Optimized identification of glacial lake outburst flood hazard using multi-criteria decision analysis

The increasing frequency of glacial lake outburst floods (GLOFs) in Chitral River Basin, driven by glacier melting and rising temperatures, poses a serious threat to downstream communities and infrastructure. In this study, multi-criteria decision analysis (MCDA) framework integrated with stochastic multi-criteria acceptability analysis (SMAA) software was applied to evaluate GLOF hazard-prone lakes using 25 years (1997–2022) of climatic data with satellite missions (Sentinel-2, Google Earth imagery, and ASTER DEM). Lake characteristics such as slope, lake depth, volume, and distances from glaciers analysed by SMAA-2 and SMAA-TRI (where TRI stands for triage “order preferences”) were applied to evaluate uncertainties and variable weight distribution. The model’s validation through identified lakes and existing inventories confirmed its reliability. Results identified five high-risk, three medium-risk, and the remaining low-risk lakes. Sensitivity analysis highlighted key criteria influencing hazard levels, while SMAA-TRI revealed shifts in risk classes under varying thresholds, demonstrating the models’ robustness for GLOF risk assessment and mitigation.