DOI: 10.5194/hess-19-2999-2015
Scopus记录号: 2-s2.0-84944460282
论文题名: Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance
作者: Rasmussen J ; , Madsen H ; , Jensen K ; H ; , Refsgaard J ; C
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 7 起始页码: 2999
结束页码: 3013
语种: 英语
Scopus关键词: Groundwater
; Hydrology
; Kalman filters
; Adaptive localizations
; Discharge assimilations
; Discharge observations
; Distance-based localizations
; Ensemble Kalman filtering
; Estimating parameters
; Filter performance
; Integrated hydrological modeling
; Parameter estimation
; data assimilation
; discharge
; error analysis
; groundwater resource
; hydraulic head
; hydrological modeling
; Kalman filter
; performance assessment
; spatial distribution
; streamflow
英文摘要: Groundwater head and stream discharge is assimilated using the ensemble transform Kalman filter in an integrated hydrological model with the aim of studying the relationship between the filter performance and the ensemble size. In an attempt to reduce the required number of ensemble members, an adaptive localization method is used. The performance of the adaptive localization method is compared to the more common distance-based localization. The relationship between filter performance in terms of hydraulic head and discharge error and the number of ensemble members is investigated for varying numbers and spatial distributions of groundwater head observations and with or without discharge assimilation and parameter estimation. The study shows that (1) more ensemble members are needed when fewer groundwater head observations are assimilated, and (2) assimilating discharge observations and estimating parameters requires a much larger ensemble size than just assimilating groundwater head observations. However, the required ensemble size can be greatly reduced with the use of adaptive localization, which by far outperforms distance-based localization. The study is conducted using synthetic data only. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78477
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geosciences and Natural Resource Management, University of Copenhagen, Denmark; DHI, Hørsholm, Denmark; Geological Survey of Denmark and GreenlandCopenhagen, Denmark
Recommended Citation:
Rasmussen J,, Madsen H,, Jensen K,et al. Data assimilation in integrated hydrological modeling using ensemble Kalman filtering: evaluating the effect of ensemble size and localization on filter performance[J]. Hydrology and Earth System Sciences,2015-01-01,19(7)