Application Of Multivariate Statistical
Techniques For Surface Water Quality
Assessment: Case Study Of Karaj River, Iran
Author(s)
G. Badalians Gholikandi, H. R. Orumieh, S. Haddadi
& N. Mojir
Abstract
Water quality monitoring has one of the highest priorities in surface water
protection policy. Multivariate statistical methods have been used successfully in
hydrochemistry for many years. In the present study, evaluation of spatial
variations and interpretation of Karaj River water quality data were made by
using multivariate analytical techniques including factor analysis and cluster
analysis. Data set consisted of 11250 observations of a three-year monitoring
program (measurement of 24 variables at 20 stations from April 2006 to March
2009). Factor analysis with principal component analysis extraction of the data
set yielded seven varifactors contributing to 82% of total variance and evaluated
incidence of each varifactor on the total variance. Three groups of quality
parameters, e.g. salinity, organic matter, and nutrients were investigated. Natural
sources pollution originates most variation on water quality. Cluster analysis
clustered 20 sampling sites into two major groups and demonstrated usefulness
of this method for data reduction. This spatial similarity and site clustering
makes possible optimal designing of the future sampling strategy that saves both
time and costs. The results of cluster analysis came complete with T test and
made water quality comparison between two clusters possible. Results of factor
Keywords
surface water quality, multivariate statistical techniques, factor analysis, cluster analysis, Karaj River
Related Book
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