International Journal of Environmental Protection and Policy

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Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China

Received: 13 July 2019    Accepted: 06 August 2019    Published: 19 August 2019
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Abstract

Analyses on the spatial evolution and distribution of surface water quality are important to the treatment and protection of water environment in a lake. In Balihe Lake, an inland freshwater lake in east China, 7 water environmental factors at 45 sampling sites were monitored and served as the basis of this study. Cluster analysis (CA), a multivariate statistical analysis method, was utilized to study the spatial variation and grouping of these sampling sites based on the monitored water quality data. The results of this study showed that the water quality characteristics at these 45 sampling sites, which was grouped into the clusters of upstream, midstream and downstream, highly depended on the spatial location of the lake. Some nutrients content of the upstream area was much higher, while the water quality of the downstream area was much better although some of water quality indicators at the outlet still didn’t match the standards of local government. The CA results of the study may provide some guidance to the priority areas of water environment protection or treatment for the government.

DOI 10.11648/j.ijepp.20190703.12
Published in International Journal of Environmental Protection and Policy (Volume 7, Issue 3, May 2019)
Page(s) 93-98
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Cluster Analysis, Surface Water Quality, Balihe Lake, Freshwater Lake

References
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[8] M. F. Zhong, H. Y. Zhang, X. W. Sun, et al. (2018) Analyzing the Significant Environmental Factors on The Spatial and Temporal Distribution of Water Quality Utilizing Multivariate Statistical Techniques: A Case Study in The Balihe Lake, China. Environmental Science and Pollution Research 25, 29418–29432.
[9] Environmental Protection Administration of Peoples Republic of China (2009) Monitoring and Analysis Methods of Water and Wastewater (4th Edition). Beijing: China Environmental Science Press. (in Chinese)
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[11] S. Alelyani, J. L. Tang and H. Liu (2018) “Feature Selection for Clustering: A Review,” in Data Clustering, C. C. Aggarwal and C. K. Reddy Eds. New York: Chapman and Hall/CRC.
[12] C. P. Yue, X. Li (2019) Study on Water Quality Factors in Wuliangsuhai Lake Based on Clustering Analysis. Yellow River 41 (5), 67-70+76. (In Chinese)
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[14] X. X. Li, H. Li and H. J. Song (2003) Analysis of Quality and Trend of Surface Water Resources in Xinjiang. Arid Land Geography, 26 (3), 254-259. (In Chinese)
[15] S. Shrestha, and F. Kazama (2007) Assessment of surface Water Quality Using Multivariate Statistical Techniques: A Case Study of The Fuji River Basin, Japan. Environmental Modelling & Software 22 (4), 464-475.
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[17] Z. Zhang, F. L. Tao, J. Du, et al. (2010) Surface Water Quality and Its Control in A River with Intensive Human Impacts-A Case Study of The Xiangjiang River, China. Journal of Environmental Management 91 (12), 2483-2490.
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Author Information
  • Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing, China

  • Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing, China

  • Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing, China

  • Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing, China

  • Research Center for Engineering Ecology and Nonlinear Science, North China Electric Power University, Beijing, China

Cite This Article
  • APA Style

    Jiazhu Lan, Meifang Zhong, Yixin Xu, Zhongyu Wang, Hai Huang. (2019). Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China. International Journal of Environmental Protection and Policy, 7(3), 93-98. https://doi.org/10.11648/j.ijepp.20190703.12

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    ACS Style

    Jiazhu Lan; Meifang Zhong; Yixin Xu; Zhongyu Wang; Hai Huang. Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China. Int. J. Environ. Prot. Policy 2019, 7(3), 93-98. doi: 10.11648/j.ijepp.20190703.12

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    AMA Style

    Jiazhu Lan, Meifang Zhong, Yixin Xu, Zhongyu Wang, Hai Huang. Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China. Int J Environ Prot Policy. 2019;7(3):93-98. doi: 10.11648/j.ijepp.20190703.12

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  • @article{10.11648/j.ijepp.20190703.12,
      author = {Jiazhu Lan and Meifang Zhong and Yixin Xu and Zhongyu Wang and Hai Huang},
      title = {Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China},
      journal = {International Journal of Environmental Protection and Policy},
      volume = {7},
      number = {3},
      pages = {93-98},
      doi = {10.11648/j.ijepp.20190703.12},
      url = {https://doi.org/10.11648/j.ijepp.20190703.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijepp.20190703.12},
      abstract = {Analyses on the spatial evolution and distribution of surface water quality are important to the treatment and protection of water environment in a lake. In Balihe Lake, an inland freshwater lake in east China, 7 water environmental factors at 45 sampling sites were monitored and served as the basis of this study. Cluster analysis (CA), a multivariate statistical analysis method, was utilized to study the spatial variation and grouping of these sampling sites based on the monitored water quality data. The results of this study showed that the water quality characteristics at these 45 sampling sites, which was grouped into the clusters of upstream, midstream and downstream, highly depended on the spatial location of the lake. Some nutrients content of the upstream area was much higher, while the water quality of the downstream area was much better although some of water quality indicators at the outlet still didn’t match the standards of local government. The CA results of the study may provide some guidance to the priority areas of water environment protection or treatment for the government.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Applications of Cluster Analysis Method in Surface Water Quality Assessment: A Case Study in Balihe Lake, China
    AU  - Jiazhu Lan
    AU  - Meifang Zhong
    AU  - Yixin Xu
    AU  - Zhongyu Wang
    AU  - Hai Huang
    Y1  - 2019/08/19
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ijepp.20190703.12
    DO  - 10.11648/j.ijepp.20190703.12
    T2  - International Journal of Environmental Protection and Policy
    JF  - International Journal of Environmental Protection and Policy
    JO  - International Journal of Environmental Protection and Policy
    SP  - 93
    EP  - 98
    PB  - Science Publishing Group
    SN  - 2330-7536
    UR  - https://doi.org/10.11648/j.ijepp.20190703.12
    AB  - Analyses on the spatial evolution and distribution of surface water quality are important to the treatment and protection of water environment in a lake. In Balihe Lake, an inland freshwater lake in east China, 7 water environmental factors at 45 sampling sites were monitored and served as the basis of this study. Cluster analysis (CA), a multivariate statistical analysis method, was utilized to study the spatial variation and grouping of these sampling sites based on the monitored water quality data. The results of this study showed that the water quality characteristics at these 45 sampling sites, which was grouped into the clusters of upstream, midstream and downstream, highly depended on the spatial location of the lake. Some nutrients content of the upstream area was much higher, while the water quality of the downstream area was much better although some of water quality indicators at the outlet still didn’t match the standards of local government. The CA results of the study may provide some guidance to the priority areas of water environment protection or treatment for the government.
    VL  - 7
    IS  - 3
    ER  - 

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