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The use of environmental tracers brings comprehensive benefits to the management of water resources since it helps to prevent their pollution, minimize public health risks, and thus reduce the impact of urbanization. In Brazil, the Guarani Aquifer System (GAS) has strategic and environmental importance, making its preservation and sustainable exploitation mandatory. The present study aimed at evaluating sources of contamination in the GAS using the combination of geochemical data and two environmental tracers: nitrate isotopes (15NNO3 and 18ONO3) and one rare earth element (Gadolinium—Gd). For that, five wells—four exploiting the GAS and one the Bauru Aquifer System (BAS)—were selected to discuss the human inputs in groundwater used for public supply in an urban area. Traditional physicochemical analyses were conducted for six campaign samplings and nitrate monitoring for this period was evaluated on a time scale, also considering the accumulated rainfall. Besides that, the double isotopic method (DIM), e.g., δ18ONO3 e δ15NNO3, was applied to identify the fractionation and enable the distinction of the nitrate contamination source. In addition, the determination of anomalies of Gd, a wastewater-derived contaminant, was also performed to verify recent human inputs in groundwater. The results show that the local existence of nitrate in the GAS and BAS—even at low concentrations (values from 0.26 to 6.68 mg L−1)—originated from anthropogenic inputs (septic waste), as indicates the typical isotopic signals ratio in the isotopic approach. Associated with that, the evaluation of Gd permitted the separation of groundwater samples into older or more recent leakages. The use of environmental tracers to assess anthropogenic inputs in groundwater reiterates the importance of adopting more effective protection strategies for water resources management systems, in order to prevent contamination. [ABSTRACT FROM AUTHOR]

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Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS. [ABSTRACT FROM AUTHOR]