Assessment of Groundwater Quality Using Multivariate Statistical Techniques
The most vital source of freshwater for domestic, agriculture and industry is groundwater. The physical and chemical compositions of this main source of water are primarily determined by natural and anthropogenic activities. This study is carried out to monitor the groundwater quality in the Jaen di...
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oai:scholars.utp.edu.my:340862023-01-03T07:22:39Z http://scholars.utp.edu.my/id/eprint/34086/ Assessment of Groundwater Quality Using Multivariate Statistical Techniques Suleiman, A.A. Abdullahi, U.A. Suleiman, A. Yunus, R.B. Suleiman, S.A. The most vital source of freshwater for domestic, agriculture and industry is groundwater. The physical and chemical compositions of this main source of water are primarily determined by natural and anthropogenic activities. This study is carried out to monitor the groundwater quality in the Jaen district of Nigeria using several multivariate statistical procedures including principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). Thirty different samples were obtained to analyse the physical and chemical parameters during raining season in the year 2020. The collected parameters include electric conductivity (EC), pH, total dissolved solids (TDS), temperature (Temp.), carbonate (CO3), magnesium (Mg), sodium (Na), potassium (K), calcium (Ca), bicarbonate (HCO3), chloride (Cl), sulphate (SO4), fluoride (F), nitrate (NO3), total hardness (TH), chromium (Cr), iron (Fe), zinc (Zn), manganese (Mn), and copper (Cu). The result from PCA identified major pollutants which account for 56.4 of the three first components of differences altogether, the first component accounting for 24.9, the second for 18.2 and the third for 13.3 of the contribution, respectively. The major groundwater parameters responsible for water pollution in the study area were Cr, Cu, Zn, Mn, Fe, EC, TDS, Temp., Mg, Ca, Na, HCO3 and F compared to other parameters. In addition, PCA showed that the main sources of groundwater contamination in the study area are industrial and domestic activities. Furthermore, based on similarities in pollution levels, CA grouped the sampling stations into three distinct groups; less polluted, moderately polluted, and highly polluted. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. 2022 Article NonPeerReviewed Suleiman, A.A. and Abdullahi, U.A. and Suleiman, A. and Yunus, R.B. and Suleiman, S.A. (2022) Assessment of Groundwater Quality Using Multivariate Statistical Techniques. Studies in Systems, Decision and Control, 444. pp. 567-579. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140255964&doi=10.1007%2f978-3-031-04028-3_36&partnerID=40&md5=2fb499d5a3024c5b0246e11dbca24504 10.1007/978-3-031-04028-3₃₆ 10.1007/978-3-031-04028-3₃₆ |
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The most vital source of freshwater for domestic, agriculture and industry is groundwater. The physical and chemical compositions of this main source of water are primarily determined by natural and anthropogenic activities. This study is carried out to monitor the groundwater quality in the Jaen district of Nigeria using several multivariate statistical procedures including principal component analysis (PCA), factor analysis (FA), and cluster analysis (CA). Thirty different samples were obtained to analyse the physical and chemical parameters during raining season in the year 2020. The collected parameters include electric conductivity (EC), pH, total dissolved solids (TDS), temperature (Temp.), carbonate (CO3), magnesium (Mg), sodium (Na), potassium (K), calcium (Ca), bicarbonate (HCO3), chloride (Cl), sulphate (SO4), fluoride (F), nitrate (NO3), total hardness (TH), chromium (Cr), iron (Fe), zinc (Zn), manganese (Mn), and copper (Cu). The result from PCA identified major pollutants which account for 56.4 of the three first components of differences altogether, the first component accounting for 24.9, the second for 18.2 and the third for 13.3 of the contribution, respectively. The major groundwater parameters responsible for water pollution in the study area were Cr, Cu, Zn, Mn, Fe, EC, TDS, Temp., Mg, Ca, Na, HCO3 and F compared to other parameters. In addition, PCA showed that the main sources of groundwater contamination in the study area are industrial and domestic activities. Furthermore, based on similarities in pollution levels, CA grouped the sampling stations into three distinct groups; less polluted, moderately polluted, and highly polluted. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. |
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Suleiman, A.A. Abdullahi, U.A. Suleiman, A. Yunus, R.B. Suleiman, S.A. |
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Suleiman, A.A. Abdullahi, U.A. Suleiman, A. Yunus, R.B. Suleiman, S.A. Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
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Suleiman, A.A. Abdullahi, U.A. Suleiman, A. Yunus, R.B. Suleiman, S.A. |
author_sort |
Suleiman, A.A. |
title |
Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
title_short |
Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
title_full |
Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
title_fullStr |
Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
title_full_unstemmed |
Assessment of Groundwater Quality Using Multivariate Statistical Techniques |
title_sort |
assessment of groundwater quality using multivariate statistical techniques |
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2022 |
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http://scholars.utp.edu.my/id/eprint/34086/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85140255964&doi=10.1007%2f978-3-031-04028-3_36&partnerID=40&md5=2fb499d5a3024c5b0246e11dbca24504 |
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