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2023 | OriginalPaper | Chapter

22. Groundwater Quality Assessment Using Principal Component and Cluster Analysis

Authors : Ahmed Garba, Ahmed Muhd Idris, Jibrin Gambo

Published in: Water Resources Management and Sustainability

Publisher: Springer Nature Switzerland

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Abstract

The application of statistical techniques for the study of groundwater data provides an authentic understanding of aquifer and ecological condition and leads to the recognition of the potential sources that determine the groundwater system. The groundwater quality data generated was analyzed using Principal Component Analysis and Cluster analysis. Principal Component Analysis result yielded five principal factor which accounted for 78.69% total variance dominated by Total Hardness, Total Dissolved Solids, Cu, Cl⁻, NO₃⁻, Cu, Electrical Conductivity indicating that the major variations are related to human actions and natural processes. Cluster analysis grouped the 20 boreholes into four statistically substantial clusters.

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previous chapter Effects of Leachate from Osisioma Open Dumpsite in Aba, Abia State, Nigeria on Surrounding Borehole Water Quality

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Title: Groundwater Quality Assessment Using Principal Component and Cluster Analysis
Authors: Ahmed Garba
Ahmed Muhd Idris
Jibrin Gambo
Publisher: Springer Nature Switzerland
Book: Water Resources Management and Sustainability
Print ISBN: 978-3-031-24505-3

Electronic ISBN: 978-3-031-24506-0

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-24506-0_22

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