GSTDTAP  > 资源环境科学
DOI10.1029/2020WR027468
Improving forecast skill of lowland hydrological models using ensemble Kalman filter and unscented Kalman filter
Y. Sun; W. Bao; K. Valk; C. C. Brauer; Julius Sumihar; A. H. Weerts
2020-07-13
发表期刊Water Resources Research
出版年2020
英文摘要

For operational water management in lowlands and polders (for instance in the Netherlands), lowland hydrological models are used for flow prediction, often as an input for a real‐time control system to steer water with pumps and weirs to keep water levels within acceptable bounds. Therefore, proper initialization of these models is essential. The ensemble Kalman filter (EnKF) has been widely used due to its relative simplicity and robustness, while the unscented Kalman filter (UKF) has received little attention in the operational context. Here, we test both UKF and EnKF using a lowland lumped hydrological model. The results of a reforecast experiment in an operational context using an hourly time step show that when using nine ensemble members, both filters can improve the accuracy of the forecast by updating the state of a lumped hydrological model (Wageningen Lowland Runoff Simulator, WALRUS) based on the observed discharge, while UKF has achieved better performance than EnKF. Additionally, we show that an increase in the ensemble members does not necessarily mean a significant increase in performance. WALRUS model with either UKF or EnKF could be considered for hydrological forecasting for supporting water management of polders and lowlands, with UKF being the computational leaner option.

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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/284222
专题资源环境科学
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Y. Sun,W. Bao,K. Valk,et al. Improving forecast skill of lowland hydrological models using ensemble Kalman filter and unscented Kalman filter[J]. Water Resources Research,2020.
APA Y. Sun,W. Bao,K. Valk,C. C. Brauer,Julius Sumihar,&A. H. Weerts.(2020).Improving forecast skill of lowland hydrological models using ensemble Kalman filter and unscented Kalman filter.Water Resources Research.
MLA Y. Sun,et al."Improving forecast skill of lowland hydrological models using ensemble Kalman filter and unscented Kalman filter".Water Resources Research (2020).
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