Flood Susceptibility Mapping in Southern Plateau State, Nigeria Using Frequency Ratio Model and Geospatial Techniques

Flooding is a significant natural hazard in Sub-Saharan Africa, exacerbated by climate variability, rapid urbanisation, and inadequate drainage systems. This study aims to develop and validate a high-resolution (30 m) flood susceptibility map for Southern Plateau State, Nigeria, using the Frequency Ratio (FR) model and multi-source geospatial datasets. Specifically, the study aims to develop a flood inventory from Sentinel-1 SAR imagery and ancillary records, evaluate the influence of ten flood-conditioning factors, generate a Flood Susceptibility Index (FSI), assess model performance using independent validation and spatial-block cross-validation, and provide a decision-support tool for flood risk management and land-use planning. A flood inventory derived from Sentinel-1 SAR flood extents (2021–2022) and ancillary records was divided into training (70%) and validation (30%) datasets. Ten flood-conditioning factors, including elevation, Topographic Wetness Index, rainfall, land use/land cover, NDVI, lineament density, soil type, geology, and distances to rivers and roads were incorporated into the model. The FR model demonstrated excellent predictive performance (AUC = 0.933; 95% CI: 0.882–0.983), with spatial-block cross-validation confirming its robustness (mean AUC = 0.933 ± 0.034). Rainfall, drainage density, built-up areas, elevation, and lineament density were the most influential flood drivers, while High and Very High susceptibility zones occupied 19.13% of the study area. The resulting susceptibility map provides a reproducible framework and practical decision-support tool for flood risk management, land-use planning, and climate adaptation in data-scarce regions. State and local planning authorities should integrate the flood susceptibility map into development control, environmental impact assessment, and urban expansion planning to reduce future flood exposure.