LAUSR

Several irrigation projects are not delivering to their expectations; therefore, benchmarking of irrigation projects has been recommended in all national water policies of India. To simplify the benchmarking exercise, a geospatial benchmarking approach was employed in this study for the Latratu medium irrigation project in Jharkhand, India. Satellite‐based indicators were derived, and the random forest algorithm was used to classify the images. With overall classification accuracies of 97% (Rabi) and 98% (Kharif), the classification successfully delineated the extent of seasonal cultivation. The normalized difference vegetation index showed clear phenological changes when analysed over time at 15‐day intervals. Vegetation condition index mapping also revealed seasonal differences in crop health. The shuttle radar topography mission digital elevation data and normalized difference water index data collected from Sentinel‐2 were used to estimate reservoir storage capacity via the Prismoidal approach to evaluate water availability. The reservoir capacity decreased after monsoonal recharge, which impacted the Rabi crop. Furthermore, only 53% of the irrigation potential was used in agricultural landscapes. This study shows the integration of geospatial approaches for improving crop monitoring, irrigation planning and sustainable water management. Increasing the canal network and water‐use efficiency may reduce water stress during the Rabi season.