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Characterizing the Influence of Multiple Uncertainties on Predictions of Contaminant Discharge in Groundwater Within a Lagrangian Stochastic Formulation
Author(s) -
Ciriello Valentina,
Barros Felipe P. J.
Publication year - 2020
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2020wr027867
Subject(s) - groundwater recharge , hydraulic conductivity , aquifer , hydrogeology , robustness (evolution) , environmental science , polynomial chaos , groundwater , soil science , uncertainty analysis , hydrology (agriculture) , geology , mechanics , monte carlo method , geotechnical engineering , mathematics , statistics , physics , biochemistry , chemistry , gene , soil water
Assessing the risks associated with transport of contaminants in hydrogeological systems requires the characterization of multiple sources of uncertainty. This paper examines the impact of the uncertainty in the source zone mass release rate, aquifer recharge, and the spatial structure of the hydraulic conductivity on transport predictions. Through the use of the Lagrangian framework, we develop semianalytical solutions for the first two moments of the total solute discharge through a control plane while accounting for source zone release conditions and recharge. We employ global sensitivity analysis (GSA) to investigate how the predictive uncertainty of the mass discharge is affected by uncertainty in source zone mass release rate, recharge, and the variance of the log‐conductivity field. The semianalytical solutions are employed with the polynomial chaos expansion technique to perform a GSA. Our results reveal the relative influence of each source of uncertainty on the robustness of model predictions, which is critical for site managers to allocate resources and design mitigation strategies.