Hydrodynamic Modelling of Floods and Estimating Socio-economic Impacts of Floods in Ugandan River Malaba Sub-catchment

Abstract

River Malaba sub-catchment tends to experience dramatic flooding events, with several socio-economic impacts to the nearby communities, such as loss of lives and destructions of physical infrastructure. Analysis of spatiotemporal extents to which settlements, crops and physical infrastructures tend to be inundated are vital for predictive planning of risk-based adaptation measures. This paper presents a case study on flood risk assessment for Ugandan River Malaba sub-catchment. We applied the two-dimensional Hydraulic Engineering Center’s River Analysis System (2D HEC-RAS) for modelling of flooding extents. We considered extreme flow quantiles, lower and upper quantiles corresponding to the 95% confidence interval limits aimed at determining uncertainties in the flooding extents. Spatial extents of inundation on human settlement, land cover and infrastructure were analysed with respect to return periods of extreme flow quantiles. Finally, we estimated economic loss on infrastructure due to flooding. Results from the 2D HEC-RAS model were satisfactorily comparable with the results of observations. Amongst the land use types, cropland exhibited the highest vulnerability with at least 10,234.8 hectare (ha) susceptible to flooding event of 100-year return period (YRP). Inundated built-up land-use exhibited the highest vulnerability percentage increase (90%) between 2- and 100-YRP. In US Dollar, about US$ 33 million and US$ 39 million losses are estimated at 2- and 100-YRP, respectively, due to inundated rice gardens and these indicate a looming high risk of household food insecurity and poverty. Several infrastructure including 15 academic institutions, 12 health facilities, 32 worshiping places remain annually vulnerable to flooding. At least 6 km and 7 km of road network are also susceptible to flooding under extreme flows of return periods 2 and 100 years, respectively. Churches exhibited the highest economic losses of US$ 855,065 and US$ 1,623,832 at 2-YRP and 100-YRP, respectively. This study findings are relevant for planning the development of sustainable flood risk adaptation pathways given the established destructions within the sub-catchment due to flooding.

An Integrated Artificial Intelligence of Things Environment for River Flood Prevention

“…A study by Wang et al [ 4 ] put forward the impact of the Yangtze River floods in 2020 on China’s importation of feeds and grains from the USA, raising its rates to over 316% in the first semester of 2021. In Uganda, Mubialiwo et al [ 5 ] presented a model that estimated the direct losses due to the recurrent Malaba river flooding as $33 Million in a two-year return period, including over $855,000 in worshipping places alone. Other socioeconomic infrastructures remain under direct flood threat, including 27 health and education facilities.…”