Modeling Worst-Case GLOF Scenarios Under Probable Maximum Flood Conditions in the Sutlej River Basin

The western Himalayas are becoming increasingly vulnerable to climate-driven hazards, particularly Glacial Lake Outburst Floods (GLOFs) compounded by Extreme Rainfall Events (EREs). These compound flood events pose significant threats to downstream populations, hydropower infrastructure, and fragile ecosystems. However, most existing assessments tend to analyze GLOFs in isolation, often overlooking the amplifying effect of EREs, thereby underestimating the real extent and magnitude of the hazard. This study aims to address this gap by integrating EREs into a coupled hydrological–hydrodynamic modeling framework for high-hazard glacial lakes with considerable downstream exposure. The selected case study, a moraine-dammed lake in the Sutlej River Basin, lies in proximity to key infrastructure and densely populated settlements. Probable Maximum Precipitation (PMP) was estimated at 530.68 mm using the Hershfield method, which informed the simulation of Probable Maximum Flood (PMF) scenarios. Peak PMF discharge at the Bhakra Dam was estimated to reach 23,478 m³/s. The hydrological model achieved a Nash–Sutcliffe Efficiency (NSE) score of 0.75, indicating strong model performance and predictive reliability. Breach modeling and subsequent flood simulations under worst-case conditions reveal widespread downstream inundation. Over 588 structures, including dams, bridges, industrial installations, and road networks, are projected to fall within the inundation footprint. These results highlight the urgent need to reassess flood risks in light of compound hazards, especially in regions experiencing rapid glacial lake expansion and increasing rainfall extremes. The study underscores the necessity of early warning systems, climate-resilient infrastructure, and integrated risk assessment frameworks to reduce the impact of cascading flood hazards in high-mountain environments like Himachal Pradesh.