Integrating Hydrological Models for Improved Flash Flood Risk Assessment and Mitigation Strategies in Northeastern Thailand

This study focuses on assessing flash flood risks in Northeastern Thailand, particularly within the Lam Saphung, Phrom, and Chern River Basins, which are highly susceptible to flash floods and debris flows. Using the HEC-RAS hydraulic model integrated with GIS tools, the research analyzes historical and scenario-based flood events to evaluate the impact of land use changes and hydrological dynamics. The model was calibrated and validated with statistical metrics such as R2 values ranging from 0.745 to 0.994 and NSE values between 0.653 and 0.893, indicating strong agreement with the observed data. This study also identified high-risk areas, with up to 5.49% and 5.50% increases in flood-prone areas in the Phrom and Chern River Basins, respectively, from 2006 to 2019. Key findings highlight the critical role of proactive risk management and targeted mitigation strategies in enhancing community resilience. The integration of advanced hydraulic modeling with detailed datasets enables precise flood hazard mapping, including flood depths exceeding 1.5 m in certain areas and high-risk zones covering up to 105.2 km2 during severe flood events. These results provide actionable insights for emergency response and land use planning. This research significantly contributes to hydrological risk assessments by advancing modeling techniques and delivering practical recommendations for sustainable flood management. The outcomes are particularly relevant for stakeholders, including urban planners, emergency management officials, and policymakers, who aim to strengthen resilience in vulnerable regions. By addressing the complexities of flash flood risk assessments with robust quantitative evidence, this study not only enhances the understanding of flood dynamics, but also lays the groundwork for developing adaptive strategies to mitigate the adverse impacts of flash floods, safeguarding both communities and infrastructure in the region.