IIT Guwahati Maps 492 Potential Glacial Lake Sites

Researchers from IIT Guwahati have developed a predictive framework that identifies hundreds of locations in the Eastern Himalayas where new glacial lakes are likely to form. The study offers critical insights for disaster-risk reduction, infrastructure planning, and long-term water-resource management in high-mountain regions vulnerable to climate change.

Predictive Framework For Eastern Himalayas

The research team from Indian Institute of Technology Guwahati analysed high-resolution Google Earth imagery and digital elevation models to assess terrain characteristics across the Eastern Himalaya. Using this approach, the model identified 492 sites with a high likelihood of future glacial lake formation, flagging zones that require close monitoring and preventive planning.

Implications For Hazard And Water Management

According to Prof. Ajay Dashora, the framework can support early-warning systems for Glacial Lake Outburst Floods (GLOFs) and guide safer planning of roads, hydropower projects, and settlements. Beyond disaster mitigation, the findings help anticipate how water systems may evolve as glaciers retreat, supporting climate-resilient development in Himalayan regions.

Advanced Modelling And Key Predictors

The study tested three predictive methods—Logistic Regression, Artificial Neural Networks, and Bayesian Neural Networks. Among them, the Bayesian Neural Network emerged as the most accurate, as it effectively captured complex landscape features and quantified uncertainty. The analysis highlighted neighbouring lakes, cirques, gentle slopes, and retreating glaciers as the strongest predictors of new glacial lake formation, underscoring the role of landform structure in glacial dynamics.

Important Facts for Exams

• Glacial Lake Outburst Floods (GLOFs) pose major risks in Himalayan regions.
• Bayesian Neural Networks help model uncertainty in climate-related predictions.
• Eastern Himalayas are highly sensitive to glacier retreat.
• Terrain features influence the formation of glacial lakes.

Future Enhancements And Global Relevance

The researchers plan to integrate moraine development histories, automate data preparation, and include field-based validation to improve accuracy. The framework is adaptable to other glaciated mountain regions worldwide, making it a valuable tool for global climate adaptation, large-scale glacial hazard monitoring, and disaster-risk reduction strategies.