DOI: 10.5194/hess-20-1809-2016
Scopus记录号: 2-s2.0-84969627117
论文题名: Accounting for three sources of uncertainty in ensemble hydrological forecasting
作者: Thiboult A ; , Anctil F ; , Boucher M ; -A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 5 起始页码: 1809
结束页码: 1825
语种: 英语
Scopus关键词: Dispersions
; Forecasting
; Ensemble forecasting
; Ensemble Kalman Filter
; Forecasting performance
; Hydrological forecast
; Hydrological forecasting
; Meteorological forcing
; Sources of uncertainty
; Structural uncertainty
; Uncertainty analysis
; accuracy assessment
; climate forcing
; dispersion
; ensemble forecasting
; error analysis
; hydrological modeling
; hydrometeorology
; Kalman filter
; uncertainty analysis
; weather forecasting
英文摘要: Seeking more accuracy and reliability, the hydrometeorological community has developed several tools to decipher the different sources of uncertainty in relevant modeling processes. Among them, the ensemble Kalman filter (EnKF), multimodel approaches and meteorological ensemble forecasting proved to have the capability to improve upon deterministic hydrological forecast. This study aims to untangle the sources of uncertainty by studying the combination of these tools and assessing their respective contribution to the overall forecast quality. Each of these components is able to capture a certain aspect of the total uncertainty and improve the forecast at different stages in the forecasting process by using different means. Their combination outperforms any of the tools used solely. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial conditions uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improving the general forecasting performance and prevents this performance from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. Particular attention needs to be paid to the combination of the tools, especially in the EnKF tuning to avoid overlapping in error deciphering. © Author(s) 2016. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78850
Appears in Collections: 气候变化事实与影响
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作者单位: Dept. of Civil and Water Engineering, Université Laval, 1065 avenue de la MédecineQC, Canada; Dept. of Applied Sciences, Université du Québec à Chicoutimi, 555, boulevard de l'Université, Chicoutimi, QC, Canada
Recommended Citation:
Thiboult A,, Anctil F,, Boucher M,et al. Accounting for three sources of uncertainty in ensemble hydrological forecasting[J]. Hydrology and Earth System Sciences,2016-01-01,20(5)