Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone
The current study combined the water quality index, multivariate statistical techniques, environmental isotopes, and the Bayesian isotope mixing model to determine the extent of groundwater pollution, origin, age, and proportional source contribution to groundwater recharge in the Freetown peninsula...
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oai:scholars.utp.edu.my:341282023-01-04T02:45:40Z http://scholars.utp.edu.my/id/eprint/34128/ Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone Sankoh, A.A. Laar, C. Rashid, A. Frazer-Williams, R. The current study combined the water quality index, multivariate statistical techniques, environmental isotopes, and the Bayesian isotope mixing model to determine the extent of groundwater pollution, origin, age, and proportional source contribution to groundwater recharge in the Freetown peninsula. The water quality index analysis depicts that all the groundwaters are excellent and suitable for drinking purposes. The Gibb's diagram suggests that water-rock interaction and precipitation are the dominant sources impacting the groundwater chemistry while sodium chloride and magnesium bicarbonate are the dominant water types in the Freetown peninsula. This study finds that saltwater and anthropogenic contamination from agriculture and domestic sewage significantly impact the groundwater quality in the study area. Two (2) clusters were delineated; cluster 1 showed the characteristics of groundwater while cluster 2 demonstrated the characteristics of estuary water. A plot of 2H versus 18O showed that the groundwaters in the study area are of meteoric origin. The Bayesian model (SIMMR) output revealed that precipitation (83) was the dominant source of groundwater recharge in the study area. The tritium analysis revealed that the majority of the groundwaters (83.3) are young and of recent recharge. This study serves as a baseline to evaluate the percentage sources of salinity in groundwater. © 2022 Elsevier Ltd 2023 Article NonPeerReviewed Sankoh, A.A. and Laar, C. and Rashid, A. and Frazer-Williams, R. (2023) Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone. Journal of African Earth Sciences, 198. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144049496&doi=10.1016%2fj.jafrearsci.2022.104808&partnerID=40&md5=ade59b5db04ec1d092a503b90e89f3b7 10.1016/j.jafrearsci.2022.104808 10.1016/j.jafrearsci.2022.104808 10.1016/j.jafrearsci.2022.104808 |
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The current study combined the water quality index, multivariate statistical techniques, environmental isotopes, and the Bayesian isotope mixing model to determine the extent of groundwater pollution, origin, age, and proportional source contribution to groundwater recharge in the Freetown peninsula. The water quality index analysis depicts that all the groundwaters are excellent and suitable for drinking purposes. The Gibb's diagram suggests that water-rock interaction and precipitation are the dominant sources impacting the groundwater chemistry while sodium chloride and magnesium bicarbonate are the dominant water types in the Freetown peninsula. This study finds that saltwater and anthropogenic contamination from agriculture and domestic sewage significantly impact the groundwater quality in the study area. Two (2) clusters were delineated; cluster 1 showed the characteristics of groundwater while cluster 2 demonstrated the characteristics of estuary water. A plot of 2H versus 18O showed that the groundwaters in the study area are of meteoric origin. The Bayesian model (SIMMR) output revealed that precipitation (83) was the dominant source of groundwater recharge in the study area. The tritium analysis revealed that the majority of the groundwaters (83.3) are young and of recent recharge. This study serves as a baseline to evaluate the percentage sources of salinity in groundwater. © 2022 Elsevier Ltd |
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Sankoh, A.A. Laar, C. Rashid, A. Frazer-Williams, R. |
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Sankoh, A.A. Laar, C. Rashid, A. Frazer-Williams, R. Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
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Sankoh, A.A. Laar, C. Rashid, A. Frazer-Williams, R. |
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Sankoh, A.A. |
title |
Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
title_short |
Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
title_full |
Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
title_fullStr |
Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
title_full_unstemmed |
Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone |
title_sort |
coupling multivariate analysis and bayesian isotope mixing model to assess the origin and quality of groundwater in the freetown layered complex, sierra leone |
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2023 |
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http://scholars.utp.edu.my/id/eprint/34128/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144049496&doi=10.1016%2fj.jafrearsci.2022.104808&partnerID=40&md5=ade59b5db04ec1d092a503b90e89f3b7 |
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