Beiyun River Basin is holistically suffering a water shortage and relatively concentrated flood risk. The current operation (level-control) of dams and floodgates, which is in passive defense mode, cannot meet the demands of both flood control and storm water resources. An integrated flood forecasting and management system is developed by the connecting of the hydrological model and hydrodynamic model and coupling of the hydrodynamic model and hydraulic model for dams and floodgates. Based upon the forecasted runoff processes, a discharge-control operation mode of dams and floodgates is proposed to be utilized in order to well regulate the flood routing in channels. The simulated water level, discharge, and water storage volume under different design conditions of rainfall return periods and floodgates operation modes are compared. The results show that: (1) for small floods, current operation modes can satisfy the objectives, but discharge-control operation can do better; (2) for medium size floods, since pre-storing of the floods affects the discharge of follow-up floods by floodgates, the requirement of flood control cannot be satisfied under current operations, but the discharge-control operation can; (3) for large floods, neither operation can meet the requirement because of the limited storage of these dams. Then, the gravel pits, wetlands, ecological lakes and flood detention basins around the river must be used for excess flood waters. Using the flood forecasting and management system can change passive defense to active defense mode, solving the water resources problem of Beijing city and Beiyun River Basin to a certain extent.
This paper reports on experience with developing the flood forecasting model for the Upper Danube basin and its operational use since 2006. The model system consists of hydrological and hydrodynamic components, and involves precipitation forecasts. The model parameters were estimated based on the dominant processes concept. Runoff data are assimilated in real time to update modelled soil moisture. An analysis of the model performance indicates 88% of the snow cover in the basin to be modelled correctly on more than 80% of the days. Runoff forecasting errors decrease with catchment area and increase with forecast lead time. The forecast ensemble spread is shown to be a meaningful indicator of the forecast uncertainty. During the 2013 flood, there was a tendency for the precipitation forecasts to underestimate event precipitation and for the runoff model to overestimate runoff generation which resulted in, overall, rather accurate runoff forecasts. It is suggested that the human forecaster plays an essential role in interpreting the model results and, if needed, adjusting them before issuing the forecasts to the general public.
The second part of the study presents the results of the investigation of the flood control in the synthetic flood waves. This part is the continuation of the first part with methodology, published in 2/2007 of the JHH. and Tato část studie uvádí výsledky řešení povodňového řízení odtoku z nádrží v syntetických povodňových vlnách. Navazuje na první část s metodickými postupy, publikovanou v č. 2/2007 Vodohospodářského časopisu.