Study of flooding in Kasese for effective flood risk management
Abstract
Kasese district has been repeatedly affected by destructive floods caused by six major rivers, with the most significant impact observed in the catchment of R. Nyamwamba. The district has seen an alarming rise in the frequency and severity of flooding events, resulting in loss of life, property damage, and infrastructural destruction.
Despite advancements in flood risk management and response strategies, the district faces challenges in disaster preparedness, response, and recovery that include lack of real-time data, limited use of emerging technologies, and insufficient integration of climate change projections into flood risk assessment models. This study employed remote sensing, Geographic Information System (GIS), hydrological, and hydraulic modelling techniques, to assess flood risk with the objective of improving disaster response and reducing community vulnerability.
The hydrological modelling was conducted using HEC-HMS, employing the Soil Curve Number method as the loss method, and Muskingum routing to simulate runoff from the catchment. Flow simulations were forecasted for various design storms generated from rainfall data analysis using the Rational method, enabling the generation of flow hydrographs for each flood event. Subsequently, hydraulic modelling was performed using HEC-RAS, incorporating the runoff data to develop floodplain maps for each flood event.
The catchment covered an area of approximately 122 km². The simulated peak discharge values for the catchment at the outlet were 1224.4, 1465.5, 1840.1, and 2763.6 m³/s for the 10, 25, 50, and 100-year design storms, respectively. The analysis of the results identified six hotspot areas, indicating infrastructure and livelihoods at risk, and suggesting flood protection action.
By leveraging geospatial technologies and interdisciplinary collaboration the study develops effective flood risk management strategies, empowering communities, and authorities with accurate information for informed decisions. This adaptive flood hazard management system promotes community resilience and sustainable development in a rapidly changing world.