基于节点水位信息的复杂河网实时校正方法

Real-time correction method for complex flow in river network based on nodal water stage updating

为提高复杂河网水流预报精度,采用四点线性隐格式求解圣维南方程组,利用河道断面水位、流量与首末节点水位的关系,结合卡尔曼滤波技术建立以河网节点水位为状态量的卡尔曼滤波实时校正模型。采用在线获得信息,校正节点水位进而更新河网内各断面水位、流量,提高预报初始条件精度。选择长江下游澄通河段进行演算,共229个断面,采用2004年8月至9月资料进行实时校正,结果显示节点水位校正能够将其校正影响带动到河网其他断面上,使河网内各断面的水流状态得以修正,且带动效果良好,由此表明本文复杂河网实时校正方法可行。

To improve flood forecast accuracy, Kalman filter was introduced to a hydraulic model for establishing a real-time correction model. In the correction model, water level at river nodes are used as state variables and the system state equation of Kalman filter was derived from the Saint-Venant equations, which were solved with a linear implicit four-point scheme. By using the relationship between the water levels at river system nodes and the variables （water level and discharge） at the observed cross sections of new data available, the water levels at all the nodes and all the cross sections can be updated online based on the new data. This model was applied to a network of 229 cross sections with hydrological data from August to September for the Chengtong section of the Yangtze River. The calculations show that the model corrects the simulated values at both local and nearby cross sections and effectively updates the state of the whole network system. Thus, the presented correction model demonstrates an effective method for real-time correction of river network.