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This dataset is associated with the peer-reviewed publication "River plastic transport and storage budget". This scientific article can be accessed at: https://doi.org/10.1016/j.watres.2024.121786. It comprises data on river macroplastic measurements, notably on macroplastic concentrations on riverbanks, suspended macroplastic transport (in the water column) and surface macroplastic transport. The observations used in the publication were taken at the IJssel and Waal rivers in the Netherlands. The exact locations are indicated in the dataset.

During the July 2021 European floods approximately 8 million pieces of plastic dairy packaging were flushed from a severely damaged dairy processing facility located at the Vesdre river in Belgium. Some of these dairy packaging 'buttertubs' were ultimately flushed into the Meuse river and counted on riverbanks along the Dutch Meuse between July 2021 and July 2023. In addition to recording when and where they were found, some were collected for analysis on their development of mass over the two years between July 2021 - July 2023. The article attached to this dataset is called "Flood-induced buttertub spill reveals riverine plastic transport dynamics" and has the DOI 10.1186/s12302-024-00962-1. Dataset 1 contains the locations where buttertubs were found over the two years, with the location coordinates and sampled area of riverbank. Dataset 2 contains the mass analysis of the collected buttertubs before and after they were cleaned and dried. Dataset 3 contains pictures of the buttertubs analyzed for their mass prior to cleaning.

Rivers play an important role in the macroplastics transport and retention dynamics in the environment. Therefore, gaining an understanding of these processes is vital in order to help determine the fate of macroplastic in the environment. During flood events the transport of floating macroplastic is known to increase. We compared plastic accumulation and flushing on sixteen riverbanks along the Dutch Meuse river during the period that includes the July 2021 extreme flood to plastic accumulation on the same riverbanks as during normal discharge conditions between 2018 and 2021. Here we show that following the flood small macroplastic categories ($\lt\!2.5$ cm) were flushed from the riverbanks, while larger soft plastic fragments (2.5–50 cm) and wet tissues were deposited. We found that for all plastic categories and for all riverbanks averaged, the plastic accumulation rate during the July 2021 flood was higher than that which would be expected for that time of year. However, the average accumulation rate for all locations during the period that included the flood was lower than the average accumulation rate over the Dutch winter (Oct/Nov–Feb/Mar). Our results show that litter category composition following the July 2021 flood differed from normal conditions. This indicates that plastic deposition and remobilization processes on riverbanks differ between extreme flood and annually average conditions. These observations contribute to a better understanding of the fate of macroplastic in the environment in terms of the drivers of both its transport and deposition.

Litter sampling on riverbanks along the Dutch Meuse river, between July 22, 2021 and August 4, 2021. Litter items on riverbanks covered by an ongoing montoring were sampled immediately after the July 2021 European floods. All litter items in the measurement area on each riverbank were counted and classified into the River-OSPAR categories (except wooden litter items). The article attached to this dataset is called "Macroplastic deposition and flushing in the Meuse river following the July 2021 European floods" and has the doi https://doi.org/10.1088/1748-9326/ad0768. The dataset contains the litter sampling in July and August 2021. Dataset 1 contains the complete raw dataset that is more extensive than the dataset used for the publication and dataset 2 contains the simplified dataset underlying the publication.

Anthropogenic macrolitter (>0.5 cm) in rivers is of increasing concern. It has been found to have an adverse effect on riverine ecosystem health, and the livelihoods of the communities depending on and living next to these ecosystems. Yet, little is known on how macrolitter reaches and propagates through these ecosystems. A better understanding of macrolitter transport dynamics is key in developing effective reduction, preventive, and cleanup measures. In this study, we analyzed a novel dataset of citizen science riverbank macrolitter observations in the Dutch Rhine-Meuse delta, spanning two years of observations on over 200 unique locations, with the litter categorized into 111 item categories according to the river-OSPAR protocol. With the use of regression models, we analyzed how much of the variation in the observations can be explained by hydrometeorology, observer bias, and location, and how much can instead be explained by temporal trends and seasonality. The results show that observation bias is very low, with only a few exceptions, in contrast with the total variance in the observations. Additionally, the models show that precipitation, wind speed, and river flow are all important explanatory variables in litter abundance variability. However, the total number of items that can significantly be explained by the regression models is 19% and only six item categories display an R2 above 0.4. This suggests that a very substantial part of the variability in macrolitter abundance is a product of chance, caused by unaccounted (and often fundamentally unknowable) stochastic processes, rather than being driven by the deterministic processes studied in our analyses. The implications of these findings are that for modeling macrolitter movement through rivers effectively, a probabilistic approach and a strong uncertainty analysis are fundamental. In turn, point observations of macrolitter need to be planned to capture short-term variability., Water Resources

Anthropogenic macrolitter (>0.5 cm) in rivers is of increasing concern. It has been found to have an adverse effect on riverine ecosystem health, and the livelihoods of the communities depending on and living next to these ecosystems. Yet, little is known on how macrolitter reaches and propagates through these ecosystems. A better understanding of macrolitter transport dynamics is key in developing effective reduction, preventive, and cleanup measures. In this study, we analyzed a novel dataset of citizen science riverbank macrolitter observations in the Dutch Rhine-Meuse delta, spanning two years of observations on over 200 unique locations, with the litter categorized into 111 item categories according to the river-OSPAR protocol. With the use of regression models, we analyzed how much of the variation in the observations can be explained by hydrometeorology, observer bias, and location, and how much can instead be explained by temporal trends and seasonality. The results show that observation bias is very low, with only a few exceptions, in contrast with the total variance in the observations. Additionally, the models show that precipitation, wind speed, and river flow are all important explanatory variables in litter abundance variability. However, the total number of items that can significantly be explained by the regression models is 19% and only six item categories display an R2 above 0.4. This suggests that a very substantial part of the variability in macrolitter abundance is a product of chance, caused by unaccounted (and often fundamentally unknowable) stochastic processes, rather than being driven by the deterministic processes studied in our analyses. The implications of these findings are that for modeling macrolitter movement through rivers effectively, a probabilistic approach and a strong uncertainty analysis are fundamental. In turn, point observations of macrolitter need to be planned to capture short-term variability.