The Optimal Flood Forecasting Models in the Northeast of Thailand

Flood occasionally occurs in Northeast of Thailand especially in Mun river basin and cause of damage for socioeconomic loss and losses to humans and poses a potential danger in urban areas located downstream of large river basins. The research focuses on discharge and comparing of Artificial Neural Network, Long Short-Term Memory, and the Physics-Guided Long Short-Term Memory models to developed prediction models. Evaluation of the models’ performance shows that the Artificial Neural Network model outperforms Long Short-Term Memory and the Physics-Guided Long Short-Term Memory models in predicting daily discharge, achieving lower Root Mean Square Error, Percentage Bias, and higher Nash–Sutcliffe Efficiency. The findings suggest that Artificial Neural Network based models offer good performance in river discharge prediction for flood warring system, with potential for further enhancement through model architecture adjustments.