Data mining and multivariate statistical analysis for ecological system in coastal waters

Kwok Wing Chau, Nitin Muttil

Research output: Journal article publicationJournal articleAcademic researchpeer-review

74 Citations (Scopus)


In this study, data mining using box plots and multivariate statistical analysis using factor analysis are employed for a spatio-temporal analysis of coastal water quality data from Tolo Harbour, Hong Kong. The analysis of box plots reveals pronounced spatial heterogeneity of the parameters studied. The spatial analysis clearly shows monitoring station TM2 in the Harbour Subzone to be most susceptible to eutrophication with the highest nutrient and algal biomass concentrations. The factor analysis brings to light dominant parameters to the ecological system under the coastal marine environment. The temporal analysis confirms the considerable decline in nutrient levels in recent years. In spite of this decline, the factor analysis indicates that nutrient processes play an important role even in recent years, suggesting an adequate supply of nutrients. It seems that they are being released from sources other than known point sources, possibly from nutrients accumulated in the sediments, necessitating steps to be undertaken for their control also. This study demonstrates the use of data mining techniques in the ecological system in Tolo Harbour.
Original languageEnglish
Pages (from-to)305-317
Number of pages13
JournalJournal of Hydroinformatics
Issue number4
Publication statusPublished - 1 Oct 2007


  • Box plots
  • Data mining
  • Factor analysis
  • Harmful algal blooms
  • Multivariate statistical analysis

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Atmospheric Science


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