Abstract
We examine the temporal evolution of the maximum concentration of a dissolved inert solute in spatially heterogeneous subsurface flows. The maximum concentration of a given substance is at the basis of most of environmental regulatory practices where maximum tolerable levels of concentration are typically prescribed for a variety of known contaminants. Through the use of the Lagrangian framework, we elaborate over a physically based, semi-analytical model for the maximum concentration. Specifically, we address how the maximum concentration is affected by key geostatistical parameters (i.e., logconductivity variance), local-scale dispersion processes and engineering design variables such as the dimensions of the solute injection zone. The model will help in identifying the major components that determine the maximum concentration, which is important in order to better allocate resources toward site characterization and reduce uncertainty in predictions. The ultimate scope is to provide a theoretical framework that is application-oriented to estimate the maximum concentration in natural aquifers and provide some guidance in applications. It also provides an useful tool for preliminary, screening analysis and testing scenarios. We test the performance of the model against the MADE transport experiment, with reasonably good agreement.
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Acknowledgements
FPJdB gratefully acknowledges the financial support by the National Science Foundation under Grant 1654009. AF acknowledges funding from the Italian Ministry of Education, University and Research (MIUR) in the frame of the Departments of Excellence Initiative 2018-2022 granted to the Dept. of Engineering of Roma Tre University.
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de Barros, F.P.J., Fiori, A. On the Maximum Concentration of Contaminants in Natural Aquifers. Transp Porous Med 140, 273–290 (2021). https://doi.org/10.1007/s11242-021-01620-3
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DOI: https://doi.org/10.1007/s11242-021-01620-3
Keywords
- Maximum concentration
- Groundwater contamination
- Solute dispersion
- Risk analysis
- Stochastic hydrogeology
- Uncertainty analysis