Comparison of the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Logic for Flood Exposure Risk Assessment in Arid Regions

Abstract

Flood risk assessment is an important tool for urban planning, land development, and hydrological analysis. The flood risks are very high in arid countries due to the nature of the rainfall resulting from thunderstorms and the land cover, which comprises mostly very dry arid soil. Several methods have been used to assess the flood risk, depending on various factors that affect the likelihood of occurrence. However, the selection of these factors and the weight assigned to them remain rather arbitrary. This study assesses the risk of flood occurrence in arid regions based on land cover, soil type, precipitation, elevation, and flow accumulation. Thematic maps of the aforementioned factors for the study area were prepared using GIS. The Fuzzy Analytic Hierarchy Process (F-AHP) was used to calculate the likelihood of the flood occurrence, and land use was used to assess the exposure impact. Using the likelihood map (i.e., probability) from the Fuzzy-AHP and an exposure map, the flood risk was assessed. This method was applied to Qatar as a case study. Results were compared with those produced by fuzzy logic. To explore the pairwise importance of the F-AHP, equal weight analysis was performed. The resulting risk map shows that the majority of urbanized areas in Qatar are within the high-risk zone, with some smaller parts within the very high flood-risk area. The majority of the country is within the low-risk zone. Some areas, especially land depressions, are located within the intermediate-risk category. Comparison of Fuzzy logic and the F-AHP showed that both have similarities in the low-risk and differences in the high-risk zones. This reveals that the F-AHP is probably more accurate than other methods as it accounts for higher variability.