A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal

James L. McCallum, Anja Höhne, Jonas L. Schaper, Margaret Shanafield, Edward W. Banks, Malte Posselt, Okke Batelaan, Jörg Lewandowski

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Abstract

Understanding the mechanisms and controls on contaminant removal in streams is essential in managing human and ecosystem health. The hyporheic zone (HZ) plays a key role in the removal of contaminants from streams. Often, tracer tests are implemented in conjunction with measurements of compounds to assess the removal rates of contaminants in streams. The predicted removal rates largely rely on the estimated hyporheic residence time, and hence, the chosen conceptual model of hyporheic exchange flows (HEFs) will influence the predicted removal rate. Despite this, different HEF models are generally not considered when assessing contaminant removal rates. In this paper, we present a numerical modeling approach for interpreting tracer tests to determine contaminant removal rates that allows for multiple conceptual models of HEF to be considered. We demonstrate this method by interpreting data from a conservative tracer test in conjunction with grab samples of trace organic compounds using two commonly used models of HEF: one that assumes first-order exchange between the stream and the HZ and one that considers a power law weighting of first-order exchange coefficients. For the three degrading compounds measured, guanylurea, valsartan, and diclofenac, we observed that the power law model consistently predicted higher removal rates in the stream compared to the first-order model. Variations were also observed between the removal rates estimated in the HZ. Our results highlight the importance of considering multiple conceptualizations of the HEF when assessing contaminant removal rates.

Original languageEnglish
Article numbere2019WR024987
JournalWater Resources Research
Volume56
Issue number3
DOIs
Publication statusPublished - Mar 2020

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