Abstract
The hydrogeochemical characteristics of the significant subterranean water body between “Cecina River and San Vincenzo” (Italy) was evaluated using multivariate statistical analysis methods, like principal component analysis and self-organizing maps (SOMs), with the objective to study the spatiotemporal relationships of the aquifer. The dataset used consisted of the chemical composition of groundwater samples collected between 2010 and 2018 at 16 wells distributed across the whole aquifer. For these wells, all major ions were determined. A self-organizing map of 4 × 8 was constructed to evaluate spatiotemporal changes in the water body. After SOM clustering, we obtained three clusters that successfully grouped all data with similar chemical characteristics. These clusters can be viewed to reflect the presence of three water types: (i) Cluster 1: low salinity/mixed waters; (ii) Cluster 2: high salinity waters; and (iii) Cluster 3: low salinity/fresh waters. Results showed that the major ions had the greater influence over the groundwater chemistry, and the difference in their concentrations allowed the definition of three clusters among the obtained SOM. Temporal changes in cluster assignment were only observed in two wells, located in areas more susceptible to changes in the water table levels, and therefore, hydrodynamic conditions. The result of the SOM clustering was also displayed using the classical hydrochemical approach of the Piper plot. It was observed that these changes were not as easily identified when the raw data were used. The spatial display of the clustering results, allowed the evaluation in a hydrogeological context in a quick and cost-effective way. Thus, our approach can be used to quickly analyze large datasets, suggest recharge areas, and recognize spatiotemporal patterns.
Highlights
K+ the standard deviation represents almost half of the value for the mean, reflects the high variability of these ions. It shows that the geochemistry of the study area is not homogeneous. This agrees with the chemical characteristics previously described by [14], and could suggest that there have not been significant changes in the forces that control the chemical characteristics of the groundwaters present between Cecina and San Vincenzo villages in the past 10 years
The deviation from the 1:1 ratio in the Ca2+ vs. SO4 2− plot indicates that this anion is not as influential to the Ca2+ chemistry as other ions present in the groundwaters. This result agrees with the findings reported by [14,32] for this SSWB
Based on the above-mentioned results (PCA, ionic relations and self-organizing maps (SOMs) clustering), it can be confirmed that the recharge source of the aquifers that make up the SSWB of Cecina Valley occurs through the infiltration of fresh waters that equilibrate with the lithologies over which they drain during its movement downstream to the sea
Summary
Groundwater represents nearly 30% of the global water resources and is considered the most important resource of freshwater to the planet [1] As such, it needs to be carefully monitored in order to determine as soon as possible any changes in its chemical composition and quality. Determining chemical and physical characteristics of groundwater allows an accurate and reliable classification of water bodies, usually through the trilinear plots proposed by [3,4], as suggested by [5]. These plots allow the evaluation of hydrochemical processes; as [6] acknowledges, the identification of clear boundaries between categories is not easy, and since the transitions between each water type are smooth, most of the times no clear distinction between the water types is possible. There’s been an increasing trend to use self-organizing maps (SOMs, a type of artificial neural networks) to explore the spatial patterns of different water quality parameters when large data-sets are used and regional trends are of interest (e.g., [6,7,8,9,13])
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
