Identifying geochemical processes by inverse modeling of multicomponent reactive transport in the Aquia aquifer

Abstract

Modeling reactive geochemical transport in the subsurface is a powerful tool for understanding and interpreting geochemical processes in aquifer systems. Different conceptual models can include different combinations of geochemical processes. A limitation of current inverse models is that they are based only on one conceptual model, which may lead to statistical bias and underestimation of uncertainty. We present a stepwise inverse modeling methodology that can include any number of conceptual models and thus consider alternate combinations of processes, and it can provide a quantitative basis for selecting the best among them. We applied the inverse methodology to modeling the geochemical evolution in the Aquia aquifer (Maryland, USA) over 105 yr. The inverse model accounts for aqueous complexation, acid-base and redox reactions, cation exchange, proton surface complexation, and mineral dissolution and precipitation; identifies relevant geochemical processes; and estimates key reactive transport parameters from available hydrogeochemical data. Inverse modeling provides optimum estimates of transmissivities, leakage rates, dispersivities, cation exchange capacity (CEC), cation selectivities, and initial and boundary concentrations of selected chemical components. Inverse modeling with multiple conceptual models helps to identify the most likely physical and chemical processes in the paleohydrology and paleogeochemistry of the Aquia aquifer. Identification criteria derived from information theory are used to select the best among ten candidate conceptual models. In the final model, both proton surface complexation and methane oxidation are identified as relevant geochemical processes.