Identification of Flash Flood Zones by using RS & GIS and MCDA

Flash floods are among the most destructive hazards, causing sudden loss of life, infrastructure damage, and environmental degradation, particularly in climate sensitive and rapidly urbanizing regions. The study aims to generate flash flood susceptibility maps using land use land cover, slope, lithology, drainage density, rainfall, and elevation through Multi-Criteria Decision Analysis, Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). The results reveal clear spatial variations in flash flood susceptibility across the study area. High and very high risk zones are mainly associated with low elevation, steep slope transitions, dense drainage networks, and impervious land use land cover classes. Receiver Operating Characteristic based validation confirms strong predictive accuracy, indicating the robustness of the proposed fuzzy MCDA framework. The generated thematic maps, including LULC, slope, lithology, drainage density, rainfall, and elevation, along with the final flash flood susceptibility map, provide valuable decision support tools for urban planners, engineers, disaster management authorities, and policymakers. The integration of Fuzzy AHP, Fuzzy TOPSIS, and MCDA ensures realistic handling of uncertainty and accurate prioritization of flood prone zones. Municipal bodies can apply the results for land use zoning, infrastructure design, and stormwater planning. Disaster response agencies benefit from improved preparedness and evacuation planning, while farmers and local communities gain awareness for safer settlements and agricultural activities, supporting sustainable and climate-resilient development. Remote Sensing (RS) and Geographic Information System (GIS) based flash flood assessment integrates land use, slope, drainage, rainfall and elevation to map susceptibility zones for disaster preparedness and risk mitigation.