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Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach

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dc.contributor.author Armah, Frederick Ato
dc.contributor.author Paintsil, Arnold
dc.contributor.author Yawson, David Oscar
dc.contributor.author Adu, Michael Osei
dc.contributor.author Odoi, Justice O.
dc.date.accessioned 2021-03-15T09:44:48Z
dc.date.available 2021-03-15T09:44:48Z
dc.date.issued 2017
dc.identifier.issn 23105496
dc.identifier.uri http://hdl.handle.net/123456789/4883
dc.description 15p:, ill. en_US
dc.description.abstract Chemometric techniques were applied to evaluate the spatial and temporal heterogeneities in groundwater quality data for approximately 740 goldmining and agriculture-intensive locations in Ghana. The strongest linear and monotonic relationships occurred between Mn and Fe. Sixty-nine per cent of total variance in the dataset was explained by four variance factors: physicochemical properties, bacteriological quality, natural geologic attributes and anthropogenic factors (artisanal goldmining). There was evidence of significant differences in means of all trace metals and physicochemical parameters (p < 0.001) between goldmining and non-goldmining locations. Arsenic and turbidity produced very high value F’s demonstrating that ‘physical properties and chalcophilic elements’ was the function that most discriminated between non-goldmining and goldmining locations. Variations in Escherichia coli and total coliforms were observed between the dry and wet seasons. The overall predictive accuracy of the discriminant function showed that non-goldmining locations were classified with slightly better accuracy (89%) than goldmining areas (69.6%). There were significant differences between the underlying distributions of Cd, Mn and Pb in the wet and dry seasons. This study emphasizes the practicality of chemometrics in the assessment and elucidation of complex water quality datasets to promote effective management of groundwater resources for sustaining human health. Frederick Ato Armah (corresponding author) Department of Environmental Science, School of Biological Sciences, College of Agriculture & Natural Sciences, University of Cape Coast, Cape Coast, Ghana E-mail: farmah@ucc.edu.gh Arnold Paintsil Department of Civil and Environmental Engineering, Faculty of Engineering, Spencer Engineering Building, Western University, London, Ontario N6A 5B9, Canada David Oscar Yawson Department of Soil Science, School of Agriculture, College of Agriculture & Natural Sciences, University of Cape Coast, Cape Coast, Ghana Michael Osei Adu Department of Crop Science, School of Agriculture, College of Agriculture & Natural Sciences, University of Cape Coast, Cape Coast, Ghana Justice O. Odoi Nature Today Ghana, P.O. Box OS 1455, Osu, Accra, Ghana en_US
dc.language.iso en en_US
dc.publisher University of Cape Coast en_US
dc.subject Bacteriological en_US
dc.subject Discriminant analysis en_US
dc.subject Goundwater en_US
dc.subject Negative log-log en_US
dc.subject Physicochemical en_US
dc.subject Regression en_US
dc.title Modelling spatio-temporal heterogeneities in groundwater quality in Ghana: a multivariate chemometric approach en_US
dc.type Article en_US


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