Anthropogenic litter in aquatic ecosystems negatively impacts ecosystems, species and economic activities. Rivers play a key role in transporting land-based waste towards the ocean. A large portion however is retained within river basins, for example in the estuary, in sediments and on the riverbanks. To effectively identify litter sources, sinks and transport mechanisms, reliable data are crucial. Furthermore, such data can support optimizing litter prevention mitigation and clean-up efforts. This paper presents the results of a 2-year monitoring campaign focused on riverbank macrolitter (>0.5 cm) in the Dutch Rhine–Meuse delta. Between 2017 and 2019, volunteers sampled 152 415 litter items at 212 unique locations. All items were categorized based on the River-OSPAR method (based on the OSPAR beach litter guidelines), which includes 110 specific item categories across ten parent categories. The median litter density was 2060 items/km, and the most observed items were foam, hard, and soft plastic fragments (55.8%). Plastic bottles, food wrappings and packaging, caps, lids and cotton swabs were the most abundant specific items. The litter density and most abundant items vary considerably between rivers, along the river, and over time. For both rivers however, the highest litter density values were found at the Belgian (Meuse) and German (Rhine) borders, and at the Biesbosch National Park, the most downstream location. With this paper, we aim to provide a first scientific overview of the abundance, top item categories, and spatiotemporal variation of anthropogenic litter on riverbanks in the Dutch Rhine–Meuse delta. In addition, we evaluate the used River-OSPAR method and provide suggestions for future implementation in (inter)national long-term monitoring strategies. The results can be used by scientists and policy-makers for future litter monitoring, prevention and clean-up strategies.

Dune growth and post-storm recovery of foredune systems is predominantly determined by the aeolian sand transport through the beach-dune interface. Potential sand transport rates, estimated with empirical transport equations using regionally representative wind conditions, are generally too high. This positive bias might be, at least partly, due to the effect of the beach and foredune topography on the regional airflow. Here, we investigate the relation between local (on the beach) and regional wind velocities and direction in front of the high (�22 m) and steep (�1:2.5) foredune partially vegetated with Marram grass at Egmond aan Zee, The Netherlands based on a dataset with a large variety in wind speeds spanning over all onshore wind directions. We observed that local 10-minute averaged wind speed and direction can differ from the regional wind conditions (here measured 15 km away from the study site) depending on the regional approach angle of the wind. The ratio of local over regional wind speed is smallest (�0.39) when the wind direction is dune-normal. This ratio increases with increasing obliquity towards almost 1 for alongshore winds. Wind steering only happens at the dune foot and is the largest (�13˚) with oblique approaching winds of 40˚from the dune normal. Perpendicular and nearly alongshore winds do not show any steering near the dune foot. The use of local rather than regional wind conditions in a potential transport equation reduces the predicted annual supply from 86 to 32 m 3 /m/y, substantially closer to the measured deposition of 15 m 3 /m/y. The drop in velocity was more important to the reduction in predicted supply than the alongshore steering.

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 R 2 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.

An open‐source quantitative model for predicting coastal foredune growth at monthly to multi‐annual (meso)temporal scales is developed. The model builds on the established fetch framework as a surrogate for the complex micro‐scale aeolian processes on the beach, to which rain and groundwater‐induced spatiotemporal surface moisture dynamics are added as factors limiting aeolian sand supply to foredunes. The model shows great skill in an application at Egmond aan Zee, The Netherlands, with a predicted growth of 16.5 m3/m/yr comparing favourably to the observed growth of 17.3 m3/m/yr. Rain, surface moisture dynamics as well as beach width reduction by storm‐induced elevated sea levels are shown to be important factors that jointly reduce meso‐scale sand supply below the potential (i.e., unlimited) maximum, in our case study by almost 5 m3/m/yr. These factors are most relevant for strong (here, above 15.5 m/s) onshore winds. Consistent with expectations from the literature, meso‐scale foredune growth results primarily from moderately strong (9.5–12.5 m/s) shore‐oblique winds, which are frequent and do not result in supply‐limited conditions. At the study site these winds are most common in winter and hence foredune growth is predicted to vary seasonally, consistent with the observations. Because of the promising results we believe that our model has potential for quantifying how quickly a foredune can recover after an episodic erosion event because of storm waves.

The commonly observed over prediction of aeolian saltation transport on sandy beaches is, at least in part, caused by saltation intermittency. To study small-scale saltation processes, high frequency saltation sensors are required on a high spatial resolution. Therefore, we developed a low-cost Saltation Detection System (SalDecS) with the aim to measure saltation intensity at a frequency of 10 Hz and with a spatial resolution of 0.10 m in wind-normal direction. Linearity and equal sensitivity of the saltation sensors were investigated during wind tunnel and field experiments. Wind tunnel experiments with a set of 7 SalDec sensors revealed that the variability of sensor sensitivity is at maximum 9% during relatively low saltation intensities. During more intense saltation the variability of sensor sensitivity decreases. A sigmoidal fit describes the relation between mass flux and sensor output measured during 5 different wind conditions. This indicates an increasing importance of sensor saturation with increasing mass flux. We developed a theoretical model to simulate and describe the effect of grain size, grain velocity and saltation intensity on sensor saturation. Time-averaged field measurements revealed sensitivity equality for 85 out of a set of 89 horizontally deployed SalDec sensors. On these larger timescales (hours) saltation variability imposed by morphological features, such as sand strips, can be recognized. We conclude that the SalDecS can be used to measure small-scale spatiotemporal variabilities of saltation intensity to investigate saltation characteristics related to wind turbulence.

<p>Rivers transport, and store a large share of the global plastic pollution. Riverbanks are one of the river compartments where macroplastic litter is deposited and retained. Different factors influence macroplastic deposition on riverbanks. Retention related factors such as riverbank features, and supply related factors, such as hydrometeorology or land-use. Riverbank macrolitter along the Dutch Meuse has been quantified, characterized, and removed biannually since 2017. At each monitored riverbank, macroplastic and other litter items were collected along a 100 m section and classified in over 100 specific litter categories. We assume that after each monitoring round all litter is removed, and that the litter sampled in the following round has accumulated in the time between rounds. This monitoring dataset is analyzed to identify riverbanks with plastic accumulation rates continuously below or above average, and the specific characteristics of these identified riverbanks. Furthermore, correlations are investigated between macroplastic deposition and individual riverbank features and river morphology, such as types of riparian vegetation, or curvature of the river. These correlations are tested for the total amount of plastic litter, but also categories grouped by plastic characteristics such as potential source, density, size, or flexibility. This is done based on the hypothesis that plastic litter items with different characteristics are associated to different processes of plastic emission and deposition. For example, items with low or high density, or different levels of flexibility. Items with low and high densities are transported differently, because their density is lower or higher than the density of water. Items with a high level of flexibility, such as soft plastic foils, have a higher potential for entanglement in vegetation, and a lower potential for remobilization, compared to items with a low level of flexibility. The aim of this study is to identify riverbank characteristics that explain high plastic accumulation rates.</p>

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