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Microplastics are an unavoidable part of riverine systems, altering the natural composition of rivers and the associated processes. Within a riverine system, microplastics can be present throughout the water column or within bedload, implying different transport, deposition, and erosion mechanisms. Some recent models have been developed to predict and understand the depth distribution concentration of microplastics and macroplastics, primarily relying on the Rouse model for sediments. However, the great variety in microplastics shape and size accompanied by the dynamic nature of riverine systems (e.g., variety of flow conditions, sediment composition and bedforms) question how realistic and reliable models for plastic distribution along the water column and within sediments are. Present models are often analogous to suspended sediment models and assume diffusivity to be equal to turbulent viscosity, they often exclude the bedload, neglect the effect of turbulence and bed morphology, and come short in explaining the behaviour of mixtures of microplastics and sediments. Understanding these aspects is crucial to improve present models and to aid mitigation efforts and to optimize collection systems and policy. This project targets employing both physical and numerical modelling techniques to further develop depth concentration models of microplastics. We aim to further examine and quantify the influence of turbulence on microplastics transport and concentration distribution by establishing preliminary estimates for the eddy viscosity and diffusivity of microplastics and further examine a wider range of mixtures of microplastics and sediments with different shapes and sizes.

Our current era is often referred to as the 'age of data'. Increasing amounts of data and models are generated, often without being used sustainably - because they are not accessible, difficult to understand or difficult to transfer to other data sets. With https://envsci.fastresearch.io/, we aim to improve collaboration on data sets and analyses to make them usable and reproducible for everyone. With our innovative platform, we want to enable researchers to work together on data and data analysis by giving them a tool to collaborate and to make their data and analyses open access. On our platform, large amounts of data can be combined with extensive analyses and used either privately, partially publicly or completely publicly. With FastResearch.io, data and models will be easily accessible and usable even for non-specialists, as data are modularly exchangeable and users do not need to build their own environments to use the models. While a curated software environment is offered for R and Python, users can also use customized environments (docker images) due to the modular and containerized infrastructure, which allows coding in any programming language. The great advantage of FastResearch.io compared to other platform solutions is that data and analyses connected to these data are stored together within a working software environment, which ends consistency problems in collaborative projects forever.

Plastics accumulate in the environment due to inadequate waste management, and the durability of the material. A better understanding of fundamental plastic behaviour in the aquatic environment is essential to estimate transport and accumulation, which can be used for monitoring, prevention and reduction strategies. An important process for fate models is the vertical transport of particles, for which the rising and settling velocity are crucial variables. Several studies have described these for microplastics (0.5 cm) however, such data are scarce. In this study, the rising and settling behaviour of three polymer types (PET, PP, and PE) commonly found in the environment was investigated. The plastic particles were foils of different sizes and shapes. A new method for releasing rising plastics without interfering the flow and disturbing the column was used. Observational data were used to test the performance of four models, including one developed in this study, for estimating the settling and rising velocity based on the properties of the plastic particles. These models were validated using the data obtained in this study, as well as data from another study on plastic rising and settling rates. The newly introduced foil velocity model gave the best results (R² = 0.96 and 0.29 for both data sets, respectively). This model has the potential to estimate the rising and settling velocity of plastic foils, and should be further investigated using additional observational data. The results of our work can be used to further explore the vertical distribution of plastics in rivers, lakes and oceans, which is crucial for improving future efforts to monitor and reduce plastics.

Microplastics are detected in most environmental compartments and hence receive a great deal of attention, especially in aquatic environments where rivers act as pathways for microplastics. Currently, a particularly high input of microplastics through Asian rivers is assumed predominantly by modelling data, while field measurements are scanty.Three rivers in South India were considered for this purpose to focus on their microplastic loads. The emphasis was on the comparison of microplastic concentrations in urban and rural rivers to identify if the anthropogenic influence control the loads. While two rivers in the megacity Chennai (Tamil Nadu) were found to have an average microplastic concentration of 0.4 microplastic particles/L, a rural river near Munnar (Kerala) had an average concentration of 0.2 microplastic particles/L. The results show higher loads in the urban area with a high anthropogenic influence by wastewater discharges and waste disposal through high number of residents dumping directly by the river. Fibres were the predominant shape (64.13%), black was the predominant particle colour (44.80%) and polyethylene and polyprolyene were the predominant polymers (each 46.67%) detected within the identified particles of all samples.Rough estimates of annual microplastic discharge from the Adyar River (Chennai) into the Bay of Bengal are found to be as high as 11.6 trillion microplastic particles. This study, which is one of the first baseline studies for microplastic loads in South Indian streams, should be complemented with further environmental sampling during pre-monsoon, monsoon and post-monsoon seasons to get more detailed information on the storage and transportation of fluvial microplastics and to understand the seasonal effect on the river flow characteristics as well as the fate of microplastics.

Bedform occurrence and geometry in sand-bedded rivers is traditionally predicted with phase diagrams and empirical equations, in which regional river characteristic are used. Field observations supporting these equations are often made in regions where bedform fields are known to be present and are spatially uniform. However, bedforms occurrence and geometry can vary significantly at the scale of the river width, limiting the applicability of bedform diagrams and questioning the objectivity of field study area selection. To enable the prediction of dune geometry, its spatial variability needs to be better understood. In this study, we aim to relate spatial variations in dune characteristic to grain size characteristics, river geometry, and local flow variation governed by the sub-bedform topography. We hypothesize that curvature-induced bars and pools drive local hydrodynamics, which in turn determine local dune characteristics. To test this hypothesis, bathymetric field data and sediment samples were collected in the fluvial-to-tidal-transition zone of the Fraser river, a sand-bedded lowland river in British Columbia, Canada. A 2D hydrodynamic model was created to explore the impacts of spatial variation in hydraulic conditions. We find that the cross-sectional variability in dune geometry is larger than the longitudinal variability, and that the transition of one type of dune field into another is abrupt rather than gradual. Phase diagrams do not capture these observations accurately. Local hydraulic conditions are more important in determining spatial variability in dune geometry than regional scale changes in river geometry, grain size variation and tidal influence. Dune height has an ambiguous relationship with river depth: the spatial variation in dune height depends on local shear stresses governed by the sub-bedform topography characterized by pools and troughs.