Estimating irrigation water requirement in rice by integration of satellite data and agrometeorological indices in Palakkad, Kerala.

The sustainability of irrigated agriculture is jeopardized by catastrophic climate change, with projected forecasts indicating that by 2025, one out of every four people on the planet will be experiencing extreme water scarcity. In this context, an attempt was made for scheduling irrigation at a regional scale combining satellite data and agrometeorological indices over major rice growing tracts of Palakkad district in Kerala. Normalized Difference Vegetation Index (NDVI) product of MODIS (MOD13Q1) with a temporal resolution of 16 days and a spatial resolution of 250 m was utilized to establish a relationship with crop coefficient (K_c) of rice during the Mundakan rice season (September-October to December-January) of 2020-21 and 2021-22 in 30 ground truth locations. The results revealed that NDVI values have strong relationship with K_c values with an R2 value of 0.82. Crop coefficient (K_c) maps developed using satellite derived NDVI provided K_c values at a regional scale during different stages of crop growth and it helped to estimate crop evapotranspiration with greater accuracy. Based on this crop water demands maps depicting the spatial and temporal distribution of irrigation requirement were generated for the whole study area. These maps can be used as a tool for the estimation of the crop water requirement of a rice field if the geographical coordinates of the location are known. The total crop water requirements estimated during Mundakan season 2020-21 and 2021-22 in Palakkad district were in the range of 611-976 mm and 560-897 mm respectively. Integration of remote sensing & agrometeorological techniques has scope for regional-scale crop water requirement estimation in a cost-effective and time-bound manner. [ABSTRACT FROM AUTHOR]