Spatial Modeling of Flood Hazard in Addis Ababa Using Geographic Information System ( <scp>GIS</scp> ) and Information Gain Ratio ( <scp>IGR</scp> ) Method

ABSTRACT Floods are one of nature's most disturbing catastrophes, resulting in infrastructure damage, property devastation, and mortality. In Addis Ababa, flooding has significantly impacted residents and caused millions' worth of property damage in the last decade alone. It is continuously threatening and affecting city residents. This study focused on the spatial modeling of floods and the identification of areas susceptible to flood hazards in the city. Geographic information system (GIS) techniques combined with the information gain ratio (IGR) method were employed in this study. Five major flood hazard factors were identified: elevation, slope, rainfall, drainage density, and distance from drainage channels. The results show that 1.3% (7.1 km 2 ) of the area is highly susceptible to floods, 29.4% (159 km 2 ) is highly susceptible to heavy rains, 56% (302 km 2 ) of the area is moderately susceptible, 12.5% (67.3 km 2 ) of the area has low susceptibility, and less than 1% (4.2 km 2 ) has very low susceptibility. Slope is the most influential factor (42.74%), followed by drainage density (28.21%), distance from drainage channels (18.8%), rainfall (7.69%), and elevation (2.56%). The sub‐cities of Nifas Silk Lafto and Akaki Kality are the most susceptible to flood hazards; areas with steep slopes trigger high runoff during heavy rainy periods and cause flood hazards on gentle slope surfaces. It is recommended that to improve the accuracy of identifying susceptible flood‐hazard locations, flooding simulation should be performed in conjunction with other variables and rainfall data (such as rainfall duration and intensity). Nevertheless, this research provides recommendations to municipal administration decision‐makers regarding strategic management in the prioritization of flood‐hazard zones.