Irrigation Water Management Modeling in Canal Command Using Remote Sensing

Abstract

Irrigation optimization is an important practice used in crop management, which could reduce irrigation water losses and maintain high yield in the canal command. Estimation of crop water demand based on temporal and spatial distribution is a prime requirement for efficient water management. Remote sensing based surface energy balance algorithm for land (SEBAL) has a good performance in both efficiency and applicability in evapotranspiration (ET) estimation. The crop water requirement was estimated using FAO-56 and SEBAL methods for the performance assessment of Ozat-II canal command area of Junagadh district, Gujarat, India. The irrigation efficiencies for the Ozat-II scheme were found out very low as 28.22% and 30.68% based on crop evapotranspiration (ETc) FAO-56 method and SEBAL based actual evapotranspiration (AET) respectively for year 2014. The relative water supply (RWS) estimated from crop demands based on ETc (FAO-56) and AET (SEBAL) were 1.28 and 1.17 respectively for year 2014. Whereas in year 2015, the RWS estimated from crop demands based on ETc (FAO-56) and AET (SEBAL) were 0.83 and 0.92, respectively. The over irrigation was observed in year 2014 and deficit irrigation in year 2015. More area under higher values of NDVI were found in head end zone as comparison to that of middle zone and tail end zone of study area. The water productivity of summer groundnut crop was found lower as 0.103 kg m^-3 using actual irrigation water supplied (WS). The water productivity was found out as higher 0.438 kg m^-3 as per the AET (SEBAL). The water use efficiency (WUE) of summer groundnut and sesame crop were lower as 1.03 kg ha-1 mm-1 and 0.707 kg ha^-1 mm^-1, respectively using WS. The maximum WUE of summer groundnut was found as 4.381 kg ha^-1 mm^-1 as per ETc (FAO-56) and 2.931 kg ha^-1 mm^-1 of summer sesame using AET (SEBAL). The results indicates that there is a significant scope to increase land and water productivity in Ozat-II canal command by adopting crop water requirement estimation based on remote sensing.