摘要
为解决河网水情动态系统的数据同化问题,将水情量测数据作为内边界条件,建立了一个基于误差最小二乘原理的河网水情数据同化耦合模型。同时,为了有效控制水情状态变量的校正程度,避免因校正过度而破坏河网系统的水量平衡关系,构建了一个能有效控制及平衡各量测变量校正程度的权重矩阵。通过模拟算例和实例应用,系统检验了模型在河网水情仿真与预报中的实时校正能力,并得到了理想的结果。结果表明:模型理论完备、构建简便、数据同化可控性好,能够有效地进行河网水情动态系统的数据同化,提高河网水情仿真与预报的精度。
For improving the accuracy of river network numerical model, this paper developed a data assimilation model based on the theory of least-squares method, which specified real-time observed hydrological data as internal boundary conditions of flood routing model, in order to effectively control correction degrees of state variables and to avoid destroying overly the water balance relationship, a correction weight matrix was introduced, which could control and counterpoise the correction degrees of all measurable state variables. In a simulation example and an application to a real one, it systematically examined and analyzed the real-time correction capability of the present model. The results reveal that the present model is able to carry out data assimilation of river network system efficaciously, improving the accuracy of flood simulation and forecasting.
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2014年第6期842-847,共6页
Advances in Water Science
基金
浙江省重点科技创新团队项目(2010R50035)
浙江省博士后科研资助项目(Bsh1401035)
关键词
河网
实时校正
权重矩阵
最小二乘法
river network
real-time correction
weight matrix
least-squares method
