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Flood Risk Management Decision Support Systems Of The Beiyunhe River Basin

Posted on:2010-02-28Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y ZhengFull Text:PDF
GTID:1102360308457533Subject:Hydraulic engineering
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The 2008 Beijing Olympic Games needs higher criterion for the Beijing's urban construction, water quality, supply and flood control, etc. Beiyunhe River is the crucial flood discharge channel for the northern zone of Beijing downtown, and flood forecast decision support systems acted as one of the most important safety measures. Of course, it's extremely meaningful to develop the real-time and accurate flood risk forecasting management systems for Beiyunhe River Basin.Area of Beiyunhe River Basin is about 4,348 km2, middle scale basin, however, several tributaries and main channel met together, and hydraulic structures distributed widely, including reservoirs, flood storage work and sluice gates. In the past, the strobes always flow in their largest capability in flood, but for research of flood dispatch in this dissertation, focused on not only safety of flood control, but also effective use of water resources. As the result, flood dispatch involves every sluice's working condition, for example, at the key point of Beiguan flood diversion gate, the system should provide users results of specific operation of each gate, including which one and specific height and timing. Obviously, the exact handle of gates group and gates belongs to complicated field of hydrodynamics, but runoff yield and concentration, and river flood routing belongs to field of typical hydrological problem, so it is one of the key points to couple complex hydrodynamic model and proper distributed hydrological model together.The traditional hydrodynamic model and grid-based distributed hydrological model rely on fine grid discretization, both of them take large computational cost, and it's hard to meet the real-time flood forecasting and dispatch generally, so it's another research highlight to connect computational model and neural network model to accelerate simulation efficiency. Based on research above, this dissertation developed flood risk management decision support systems about Beiyunhe River Basin based on WebGIS system and Brower/Service (B/S) structure. And the system integrated rainfall data in real-time transmission, runoff generation and concentration, river flood routing, the dispatchment of reservoirs and strobes, and also inundated area simulation resulted by flood of levee break together, which had function of immediate show of data management, simulation results output query, decision support and so on. Difficulties in the development of systems were how to choose the proper model for different simulation object, couples and connections between various models, and how to improve computing efficiency on the precondition of modeling accuracy, decide the advanced system platform, realize interrelation between man machine, vivid and direct display and network query.The dissertation adopted measured rainfall of Beiyunhe River Basin (July 3, 1998 to July 6, 1998) to calibrate main parameters of distriburted model, design rainfall (frequency of 10%, 5%, 2%, 1%) and relevant water levels as validation data. Then the author verified comprehensive influences of runoff generation and concentration, tributaries inlets, cross-river mutual function as well as combined effects on the flood evolution of reservoirs and sluices'control factors.
Keywords/Search Tags:Beiyunhe River Basin, flood forecast, integrated system, hydrological and hydrodynamic model, neural network
PDF Full Text Request
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