IGGCAS OpenIR  > 页岩气与地质工程院重点实验室
Application of Multivariate Statistical Analysis to Identify Water Sources in A Coastal Gold Mine, Shandong, China
Liu, Guowei1,2,3; Ma, Fengshan1,2; Liu, Gang1,2,3; Zhao, Haijun1,2; Guo, Jie1,2; Cao, Jiayuan1,2
2019-06-02
Source PublicationSUSTAINABILITY
ISSN2071-1050
Volume11Issue:12Pages:17
AbstractSubmarine mine water inrush has become a problem that must be urgently solved in coastal gold mining operations in Shandong, China. Research on water in subway systems introduced classifications for the types of mine groundwater and then established the functions used to identify each type of water sample. We analyzed 31 water samples from -375 m underground using multivariate statistical analysis methods. Cluster analysis combined with principle component analysis and factor analysis divided water samples into two types, with one type being near the F3 fault. Principal component analysis identified four principle components accounting for 91.79% of the total variation. These four principle components represented almost all the information about the water samples, which were then used as clustering variables. A Bayes model created by discriminant analysis demonstrated that water samples could also be divided into two types, which was consistent with the cluster analysis result. The type of water samples could be determined by placing Na+ and CHO3- concentrations of water samples into Bayes functions. The results demonstrated that F3, which is a regional fault and runs across the whole Xishan gold mine, may be the potential channel for water inrush, providing valuable information for predicting the possibility of water inrush and thus reducing the costs of the mining operation.
Keywordsubmarine mine water inrush principle component analysis factor analysis cluster analysis discriminant analysis Bayes model
DOI10.3390/su11123345
Funding OrganizationNational 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 ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China
WOS KeywordPRINCIPAL-COMPONENT ANALYSIS ; SOURCE IDENTIFICATION ; STABLE-ISOTOPES ; GROUNDWATER ; CHEMISTRY ; CONNECTIVITY ; QUALITY ; REGION ; BASIN
Language英语
Funding ProjectNational Key Research Projects of China[2016YFC0402802] ; National Science Foundation of China[41772341]
Funding OrganizationNational 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 ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China ; National Science Foundation of China
WOS Research AreaScience & Technology - Other Topics ; Environmental Sciences & Ecology
WOS SubjectGreen & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS IDWOS:000473753700115
PublisherMDPI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/92691
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, Inst Earth Sci, Beijing 100029, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
First Author AffilicationKey Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences;  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;  Institute of Geology and Geophysics, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Liu, Guowei,Ma, Fengshan,Liu, Gang,et al. Application of Multivariate Statistical Analysis to Identify Water Sources in A Coastal Gold Mine, Shandong, China[J]. SUSTAINABILITY,2019,11(12):17.
APA Liu, Guowei,Ma, Fengshan,Liu, Gang,Zhao, Haijun,Guo, Jie,&Cao, Jiayuan.(2019).Application of Multivariate Statistical Analysis to Identify Water Sources in A Coastal Gold Mine, Shandong, China.SUSTAINABILITY,11(12),17.
MLA Liu, Guowei,et al."Application of Multivariate Statistical Analysis to Identify Water Sources in A Coastal Gold Mine, Shandong, China".SUSTAINABILITY 11.12(2019):17.
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