ABSTRACT GIS-AHP framework for Northeastern Bangladesh integrates 19 indicators to prioritize flood risk. It identifies Sunamganj and Sylhet as high-priority zones, supporting Sendai Framework resilience planning. Flood risk assessments in monsoon-dominated, data-scarce regions often emphasize physical susceptibility while insufficiently integrating exposure and vulnerability, limiting actionable risk prioritization. This study develops a validated flood risk prioritization index (FRPI) for northeastern Bangladesh (Sylhet Division) using a geographical information system-based analytic hierarchy process (AHP) framework that integrates 19 geospatial indicators across susceptibility (9 parameters), exposure (5 parameters), and vulnerability (5 parameters). Flood susceptibility was evaluated using independent flood inventories from June 2022 and June 2024 through zonal overlay and receiver operating characteristic-area under the curve (AUC) analysis, yielding strong predictive performance (AUC = 0.836 and 0.794). A one-at-a-time sensitivity analysis across 114 perturbation scenarios demonstrated high stability (κ 0.94). By combining multidimensional risk components within a unified structure, incorporating exposure proxies such as nighttime light intensity and critical infrastructure density, and implementing temporal validation with uncertainty assessment, the framework advances conventional AHP-based flood mapping approaches. Results identify Sunamganj and Sylhet districts as the highest priority zones, with over 72% and 42% of land classified as high to very high risk, respectively. The FRPI is scalable and transferable, supporting data-driven flood risk governance and resilience planning across transboundary, data-scarce basins, aligning with the Sendai Framework's aim of enhancing localized flood risk intelligence.
Swarup et al. (Wed,) studied this question.