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DOI	10.1016/j.jhydrol.2021.126380
	A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction
	Beyaztas, Ufuk; Shang, Han Lin; Yaseen, Zaher Mundher
通讯作者	Yaseen, ZM (corresponding author), Al Ayen Univ, Sci Res Ctr, New Era & Dev Civil Engn Res Grp, Thi Qar 64001, Iraq.
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2021
卷号	598
英文摘要	In this research, a functional time series model was introduced to predict future realizations of river flow time series. The proposed model was constructed based on a functional time series's correlated lags and the essential exogenous climate variables. Rainfall, temperature, and evaporation variables were hypothesized to have substantial functionality in river flow simulation. Because an actual time series model is unspecified and the input variables' significance for the learning process is unknown in practice, it was employed a variable selection procedure to determine only the significant variables for the model. A nonparametric bootstrap model was also proposed to investigate predictions' uncertainty and construct pointwise prediction intervals for the river flow curve time series. Historical datasets at three meteorological stations (Mosul, Baghdad, and Kut) located in the semi-arid region, Iraq, were used for model development. The prediction performance of the proposed model was validated against existing functional and traditional time series models. The numerical analyses revealed that the proposed model provides competitive or even better performance than the benchmark models. Also, the incorporated exogenous climate variables have substantially improved the modeling predictability performance. Overall, the proposed model indicated a reliable methodology for modeling river flow within the semi-arid region.
英文关键词	River flow prediction Hydrometeorological variables Functional autoregressive Semi-arid environment
类型	Article
语种	英语
开放获取类型	Green Submitted
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000661813200134
WOS关键词	NEURAL-NETWORKS ; WEST-AFRICA ; HYDROLOGY ; INTERVALS ; PATTERNS ; PACKAGE ; DEMAND ; BASIN
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/350902
作者单位	[Beyaztas, Ufuk] Marmara Univ, Dept Stat, Istanbul, Turkey; [Shang, Han Lin] Macquarie Univ, Dept Actuarial Studies & Business Analyt, Sydney, NSW, Australia; [Yaseen, Zaher Mundher] Al Ayen Univ, Sci Res Ctr, New Era & Dev Civil Engn Res Grp, Thi Qar 64001, Iraq
推荐引用方式 GB/T 7714	Beyaztas, Ufuk,Shang, Han Lin,Yaseen, Zaher Mundher. A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction[J],2021,598.
APA	Beyaztas, Ufuk,Shang, Han Lin,&Yaseen, Zaher Mundher.(2021).A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction.JOURNAL OF HYDROLOGY,598.
MLA	Beyaztas, Ufuk,et al."A functional autoregressive model based on exogenous hydrometeorological variables for river flow prediction".JOURNAL OF HYDROLOGY 598(2021).