Geography Reference
In-Depth Information
8.
GIS-C
OUPLED
M
ULTIVARIATE
S
TATISTICAL
T
ECHNIQUES
Multivariate statistical analyses techniques such as principal component
analysis (PCA) and cluster analysis (CA) are very useful for classifying
aquifer groundwater quality according to the different pollution sources. It is
observed that the results of the multivariate statistical analyses of water quality
data can easily be combined with GIS in order to delineate the different
groundwater quality zones.
Mapping of groundwater contamination is often complicated by infrequent
and uneven distribution of sampling locations, analytical errors in sample
analyses, and large spatial variation in observed contaminants over short
distances due to complex hydrogeologic conditions.
Also, uncertainty may be associated with numerical modelling approach
used to delineate groundwater contamination plumes due to inadequate
knowledge about local hydrogeological conditions.
Water Quality Data
WHO Guidelines for Drinking Water
Concentration Maps by Spatial Interpolation
Normalized Difference Index Maps
Generating Rank Maps
Computation of Weights for Rank Maps
Developing Water Quality Index Map
Figure 9. Flowchart depicting methodology for developing GIS-based water quality
index maps.
