Combined Flood Forecasting Model of Hydrology and Hydraulics
|Course||Hydrology and Water Resources|
|Keywords||River Flood Forecast Hydrology methods Hydraulics Synthetically Real-time correction Fading Memory least squares BP neural network|
The hydrology of the river flow model and the hydraulic model , after decades of development , the technology is becoming more and more mature , and achieved good results in practical applications . Single model hydrology or hydraulics model is often inadequate when dealing with complex channel flow problems , the urgent need for comprehensive and considered together . This thesis Xijiang River in Wuzhou - Gaoyao reach relatively flat, so should consider using the hydraulic method of flood forecasting . But in recent years , due to the combined effects of river erosion changes and other factors , so greatly reducing river flow from Wuzhou to Gaoyao the time , taking into account the river under the double impact of natural and man-made factors continue to change the use of existing the the river terrain data hydraulics confluence calculation method it is possible deviations occur , and only need hydrology hydrology methods for river flood forecasting , so it can be considered in the flow conditions are relatively simple and lack of recent river terrain data water literature method for river flood forecasting . Thus, the river flow method of combining hydrology and hydraulics . At the same time , in order to improve the accuracy of flood forecasting , it is necessary to hydrology and hydraulics in real - time correction . Choice of real-time correction method , the paper examines the two methods , Fading Memory least squares with BP neural network , real-time correction , and they corrected the results were analyzed , comparing . The calculation results show forth in this paper hydrology and hydraulics combining the method is feasible in Wuzhou - the Gaoyao river flood forecasting .