Decision support system for climate-resilient runoff estimation

This study addresses the critical need for climate-resilient hydrological tools by developing Decision Support System (DSS). The DSS integrates a modified Soil Conservation Service Curve Number (SCS-CN) method with high-resolution geospatial datasets, such as Sentinel-2 Land-Use/Land-Cover (LULC), OpenLand soil properties, Shuttle Radar Topography Mission (SRTM)- Digital Elevation Model (DEM) topography and Climate Hazards Group Infrared Precipitation with Station (CHIRPS) precipitation, to simulate historical and near-real-time runoff. Furthermore, it incorporates CMIP6 climate projections to facilitate future runoff estimation. Validated across two contrasting Indian watersheds-the monsoon-driven Salebhata catchment (R² = 0.82) and semi-arid Venkatapur sub-watershed (R² = 0.78). The model performs well at capturing seasonal variability, including monsoon floods, runoff during dry spells, seasonal extremes and variations across different areas. Its user-friendly application enables stakeholders to create real-time, location-specific runoff estimates through polygon-based analysis, which directly facilitates flood forecasting and adaptive water resource management. By incorporating climate projections and high-resolution geospatial analysis, this framework provides a reproducible platform for climate-resilient water resource planning, especially in data-poor regions exposed to hydroclimatic extremes.