Advanced Geospatial Analysis and Frequency Ratio Modelling for Flood Hazard Zonation in the Nagavali Basin, India

Year 2026, Volume: 10 Issue: 2 , 493 - 504 , 01.05.2026

Ruba Maarouf , Vazeer Mahammood , Jagadeeswara Rao P

https://doi.org/10.31127/tuje.1819040

https://izlik.org/JA77JA38WZ

Abstract

Flooding remains one of the most destructive natural hazards in the eastern Indian river basins, but the controlling factors and spatial extent have not been thoroughly measured. The research investigates the geospatial assessment of flood prone areas in the Nagavali Basin using the Frequency Ratio (FR) model. The main aim of the study is to delineate monsoon-driven flood susceptibility zones. To do this, geospatial variables, including land use/land cover, distance from river, elevation, slope, landforms, lithology, surface runoff, soil drainage, soil type, topographic wetness index and rainfall were considered. Using Remote Sensing and GIS techniques, the flood susceptible areas of the research area were systematically analyzed and classified into the following five zones: Very Low Susceptibility Zone (36.93%); Low Susceptibility Zone (12.92%); Moderate Susceptibility Zone (18.27%); High Susceptibility Zone (21.19%); and Very High Susceptibility Zone (10.69%). The performance of the FR model was evaluated using 80% of the data for training and 20% for testing. The model had an accuracy of 97% for Very Low Susceptibility Zones for the testing datasets tested. Overall, the model had 100% accuracy in all of the susceptibility zones. The analysis utilized in this study demonstrates the operational efficiency of using the Frequency Ratio model in delineating flood prone areas and showcases the effectiveness of geospatial technologies in risk mapping and disaster management. This study fills the research gap by defining flood susceptibility zones using the Frequency Ratio (FR) model and sophisticated geospatial techniques. Actionable recommendations for local authorities and policy makers to improve their flood preparedness, develop localised mitigation measures and design more sustainable interventions are provided by the results, which can reduce the negative impacts of floods in vulnerable areas of the Nagavali Basin.

Keywords

Flood Susceptibility , Frequency Ratio Model , Geospatial Analysis , Remote Sensing , LuLc

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