The Use of GIS and Multi-Criteria Fuzzy Logic to Assess and Identify Flood-Prone Areas in the Greater Ghat Region

Abstract

This study presents an approach to integrate GIS with a multi-criteria fuzzy logic model to identify potential flood risk areas in Ghat region, Libya. The study included six criteria, namely, runoff number (CN) curve number, slope (S) Slope, elevations (E) elevation, Drainage density (Dd) and TWI Topographic Wetness Index, and Topographic Position Index (TPI) to prepare the risk index. Using the fuzzy logic analysis tools in ArcGIS, Fuzzy Function Membership functions are mapped to related raster values ​​in criteria map layers between 0 and 1 and the Fuzzy overlay tools are used to integrate the multi-criteria ambiguous membership outcome maps into the flood risk map. Then, defuzzification was carried out by reclassification using a Natural Separation Classifier (Jenks) and transformed into a conventional final fitting map to identify the flood-prone areas of Ghat. In addition, historical flood inundation data obtained from the SENTINEL-2 satellite platform was used to validate the methodology. The analysis found that 40% of floods are associated with areas of high to very high flood risk. Residential land is more prone to flooding than other types of land use. The results showed that the GIS-based multi-criteria analysis framework can be effectively applied for flood risk analysis to support decision-making in disaster management.