Longitudinal stage profiles forecasting in rivers for flash floods

Abstract

A flash flood routing model with artificial neural networks predictions was developed for stage profiles forecasting. The artificial neural network models were used to predict the 1-3 h lead time river stages at gauge stations along a river. The predictions were taken as interior boundaries in the flash flood routing model for the forecast of longitudinal stage profiles, including the un-gauged sites of a whole river. The flash flood routing model was based on the dynamic wave equations with discretization processes of the four-point finite difference method. Five typhoon events were applied to calibrate the rainfall-stage model and the other three events were simulated to verify the model's capability. The results revealed that the flash flood river routing model conjunction with artificial neural networks can provide accurate river stages for flood forecasting.