Developing an Integrated Spatial Framework for Flash Flood Risk Assessment Using GIS, Multi-Criteria Decision Models, and Empirical Village-Level Data

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Flash floods are one of the most destructive natural hazards, especially in rural areas where communities are highly exposed and have limited capacity to adapt. Their rapid onset, short warning times, and the intense transport of sediments pose serious risks to settlements, infrastructure, and livelihoods. In the Gorganrood watershed of Golestan Province, the combination of diverse climatic conditions, land use patterns, and various environmental, social, and economic vulnerabilities further exacerbates these risks. The goal of this research is to create a detailed model for assessing the risk of flash floods and their impacts on rural communities. This study examines the factors that contribute to flash floods and the vulnerability of rural populations. Additionally, it aims to provide a comprehensive scientific basis for understanding flash flood dynamics and their impacts, which can support community preparedness and effective risk reduction measures. The study employs a mixed-methods approach that combines spatial analysis with field-based data collection. A structured questionnaire was distributed to 75 participants, including residents, experts, and local officials, to assess the significance of various indicators: physical, institutional, socio-cultural, economic, and environmental. Statistical analysis was conducted using SPSS, and GIS was utilized to examine spatial patterns and identify hotspots of vulnerability. The findings show that land-use dynamics are the most influential factor in determining flash flood risk, receiving the highest mean score (3.41), while environmental indicators ranked lowest (2.94). Risk assessments further revealed that villages in central and northern sub-basins face the greatest exposure, though vulnerability patterns remain fragmented and lack spatial coherence. Importantly, socio-cultural and institutional factors—including income, education, preparedness, governance, and coordination—were consistently prioritized by both experts and community members as decisive drivers of resilience. The principal outcome of the study is an integrated spatial model that combines hazard parameters with socio-economic and institutional vulnerabilities. Structured across five analytical stages, the model provides a comprehensive framework for identifying high-risk areas and explaining variations in community resilience. By demonstrating the interplay between physical drivers and social dynamics, the research advances the understanding of flash flood risks in rural settings and delivers practical insights that can guide more effective preparedness and risk reduction measures.

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