Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series
Using a spatio-temporal dynamic state-space model with the EM algorithm to patch gaps in daily riverflow series
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DOI：
10.5194/hess-9-209-2005
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发表时间：
2005-01-01
影响因子：
6.3
通讯作者：
van de Giesen, NC
中科院分区：
文献类型：
--
作者：
Amisigo, BA;van de Giesen, NC
建立了一个用于修补日径流序列短间隙的时空线性动态模型。模型以状态空间的形式建立，其中状态变量使用卡尔曼平滑器(RTS平滑器)进行估计。EM算法被用来同时估计参数和丢失的径流值。将该模型应用于西非Volta盆地的日径流序列表明，该模型能够很好地从同一子流域内测站的剩余时间序列和空间相关的站提供缺失的径流估计值。
A spatio-temporal linear dynamic model has been developed for patching short gaps in daily river runoff series. The model was cast in a state-space form in which the state variable was estimated using the Kalman smoother (RTS smoother). The EM algorithm was used to concurrently estimate both parameter and missing runoff values. Application of the model to daily runoff series in the Volta Basin of West Africa showed that the model was capable of providing good estimates of missing runoff values at a gauging station from the remaining time series at the station and at spatially correlated stations in the same sub-basin.