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	Wavelet analysis-artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China
	Wen, Xiaohu1,2; Feng, Qi1,2; Deo, Ravinesh C.3; Wu, Min1,2; Si, Jianhua1,2
刊名	HYDROLOGY RESEARCH
	2017-12-01
卷号	48期号:6页码:1710-1729
关键词	arid environment artificial neural network discrete wavelet transforms forecasting groundwater level
ISSN号	1998-9563
DOI	10.2166/nh.2016.396
通讯作者	Wen, Xiaohu(xhwen@lzb.ac.cn)
英文摘要	In this study, the ability of a wavelet analysis-artificial neural network (WA-ANN) conjunction model for multi-scale monthly groundwater level forecasting was evaluated in an arid inland river basin, northwestern China. The WA-ANN models were obtained by combining discrete wavelet transformation with ANN. For WA-ANN model, three different input combinations were trialed in order to optimize the model performance: (1) ancient groundwater level only, (2) ancient climatic data, and (3) ancient groundwater level combined with climatic data to forecast the groundwater level for two wells in Zhangye basin. Based on the key statistical measures, the performance of the WA-ANN model was significantly better than ANN model. However, WA-ANN model with ancient groundwater level as its input yielded the best performance for 1-month groundwater forecasts. For 2- and 3-monthly forecasts, the performance of the WA-ANN model with integrated ancient groundwater level and climatic data as inputs was the most superior. Notwithstanding this, the WA-ANN model with only ancient climatic data as its inputs also exhibited accurate results for 1-, 2-, and 3-month groundwater forecasting. It is ascertained that the WA-ANN model is a useful tool for simulation of multi-scale groundwater forecasting in the current study region.
收录类别	SCI
WOS关键词	TABLE DEPTH FLUCTUATIONS ; CLIMATE-CHANGE ; SURFACE-WATER ; ZHANGYE BASIN ; SIMULATION ; AQUIFER ; UNCERTAINTY ; HYDROLOGY ; FLOW
WOS研究方向	Water Resources
WOS类目	Water Resources
语种	英语
出版者	IWA PUBLISHING
WOS记录号	WOS:000416144600018
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2557627
专题	寒区旱区环境与工程研究所
通讯作者	Wen, Xiaohu
作者单位	1.Chinese Acad Sci, Key Lab Ecohydrol Inland River Basin, Donggang West Rd 320, Lanzhou 730000, Gansu, Peoples R China 2.Chinese Acad Sci, Cold & Arid Regions Environm & Engn Res Inst, Donggang West Rd 320, Lanzhou 730000, Gansu, Peoples R China 3.Univ Southern Queensland, Int Ctr Appl Climate Sci, Sch Agr Computat & Environm Sci, Springfield, Qld 4300, Australia
推荐引用方式 GB/T 7714	Wen, Xiaohu,Feng, Qi,Deo, Ravinesh C.,et al. Wavelet analysis-artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China[J]. HYDROLOGY RESEARCH,2017,48(6):1710-1729.
APA	Wen, Xiaohu,Feng, Qi,Deo, Ravinesh C.,Wu, Min,&Si, Jianhua.(2017).Wavelet analysis-artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China.HYDROLOGY RESEARCH,48(6),1710-1729.
MLA	Wen, Xiaohu,et al."Wavelet analysis-artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China".HYDROLOGY RESEARCH 48.6(2017):1710-1729.

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