Modelling on assessment of flood risk susceptibility at the Jia Bharali River basin in Eastern Himalayas by integrating multicollinearity tests and geospatial techniques

Climate change and anthropogenic factors have exacerbated flood risks in many regions across the globe, including theHimalayan foothill region in India. The Jia Bharali River basin, situated in this vulnerable area, frequently experienceshigh-magnitude floods, causing significant damage to the environment and local communities. Developing accurate andreliable flood susceptibility models is crucial for effective flood prevention, management, and adaptation strategies. In thisstudy, we aimed to generate a comprehensive flood susceptibility zone model for the Jia Bharali catchment by integratingstatistical methods with expert knowledge-based mathematical models. We applied four distinct models, including the FrequencyRatio model, Fuzzy Logic (FL) model, Multi-criteria Decision Making based Analytical Hierarchy Process model,and Fuzzy Analytical Hierarchy Process model, to evaluate the flood susceptibility of the basin. The results revealed thatapproximately one-third of the Jia Bharali basin area fell within moderate to very high flood-prone zones. In contrast, over50% of the area was classified as low to very low flood-prone zones. The applied models demonstrated strong performance,with ROC-AUC scores exceeding 70% and MAE, MSE, and RMSE scores below 30%. FL and AHP were recommendedfor application among the models in areas with similar physiographic characteristics due to their exceptional performanceand the training datasets. This study offers crucial insights for policymakers, regional administrative authorities, environmentalists,and engineers working in the Himalayan foothill region. By providing a robust flood susceptibility model, theresearch enhances flood prevention efforts and management, thereby serving as a vital climate change adaptation strategyfor the Jia Bharali River basin and similar regions. The findings also have significant implications for disaster risk reductionand sustainable development in vulnerable areas, contributing to the global efforts towards achieving the United Nations'Sustainable Development Goals.