Exploring Macroplastic Transport and Retention Dynamics in Country-Wide River Networks

Over the last years macroplastic has been increasingly monitored not only in oceans but also in freshwaters. Despite the ongoing discussion of linking plastic masses in rivers with masses in oceans, multiple studies showed a highly complex transport of plastic debris from in land-based sources towards the oceans. However, current modeling and monitoring studies mostly focused on specific processes in single rivers or used highly simplified approaches. While such studies may be helpful to identify the fate mechanisms, they are less suitable to predict macroplastic flows in a large river network on country-scale. The aim of our work was therefore to develop a macroplastic fate model for a whole country which was parameterized based on measurements in specific rivers. For the macroplastic modelling we considered four different states: (1) in suspension, (2) temporally stored (3) long term burial or accumulated and (4) removal / cleaning from in suspension or temporally stored masses. The model considers a high spatial resolution with river sections of few meters to kilometers in length which are connected to the overall river network. As input data we used macroplastic emissions predicted by a material flow analysis model on the same spatial resolution. The model was applied before to predict macroplastic masses on a river level.

Using our model we found that the considered transport and fate processes for macroplastics must clearly differ from processes considered for microplastics. As possible influencing fate and transport factors we compared the influence of parameters such as sinuosity of rivers, the land use in close river distance, the discharge or impact of weirs with macroplastic removals. Each parameter was identified by other studies as potential factor for macroplastic retention. Here, we explore their influence on the output on a country-scale. We conclude that based on our modelling a high retention of macroplastics must occur within the system to match monitoring data with predicted macroplastic releases. While we assume that high amounts of macroplastics will be temporally stored until the next flooding event, it remains challenging to predict the long term in-situ accumulation. As a first step, we simulated different parameter settings to mimic "normal" discharge conditions in comparison with flooding events.

Overall our results bring existing concepts and understanding in a wider context by coupling emission modelling with fate modeling and monitoring results from literature. Moreover, we are able to predict macroplastic masses in rivers and temporally stored in river banks and compare predicted values with first available measurements. Especially, predicting microplastic masses is of high importance for policy makers to manage plastic pollutions along riversides.