干旱区生态环境知识资源中心(Arid): Estimation of surface water quality parameters based on hyper-spectral and 3D-EEM fluorescence technologies in the Ebinur Lake Watershed, China

Arid

DOI	10.1016/j.pce.2020.102895
	Estimation of surface water quality parameters based on hyper-spectral and 3D-EEM fluorescence technologies in the Ebinur Lake Watershed, China
	Zhang, Fei; Wang, Xiaoping; Chen, Yun; Airiken, Muhadaisi
通讯作者	Zhang, F
来源期刊	PHYSICS AND CHEMISTRY OF THE EARTH
ISSN	1474-7065
EISSN	1873-5193
出版年	2020
卷号	118
英文摘要	Water quality research relies on field sampling, which is often very difficult to obtain, especially in arid areas. This study chose the Ebinur Lake Watershed in arid region as a study area. It analyzed 12 water quality parameters (WQPs) and hyper-spectral derived from 48 field samples. Parallel factor analysis (PARAFAC) method was employed to extract four fluorescent components from the fluorescence excitation-emission matrix (EEM) data. Four fluorescence spectral indices (Fn (355), the fluorescence index (FI), the humification index (HIX)) were used to characterize the organic matter. Estimated WQPs were then coupled with hyper-spectral and three-dimensional fluorescence technologies using the Back Propagation-Artificial Neural Network (BPANN) method developed in this study. The main findings are: (1) Higher correlations exist among the reflectance peaks, spectral indices (DI, NDI, RI) and WQPs, which is helpful to improve the accuracy of water quality estimation. (2) There are also high correlations among fluorescent components (peak) (C1, W2, W3, W4, W5 and W7), fluorescence spectral index and some of WQPs. This indicated that fluorescent components and fluorescence indices can be used to accurately monitor WQPs in surface water. (3) The BPANN model has a great potential for estimating WQPs, because of residual predictive deviation (RPD) of estimation model and verify model more than 1.4. These preliminary results have proved that hyper-spectral and fluorescence technologies is a valuable tool for monitoring surface water quality.
英文关键词	Back propagation-artificial neural network (BPANN) Three-dimensional excitation-emission matrix (3D-EEM) Fluorescence spectral Hyper-spectral Water quality parameters (WQPs)
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000575782800004
WOS关键词	DISSOLVED ORGANIC-MATTER ; EMISSION MATRIX FLUORESCENCE ; EEM-PARAFAC ; CLIMATE ; APPLICABILITY ; REGION ; INDEX ; BASIN ; PLAIN
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences ; Water Resources
来源机构	新疆大学 ; 南京大学 ; Commonwealth Scientific and Industrial Research Organisation
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/326653
作者单位	[Zhang, Fei; Wang, Xiaoping; Airiken, Muhadaisi] Xinjiang Univ, Coll Resources & Environm Sci, Key Lab Smart City & Environm Modeling, Higher Educ Inst, Urumqi 830046, Peoples R China; [Zhang, Fei; Airiken, Muhadaisi] Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China; [Zhang, Fei; Chen, Yun] Commonwealth Sci & Ind Res Org Land & Water, Canberra, ACT 2601, Australia; [Wang, Xiaoping] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210046, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Fei,Wang, Xiaoping,Chen, Yun,et al. Estimation of surface water quality parameters based on hyper-spectral and 3D-EEM fluorescence technologies in the Ebinur Lake Watershed, China[J]. 新疆大学, 南京大学, Commonwealth Scientific and Industrial Research Organisation,2020,118.
APA	Zhang, Fei,Wang, Xiaoping,Chen, Yun,&Airiken, Muhadaisi.(2020).Estimation of surface water quality parameters based on hyper-spectral and 3D-EEM fluorescence technologies in the Ebinur Lake Watershed, China.PHYSICS AND CHEMISTRY OF THE EARTH,118.
MLA	Zhang, Fei,et al."Estimation of surface water quality parameters based on hyper-spectral and 3D-EEM fluorescence technologies in the Ebinur Lake Watershed, China".PHYSICS AND CHEMISTRY OF THE EARTH 118(2020).