干旱区生态环境知识资源中心(Arid): Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets

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DOI	10.1016/j.ejrh.2022.101146
	Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets
	Borne, Maurus; Lorenz, Christof; Portele, Tanja C.; Martins, Eduardo Savio P. R.; Vasconcelos Junior, Francisco das Chagas; Kunstmann, Harald
通讯作者	Borne, M
来源期刊	JOURNAL OF HYDROLOGY-REGIONAL STUDIES
EISSN	2214-5818
出版年	2022
卷号	42
英文摘要	Study region: The Sa tilde o Francisco River Basin (SFRB) in Brazil Study focus: In semi-arid regions, interannual variability of seasonal rainfall and climate change is expected to stress water availability and increase the recurrence and intensity of extreme events such as droughts or floods. Local decision makers therefore need reliable long-term hydro meteorological forecasts to support the seasonal management of water resources, reservoir operations and agriculture. In this context, an Ensemble Kalman Filter framework is applied to predict sub-basin-scale runoff employing global freely available datasets of reanalysis precipitation (ERA5-Land) as well as bias-corrected and spatially disaggregated seasonal forecasts (SEAS5BCSD). Runoff is estimated using least squares predictions, exploiting the covariance structures between runoff and precipitation. The performance of the assimilation framework was assessed using different ensemble skill scores. New hydrological insights for the region: Our results show that the quality of runoff predictions are closely linked to the performance of the rainfall seasonal predictions and allows skillful predictions up to two months ahead in most sub-basins. The anthropogenic conditions such as in the Western Bahia state, however, must be taken under consideration, since non-stationary runoff time-series have poorer skill as such unnatural variations can not be captured by long-term co variances. In sub-basins which are dominated by little anthropogenic influence, the presented framework provides a promising and easily transferable approach for skillful operational seasonal runoff predictions on sub-basin scale.
英文关键词	Hydro-meteorology Seasonal forecast River basin management Data-assimilation
类型	Article
语种	英语
开放获取类型	gold, Green Published
收录类别	SCI-E
WOS记录号	WOS:000822958700005
WOS关键词	BAIU FRONTAL ZONE ; RIVER-BASIN ; COMMON FEATURES ; SOUTH-AMERICA ; SOIL-MOISTURE ; BRAZIL ; PRECIPITATION ; RAINFALL ; PREDICTABILITY ; NORTHEAST
WOS类目	Water Resources
WOS研究方向	Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393526
推荐引用方式 GB/T 7714	Borne, Maurus,Lorenz, Christof,Portele, Tanja C.,et al. Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets[J],2022,42.
APA	Borne, Maurus,Lorenz, Christof,Portele, Tanja C.,Martins, Eduardo Savio P. R.,Vasconcelos Junior, Francisco das Chagas,&Kunstmann, Harald.(2022).Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets.JOURNAL OF HYDROLOGY-REGIONAL STUDIES,42.
MLA	Borne, Maurus,et al."Seasonal sub-basin-scale runoff predictions: A regional hydrometeorological Ensemble Kalman Filter framework using global datasets".JOURNAL OF HYDROLOGY-REGIONAL STUDIES 42(2022).