Researchers at the Indian Institute of Technology (IIT) Guwahati have developed a new predictive framework to assess glacial hazards in the Eastern Himalayas, identifying hundreds of locations where new glacial lakes are likely to form in the coming years as glaciers continue to retreat.
Using high-resolution Google Earth imagery combined with digital elevation models, the research team mapped 492 potential sites where glacial lakes could emerge. The study provides crucial inputs for disaster-risk reduction, infrastructure planning and long-term water-resource management in ecologically fragile, high-mountain regions.
The newly developed framework is designed to capture complex terrain characteristics while also accounting for uncertainty in predictions, making its forecasts more realistic and operationally useful. By identifying high-risk zones in advance, the model can support early-warning systems for Glacial Lake Outburst Floods (GLOFs) and guide safer decision-making on the placement of roads, hydropower projects and human settlements.
Professor Ajay Dashora of the Department of Civil Engineering at IIT Guwahati said the framework offers a practical tool to reduce risks faced by Himalayan communities and critical infrastructure. He added that the approach can also help scientists better understand how mountain water systems may evolve as climate change accelerates glacier retreat.
The findings, published in the journal Scientific Reports, underscore the critical role of landform characteristics in glacial lake development. The study confirms that terrain features such as nearby existing lakes, cirques, gentle slopes and retreating glaciers strongly influence where new lakes are likely to form — factors that earlier studies often underestimated.
During the research, the team evaluated three predictive approaches— Logistic Regression, Artificial Neural Networks and Bayesian Neural Networks. Among these, the Bayesian Neural Network was found to be the most accurate in forecasting potential glacial lake formation.
Beyond the Himalayas, the researchers said the framework has wider global relevance and can be adapted for use in other glaciated mountain regions. This could contribute to climate-resilient planning and disaster-risk reduction efforts worldwide.
The team plans to further strengthen the framework by incorporating moraine development histories, automating data preparation processes and adding field-based validation. These enhancements are expected to improve predictive accuracy and expand the model’s applicability for large-scale monitoring of glacial hazards in high-altitude regions.
Also read: PM Modi to visit Assam on Feb 14: Himanta
Follow us
