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Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods

Author

Listed:
  • Jianwei Bu

    (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)

  • Wei Liu

    (Institute of Geological Survey, China University of Geosciences, No. 388 Lumo Road, Wuhan 430074, China)

  • Zhao Pan

    (School of Environmental Studies, China University of Geosciences, No. 68 Jincheng Street, Wuhan 430078, China)

  • Kang Ling

    (School of Environmental Studies, China University of Geosciences, No. 68 Jincheng Street, Wuhan 430078, China)

Abstract

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.

Suggested Citation

  • Jianwei Bu & Wei Liu & Zhao Pan & Kang Ling, 2020. "Comparative Study of Hydrochemical Classification Based on Different Hierarchical Cluster Analysis Methods," IJERPH, MDPI, vol. 17(24), pages 1-23, December.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:24:p:9515-:d:464601
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    References listed on IDEAS

    as
    1. Jianwei Bu & Ziyong Sun & Aiguo Zhou & Youning Xu & Rui Ma & Wenhao Wei & Meng Liu, 2016. "Heavy Metals in Surface Soils in the Upper Reaches of the Heihe River, Northeastern Tibetan Plateau, China," IJERPH, MDPI, vol. 13(3), pages 1-19, February.
    2. Jianwei Bu & Ziyong Sun & Rui Ma & Yunde Liu & Xulong Gong & Zhao Pan & Wenhao Wei, 2020. "Shallow Groundwater Quality and Its Controlling Factors in the Su-Xi-Chang Region, Eastern China," IJERPH, MDPI, vol. 17(4), pages 1-18, February.
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    Cited by:

    1. Louis Maximilian Ronalter & Merce Bernardo & Javier Manuel Romaní, 2023. "Quality and environmental management systems as business tools to enhance ESG performance: a cross-regional empirical study," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9067-9109, September.

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