Coupling geostatistical approaches with PCA and fuzzy optimal model (FOM) for the integrated assessment of sampling locations of water quality monitoring networks (WQMNs)

J Environ Monit. 2012 Dec;14(12):3118-28. doi: 10.1039/c2em30372h. Epub 2012 Oct 29.

Abstract

The assessment of the adequacy of sampling locations is an important aspect in the validation of an effective and efficient water quality monitoring network. Two geostatistical approaches (e.g., kriging and Moran's I) are presented to assess multiple sampling locations. A flexible and comprehensive framework was developed for the selection of multiple sampling locations of multiple variables which was accomplished by coupling geostatistical approaches with principal component analysis (PCA) and fuzzy optimal model (FOM). The FOM was used in the integrated assessment of both multiple principal components and multiple geostatistical approaches. These integrated methods were successfully applied to the assessment of two independent water quality monitoring networks (WQMNs) of Lake Winnipeg, Canada, which respectively included 14 and 30 stations from 2006 to 2010.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Fuzzy Logic*
  • Manitoba
  • Models, Chemical
  • Models, Statistical*
  • Principal Component Analysis*
  • Spatial Analysis
  • Water Pollutants / analysis*
  • Water Pollution / statistics & numerical data
  • Water Quality / standards*
  • Water Supply

Substances

  • Water Pollutants