{"title":"Flood hazard and risk assessment using GIS and remote sensing in the case of Ziway Lake watershed, central Main Ethiopian Rift","authors":"Musa Husein , Tariku Takele , Dechasa Diriba , Shankar Karuppannan","doi":"10.1016/j.indic.2025.100920","DOIUrl":null,"url":null,"abstract":"<div><div>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<sup>2</sup>) fall within the high to very high-risk zones. The rest are classified as moderate (1995 km<sup>2</sup> or 27 %) and low (906 km<sup>2</sup> or 12 %), while the high and very high categories specifically account for 2328 km<sup>2</sup> (32 %) and 2043 km<sup>2</sup> (28 %), respectively. According to the flood risk map, 2424 km<sup>2</sup> (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.</div></div>","PeriodicalId":36171,"journal":{"name":"Environmental and Sustainability Indicators","volume":"28 ","pages":"Article 100920"},"PeriodicalIF":5.6000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental and Sustainability Indicators","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2665972725003411","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
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 km2) fall within the high to very high-risk zones. The rest are classified as moderate (1995 km2 or 27 %) and low (906 km2 or 12 %), while the high and very high categories specifically account for 2328 km2 (32 %) and 2043 km2 (28 %), respectively. According to the flood risk map, 2424 km2 (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.