Near Real Time (NRT) Flood Forecasting for the Great Chao Phraya River Basin using Rainfall-Runoff-Inundation Model

Abstract

A flood is a major natural disaster caused by heavy rainfall and rain accumulated for a long time that causes severe problems and extensive damage to socio-economic and ecological systems. The flood problem has become more severe in Thailand, with higher damage value. The World Bank’s estimate for the 2011 Thailand flood has estimated 1,425 trillion baht in economic damages and losses. Near-Real-Time (NRT) flood forecasting is crucial to avoid damage from flood disasters. This study proposes an NRT flood forecasting approach in the Great Chao Phraya River Basin, Thailand. The Rainfall-Runoff-Inundation model first simulated river discharge and inundation depth from observed data such as rainfall, evaporation, and dam release. Then, 10-day forecasted rainfall from the Thai Meteorological Department (TMD) and previous results were used to simulate flood forecasting. The discharge hydrograph and flood inundation map from the NRT flood forecasting model provide flood forecasting to reduce the emergency response time to flood disasters to minimize flood damage in the Chao Phraya River Basin, Thailand. However, the NRT flood forecasting model had an error in the flood simulations that could be coming from the systematic accumulated errors in the model. Therefore, this preliminary study will lead to further development with more accuracy and precision.