A comparative assessment of data-driven flood susceptibility mapping in Nigeria

Abstract Flood risk in West Africa, particularly Nigeria, has significantly increased over the past 5 decades due to changing hydrological conditions, insufficient mitigation measures, and limited adaptation efforts. This study responds to the need for accurate and high-resolution data to support effective disaster risk management by developing a nationwide, 30 m flood susceptibility map using only open-access data and scalable methods. Leveraging open-access and multi-source remote sensing and geospatial datasets, we systematically compared four digital elevation models (DEMs) and four hydrological methods (D8, D-inf, FD8, and Rho8). Additional flood-influencing factors, including land cover, soil characteristics, and proximity to water bodies, were also incorporated to capture the complex drivers of flood susceptibility. Three machine learning models were developed and evaluated: random forest, binary logistic regression, and linear discriminant analysis. Across all models, the highest accuracy was achieved using the Copernicus DEM in combination with the D8 and FD8 methods. Model performance was validated against the September–October 2022 floods, one of the most catastrophic and well-documented events in Nigeria, demonstrating a strong predictive capability. To reconcile differences among model outputs, we generated an ensemble map that consolidates their strengths while accounting for uncertainty. Compared with previous studies our approach demonstrates how open and reproducible methods can be scaled to the national level and to other African countries. We estimated that approximately 11 million people in Nigeria live in flood-prone areas, underscoring the urgency of integrating susceptibility information into disaster risk management and spatial planning. Our results provide actionable insights for policymakers and practitioners: delineating high-risk zones for land-use regulation, avoiding urban expansion in floodplains, and prioritizing mitigation and adaptation measures. To promote transparency and reproducibility, we release both the scripts and the final flood susceptibility maps for Nigeria ( https://figshare.com/s/dc2318c9884f57b22c0d ).