Uwe Schneidewind

In rivers, small and lightweight microplastics are transported downstream, but they are also found frequently in riverbed sediment, demonstrating long-term retention. To better understand microplastic dynamics in global rivers from headwaters to mainstems, we developed a model that includes hyporheic exchange processes, i.e., transport between surface water and riverbed sediment, where microplastic retention is facilitated. Our simulations indicate that the longest microplastic residence times occur in headwaters, the most abundant stream classification. In headwaters, residence times averaged 5 hours/km but increased to 7 years/km during low-flow conditions. Long-term accumulation for all stream classifications averaged ~5% of microplastic inputs per river kilometer. Our estimates isolated the impact of hyporheic exchange processes, which are known to influence dynamics of naturally occurring particles in streams, but rarely applied to microplastics. The identified mechanisms and time scales for small and lightweight microplastic accumulation in riverbed sediment reveal that these often-unaccounted components are likely a pollution legacy that is crucial to include in global assessments.

Detailed information on the spatial structure of hydraulic conductivity ( K ) is important for understanding and predicting groundwater flow and transport. Direct‐push injection logging (DPIL) is a promising technology for rapid measurement of K in unconsolidated formations. This technology was used to gain information on the highly heterogeneous aquifer at the Lauswiesen test site in Germany. Using a large body of DPIL and direct‐push slug testing measurements, we characterize the structure of K on scales not previously possible. Two new applications of DPIL are put forward: (1) use of raw DPIL measurements of relative conductivity K r to characterize the spatial distribution of K and (2) transformation of K r measurements to K values based on their statistical moments. The DPIL results are compatible to those obtained using more conventional methodologies. The main achievement of the methodology is the possibility to delineate deterministic aquifer subunits as well as the identification of the statistical parameters of the log conductivity for each subunit. In particular, the horizontal integral scale I , a parameter affecting solute transport, is difficult and costly to identify using other approaches. Nevertheless, further studies are needed to clarify questions on low K r measurements and the nature of the relationship between K r and K .

Abstract An overview of the current state of knowledge on the pollution of agricultural soils with microplastic and nanoplastic (MnP) particles is provided and the main MnP sources are discussed. MnP transport mechanisms from soil to groundwater, as well as the potential impact of MnPs on soil structure are considered, and the relevance of co-contaminants such as agrochemicals is further highlighted. We elaborate on why MnPs in soil and groundwater are understudied and how analytical capabilities are critical for furthering this crucial research area. We point out that plastic fragmentation in soils can generate secondary MnPs, and that these smaller particles potentially migrate into aquifers. The transport of MnP in soils and groundwater and their migration and fate are still poorly understood. Higher MnP concentrations in agricultural soils can influence the sorption behavior of agrochemicals onto soil grains while attachment/detachment of MnPs onto soil grains and MnP-agrochemical interactions can potentially lead to enhanced transport of both MnP particles and agrochemicals towards underlying groundwater systems.

Abstract The use of temperature‐time series measured in streambed sediments as input to coupled water flow and heat transport models has become standard when quantifying vertical groundwater‐surface water exchange fluxes. We develop a novel methodology, called LPML, to estimate the parameters for 1‐D water flow and heat transport by combining a local polynomial (LP) signal processing technique with a maximum likelihood (ML) estimator. The LP method is used to estimate the frequency response functions (FRFs) and their uncertainties between the streambed top and several locations within the streambed from measured temperature‐time series data. Additionally, we obtain the analytical expression of the FRFs assuming a pure sinusoidal input. The estimated and analytical FRFs are used in an ML estimator to deduce vertical groundwater‐surface water exchange flux and its uncertainty as well as information regarding model quality. The LPML method is tested and verified with the heat transport models STRIVE and VFLUX. We demonstrate that the LPML method can correctly reproduce a priori known fluxes and thermal conductivities and also show that the LPML method can estimate averaged and time‐variable fluxes from periodic and nonperiodic temperature records. The LPML method allows for a fast computation of exchange fluxes as well as model and parameter uncertainties from many temperature sensors. Moreover, it can utilize a broad frequency spectrum beyond the diel signal commonly used for flux calculations.