Modeling Flood and Drought Risks in Mubuku River Catchment

Abstract

River Mubuku has been exposed to series of alternating hydrologic droughts and flash floods that constantly affect the social and economic livelihood of the riparian population within the catchment and the surrounding communities. Some of the most severe floods and drought events include; the flash flood of May 2013 that led to displacement of up to 7000 people and massive destruction of property, facilities like schools, hospitals and other utilities; the flood of May 2020 that affected 120,000 people. Drought has equally had a lion share with 21 drought events out of 35 drought and flood events reported between February 2017 and March 2018, which affects livelihood of the communities. Additionally, there is a challenge of limited resources, therefore there is need for identification of the most prone areas, to be considered as priority in floods and drought mitigation strategies and possible assistance to the would be affected population. The aim of this study was to model flood and drought risks in River Mubuku so as to provide a better understanding of their spatial distribution as well as identify hotspot areas. The study employed Microsoft excel, R-Studio, hydrologic and hydraulics models coupled with GIS tools to rainfall analysis, flood discharge simulation, drought forecasting and hazard and risks maps. The results and findings were presented in tables and maps. HEC-RAS generated flood inundation maps which were subsequently overlaid on the base map of the study area to produce hazard map which showed 164.1, 175.2, 184.8, 194.0, 201.3 and 207.2 hectare of catchment area are submerged in water on occurrence of 2, 5, 10-, 25-, 50- and 100- years floods respectively with Kyanya Community, Ruboni community camp, Near Fort Portal Highway bridge and portion of Nkenda-Bugoye-Nyakalingijo road (from (30°5’10’’E, 0°19’23’’N) to (30°5’’16’’E,0°19’’14’’N) identified as hotspot areas and 0.55%, 27.92%, 52.63%, 18.87% and 0.031% of the total catchment area under very low, low, medium, high and extreme risks respectively. In Drought forecasting, the model parameters were checked for significance and all the p-values were below 0.01 and therefore would adequately predict the scenarios. The model was then calibrated by checking the RMSE errors which was least for 5 forecasting scenarios and the 3-year lead time which had the least RMSE of 2.229 and had residuals which followed a normal distribution was used. The Streamflow Drought Indices model identified several droughts and the most severe of all being in the months of July in 2022, 2023 and 2024. The river Mubuku catchment is prone to flash floods with even at lower rainfall intensities of 2 years return period where about 8% of the total catchment area is submerged by more than 5m depth of water which considered extreme risk according to MLIT(MLIT,2005) flood risk criteria and a total area of about 80% of area submerged by 100-year return flood at all levels of hazard. While majority of the catchment (52.63%) experiences medium flood risk, the high elevation areas near Mountain Rwenzori ranges are less prone compared to low-lying areas that are under extreme risk and are recommended for immediate attention and assistance in case of floods. The catchment is equally prone to hydrologic drought with the sub-counties of Maliba and Bugoye had the most severe drought risks based on socioeconomic and non-socio-economic indicators.