This work examines flood-prone areas in Wadi Numan, Makkah, Saudi Arabia, using an integrated geographic information system (GIS) approach combined with three multicriteria decision-making (MCDM) techniques analytical hierarchy process (AHP), best-worst method, and full consistency method (FUCOM) and two fuzzy logic methods fuzzy analytical hierarchy process (F-AHP) geometric mean and F-AHP extent analysis. A geospatial data set was created, including 70 historical flood sites, 55 nonflood locations, and nine flood-related factors covering hydrological, topographical, and environmental variables. These factors include rainfall depth, surface elevation, hydrologic soil group, slope, topographic wetness index, stream density, topographic ruggedness index, stream power index, and sediment transport index. The area under the curve (AUC) was used to assess the model’s output. The outcomes show that, especially in low-lying areas, 53% of the research area is at high or extremely high flood vulnerability. Among the decision-making methods, F-AHP with the geometric mean and FUCOM demonstrated the highest accuracy in identifying flood vulnerability, with AUC values of 87.2% and 84.8%, respectively, while F-AHP with extent analysis exhibited lower accuracy, with an AUC of 71.8%. Sensitivity analysis highlighted the significant role of topography in flood vulnerability, emphasizing its importance for effective flood management. This work demonstrates the effectiveness of GIS-based MCDM and fuzzy approaches in flood vulnerability assessment, providing valuable insights for decision-makers involved in flood mitigation and urban planning.
Al-Juaidi et al. (2026) studied this question.