What is it about?
This study analyzed the Rangit River Basin's morphometry to assess flood risk. Six sub-watersheds (SW1-SW6) were prioritized via morphometric parameters. SW1, SW4, and SW5 are high priority. A Random Forest ML model (24 variables) created a flood risk map. The results aid flood mitigation efforts.
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Photo by KHAWAJA UMER FAROOQ on Unsplash
Why is it important?
Sub-watersheds’ ranking in terms of their flood susceptibility is of prime importance for flood risk management and conservation policies. On the basis of the identification of the most vulnerable sub-watersheds (those with the lowest compound values and highest priority rankings), policymakers and planners can identify these as the most critical areas for urgent intervention. These rankings assist in strategic resource distribution, including the development of flood control structures (e.g., embankments, detention basins, and check dams) in risk-prone sub-watersheds. Watershed conservation, including afforestation, soil conservation, and sustainable land-use planning, can also be suited to the degree of flood susceptibility in each sub-watershed. Less intensive interventions may be suitable in low-risk sub-watersheds, while high-risk sub-watersheds need more holistic flood mitigation measures. Through these rankings incorporated in regional planning, governments can improve flood resilience, reduce damage to infrastructure, and protect communities.
Perspectives
"Working on this publication was a deeply rewarding experience. It was a pleasure to collaborate once again with trusted, long-time colleagues, which always makes the research process smooth and insightful. What made this particular project stand out was also the opportunity to mentor and include a 'new researcher', bringing fresh perspectives to our team. The culmination of our collective effort is a significant piece of work: the creation of a sophisticated 'flood risk map for the Rangit River Himalayas', developed by uniquely integrating land shape data with powerful machine learning techniques. This study represents both the strength of established partnerships and the excitement of fostering new talent."
Prolay Mondal
Raiganj University
Read the Original
This page is a summary of: Integrated morphometric and machine learning-based flood risk assessment in the Rangit river sub-watersheds, Eastern Himalayas, Discover Applied Sciences, October 2025, Springer Science + Business Media,
DOI: 10.1007/s42452-025-07776-7.
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