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Tytuł:
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Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods.
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Autorzy:
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Bu J; School of Environmental Studies, China University of Geosciences, No. 68 Jincheng Street, Wuhan 430078, China.; Technology Innovation Center of Geo-Environmental Restoration, Ministry of Natural Resources, No. 388 Lumo Road, Wuhan 430074, China.
Liu W; Institute of Geological Survey, China University of Geosciences, No. 388 Lumo Road,Wuhan 430074, China.
Pan Z; School of Environmental Studies, China University of Geosciences, No. 68 Jincheng Street, Wuhan 430078, China.
Ling K; School of Environmental Studies, China University of Geosciences, No. 68 Jincheng Street, Wuhan 430078, China.
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Źródło:
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International journal of environmental research and public health [Int J Environ Res Public Health] 2020 Dec 18; Vol. 17 (24). Date of Electronic Publication: 2020 Dec 18.
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Typ publikacji:
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Journal Article; Research Support, Non-U.S. Gov't
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Język:
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English
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Imprint Name(s):
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Original Publication: Basel : MDPI, c2004-
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MeSH Terms:
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Cluster Analysis*
Groundwater*
Hydrodynamics ; Reproducibility of Results
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References:
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Sci Total Environ. 2020 Nov 1;741:140350. (PMID: 32886962)
Int J Environ Res Public Health. 2020 Feb 16;17(4):. (PMID: 32079130)
Environ Pollut. 2007 Jun;147(3):771-80. (PMID: 17134805)
Sci Total Environ. 2006 Feb 15;355(1-3):176-86. (PMID: 15885748)
Water Res. 2012 May 15;46(8):2737-48. (PMID: 22417739)
Int J Environ Res Public Health. 2016 Feb 23;13(3):. (PMID: 26907322)
Urol Res. 2010 Aug;38(4):233-5. (PMID: 19921168)
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Contributed Indexing:
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Keywords: Bayi Tunnel; groundwater leakage; hierarchical cluster analysis; hydrochemical classification; multivariate statistics
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Entry Date(s):
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Date Created: 20201223 Date Completed: 20210209 Latest Revision: 20210209
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Update Code:
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20240105
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PubMed Central ID:
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PMC7766391
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DOI:
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10.3390/ijerph17249515
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PMID:
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33353090
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Traditional methods for hydrochemical analyses are effective but less diversified, and are constrained to limited objects and conditions. Given their poor accuracy and reliability, they are often used in complement or combined with other methods to solve practical problems. Cluster analysis is a multivariate statistical technique that extracts useful information from complex data. It provides new ideas and approaches to hydrogeochemical analysis, especially for groundwater hydrochemical classification. Hierarchical cluster analysis is the most widely used method in cluster analysis. This study compared the advantages and disadvantages of six hierarchical cluster analysis methods and analyzed their objects, conditions, and scope of application. The six methods are: The single linkage, complete linkage, median linkage, centroid linkage, average linkage (including between-group linkage and within-group linkage), and Ward's minimum-variance. Results showed that single linkage and complete linkage are unsuitable for complex practical conditions. Median and centroid linkages likely cause reversals in dendrograms. Average linkage is generally suitable for classification tasks with multiple samples and big data. However, Ward's minimum-variance achieved better results for fewer samples and variables.
Competing Interests: The authors declare no conflict of interest.
