IGGCAS OpenIR  > 页岩气与地质工程院重点实验室
Quantification of Water Sources in a Coastal Gold Mine through an End-Member Mixing Analysis Combining Multivariate Statistical Methods
Liu, Guowei1,2,3; Ma, Fengshan1,2; Liu, Gang4; Guo, Jie1,2; Duan, Xueliang1,2; Gu, Hongyu5
2020-02-01
Source PublicationWATER
Volume12Issue:2Pages:27
AbstractMixing calculations have been widely applied to identify sources of groundwater recharge, but these calculations have assumed that the concentrations of end-members are well known. However, the end-members of water remain unclear and are not easily available in practical applications. To better determine end-members and mixing ratios, an end-member mixing analysis combining multivariate statistical methods was used on a large, complex water chemistry dataset collected from the Shashandao gold mine in China. Multivariate statistical methods, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were applied to determine the specific end-members (these two methods verified each other). On the basis of the identified end-members, a maximum likelihood method was then used to estimate the mixing ratios of the water sources. The combined method proposed in this study can help to identify more accurate end-members and deal with uncertainty in end-member concentrations, and it can also adjust the concentrations until the optimal mixing ratios for the calculation are obtained. This method can be a powerful tool for groundwater management and in predicting water inrush in mining operations.
Keywordmixing calculation ratios principal component analysis hierarchical cluster analysis end-member mixing analysis maximum likelihood method
DOI10.3390/w12020580
Funding OrganizationNational Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China
WOS KeywordCHEMISTRY ; RIVER ; SURFACE ; COMPONENTS ; MODEL ; CONTAMINATION ; CATCHMENT ; ISOTOPES ; QUALITY ; BASIN
Language英语
Funding ProjectNational Science Foundation of China[41831293] ; National Science Foundation of China[41907174] ; National Key Research Projects of China[2016YFC0402802]
Funding OrganizationNational Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China ; National Key Research Projects of China
WOS Research AreaWater Resources
WOS SubjectWater Resources
WOS IDWOS:000519846500271
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/95520
Collection页岩气与地质工程院重点实验室
Corresponding AuthorMa, Fengshan
Affiliation1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Shale Gas & Geoengn, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing 100029, Peoples R China
3.Univ Chinese Acad Sci, Coll Earth & Planetary, Beijing 100049, Peoples R China
4.China Geol Survey, Xian Ctr, Xian 710054, Shanxi, Peoples R China
5.China Geol Survey, Chengdu Ctr, Chengdu 610081, Sichuan, Peoples R China
First Author AffilicationKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences
Corresponding Author AffilicationKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Guowei,Ma, Fengshan,Liu, Gang,et al. Quantification of Water Sources in a Coastal Gold Mine through an End-Member Mixing Analysis Combining Multivariate Statistical Methods[J]. WATER,2020,12(2):27.
APA Liu, Guowei,Ma, Fengshan,Liu, Gang,Guo, Jie,Duan, Xueliang,&Gu, Hongyu.(2020).Quantification of Water Sources in a Coastal Gold Mine through an End-Member Mixing Analysis Combining Multivariate Statistical Methods.WATER,12(2),27.
MLA Liu, Guowei,et al."Quantification of Water Sources in a Coastal Gold Mine through an End-Member Mixing Analysis Combining Multivariate Statistical Methods".WATER 12.2(2020):27.
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