Flood projections over the White Volta Basin under the shared socioeconomic pathways: an analytical hierarchical approach

Abstract

Introduction Flooding in Ghana’s White Volta Basin poses significant environmental and socioeconomic challenges, driven by both natural and anthropogenic factors. This study assesses future flood vulnerabilities under climate change scenarios to inform disaster risk reduction and sustainable land-use planning. Methods Precipitation data from 15 Global Climate Models (GCMs) under Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were bias-corrected using CMhyd software, validated against observational data (1960–2015) and ERA5 reanalysis (1981–2020). Flood susceptibility maps were generated via the Analytical Hierarchy Process (AHP), integrating ten geospatial parameters (elevation, slope, drainage density, soil type, etc.). Model performance was evaluated using R² (90–100%), NSE (0.384–1), RMSE (789–10,967 mm), and PBIAS (−7.2% to 26%). Results Projections indicate a decline in precipitation across all SSPs, with the sharpest reduction under SSP5-8.5. Tamale is expected to receive the highest rainfall, while Garu experiences the lowest. Flood susceptibility mapping classified the basin into five risk zones: very high (12.09%), high (22.56%), moderate (24.38%), low (24.36%), and very low (16.64%). Future scenarios show significant reductions in high-risk areas, particularly under SSP5-8.5 (−12.21% very high, −3.12% high). Model validation achieved an AUC of 0.795, confirming robust predictive accuracy. Discussion The findings highlight the critical impact of declining precipitation on flood susceptibility, emphasizing the need for adaptive strategies in water resource management and infrastructure planning. The integration of AHP-GIS provides a scalable framework for flood risk assessment, aligning with Ghana’s National Climate Change Adaptation Strategy and the Sendai Framework.