Dynamic and Scalable Flood Risk Assessment Using GIS, AHP, and Novel Fuzzy AHP: A Case Study of the Upper Tigris Basin

Floods are one of the most frequent and destructive natural disasters, requiring advanced methodologies for effective risk assessment and management. This study evaluates flood risk in the Upper Tigris Basin using Geographic Information Systems (GIS) integrated with the Analytic Hierarchy Process (AHP) and Fuzzy AHP (FAHP). By analyzing eight critical parameters—precipitation, slope, elevation, lithology, land use, soil type, aspect, and proximity to rivers—risk maps were generated through Multi-Criteria Decision-Making (MCDM) techniques. The AHP method identified precipitation as the most critical factor, contributing 32.5% to overall risk, while FAHP refined the results by addressing uncertainties, enhancing the weights of key parameters like precipitation (32.6%) and slope (15.4%). The FAHP map showed greater differentiation in medium- and low-risk areas, improving its suitability for localized interventions. High-risk zones in northeastern districts, including Lice, Hani, and Hazro, were influenced by high precipitation and steep slopes. Beyond the local context, this study demonstrates the global applicability of integrating GIS with fuzzy logic-based methods for disaster risk assessment. By effectively capturing uncertainties and enhancing precision, these methods provide a replicable framework for other regions facing similar challenges. This research contributes to the scientific understanding of flood dynamics and offers innovative tools for improving disaster preparedness and mitigation strategies worldwide.