Markovian Models for Microplastic Transport in Open‐Channel Flows

Abstract The ubiquity of microplastics in marine environments is of growing concern and is increasingly receiving widespread attention. Due to the role of rivers and streams as suppliers of microplastics to the marine environment, it is essential to accurately capture their movements at these scales, but modeling and experimental knowledge in such settings is still limited. In this work, three Markov models, including a continuous time random walk model, Bernoulli model, and spatial Markov model (SMM), are implemented to investigate polyethylene particles transport in open‐channel flows. First, a three‐dimensional high‐resolution direct numerical simulation (DNS) fully resolves a canonical open‐channel flow, and particle transport is simulated using idealized point particles. Then, a series of laboratory transport experiments are conducted in a circulating water tank, and particle image velocimetry methods are used to obtain particle‐tracking data. We find that the correlated Bernoulli model and SMM can successfully reproduce the transport of both DNS and laboratory experiments, particularly in the prediction of measured breakthrough curves, which highlights the importance of correlation between the successive steps. A major benefit of these models is a computational cost that is several orders of magnitude less than, for example, DNS, which demonstrates their high‐efficiency and effectiveness. Therefore, this research offers new insights into the transport of microplastics in open‐channel systems like rivers and streams, which is necessary to prevent and reduce the environmental hazards of microplastics.