Abstract
A flash flood is a natural phenomenon generally occurring in regions with dense and compact rainfall. The arid Far-North Region of Cameroon (FNRC) is subject to such climate conditions which result in recurrent flash flood events. Those events often cause numerous deaths and important property damage. This article aims at mitigating and reducing flood risks in the FNRC using a GIS-based multicriteria decision-making technique. For this, data were collected from the radar sensor ALOS PALSAR 2, the optical sensor Landsat 9 Operational Land Imager (OLI), and WorldClim 2. From the aforementioned datasets, ten influencing layers, namely curvature, drainage density, elevation, distance to rivers, distance to lakes, land use/land cover (LULC), rainfall, slope, stream power index (SPI) and topographic witness index (TWI) were prepared, normalized, and combined on a GIS environment. The resulting map of the flood susceptible zones (FSZ) reveals two-fifths of the FNRC is seriously threatened by flash flood events. FSZ are clearly demarcated and mapped, and this map is of paramount importance for sustaining safe settlements in the FNRC. In the context of scarce ground data, as in the FNRC where there is a single rain gauge located at the airport, a combined remote sensing-analytical hierarchy process is effective for flash flood investigation. This approach can help in flash flood analysis in other regions of the world.