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

Abstract

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

Mean Sea Level: The Effect of the Rise in the Environment

“…Bloetscher, et al [11] noted that by proximity, the Inhabitants of the coastal zones are at more risk of sea-level rise because of coastal erosion, saltwater intrusion, and storm surge. These zones have a high groundwater level given the soil's low holding capacity, increasing the risk of groundwater flooding [7,[11][12][13].…”

Geospatial Multi-Criteria Evaluation Using AHP–GIS to Delineate Groundwater Potential Zones in Zakho Basin, Kurdistan Region, Iraq

“…Most of these techniques are based on multi-parameter statistical methods [10], including the decision tree model [11], principal component analysis (PCA) [12], the logistic regression model [13], Gravity Recovery and Climate Experiment (GRACE) [14], and another model called DRASTIC-LU/LC [15], which means "Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity". The integration of a Geographic Information System (GIS) and RS techniques with an Analytical Hierarchy Analysis (AHP) has produced an innovative model technique that is easy to use and produces precise results [16].…”