| 集合卡尔曼滤波在流域水文模型流量预报中的应用 |
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| 引用本文： | 黄小兰,李麒.集合卡尔曼滤波在流域水文模型流量预报中的应用[J].成都信息工程学院学报,2009,24(4):383-386. |
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| 作者姓名： | 黄小兰 李麒 |
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| 作者单位： | 1. 武汉工业学院,湖北,武汉,430023
2. 成都信息工程学院,四川,成都,610225 |
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| 摘 要： | 针对流域降雨入渗过程,引入集合卡尔曼滤波(EnKF)理论,视整个边坡流域为一个随机动态系统,将边坡流域流量观测值作为系统的输出,用集合卡尔曼滤波模型来描述系统的状态;结合流域流量计算方法,实现水文模型参数的随机动态估计,在有效获得待估参数的同时还给出估计值的不确定性.通过数值算例表明,集合卡尔曼滤波可以有效地对含噪声的量测数据进行处理,能够跟踪水文模型的动态变化.相对于常用最优化算法,集合卡尔曼滤波同时给出反演结果和先验知识的后验分布,显示出更好的实时性和可靠性.
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| 关 键 词： | 集合卡尔曼滤波 数据同化 降雨入渗 不确定性 数值模拟 |
Application of Ensemble Kalman filter to streamflow forecasting on hydrological model |
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| HUANG Xiao-lan,LI Qi.Application of Ensemble Kalman filter to streamflow forecasting on hydrological model[J].Journal of Chengdu University of Information Technology,2009,24(4):383-386. |
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| Authors: | HUANG Xiao-lan LI Qi |
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| Institution: | HUANG Xiao-lan1,LI Qi2 (1.Wuhan Polytechnic University,Wuhan 430023,China,2.Chengdu University of Information Technology,Chengdu 610225,China) |
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| Abstract: | The rainfall infiltration process of a slope sub-catchment is taken into consideration and the Ensemble Kalman filter(EnKF) is introduced.The whole process is treated as a dynamic stochastic system and its streamflow is taken as the output to describe the system state with Ensemble Kalman filter.It is coupled with the hydrological model to cope with the uncertainty.The dynamical estimate of the hydrological parameters is made and the parameter and its uncertainty are simultaneously obtained.The numerical ex... |
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| Keywords: | Ensemble Kalman filter data assimilation rainfall infiltration uncertainty numerical simulation |
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