Mapping Flood Vulnerability by Applying EBF And AHP Methods, in the Iraqi Mountain Region

Abstract

Flood hazards are a member of the world's catastrophic events with a hydrological climate origin. They are referred to as a situation in which the river flow and water level increase suddenly and cause human and financial losses. This research aims to determine flood-prone zones and evaluate the efficacy of RS and GIS-based evidence-based belief function (EBF) and hierarchical analysis (AHP) models in flood-prone area mapping. Using the Rezan River basin in the Mergasor area of Erbil governorate, Iraq, as an example, 11 factors such as slope, slope direction, land use, distance to the stream, distance to the road, elevation, soil, rainfall, geology, NDVI, and drainage density were utilized for flood moderation. The prediction rates of the EBF and AHP models were also analyzed to be 0.869% and 0.836%, respectively, indicating that these two models are better predictors. The findings of the study area revealed that 32% of the study area is under very high to high flooding hazard zones for the EBF method and 22% for the AHP method. This research’s conclusions are crucial for flood-prone region management, decision-making, and local administrative planning.