Prediction of Annual Flood-Prone Aras using SWAT and HEC-RAS Models

Abstract

The study focuses on predicting flood-prone areas in Niger State’s Kainji Lake watershed in 2025 using the SWAT and HEC-RAS models. The SWAT models. The SWAT model replicates key hydrological processes, integrating satellite-derived data, including precipitation, temperature, land cover, DEM, and soil maps. HEC-RAS simulates river flow and flood inundation, utilizing a 12.5 m ALOS PALSAR DEM for detailed analysis. Both models are calibrated and validated with two years of discharge data from the Nigeria Hydrological Service Agency. Results highlight the vulnerability of several settlements along the Kainji Lake floodplain, such as Kontagora, New Bussa, and Ngaski, under different climate change scenarios. Despite certain limitations, the combined use of SWAT and HEC-RAS effectively identifies areas at risk in flood prediction and management efforts.