@article{scholars18876, volume = {198}, note = {cited By 2}, year = {2023}, doi = {10.1016/j.jafrearsci.2022.104808}, journal = {Journal of African Earth Sciences}, title = {Coupling multivariate analysis and Bayesian isotope mixing model to assess the origin and quality of groundwater in the Freetown Layered Complex, Sierra Leone}, keywords = {age determination; Bayesian analysis; groundwater chemistry; hydrological modeling; multivariate analysis; recharge; tritium; water quality, Freetown; Sierra Leone; Western Area}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144049496&doi=10.1016\%2fj.jafrearsci.2022.104808&partnerID=40&md5=ade59b5db04ec1d092a503b90e89f3b7}, abstract = {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. {\^A}{\copyright} 2022 Elsevier Ltd}, author = {Sankoh, A. A. and Laar, C. and Rashid, A. and Frazer-Williams, R.} }