Abstract

Riverbank filtration (RBF) is a surface water treatment technology that uses the aquifer adjacent to the river as a natural filter. A production well in the aquifer near the river draws water from both the aquifer and the river. As river water travels through the aquifer to the well, contaminants in the water undergo biologic and chemical reactions while traveling through the subsurface materials, leading to higher quality water at the well as compared to the river. A key parameter in siting the RBF well is the travel time of the contaminants from the river to the well, which must be sufficiently long to allow adequate time for biologic and chemical reactions to occur. Since the well induces flow into the aquifer from all along the river channel, multiple travel paths exist between the river and the well, each with a different contaminant travel time. The water produced at the well contains a collection of contaminant particles from these multiple travel paths and can be characterized by a distribution of travel times. The travel time of the contaminant depends on the groundwater velocity along the flow path, the sorption properties of the contaminant and the aquifer matrix, and the chemical reactions that occur during transport. In this work, we demonstrate the use of an adjoint-based modeling approach to characterize the distribution of travel times at the RBF well. In adjoint modeling, transport is modeled backward in space and time, from the point of view of the RBF well. The output of an adjoint simulation is the distribution of solute travel times at the RBF well at any time of interest. We consider different sorption models and sorption parameters, and we consider different chemical reactions and reaction rates. We simulate the travel time distributions using either MT3DMS or RT3D, depending on the type of chemical reaction, using a flow field generated using MODFLOW. 235 World Environmental and Water Resources Congress 2014: Water without Borders © ASCE 2014

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