Identifying the major hydrogeochemical factors governing groundwater chemistry in the coastal aquifers of southwest Bangladesh using statistical analysis
Sarker, M.M.R.; Hermans, T.; Van Camp, M.; Hossain, D.; Islam, M.; Ahmed, N.; Bhuiyan, M.A.Q.; Karim, M.M.; Walraevens, K. (2022). Identifying the major hydrogeochemical factors governing groundwater chemistry in the coastal aquifers of southwest Bangladesh using statistical analysis. Hydrology 9(2): 20. https://dx.doi.org/10.3390/hydrology9020020
In: Hydrology. MDPI: Basel. e-ISSN 2306-5338, meer
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| Author keywords |
hydrochemistry; evaporite dissolution; cation exchange; cluster analysis; factor analysis |
| Auteurs | | Top |
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- Hossain, D.
- Islam, M., meer
- Ahmed, N.
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- Bhuiyan, M.A.Q.
- Karim, M.M.
- Walraevens, K., meer
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| Abstract |
People in the southwestern (SW) coastal part of Bangladesh are suffering from a severe freshwater crisis due to saline groundwater at a shallow depth. Fresh groundwater below a 200 m depth is an option, but it is costly to construct deep tubewells for the local inhabitants. The processes of salinization and freshening were previously identified using conventional methods. In this study, we brought new insight into these processes by analyzing existing datasets using multivariate statistics to identify the factors affecting groundwater chemistry. Cluster analysis (CA) revealed three major clusters. Cluster A corresponded to saline (NaCl-type) water. Cluster B was also saline (NaCl-type) water but showed mixing effects. Cluster C was fresh groundwater (NaHCO3-type) and isolated. The hydrochemical characteristics of clusters A, B and C compared remarkably well with the groundwaters from the upper shallow aquifer (USA), lower shallow aquifer (LSA) and deep aquifer (DA), respectively. Factor analysis (FA) showed that 75% of the total variance was influenced by evaporate dissolution, carbonate dissolution/precipitation, cation exchange and anthropogenic pollution to some extent. Therefore, the integrated approach showed the validity of applying multivariate statistical techniques to infer the dominant hydrochemistry and to characterize and understand a complicated hydrogeological system. |
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