Open AccessClassification of Selected Ground Water Wells within and around Mosul City according to their Water Quality Using Factor and Cluster Analysis
Author(s) -
Abdulmuhsin S. Shihab,
Abeer Hashim
Publication year - 2013
Publication title -
mağallaẗ tikrīt li-l-ʻulūm al-handasiyyaẗ/tikrit journal of engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 2312-7589
pISSN - 1813-162X
DOI - 10.25130/tjes.21.3.01
Subject(s) - cluster (spacecraft) , total dissolved solids , chloride , salinity , bicarbonate , magnesium , water quality , chemistry , conductivity , mineralogy , environmental science , environmental engineering , geology , ecology , oceanography , organic chemistry , computer science , biology , programming language
The research aimed to classify 66 wells within and around Mosul city according to theirwater quality using cluster analysis. Water samples were collected and analyzed for pH, totaldissolved solids, conductivity, calcium, magnesium, chloride, sulphate and bicarbonate usingstandard methods. The data were analyzed statistically using factor and cluster analysis. Theresults of factor analysis show four groups. Conductivity, total dissolved solids, sulphate andcalcium 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 represents15(22.7%) of the wells, most of the wells of this cluster are distributed along Tigris river withlowest pH, highest sulphate and bicarbonate concentration. The second cluster includes thelargest 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 highestpH and highest bicarbonate concentration. The research concluded that cluster analysis couldbe 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 thevariation in water quality.