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1.
Heliyon ; 10(2): e24663, 2024 Jan 30.
Article in English | MEDLINE | ID: mdl-38298644

ABSTRACT

Groundwater in karst aquifers is frequently tapped for drinking purposes, due to frequent huge volumes of resources. Unfortunately, vulnerability of these aquifers can be high, due to possible fast transfer of recharge water on springs by the karst network. On Gran Sasso Mountain regional aquifer, several springs are subjected to drinking withdrawal and an updated evaluation of their potential is now a fundamental issue to be considered, facing climate change effects, which reflect on variation of discharge regimen and values. To distinguish between different contribution of spring recharge, a tracer test has been carried out on the Vitella d'Oro spring, fed both by the regional aquifer and by a local system exposed to karst features developed in the Rigopiano Conglomerates formation. Thanks to hydrogeological, hydrogeochemical and isotopic data, a conceptual model of spring recharge has been proposed and subsequently validated by the tracer test results. All information confirms the superimposition on the regional base flow, by a relevant contribution of the karst network, influencing the spring discharge in recharge periods. In detail, a fast flow component is responsible for discharge peaks and frequently of turbidity events, having a mean velocity ranging from 30 to 70 m/h in the aquifer. Besides of this fast flow, an additional aliquot of the recharge is due to the same local aquifer, but slower flow clearly identifiable by hydrochemistry and isotopic data. Thanks to these findings, a renewed management of the spring has been suggested, considering the different degrees of aquifer vulnerability (turbidity occurrence) directly related to the discharge regimen.

2.
Sci Total Environ ; 806(Pt 1): 150345, 2022 Feb 01.
Article in English | MEDLINE | ID: mdl-34563913

ABSTRACT

The concept of natural background level (NBL) aims at distinguishing the natural and anthropogenic contributions to concentrations of specific contaminants, as groundwater management and protection tools. This is usually defined as a unique value at a regional scale, even when the hydrogeological and geochemical features of a certain territory are far from homogeneous. The concentration of target contaminants is affected by multiple hydrogeochemical processes. This is the case of arsenic in the Calabria region, where concentrations are definitely variable in groundwater. To overcome the limitation of a traditional approach and to include the intrinsic hydrogeological and geochemical heterogeneity into the definition of the natural contribution to As content in groundwater, an integrated probabilistic approach to the NBL assessment combining aquifer-based preselection criteria and multivariate non-parametric geostatistics was proposed. In detail, different NBL values were selected, based on the aquifer type and/or hydrogeochemical features. Then, these aquifer-based NBL values of arsenic were used in the Probability Kriging method to map the probability of exceedance and to provide contamination risk management tools. This multivariate geostatistical approach that takes advantage of the physico-chemical variables used in the aquifer-based NBL values definition allowed mapping the probability of exceedance of As in a physically-based way. The hydrogeochemical diversity of the study area and all the processes affecting As concentrations in the aquifers have been considered too. As a result, the obtained map was characterized by a short-range and long-range variability due to local hydrogeochemical anomalies and water-rock interaction and/or atmospheric precipitation. By this approach, the NBL exceedance probability maps proved to be less "noisy", because the local hydrogeochemical conditions were filtered, and more capable of pointing out anthropogenic inputs or very anomalous natural contributions, which need to be investigated more in detail and properly managed.


Subject(s)
Arsenic , Groundwater , Water Pollutants, Chemical , Arsenic/analysis , Environmental Monitoring , Italy , Probability , Water Pollutants, Chemical/analysis
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