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Integrated modeling of microplastics in the hyporheic zone

Zenodo (CERN European Organization for Nuclear Research) 2022
Franz Dichgans, Jan‐Pascal Boos, Pouyan Ahmadi, Sven Frei, Jan H. Fleckenstein

Summary

A combined field and modeling study investigated how microplastics interact with the hyporheic zone — the region of sediment beneath and alongside rivers where surface water and groundwater mix. The study found that microplastics can be transported into and retained in hyporheic sediments through infiltration processes, acting as a significant and poorly understood sink. Better models of hyporheic microplastic dynamics are needed to accurately account for plastic retention in river systems.

Study Type Environmental

Research on the transport of microplastic (MP) in rivers mostly focuses on their function as transport vectors between inland areas and the sea. Nonetheless, field studies indicate that MP particles can be retained in riverbed sediment, i.e. the hyporheic zone. The interaction of various transport processes, such as sedimentation, infiltration, or retention, is not yet fully understood. Our work consists of a mechanistic approach to analyze transport processes and retention of MP in the surface water and hyporheic zone. In the presented study, we investigate the transport of MP particles from surface water to the hyporheic zone using a novel hydro-numerical modeling approach. The modeling technique is based on the InterFoam solver of the open-source toolbox OpenFOAM and combines 3D hydrodynamic modeling with transport modeling of MP. Bidirectional coupling between the surface water and the hyporheic flow ensures a detailed representation of the hydrodynamic conditions and particle transport in the model system. The model is calibrated and validated with data from an accompanying flume experiment to ensure the accuracy of the modeled results. We investigate transport mechanisms of the MP particles, retention and transit time of MP in the hyporheic zone as well as the applicability of established transport models to MP. Also see: https://micro2022.sciencesconf.org/428127/document

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