Floods remain one of the most severe hydro-meteorological hazards globally, often exacerbated by rapid land-use change, geomorphic alterations, and intense rainfall in tropical regions. The Karuvannur River Basin (KRB) in central Kerala, India, has experienced frequent flood events, yet a systematic, geospatially integrated flood susceptibility assessment has been lacking. This study applies the Analytic Hierarchy Process (AHP) coupled with Geographic Information System (GIS) techniques to develop a flood susceptibility map that captures the spatial variability of flood-prone zones based on geomorphological, hydrological, and land surface parameters. A total of nine environmental variables, including slope, drainage density, land use/land cover (LULC), soil texture, and the Topographic Wetness Index (TWI), were derived from SRTM DEM, Landsat 9 OLI, Survey of India toposheets, and ancillary soil data. Model validation was carried out using National Remote Sensing Centre (NRSC) flood inundation data, and the predictive performance was evaluated using the Receiver Operating Characteristic (ROC) curve. The model achieved a high Area Under the Curve (AUC) value of 0.945, indicating excellent predictive accuracy. The AHP consistency ratio was 0.02, confirming the logical consistency of the assigned weights. The results indicate that approximately 570.38 km2 (54.9 % of the basin) fall under high and very high flood susceptibility zones, predominantly in the central and western floodplains. The study provides critical spatial insights for flood risk mitigation, landscape resilience planning, and geomorphologically informed infrastructure development, offering a replicable model for flood-prone tropical river basins.
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