Study On The Flood Forecasting Beijiang Downstream River

Beijiang River is the second largest river system in the Pearl River Basin, and itsentrance into Xijiang River is very close to Guangzhou. As the historical flood has broughtGuangzhou many disasters, It is important to control the flood of Beijiang River for thesecurity of Guangzhou city. After the complecation of Qingyuan water conservancy project in2012, the hydraulic characteristics of reach Feilaixia to Shijiao have been changing, the oldforecast scheme may nolonger applies. Therefore, It is especially significative to research themovement of the flood from Feilaixia to Shijiao, and to develop a flood forecasting system.This study makes research from several aspects on the flood forecasting of Beijiangdownstream river.1. By summing up the historical hydrological data of Feilaixia to Shijiao, four sets ofexperiental flood forecasting program were established, which are Feilaixia peak water level~Qingyuan peak water level forecasting scheme, Feilaixia peak flow~Qingyuan peak waterlevel forecasting scheme, The peak flow and Shijiao first flow~Shijiao peak flow predictionscheme, and interval rainfall and the flow rising rate in Feilaixia~Shijiao peak flowprediction scheme.2. By collecting the DEM data, this study established a Xin’An Jiang runoff model, aMuskingum flood calculation model and a one-dimensional hydrodynamic model of singlechannel. Based on these models, a single river hydrodynamic model prediction scheme and aMuskingum flood calculation model prediction scheme were established.3. This study established a hydrodynamic model based on MIKE11, and studied themotion law of Beijiang flood at the situation of some flood flows from Pajiang River, as areference for the single river hydrodynamic model prediction scheme and the Muskingumflood calculation model prediction scheme.4. This study developed a flood forecasting system of Beijiang downstream River withC#language and ArcEngine module tools, and this system contains the function of floodforecasting, data query and data management.