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the data, in order to classify the objects of the system into clusters based on
their similarities (Otto, 1998). This method creates linkages between variables
hierarchically in the configuration of a tree with different branches. Branches
that have linkages closer to each other indicate a stronger relationship among
variables or clusters of variables. Mathes and Rasmussen (2006) demonstrated
the methodology for generating GIS maps of groundwater contamination using
multivariate statistical analysis of water quality data. GIS is an important tool
that is used to organize and manage large amounts of water quality
information for use in decision support systems.
Nowadays, GIS has been started to be used routinely for displaying water
quality data in map form but still use of statistical indicators of contaminant
distributions are rarely seen. Presently, focus of GIS-coupled multivariate
statistical analysis techniques has shifted from mapping of observed
contaminant distribution to developing a map of contamination potential
created using auxiliary water quality data.
Prior to applying multivariate statistical analysis, generally the observed
water quality data, x ji are standardized by z-scale transformation as given
below:
x
x
ji
j
z
s
j
(37)
where, x ji = value of the j th water quality parameter measured at i th site, x =
mean (spatial) value of the j th parameter, and s j = standard deviation of the j th
parameter.
The analysis performed with standardized data is expected to be less
influenced by small/large variance of the data. Furthermore, standardization of
the data removes the influence of different measurement units of the data by
making the data dimensionless.
C ONCLUSION
Evaluation of water quality is necessary for managing water quality so as
to ensure environmental sustainability. The important aspects of water quality
evaluation are interpretation of water quality variables, reporting of results and
recommendations for planners and decision makers. Logical sequence of any
water quality evaluation programme consists of three key steps: monitoring ,
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