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Groundwater Quality Zonation Assessment using GIS, EOFs and Hierarchical Clustering

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Listed:
  • A. El-Hames
  • A. Hannachi
  • M. Al-Ahmadi
  • N. Al-Amri

Abstract

Three methods are utilized in this paper to assist in the groundwater clustering, in an arid region aquifer, into similar zones according to its quality. A multiple regression is first applied in order to assess the importance of the different chemical constituents in the amount of total dissolved salt, which shows the dominance of chlorine and sodium. A multivariate analysis based on empirical orthogonal functions and hierarchical clustering (EOFs) is applied to assist in water quality clustering in the studied aquifer. The clustering has produced five distinguished categories of groundwater quality, which agree well with World Health Organisation criteria and limits for water usage. Based on these categories, spatial distribution maps of groundwater quality are produced by Kriging and GIS software. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • A. El-Hames & A. Hannachi & M. Al-Ahmadi & N. Al-Amri, 2013. "Groundwater Quality Zonation Assessment using GIS, EOFs and Hierarchical Clustering," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2465-2481, May.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:7:p:2465-2481
    DOI: 10.1007/s11269-013-0297-0
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    References listed on IDEAS

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    1. Chander Singh & Satyanarayan Shashtri & Saumitra Mukherjee & Rina Kumari & Ram Avatar & Amit Singh & Ravi Singh, 2011. "Application of GWQI to Assess Effect of Land Use Change on Groundwater Quality in Lower Shiwaliks of Punjab: Remote Sensing and GIS Based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(7), pages 1881-1898, May.
    2. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    3. Insaf Babiker & Mohamed Mohamed & Tetsuya Hiyama, 2007. "Assessing groundwater quality using GIS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(4), pages 699-715, April.
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