基于集合Kalman滤波的河道洪水预报研究  

Study of River Channel Flood Forecasting by Ensemble Kalman Filtering

作　　者：岳延兵[1,2] 李致家[1] 李振兴[2] 

机构地区：[1]河海大学水文水资源学院,江苏南京210098 [2]山西水利职业技术学院,山西运城044004

出　　处：《水电能源科学》2011年第1期26-29,共4页Water Resources and Power

基　　金：国家自然科学基金资助项目(50479017)

摘　　要：为提高河道洪水预报精度,研究了集合Kalman滤波法与最小二乘法对马斯京根模型参数率定的河道洪水预报技术,并以长水白马寺实测洪水为例进行了对比检验,探讨了集合Kalman滤波法的多时段预报洪水过程及其特点。检验结果表明,应用集合Kalman滤波技术优于最小二乘法的预报效果,可有效提高河道洪水预报的精度并能适度延长预报时段。Ensemble Kalman filtering and least square method is used to estimate the Muskingum model parameter for improving the river channel flood forecasting accuracy.Taking observed flood in Changshui-Baima Temple for an example,multi-period flood forecasting and its characteristics with ensemble Kalman filtering are discussed.Test results show that the effect of ensemble Kalman filtering is better than that of the least square method;time interval and accuracy for river channel flood forecasting is improved.

关 键 词：集合KALMAN滤波 数据同化 信息融合 洪水预报 

分 类 号：TV122[水利工程—水文学及水资源]