Statistical Explanatory Assessment of Groundwater Quality in Gwale LGA, Kano State, Northwest Nigeria

Author:

Suleiman Ahmad1ORCID,Ibrahim Auwalu1ORCID,Abdullahi Usman1ORCID

Affiliation:

1. Department of Statistics, Faculty of Computing and Mathematical Sciences, Kano University of Science and Technology, Wudil 713281, Nigeria.

Abstract

Groundwater is one of the significant sources of drinking water in the world. To protect groundwater quality for domestic consumption, it is important to undertake a periodic investigation of its quality to improve the healthy living of the ever-increasing population. In this paper, we have analyzed physical and chemical (physicochemical) concentration levels in groundwater samples collected from twenty-eight sampling locations during the raining season in Gwale, Northwest Nigeria. About fifteen physicochemical parameters such as electric conductivity (EC), turbidity (Turb), pH,  temperature (Temp), nitrate (NO3), phosphate (PO4), total dissolved solid (TDS), chloride (Cl), sulphate (SO4), calcium (Ca), magnesium (mg), sodium (Na), total hardness (TH), iron (Fe) and alkalinity (Alk) were analyzed. The concentrations levels of groundwater parameters in each sampling location were compared with the permissible limits of drinking water qualities specified by the Nigerian Industrial Standard (NIS) to determine the suitability of drinking water in the study area. Karl Pearson’s coefficient of correlation was applied to the groundwater dataset to identify the influence of each physicochemical parameter to the groundwater contamination. Also, hierarchical cluster analysis was used to classify the groundwater samples based on contamination density as well as to identify the sources of water contamination. The results from correlation analysis revealed that EC, TDS, Ca, TH, Mg, SO4, Na and Cl were influenced the water contamination in many of the study locations based on the conventional significance levels (1% and 5%). From the results of cluster analysis, three statistically significant groups (cluster 1, cluster 2 and cluster 3) were formed which were defined as lower contaminated areas, moderately contaminated areas and higher contaminated areas, respectively. The contamination levels identified in the three clusters were attributed to anthropogenic and industrial activities in the raining season. Therefore, groundwater from cluster 3 (Salanta, Hauren makaranta, Dandago, Mandawari and Magashi) are found unsuitable for drinking. This study is useful in monitoring groundwater quality and could be applied in any other location.

Funder

Tertiary Education Trust Fund

Publisher

Gatha Cognition

Subject

General Computer Science

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