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DOI | 10.1029/2018WR023374 |
Comparing Seven Variants of the Ensemble Kalman Filter: How Many Synthetic Experiments Are Needed? | |
Keller, Johannes1; Franssen, Harrie-Jan Hendricks2,3; Marquart, Gabriele1 | |
2018-09-01 | |
发表期刊 | WATER RESOURCES RESEARCH
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ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2018 |
卷号 | 54期号:9页码:6299-6318 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany |
英文摘要 | The ensemble Kalman filter (EnKF) is a popular estimation technique in the geosciences. It is used as a numerical tool for state vector prognosis and parameter estimation. The EnKF can, for example, help to evaluate the geothermal potential of an aquifer. In such applications, the EnKF is often used with small or medium ensemble sizes. It is therefore of interest to characterize the EnKF behavior for these ensemble sizes. For seven ensemble sizes (50, 70, 100, 250, 500, 1,000, and 2,000) and seven EnKF variants (damped, iterative, local, hybrid, dual, normal score, and classical EnKF), we computed 1,000 synthetic parameter estimation experiments for two setups: a 2-D tracer transport problem and a 2-D flow problem with one injection well. For each model, the only difference among synthetic experiments was the generated set of random permeability fields. The 1,000 synthetic experiments allow to calculate the probability density function of the root-mean-square error (RMSE) of the characterization of the permeability field. Comparing mean RMSEs for different EnKF variants, ensemble sizes and flow/transport setups suggests that multiple synthetic experiments are needed for a solid performance comparison. In this work, 10 synthetic experiments were needed to correctly distinguish RMSE differences between EnKF variants smaller than 10%. For detecting RMSE differences smaller than 2%, 100 synthetic experiments were needed for ensemble sizes 50, 70, 100, and 250. The overall ranking of the EnKF variants is strongly dependent on the physical model setup and the ensemble size. |
英文关键词 | ensemble Kalman filter uncertainty quantification method comparison |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000448088100028 |
WOS关键词 | DATA ASSIMILATION ; GROUNDWATER-FLOW ; COUPLED MODEL ; STEADY-STATE ; PARAMETERS ; TRANSPORT ; TEMPERATURES ; TRANSIENT ; SURFACE |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/21122 |
专题 | 资源环境科学 |
作者单位 | 1.Rhein Westfal TH Aachen, Inst Appl Geophys & Geothermal Energy, EON Energy Res Ctr, Aachen, Germany; 2.Forschungszentrum Julich, IBG Agrosphere 3, Inst Bio & Geosci, Julich, Germany; 3.Geoverbund ABC J, Ctr High Performance Sci Comp Terr Syst HPSC Terr, Julich, Germany |
推荐引用方式 GB/T 7714 | Keller, Johannes,Franssen, Harrie-Jan Hendricks,Marquart, Gabriele. Comparing Seven Variants of the Ensemble Kalman Filter: How Many Synthetic Experiments Are Needed?[J]. WATER RESOURCES RESEARCH,2018,54(9):6299-6318. |
APA | Keller, Johannes,Franssen, Harrie-Jan Hendricks,&Marquart, Gabriele.(2018).Comparing Seven Variants of the Ensemble Kalman Filter: How Many Synthetic Experiments Are Needed?.WATER RESOURCES RESEARCH,54(9),6299-6318. |
MLA | Keller, Johannes,et al."Comparing Seven Variants of the Ensemble Kalman Filter: How Many Synthetic Experiments Are Needed?".WATER RESOURCES RESEARCH 54.9(2018):6299-6318. |
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