Research on flood level forecasting in tidal river based on mixture regressive model

In order to solve the problem of complex hydrological situation and flood level forecasting of tidal river in coastal areas, a mixture regressive model was built based on the method of combining mathematical statistical analysis with physical causes. The predictive factor database was formed by flood processes which were calculated by using the runoff generation and concentration model for hydrological regionalization, discharge process of reservoir and tidal level process. On this basis, the mixture regression model was built by coupling stepwise multiple regression method and threshold regression model. The results show that, compared with the stepwise multiple regression method, the mixture regression model can effectively improve the accuracy of flood level forecasting in tidal river. The certainty factor and qualified rate of verification flood are 0.88 and 76.94% respectively. Mixture regressive model is a method of strong practicability and maneuverability in terms of simple principle and simple input conditions, which can provide reference to the work of the flood forecasting in coastal areas.