Abstract:
Glacial Lake Outburst Floods (GLOFs) have emerged as one of the most significant and escalating threats to
high-altitude Himalayan regions, posing serious risks to downstream communities, infrastructure, and
hydropower installations. These hazards are increasingly exacerbated by climate-induced glacier retreat and the
intensification of extreme precipitation events, driven by global warming. Against this backdrop, the present
study offers a comprehensive, multi-dimensional assessment of GLOF risk through an integrated approach that
combines susceptibility mapping, spatiotemporal analysis of glacial lakes, extreme flood event reconstruction,
and modelling of future flood scenarios. The overarching aim is to provide a robust framework for hazard
forecasting, risk mitigation, and sustainable development in glacier-fed river basins.
The study begins by employing a Glacial Lake Outburst Flood Susceptibility Mapping (GLOFSM) framework
for the Himalayan region using a hybrid Frequency Ratio–Analytical Hierarchy Process (FR-AHP) model. By
synthesizing qualitative expert judgment with quantitative, data-driven analysis, the approach minimizes
subjectivity and enhances reliability. A total of 851 glacial lakes were analyzed against twelve weighted factors
derived from 25 historical GLOF events—such as lake area, glacier proximity, slope, avalanche risk, and
precipitation levels. The model classified 324 lakes as highly hazardous and 50 as very highly hazardous,
achieving a predictive accuracy of 86.65% based on Area Under the Curve (AUC) validation. This susceptibility
mapping provides a critical tool for prioritizing GLOF potential lakes and planning targeted mitigation
strategies.
To capture the evolution of glacial lakes over time, a spatiotemporal analysis was conducted for the Sikkim
Himalaya using Landsat satellite data from 1990 to 2020. The region witnessed a marked increase in glacial
lakes—from 309 to 440 in number, and from 22.83± 0.78 km2 to 30.71±1.07 km2 in total area—highlighting
the accelerating pace of glacier melt and hydrological transformation. An enhanced hazard assessment
framework was proposed by integrating qualitative assessments (e.g., ice avalanches, landslides) with a Fuzzy
AHP (FAHP) approach and stochastic inundation modelling using the Monte Carlo Least Cost Path (MC-LCP)
method. Among the 51 lakes flagged for potential GLOF activity, 13 were categorized as either high or highly
hazardous, informing region-specific monitoring and emergency preparedness efforts.
Recognizing the potential for cascading lake failures, the study further explores worst-case multi-lake GLOF
scenarios through two-dimensional hydrodynamic simulations in HEC-RAS. Focusing on three critically
vulnerable lakes—South Lhonak, Gurudongmar, and Shako Cho—seven breach scenarios were modeled,
ranging from individual lake outbursts to simultaneous failures. The simulations revealed flow depths between
5 and 20 m and velocities up to 4 m/s, with the most extreme event producing a peak discharge of approximately
10000 m³/s at Chungthang, a key downstream settlement. These findings underscore the immense destructive
potential of multi-lake outbursts and the pressing need for integrated, basin-wide risk assessments. To better understand real-world events, the 2023 South Lhonak GLOF—triggered by a combination of lake
breach and prolonged rainfall—was reconstructed using a coupled HEC-RAS and HEC-HMS modelling
framework. Simulated peak discharges reached ~7355 m³/s±845 at Chungthang and ~8282±952 m³/s at
Gazoldoba, closely matching observed streamflow data with an accuracy of 78%. Additionally, three future
GLOF scenarios were projected, estimating discharges of 8826±1015 m³/s, 10817±1244 m³/s, and 12385±1424
m³/s. These projections provide essential insights for developing early warning systems and long-term risk
forecasting.
Expanding the spatial scope, the study also evaluates compound hazard scenarios in the Beas and Sutlej River
basins by coupling glacial lake outburst modelling with Probable Maximum Flood (PMF) estimation. Using the
Hershfield method, Probable Maximum Precipitation (PMP) values were estimated at 650.12 mm for the Beas
Basin and 530.68 mm for the Sutlej Basin. Rainfall depth analysis using the Gumbel method further supported
the derivation of PMF discharges, which were estimated at 17086 m³/s for the Pandoh Dam and 23478±2699
m³/s for the Bhakra Dam. Under worst-case conditions involving both GLOFs and extreme precipitation, peak
discharges rose to 17356±1995. m³/s and 24723±2843 m³/s, respectively. Inundation maps identified
widespread risks to build infrastructure, affecting 94 critical assets in the Beas Basin and more than 588
structures—including major hydropower and industrial installations—in the Sutlej Basin.
In conclusion, this study presents a robust, integrative framework for GLOF hazard assessment in the
Himalayan region, leveraging satellite-based observations, advanced statistical modelling, and coupled
hydrological-hydrodynamic simulations. The findings reveal not only the accelerating vulnerability of glaciated
catchments but also the compounded threat posed by cascading failures and extreme weather events. The study
highlights the need for continuous glacial lake monitoring, improved early warning systems, and infrastructure
adaptation policies. Ultimately, this research contributes to a deeper understanding of climate-sensitive hazards
in mountainous regions and provides a scientific foundation for disaster-resilient planning and sustainable
watershed management in the Himalayas.