Using principal component analysis to monitor spatial and temporal changes in water quality

Karim Bengraïne, Taha F. Marhaba

Research output: Contribution to journalArticlepeer-review

239 Scopus citations

Abstract

Chemical, biological and physical data monitored at 12 locations along the Passaic River, New Jersey, during the year 1998 are analyzed. Principal component analysis (PCA) was used: (i) to extract the factors associated with the hydrochemistry variability; (ii) to obtain the spatial and temporal changes in the water quality. Solute content, temperature, nutrients and organics were the main patterns extracted. The spatial analysis isolated two stations showing a possible point or non-point source of pollution. This study shows the importance of environmental monitoring associated with simple but powerful statistics to better understand a complex water system.

Original languageEnglish (US)
Pages (from-to)179-195
Number of pages17
JournalJournal of Hazardous Materials
Volume100
Issue number1-3
DOIs
StatePublished - Jun 27 2003

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution
  • Health, Toxicology and Mutagenesis

Keywords

  • Discharge
  • Drought
  • New Jersey
  • Passaic River
  • Principal component analysis
  • Water quality

Fingerprint

Dive into the research topics of 'Using principal component analysis to monitor spatial and temporal changes in water quality'. Together they form a unique fingerprint.

Cite this