Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, lake Taihu basin, China

Xiangyu Mu, James C. Brower, Donald I. Siegel, Anthony J. Fiorentino, Shuqing An, Ying Cai, Delin Xu, Hao Jiang

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

We investigated the hydrochemical setting of Lake Taihu (eastern China) to determine how different land use types influence the variability of surface water chemistry in different water sources to the lake. Major water types within the watershed range from caclium-magnesium bicaxrbonate water, typical of relatively pristine water, highly ocntaminated water characterized by more sulfate, sodium, chloride and nutrients. Principal components analysis produced three principal components that explained 78% of the variance in the water quality and reflect three major types of water chemistry. Agricultural land use is associated with greater concentrations of nutrients; urban areas with high concentrations of sodium, chloride, sulfate, fluoride and potassium; and natural weathering with calcium, magnesium and bicarbonate. Discriminant analysis and hierarchical cluster analysis produce complementary and similar results. Broadly speaking, future remediation to reduce nutrient loadings to the lake or industrial contamination can now be focused on specific land use practices, which are readily identifiable by using statistics in conjunction with GIS.

Original languageEnglish (US)
Pages (from-to)234-247
Number of pages14
JournalJournal of Limnology
Volume74
Issue number2
DOIs
StatePublished - Dec 30 2015

Keywords

  • Discriminant analysis
  • Geographical information system (gis)
  • Hierarchical cluster analysis
  • Land use types
  • Principal component analysis
  • Surface water quality
  • Water-rock interaction

ASJC Scopus subject areas

  • Aquatic Science
  • Ecology
  • Water Science and Technology

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  • Cite this

    Mu, X., Brower, J. C., Siegel, D. I., Fiorentino, A. J., An, S., Cai, Y., Xu, D., & Jiang, H. (2015). Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, lake Taihu basin, China. Journal of Limnology, 74(2), 234-247. https://doi.org/10.4081/jlimnol.2014.906