Near real-time flood forecasting system for the Greater Chao Phraya River Basin

Floods are major natural disasters that cause severe problems and extensive damage to socioeconomic and ecological systems. Estimating and forecasting flood inundation are crucial for early warning, flood mitigation, and adaptation measures to manage risk and mitigate damage. This study proposes a near real-time (NRT) flood forecasting system using a rainfall-runoff-inundation model for the Greater Chao Phraya River Basin in Thailand, which covers large regions and specific high-risk areas. The NRT flood forecasting system operates through preprocessing, processing, and post-processing steps. Initially, the flood simulation model estimates river discharge and inundation depth using observed data such as rainfall, evaporation, and dam releases. Subsequently, the flood forecasting model simulates flood events based on 10-day forecasted rainfall and previous simulation results, producing discharge hydrographs and flood inundation maps. The performance of the NRT flood forecasting system was evaluated using observed daily discharge and inundation areas from satellite images during flood events in October 2023. Overall, despite the absence of notable deviations in the timing and magnitude of the forecasts, the hydrographs demonstrate the capability of the system to predict general discharge trends. Results provide crucial information for early emergency responses, potentially minimizing flood damage and enhancing the accuracy and precision of future system developments. This study lays the groundwork for further development, aiming toward a highly accurate and reliable flood forecasting system.