In a study of flood events forecasting in Flanders, hybrid neural networks based models can complete and correct the measured data of measuring stations in the study area through dynamic interpolation, thereby predicting flood water depth more accurately. In addition, hybrid neural network based models could mimic the physical characteristics of physically based models, to improve the efficiency of flood forecasting.