
• c
is calculated :
 ET
c

 K c  ETc 
where

KC : crop coefficient


• HYDRUS requires separate values of potential evaporation E p  and potential transpiration


T  as inputs (Gardens et al., 2005)


 P
• Potential evapotranspiration is partitioned into potential evaporation EP  0.05 ETC  and
potential transpiration T  0.95 ET 
p
c


COMPUTATION OF CROP EVAPOTRANSPIRATION
Stages
KC
ETC (mm/day)
EP (mm/day)
TP (mm/day)
Initial
0.60
2.88
0.144
2.74
Development
1.0
4.80
0.240
4.56
Late season
0.80
3.85
0.193
3.66
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CROP WATER REQUIREMENT
• Crop water requirement of tomato is calculated: (Source: Neelam Patel & T B S Rajput,
2006)
where Q - crop water requirement, l/day
Q
ETO  KC  l  d
 10
l - lateral spacing, cm
d - emitter spacing, cm
 - irrigation efficiency (90%)
CROP WATER REQUIREMENT FOR TOMATO
Stages
Crop water requirement (l/day)
Early
1.7
Development
3.0
Late
2.3
SYSTEM GEOMETRY
•
•
•
Each emitter is assumed to discharge water at the same flow
rate
Because of the system symmetry, the entire field is
subdivided into identical volume elements with an emitter
placed at one end
Initial condition - initial water content in different soil layers
within the flow domain, as observed in the experimental field
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INPUT PARAMETERS
• Various parameters namely saturated water content, residual water content and empirical
factors for sandy loam soils were taken from the Neural Network prediction model Rosetta Lite
• Rosetta implements pedotransfer functions which predict van Ganuchten’s (1980) water
retention parameters and saturated hydraulic conductivity in a hierarchal manner from soil
textural class, soil textural distribution, bulk density and one or two water retention points
as input
• Rosetta provides soil hydraulic parameters for analytical functions of van Ganuchten for
twelve textural classes of USDA textural triangle
• HYDRUS model was calibrated using the observed values of moisture content at various
points in the domain at 4h, 1day, 2days, and 3days after the first irrigation
• During validation, the simulation period was kept as 90days equal to the growing period of
tomato
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VALIDATION
• It can be inferred from the plots that at emitter as the root zone depth increases moisture
content decreases
• At a distance of 15 cm radially from the emitter, root density is less during early stages of
crop growth so moisture content is more
• During the development stage the root density increases and hence the moisture content
decreases
Comparison of observed and simulated moisture content at different depths observed
near the emitter
Comparison of observed and simulated moisture content at different depths observed
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at 15 cm from the emitter
STATISTICAL ANALYSIS
• To evaluate the performance of the HYDRUS 2D model predictions, the root mean square error
( RMSE) and the coefficient of determination ( R 2 ) values were evaluated
RMSE values (based on values of moisture content near the emitter)
5 days
15 days
30 days
60 days
0.006
0.008
0.004
0.003
R 2 values (based on values of moisture content 15cm away from emitter)
5 days
15 days
30 days
60 days
0.967
0.993
0.963
0.867
• Higher R 2 values showed that simulated and observed values of soil moisture content are close
enough
• Based on the results, it can be confirmed that the HYDRUS model is a suitable tool and guide for
modelling soil moisture distribution in the vadose zone
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CONCLUSIONS
• Simulation studies and experimental work have led to the conclusion that adequate water
content is maintained in the active root zone during the crop growth period
• Properly designed and installed drip irrigation system will facilitate uniform distribution
of water in the radial direction - can enhance the overall irrigation efficiency - reduce the
possibility of leaching of nutrients and consequent contamination of groundwater
• Understanding how soil properties affect water storage can help in optimizing water
application and thereby water use by plants
• In this study, it is observed that the HYDRUS-2D predictions of moisture content fairly
matched with the measured values in the experimental plot located in sandy loam soil
• Results of this study justify the use of HYDRUS-2D as a tool for prediction of soil
moisture profiles and as an aid in designing drip irrigation systems
• By predicting the moisture content in the soil, the model enables estimation of how much
more water is to be applied and when and this can help to significantly improve the
efficiency of water use
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REFERENCES
• Ajdary, K., Singh, D. K. and M. Khanna (2007), Modelling of nitrogen leaching from
experimental onion field under drip fertigation, Agricultural Water Management, 89: 15-28
• Gardenas, A. , Hopmans J. W. , Hanson B. R. , and J. Simunek (2005), Two dimensional
modelling of nitrate leaching for different fertigation strategies under micro irrigation,
Agricultural Water Management., 74: 219-242
• Giuseppe Provenzano (2007), Using HYDRUS-2D Simulation Model to Evaluate Wetted Soil
Volume in Subsurface Drip Irrigation Systems, Journal of Irrigation Drainage Engineering,
133:342-349
• Mualem Y. (1976), A new model for predicting the hydrualic conductivity of unsaturated
porous media, Water Resource Research,pp: 12 :593-622
• Neelam Patel and T B S Rajput, (2006), Simulation of modeling of moisture distribution in
drip irrigated onion, Journal of Agricultural Engineering, 43:2, pp: 22-27
• Skaggs, T.H., Trout, T. J., Simunek, J. and Shouse, P. J. (2004): Comparison of HYDRUS-2D
simulations of drip irrigation with experimental observations, Journal of Irrigation and
Drainage Engineering, 130, pp:304-310
• Simunek, J., Sejna, M. and van Genuchten, M.Th. (1998): The HYDRUS 1D software
package for simulating water flow and solute transport in two dimensionally variably
saturated media. Version 2.0, International Ground Water Modelling Center-TPS-70
• van Genuchten M.Th. (1980): A closed-form equation for predicting the hydraulic
conductivity of unsaturated soils, Soil Science Society Of America Journal, 44, pp:892-898
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THANK YOU
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