Assessing flood susceptibility and effectiveness of structural flood mitigation measures applied within Mubuku catchment in Rwenzori Region, Uganda

Floods are an inherent component of the hydrological cycle threatening the socioeconomic and environmental systems. The use of geographic information systems and remote sensing in flood risk modeling remains integral to its mitigation. This study modeled the flood susceptibility in the Mubuku catchment area, a flood hotspot in the Rwenzori region of Western Uganda. The study objectives were twofold: identifying flood risk-prone areas and assessing effective flood mitigation practices. Remote sensing techniques were used to identify flood risk areas, while a semi-structured questionnaire evaluated mitigation strategies. The Relative Frequency Ratio model and the Spatial Multi-Criteria Evaluation method assessed both flood susceptibility and the effectiveness of the mitigation measures. Interviews were conducted with 171 households and eight flood-contributing factors were analysed. The study found that very high- and high-flood-risk areas downstream covered 75.23 km², whereas low-risk areas upstream covered 23.91 km². The accuracy of the susceptibility map, measured by the Receiver Operating Curve, was 89.9%. Low altitude, grey sands and sandy clay loam soils, and high drainage density significantly influenced flooding. Other factors included topographical wetness index, slope, precipitation, land use and land cover, and stream power index. Tree planting and gabions were perceived by the community as more effective compared to trenches and structural reinforcements in flood mitigation. The study recommends implementing policies for controlled settlements in flood-prone areas. Adopt early warning systems, community sensitization, harness local ecological knowledge, and integrate existing measures like tree planting along gabions and scaling them up to the catchment level for comprehensive flood mitigation.