A GIS-enabled AHP approach for mapping urban flood susceptibility in Bhubaneswar city

Urban floods are among the most devastating natural disasters, causing severe damage to human life, property, and the economy. In this study, we focused on mapping Urban Flood Susceptibility Zones (UFSZ) within the Bhubaneswar Municipal Corporation (BMC), as it used a GIS-based Analytical Hierarchy Process (AHP) model integrated via Remote Sensing (RS) with Multi-Criteria Decision-Making (MCDM) techniques. Twelve flood-inducing factors were given weight by the model. Elevation had 25%, Land Use and Land Cover had 19%, and Distance to River received 15%, marking these as critical parameters. We analyzed 130 flood event locations collected through field surveys conducted between June and September 2023, validating flood-prone zones using the Google Earth Engine (GEE). A Consistency Ratio (CR) of 0.06 (<0.1) confirmed the reliability of the weight calculations. The results showed that 45.82% of the area of Bhubaneswar lies within the southern, southeastern, and central parts of the city that are identified under high to very high flood susceptibility zones. This research uniquely fulfils the need for a high-resolution flood susceptibility map and provides crucial insight to city planners and policymakers for improving urban flood resilience, urban infrastructure development, and flood disaster risk management.