Food sustain (Network for Sustainable crop production under climate change: designing and testing regional climate adaptation measures through enhanced ecohydrological modelling) field survey pictures

This project aims to enhance the SWAT+ hydrological model by incorporating region-specific, remote sensing (RS)-based crop biophysical parameters to improve crop yield simulation and water balance prediction in two contrasting watersheds—the Upper Godavari Basin (India) and the Kielstau watershed (Germany). Through field surveys, machine learning, and interdisciplinary collaboration between IIT Roorkee, CAU, and AVV, the study will improve model accuracy by regionalizing leaf area index (LAI) and root biomass parameters. The enhanced model will be used to evaluate future crop yields and hydrological responses under climate change scenarios, contributing to food and water security while supporting SDG-aligned sustainable agriculture practices.