A Remote Sensing Approach to Map Crop Stress and Optimize Irrigation through Crop-Water Production Functions

Abstract

rrigated agriculture consumes over 70 % of global freshwater, intensifying competition among
agricultural, urban, industrial and environmental needs. This study presents a geospatial
framework that integrates remote sensing–derived evapotranspiration (ET) with crop–water
production (CWP) functions to map wheat stress and optimize irrigation across Allahabad
district, India. Using surface energy-balance modelling (METRIC/SEBAL) and FAO 56
reference-ET, we estimated actual (ETa) and potential (ETp) evapotranspiration for the
December 2015–April 2016 season. Remote sensing–based biomass and harvest-index models
yielded actual and potential grain output, enabling stage-wise yield response factor (Ky),
calculation - the key coefficient in many CWP formulations via the Doorenbos–Kassam
approach (FAO 33).