Flood Susceptibility Mapping Using an Analytic Hierarchy Process Model Based on Remote Sensing and GIS Approaches in Akre District, Kurdistan Region, Iraq

In recent decades, floods have been the most common, complex, and destructive natural calamities worldwide. Hence, for inclusive flood risk assessment, creating susceptibility mapping to demarcate flood-vulnerable zones is fundamental decision makers. To assess flood-prone locations in Akre, Iraqi Kurdistan Region, was undertaken using geographic information systems, remote sensing, an analytic hierarchy process model. susceptibility, systems framework used 15 ideal causative factors flooding: altitude, slope, distance streams, flow accumulation, drainage density, rainfall, soil type, lithology, curvature, topographic wetness index (TWI), roughness stream power index, transport land use/land cover, normalized difference vegetation index. The contributing flooding were optimally weighted with respect proposed final map reclassified into five different classes of very low (16.64% study area); (19.53%); moderate (38.92%); high (17.83%); (7.08%). area under curve values predicted rate success AHP model 0.956 0.971, respectively. Therefore, results accurate reliable. a powerful method mitigate serious impacts assist scholars, local governments policymakers future master planning.