Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index

The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.