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Multivariate Analysis for Water Quality Parameters Assessment: A Case Study of Lamingo Dam Jos, Plateau State, Nigeria
Subject area: Science,Engineering and Technology · Area of research: Statistics
Abstract
The water quality in Jos, Plateau State, Nigeria, has become a critical issue with significant public health, ecological, and economic implications. Despite ongoing efforts to manage water resources, substantial challenges remain in ensuring safe and clean water provision. This study aims to improve water quality by analyzing the various water quality parameters using Principal Component Analysis (PCA) and Factor Analysis (FA). Secondary data from the Plateau State Water Board's Lamingo Treatment Plant for the year 2023 was used. The correlation analysis revealed significant interdependencies among parameters such as pH, Alkalinity, and Chlorine, highlighting the need for integrated management. PCA identified two principal components explaining 72.44% of the variance in water quality, with the primary component driven by pH, Alkalinity, and Chlorine, and the secondary component influenced by Total Hardness and Turbidity. FA uncovered two underlying factors: the "Water Chemistry Factor" driven by “Human Activities” and the "Water Mineral Factor" influenced by “Geological Processes”. The study concludes with recommendations for targeted monitoring, optimized chlorine dosing, advanced filtration systems, and holistic water quality improvement strategies. Additionally, infrastructure improvements, public awareness campaigns, and strict regulation of industrial effluents and agricultural runoff are essential. These findings provide a comprehensive understanding of the factors affecting water quality and offer actionable insights for enhancing water quality and management practices in Jos, Plateau State.
Keywords
Water, Water Quality, Principal Component Analysis, Factor Analysis, Eigenvalue, Eigenvector
References
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How to cite this paper
@article{1715231,
author = {Akanihu, C. N., Ali, H., Sakya M. R.},
title = {Multivariate Analysis for Water Quality Parameters Assessment: A Case Study of Lamingo Dam Jos, Plateau State, Nigeria},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {1386-1398},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715231.pdf},
abstract = {The water quality in Jos, Plateau State, Nigeria, has become a critical issue with significant public health, ecological, and economic implications. Despite ongoing efforts to manage water resources, substantial challenges remain in ensuring safe and clean water provision. This study aims to improve water quality by analyzing the various water quality parameters using Principal Component Analysis (PCA) and Factor Analysis (FA). Secondary data from the Plateau State Water Board's Lamingo Treatment Plant for the year 2023 was used. The correlation analysis revealed significant interdependencies among parameters such as pH, Alkalinity, and Chlorine, highlighting the need for integrated management. PCA identified two principal components explaining 72.44% of the variance in water quality, with the primary component driven by pH, Alkalinity, and Chlorine, and the secondary component influenced by Total Hardness and Turbidity. FA uncovered two underlying factors: the "Water Chemistry Factor" driven by “Human Activities” and the "Water Mineral Factor" influenced by “Geological Processes”. The study concludes with recommendations for targeted monitoring, optimized chlorine dosing, advanced filtration systems, and holistic water quality improvement strategies. Additionally, infrastructure improvements, public awareness campaigns, and strict regulation of industrial effluents and agricultural runoff are essential. These findings provide a comprehensive understanding of the factors affecting water quality and offer actionable insights for enhancing water quality and management practices in Jos, Plateau State.},
keywords = {Water, Water Quality, Principal Component Analysis, Factor Analysis, Eigenvalue, Eigenvector},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715231}
}