Climate change is increasingly altering hydrological processes in low-lying coastal environments, intensifying flood risks in vulnerable regions such as Bayelsa State in the Niger Delta, Nigeria. This study applied the Soil and Water Assessment Tool (SWAT+) to evaluate the impact of climate variability on flood frequency and intensity in the region. Hydrological modeling was conducted using a 30 m Shuttle Radar Topography Mission (SRTM) Digital Elevation Model, Landsat-derived land use data, FAO soil maps, and climate data obtained from the Nigerian Meteorological Agency (NiMet) and CORDEX-Africa datasets. The model was calibrated and validated using observed streamflow data through the SWAT-CUP SUFI-2 algorithm. Model performance indicated good agreement with observed data, with calibration statistics of NSE = 0.72, R2 = 0.78, and PBIAS = −5.2%, and validation statistics of NSE = 0.65, R2 = 0.70, and PBIAS = +8.3%. Historical analysis (2001–2024) revealed mean annual rainfall of approximately 3,055 mm, with a maximum flood peak of 45 m3/s recorded in 2009. Future projections under the RCP 8.5 scenario (2025–2045) indicate increased rainfall variability, rising temperatures (+1.9 °C), and a projected 15% increase in mean streamflow. Peak flood discharge is expected to increase significantly, suggesting heightened flood magnitude and frequency. These findings highlight the urgent need for climate-informed flood management strategies and resilient infrastructure planning in Bayelsa State.
Moses (Thu,) studied this question.