Applied multivariate statistical analysis as a tool for assessing groundwater reactions in the Niebla-Posadas aquifer, Spain
In the current context of population growth and climate change, it is essential to effectively manage groundwater resources, to improve their quality, and to determine the behaviour of certain contaminants. Groundwater quality can be worsened most often by anthropogenic factors but can also be altered by natural factors depending on the chemical signatures of water sources (i.e., hydrochemical reactions) as a result of mixing processes. In these cases, the use of mixing calculations and multivariate statistical analysis (MSA) methods is crucial for determining the reactions that occur, the origin and fate of the detected compounds, ions or parameters, and the behaviour of the system. Thus, these methods ascertain processes that affect the chemical composition (i.e., quality) of groundwater bodies, and this information is needed for designing groundwater management strategies that exploit aquifers in a sustainable way. However, these methods are rarely employed, as few investigations that consider them focus on urban aquifers. Here, mixing calculations and other MSA methods that consider major ions and environmental isotopes are utilized in an aquifer located in a rural area associated with the Niebla-Posadas aquifer, Spain, where groundwater quality has deteriorated due to geogenic factors. This study proves the usefulness of these methods for deriving essential information that is needed (1) to properly manage the exploitation of aquifers, (2) to avoid the deterioration of groundwater bodies, and (3) to identify the reasons behind poor groundwater quality.
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | artículo biblioteca |
| Language: | English |
| Published: |
Springer Nature
2023-01
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| Subjects: | Selectivity coefficient, Cluster analysis, Groundwater management, Isotopes, Principal component analysis, |
| Online Access: | http://hdl.handle.net/10261/286908 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100003339 http://dx.doi.org/10.13039/501100000780 https://api.elsevier.com/content/abstract/scopus_id/85145689872 |
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| Summary: | In the current context of population growth and climate change, it is essential to effectively manage groundwater resources, to improve their quality, and to determine the behaviour of certain contaminants. Groundwater quality can be worsened most often by anthropogenic factors but can also be altered by natural factors depending on the chemical signatures of water sources (i.e., hydrochemical reactions) as a result of mixing processes. In these cases, the use of mixing calculations and multivariate statistical analysis (MSA) methods is crucial for determining the reactions that occur, the origin and fate of the detected compounds, ions or parameters, and the behaviour of the system. Thus, these methods ascertain processes that affect the chemical composition (i.e., quality) of groundwater bodies, and this information is needed for designing groundwater management strategies that exploit aquifers in a sustainable way. However, these methods are rarely employed, as few investigations that consider them focus on urban aquifers. Here, mixing calculations and other MSA methods that consider major ions and environmental isotopes are utilized in an aquifer located in a rural area associated with the Niebla-Posadas aquifer, Spain, where groundwater quality has deteriorated due to geogenic factors. This study proves the usefulness of these methods for deriving essential information that is needed (1) to properly manage the exploitation of aquifers, (2) to avoid the deterioration of groundwater bodies, and (3) to identify the reasons behind poor groundwater quality. |
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