Abstract
The research aimed to classify 66 wells within and around Mosul city according to their
water quality using cluster analysis. Water samples were collected and analyzed for pH, total
dissolved solids, conductivity, calcium, magnesium, chloride, sulphate and bicarbonate using
standard methods. The data were analyzed statistically using factor and cluster analysis. The
results of factor analysis show four groups. Conductivity, total dissolved solids, sulphate and
calcium represents the first group with the highest percent of variation (30.55%) between wells.
Cluster analysis divided the wells into four homogenous clusters. The first cluster represents
15(22.7%) of the wells, most of the wells of this cluster are distributed along Tigris river with
lowest pH, highest sulphate and bicarbonate concentration. The second cluster includes the
largest number of wells 33(50%) with the lowest salinity since it had the lowest conductivity,
total dissolved solids, calcium, magnesium and chloride. The third cluster with 4(6.1%) wells,
had the highest salinity since it had the highest conductivity, total dissolved solids, calcium,
magnesium and chloride. The fourth cluster includes 14(21.2%) of less acidity wells with highest
pH and highest bicarbonate concentration. The research concluded that cluster analysis could
be used as an efficient statistical grouping tool according to water quality parameters.
Additionally, factor analysis can be used to analyze a large number of data and study the
variation in water quality.
water quality using cluster analysis. Water samples were collected and analyzed for pH, total
dissolved solids, conductivity, calcium, magnesium, chloride, sulphate and bicarbonate using
standard methods. The data were analyzed statistically using factor and cluster analysis. The
results of factor analysis show four groups. Conductivity, total dissolved solids, sulphate and
calcium represents the first group with the highest percent of variation (30.55%) between wells.
Cluster analysis divided the wells into four homogenous clusters. The first cluster represents
15(22.7%) of the wells, most of the wells of this cluster are distributed along Tigris river with
lowest pH, highest sulphate and bicarbonate concentration. The second cluster includes the
largest number of wells 33(50%) with the lowest salinity since it had the lowest conductivity,
total dissolved solids, calcium, magnesium and chloride. The third cluster with 4(6.1%) wells,
had the highest salinity since it had the highest conductivity, total dissolved solids, calcium,
magnesium and chloride. The fourth cluster includes 14(21.2%) of less acidity wells with highest
pH and highest bicarbonate concentration. The research concluded that cluster analysis could
be used as an efficient statistical grouping tool according to water quality parameters.
Additionally, factor analysis can be used to analyze a large number of data and study the
variation in water quality.
Keywords
Cluster Analysis
Factor Analysis
Water Quality Parameters
Wells