Key points are not available for this paper at this time.
Among the most destructive natural disasters, floods cause more property damage and fatalities than any other natural hazard. This research aimed to identify flood hazard and risk-prone areas in Ziway Lake watershed, which is situated in the central Main Ethiopian Rift, utilizing geospatial technology such as GIS (geographic information system) and remote sensing techniques. Flood hazard zones have been mapped by analyzing eleven significant indicators: Topographic Wetness Index (TWI), elevation, slope, Normalized Difference Vegetation Index (NDVI), drainage density, rainfall, land-use, soil texture, distance from rivers, distance from roads, and lithology. The weightage of each factor was assigned using the Analytical Hierarchy Process (AHP). Three main factors, such as population density, flood hazard, and land-use, have been employed to identify flood risk zones. According to the flood hazard map, 60 % of watersheds (4371 km 2 ) fall within the high to very high-risk zones. The rest are classified as moderate (1995 km 2 or 27 %) and low (906 km 2 or 12 %), while the high and very high categories specifically account for 2328 km 2 (32 %) and 2043 km 2 (28 %), respectively. According to the flood risk map, 2424 km 2 (35 %) of the region is located in areas with high to very high flood risk. Historical flood data verified the model's reliability and accuracy in identifying regions vulnerable to floods. The findings can be valuable tools for decision-makers to guide preventive measures, improve land use planning, and enhance flood risk management. • GIS and Remote Sensing, approaches assess flood hazard and risk areas. • Mapped flood hazard area using eleven thematic layers: EL, SL, DD, DRV, TWI, NFVI, RF, LULC, FRO, ST, and LIT. • Identified flood risk area using three layers: Flood hazard, LULC and population density. • Flood risk map revealed that 35 % of the watershed is under high to very high flood risk. • The resulting can serve as valuable tools for decision-makers in guiding preventive measures.
Husein et al. (Fri,) studied this question.