中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Assimilating Observation Data into Hydrological Model with Ensemble Kalman Filter

文献类型:会议论文

作者Xiong, Jun1,2; Huang, Xiaolan1,3; Cao, Zengyan4
出版日期2011
会议日期JUL 29-31, 2011
会议地点Kunming, PEOPLES R CHINA
关键词hydrological forecast ensemble Kalman filter data assimilation rainfall infiltration tank model numerical simulation
卷号255-260
DOI10.4028/www.scientific.net/AMR.255-260.3632
页码3632
英文摘要The ensemble Kalman filter (EnKF) is employed to simulate of streamflow of a slope sub-catchment during the rainfall infiltration process. With this method the whole process is treated as a dynamic stochastic system, and its streamflow is taken as the variable to describe the state of system. Furthermore, it is coupled with a hydrology model to cope with system uncertainty. Thus, the dynamical estimation of hydrological parameters is performed; the model variables and their uncertainty are obtained simultaneously. Numerical examples show that this strategy can effectively deal with observation noises and can provide the inversion results and the posteriori distribution of the priori information together. Compared with the conventional optimization algorithm, the new strategy combined with EnKF shows better character of real time response and model reliability.
源文献作者Zhao, JY
会议录ADVANCES IN CIVIL ENGINEERING, PTS 1-6
会议录出版者TRANS TECH PUBLICATIONS LTD
会议录出版地DURNTEN-ZURICH
语种英语
WOS研究方向Construction & Building Technology ; Engineering ; Materials Science
WOS记录号WOS:000302894902033
源URL[http://119.78.100.198/handle/2S6PX9GI/4629]  
专题岩土力学所知识全产出_会议论文
国家重点实验室知识产出_会议论文
作者单位1.Chinese Acad Sci, State Key Lab Geomech & Geotech Engn, Inst Rock & Soil Mech ;
2.Univ Alberta, Civil & Environm Engn Dept;
3.Coll Resource & Environm Sci ;
4.Social & Environm Engn Dept
推荐引用方式
GB/T 7714
Xiong, Jun,Huang, Xiaolan,Cao, Zengyan. Assimilating Observation Data into Hydrological Model with Ensemble Kalman Filter[C]. 见:. Kunming, PEOPLES R CHINA. JUL 29-31, 2011.

入库方式: OAI收割

来源:武汉岩土力学研究所

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