A Basin‐Wise GLOF Susceptibility Assessment in the Western Himalayas: Integrating Remote Sensing‐ GIS and Multi‐Criteria Decision Analysis

Glacial Lake Outburst Floods (GLOFs) pose an increasing threat to high mountain environments across the world, especially in the Himalayas where climate change is accelerating glacier retreat and permafrost degradation. This study presents a detailed GLOF susceptibility analysis of the western Himalayas covering five major river basins, ie Satluj, Chenab, Jhelum, Beas, and Ravi by integrating high‐resolution remote sensing data with a multi‐criteria decision‐making approach. A detailed inventory of 1573 glacial lakes was developed using manual delineation of Sentinel‐2A and LISS‐IV images. Forty‐eight potentially dangerous lakes were identified based on size and dam composition. Following the guidelines of NDMA and GAPHAZ, 12 important physical and geomorphic parameters were selected and evaluated using Analytic Hierarchy Process (AHP) with the addition of Cumulative Weightage Technique (CWT). AHP Analysis indicated that 20 lakes were high hazard, 23 lakes were medium hazard, and five lakes were low hazard. The basin‐wise analysis revealed that Satluj and Chenab are particularly vulnerable owing to the presence of large and fast‐growing lakes. A temporal assessment of 48 selected potentially dangerous lakes from 2000 to 2024 revealed a 115% increase in total lake area, highlighting their rapid expansion under a warming climate. The susceptibility framework was validated using seven historical GLOF events, all of which had hazard scores > 0.7, in agreement with the high susceptibility lakes identified in this study. The study recommends that detailed field investigations be carried out on high‐hazard lakes including bathymetric surveys, assessments of moraine stability, and real‐time monitoring to validate remote sensing findings and to inform early warning systems. This approach offers a transferable and policy‐relevant framework to support GLOF risk mitigation and climate adaptation planning in glacierized regions. This study relies primarily on remote sensing data, and uncertainties in lake identification and the lack of field validation may affect susceptibility classification.