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Water shortage is one of the world's most critical issues, and climate change
projections suggest that it will get worse in the future. Since, water availability and
accessibility are the most significant constraints to agricultural production in waterscarce areas, resolving this issue is crucial. In order to overcome this, farmers must
better estimate crop water requirements and use irrigation water more efficiently. Proper
irrigation management and water conservation depend on accurate estimation of crop
water demands. This study was done to estimate crop water requirement in rice crop
during mundakan season 2020-21 in Palakkad district of Kerala using remote sensing
and land based observations.
Remote sensing technology relies on the spectral signatures of the vegetation
and other land covers in an area. In order to proceed with the analysis of remote sensing
products, the major rice growing areas were delineated using multi temporal cloud free
Sentinel-2 imageries at a spatial resolution of 10 m following iso cluster unsupervised
classification. The overall classification accuracy was 88.33 % with a Kappa coefficient
of 0.77. Small fragmented heterogeneous rice areas and large homogeneous rice areas
were classified equally well.
A commonly used and recommended method for estimating crop water
requirements is the use of reference evapotranspiration (ETo) and crop coefficient (Kc).
Under field conditions, standard methods to estimate evapotranspiration (ET) over
homogenous surfaces include conventional techniques such as weighing lysimeters that
measure the water consumed through ET directly based on a mass balance, or flux
measurements using Bowen Ratio or Eddy Covariance instrument systems that measure
components of the surface energy balance to estimate evapotranspiration. However, a
limitation of these systems is that they provide point measurements that may not
adequately represent the ET from fields other than where the measurement is taken. To
overcome this problem of estimating ET from multiple fields, satellite-based remote
sensing is a useful method for estimating ET on a field-by-field basis at a regional scale
The use of remotely sensed vegetation indices, such as the Normalized
Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI), has
been tested by scientists to predict crop coefficient (Kc) at field and regional scale.In
this study, analysis was done to establish a relationship between Normalized Difference
Vegetation Index (NDVI) and crop coefficient (Kc) values for the 30 ground truth
locations spread over 5 blocks viz, Alathur, Nenmara, Kollengode, Chittur and
Kuzhalmannam, which represents the major rice growing tract of Palakkad district. A
linear equation was set, between NDVI values obtained from MODIS NDVI
(MOD13Q1) 16 day composite with a spatial resolution of 250 m and Kc table values
collected from literature, and the equation showed a strong relation with an R2
value of
0.8156. The Normalized Difference Vegetation Index (NDVI) was calculated from
reflectance of the red and near infrared bands. Kc values vary from season to season and
field to field. Also, Kc depends on crop growth stage, plant density, and irrigation
management. Hence, it becomes necessary to test the relationship between NDVI and
Kc to confirm crop coefficient under local conditions.
The Kc predicted values during early vegetative were in the range of 0.5-0.8,
towards the late vegetative stage, it showed an increasing trend from 0.8 to 1.2, during
the reproductive stage the value raised to 1.3, and when the rice crop reached maturity
stage Kc values decreased to 0.58. The potential evapotranspiration during different crop
growth stages ranged between 120-176 mm. The total crop evapotranspiration during
the entire mundakan season 2020-21 in the training sites considered for the study was
in the range of 500-626 mm. Water lost through crop evapotranspiration is compensated
by effective rainfall and water supplied through irrigation. The rainfall received during
early vegetative stage ie; during October and November months were sufficient to
compensate evapotranspiration losses of the rice crop. But irrigation is necessary for
sustaining crop growth during late vegetative, reproductive and maturity stages due to
the lack of rainfall in the corresponding months so as to compensate crop
evapotranspiration. In rice, total irrigation requirement includes water required to
compensate crop evapotranspiration and additional water supplied to maintain standing
water in the fields. The total irrigation requirement of rice during mundakan 2020-21 in
Palakkad district was in the range of 611-975 mm.
Crop coefficient (Kc) maps created at a regional scale provided Kc values during
various stages of crop growth, allowing for more accurate estimation of crop
evapotranspiration for the research area. Crop water demands maps were also created
for the entire study area, demonstrating the spatial and temporal distribution of irrigation
requirements. If the geographical coordinates of the place are known, these maps make
estimates of crop water requirement of a rice field much easier.
Global warming and climate change may lead to increased frequency of
irrigation in the near future. This in turn causes increased the demand of water for
irrigation purposes. Information regarding crop specific area under irrigated agriculture
and crop growing season are important for efficient use of available water resources.
The delineated rice field will provide a clear view of the geographical coverage of
irrigation requirements, and the crop water demand maps will show the stage wise
irrigation water requirements. The irrigation requirement map prepared for the study
area covering 5 blocks of Palakkad district can be used for water resource planning and
management. This is particularly useful for understanding inter seasonal variations in
irrigation water demand at different geographical and temporal dimensions.