Flood risk assessment in Namisindwa district using GIS.

dc.contributor.authorMbeiza, Delorence
dc.date.accessioned2022-03-30T11:44:19Z
dc.date.available2022-03-30T11:44:19Z
dc.date.issued2022
dc.descriptionDissertationen_US
dc.description.abstractThroughout the human history floods have been an integral part of the civilization. Still men have not quite coped well to live with floods. Flooding is the most frequent global natural disaster; rural areas are becoming more vulnerable to flooding due to effect of climate change. Flash flood is one of the most prominent phenomena caused by heavy rains. In developing countries drainage channels is the most common strategy employed for flood control. The failure of preventive measures has led to most authors and researchers to advocate a shift in thinking from preventive measures to flood risk and structural management measures. Recently, the advancement in computer-aided technology has been extensively used in formulating models used for flood calculation and hazard analysis. This study focuses on using a hydraulic model HEC-HMS and HEC-RAS in a GIS environment for the affected areas of Namisindwa, generates the inundation area and the return period for the specified flood events. The research involved studying various literature and collecting ancillary data in form of journals and reports. This helped to formulate the methodology for the whole project. Hydrological modeling was performed using HEC HMS software, after delineating the catchment basin model using HEC GeoHMS in ArcGIS environment, populating the meteorological model with design storm data and defining control specifications. The 2, 5, 10, 20, 50- and 100-year design storms data input into the model generated design floods of 33.8m 3 /s, 52.0m 3 /s, 66.2m 3 /s, 80.6m 3 /s, 99.9m 3 /s and 114.9m 3 /s magnitudes respectively. Hydraulic modelling was performed using HEC RAS software. The model output channel flood depths at the gauging station were 1.29m, 1,53m, 1.68m, 1.81m, 1.98m and 2.09m for stimulated 2, 5, 10, 20, 50 and 100year design floods respectively. Flood hazard maps were generated by exporting the HEC RAS model output results to Arc GIS where they were processed to identify the flood prone areas. From the flood hazard maps, the most flood prone areas were around the river middle reach.en_US
dc.description.sponsorshipMr. Oketcho Yoronimo, Busitema Universityen_US
dc.identifier.citationMbeiza, Delorence. (2022). Flood risk assessment in Namisindwa district using GIS. Busitema University. Unpublished dissertation.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12283/986
dc.language.isoenen_US
dc.subjectFloodsen_US
dc.subjectCivilizationen_US
dc.subjectFloodingen_US
dc.subjectNatural disasteren_US
dc.subjectHeavy rainsen_US
dc.subjectDrainage channelsen_US
dc.subjectGIS environmenten_US
dc.titleFlood risk assessment in Namisindwa district using GIS.en_US
dc.typeThesisen_US

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