Application of Multivariate Statistical Techniques for the Interpretation of Groundwater Quality in Gombe and Environs, North-East Nigeria

I.A Kwami^1, , J.M Ishaku², Y.S Hamza², A.M Bello¹ and S. Mukkafa³

¹Geology Department, Gombe State University, P.M.B.0127, Gombe, Nigeria

²Department of Geology, School of Physical Science, Modibbo Adama University of Technology, PMB 2076, Yola, Nigeria

³Department of environmental management and toxicology, Federal University Dutse, P.M.B 7156, Dutse, Jigawa State, Nigeria

Cite this paper

I.A Kwami, J.M Ishaku, Y.S Hamza, A.M Bello and S. Mukkafa. Application of Multivariate Statistical Techniques for the Interpretation of Groundwater Quality in Gombe and Environs, North-East Nigeria. Journal of Geosciences and Geomatics. 2019; 7(1):9-14. doi: 10.12691/JGG-7-1-2

Abstract

A total of 50 groundwater samples were collected from Hand dug Wells and Bore holes in Gombe area and environs and were analyzed for their physio-chemical characteristics aimed at interpreting the groundwater quality. Multivariate statistical methods, namely: the hierarchical cluster analysis (HCA), and the principal component analysis (PCA) were used to study the spatial variations of the most significant water quality variables and to determine the dominant processes affecting the water quality. Principal Component Analysis (PCA) on the data indicates three factors which explain about 61.004% of the total variance, and suggests temporary hardness of water, salinity of the groundwater and dissolution of bedrock material as the dominant processes affecting the water quality in the study area. Whereas hierarchical cluster analysis HCA indicate two clusters, and suggests salinity of the groundwater, natural mineralization, bedrock dissolution, Temporary Hardness and anthropogenic contamination as the dominant processes affecting the water quality parameters in the study area.

Keywords

hierarchical cluster analysis (HCA), principal component analysis (PCA), groundwater chemistry, physio-chemical, and Gombe

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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