tuje Turkish Journal of Engineering 2587-1366 Murat YAKAR 10.31127/tuje.1819040 Photogrammetry and Remote Sensing Fotogrametri ve Uzaktan Algılama Advanced Geospatial Analysis and Frequency Ratio Modelling for Flood Hazard Zonation in the Nagavali Basin, India https://orcid.org/0009-0005-3852-6459 Maarouf Ruba Andhra University https://orcid.org/0009-0009-5945-4561 Mahammood Vazeer Andhra University https://orcid.org/0009-0009-9586-7742 Rao P Jagadeeswara Andhra University 05 01 2026 10 2 493 504 11 06 2025 12 13 2025 Copyright © 2017, Turkish Journal of Engineering 2017 Turkish Journal of Engineering

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.

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