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Microplastics (MPs) have been detected ubiquitously in fluvial systems and advective transfer has been proposed as a potential mechanism for the transport of (sub‐) pore‐scale MPs from surface waters into streambed sediments. However, the influence of particle and sediment properties, as well as the hydrodynamic flow regime, on the infiltration behavior and mobility of MPs in streambed sediments remains unclear. In this study, we conducted a series of flume experiments to investigate the effect of particle size (1–10 μm), sediment type (fine and coarse sand), and flow regime (high/low flow) on particle infiltration dynamics in a rippled streambed. Quantification of particles in the flume compartments (surface flow, streambed interface, and in the streambed) was achieved using continuous fluorescence techniques. Results indicated that the maximum infiltration depth into the streambed decreased with increasing particle size (11, 10, and 7 cm for 1, 3, and 10 μm). The highest particle retardation was observed in the fine sediment experiment, where 22% of the particles were still in the streambed at the end of the experiment. Particle residence times were shortest under high flow conditions, suggesting that periods of increased discharge can effectively flush MPs from streambed sediments. This study provides novel insights into the complex dynamics of MP infiltration and retention in streambed sediments and contributes to a better understanding of MPs fate in fluvial ecosystems. Quantitative data from this study can improve existing modeling frameworks for MPs transport and assist in assessing the exposure risk of MPs ingestion by benthic organisms. Plain Language Summary Microplastics (MPs) (small plastic particles) are present in river systems worldwide. The processes that lead to their transport and retention in rivers are not fully understood. Scientists have proposed that the infiltration of surface water into the streambed can carry MPs with it. In this study, we conducted experiments in a controlled environment that resembles a stream and its streambed. We investigated how different sizes of plastic particles (1, 3, and 10 μm), the types of sediment (fine and coarse sand), and water flow rates (low and high) affect how far particles travel in a streambed. We found that the size of MPs played a significant role in their depth of infiltration. Larger particles did not infiltrate as deeply as smaller particles, and were also retained in the streambed. Fine sand trapped particles for a longer time than coarse sand, and 22% of the particles remained in the streambed until the end of the experiment. Faster flowing water quickly removed MPs from the streambed. Our research helps understand how MPs spread in river systems and how long they remain in the streambed. The data can be used to improve transport models and assess the risk MPs pose to aquatic organisms. Key Points (Sub‐) Pore‐scale microplastics were advectively transferred from the surface water into the streambed sediments in flume experiments Infiltration patterns depend on microplastic size, streambed sediment type and surface flow velocities Microplastic retention was observed for 10 μm beads, 1 μm beads were considerably retarded in fine sediments

Although recent studies indicate that fluvial systems can be accumulation areas for microplastics (MPs), the common perception still treats rivers and streams primarily as pure transport vectors for MPs. In this study we investigate the occurrence of MPs in a yet unnoticed but essential compartment of fluvial ecosystems - the hyporheic zone (HZ). Larger MP particles (500–5,000 µm) were detected using attenuated total reflectance (ATR) - Fourier-transform infrared (FTIR) spectroscopy. Our analysis of MPs (500–5,000 µm) in five freeze cores extracted for the Roter Main River sediments (Germany) showed that MPs were detectable down to a depth of 0.6 m below the streambed in low abundances (≪1 particle per kg dry weight). Additionally, one core was analyzed as an example for smaller MPs (20–500 µm) with focal plane array (FPA)- based µFTIR spectroscopy. Highest MP abundances (~30,000 particles per kg dry weight) were measured for pore scale particles (20–50 µm). The detected high abundances indicate that the HZ can be a significant accumulation area for pore scale MPs (20–50 µm), a size fraction that yet is not considered in literature. As the HZ is known as an important habitat for invertebrates representing the base of riverine food webs, aquatic food webs can potentially be threatened by the presence of MPs in the HZ. Hyporheic exchange is discussed as a potential mechanism leading to a transfer of pore scale MPs from surface flow into streambed sediments and as a potential vector for small MPs to enter the local aquifer. MPs in the HZ therefore may be a potential risk for drinking water supplies, particularly during drinking water production via river bank filtration.

Most fluvial networks worldwide include watercourses that recurrently cease to flow and run dry. The spatial and temporal extent of the dry phase of these temporary watercourses is increasing as a result of global change. Yet, current estimates of carbon emissions from fluvial networks do not consider temporary watercourses when they are dry. We characterized the magnitude and variability of carbon emissions from dry watercourses by measuring the carbon dioxide (CO2) flux from 10 dry streambeds of a fluvial network during the dry period and comparing it to the CO2 flux from the same streambeds during the flowing period and to the CO2 flux from their adjacent upland soils. We also looked for potential drivers regulating the CO2 emissions by examining the main physical and chemical properties of dry streambed sediments and adjacent upland soils. The CO2 efflux from dry streambeds (mean +/- A SD = 781.4 +/- A 390.2 mmol m(-2) day(-1)) doubled the CO2 efflux from flowing streambeds (305.6 +/- A 206.1 mmol m(-2) day(-1)) and was comparable to the CO2 efflux from upland soils (896.1 +/- A 263.2 mmol m(-2) day(-1)). However, dry streambed sediments and upland soils were physicochemically distinct and differed in the variables regulating their CO2 efflux. Overall, our results indicate that dry streambeds constitute a unique and biogeochemically active habitat that can emit significant amounts of CO2 to the atmosphere. Thus, omitting CO2 emissions from temporary streams when they are dry may overlook the role of a key component of the carbon balance of fluvial networks.

Most rivers exchange water with surrounding aquifers 1 , 2 . Where groundwater levels lie below nearby streams, streamwater can infiltrate through the streambed, reducing streamflow and recharging the aquifer 3 . These ‘losing’ streams have important implications for water availability, riparian ecosystems and environmental flows 4 – 10 , but the prevalence of losing streams remains poorly constrained by continent-wide in situ observations. Here we analyse water levels in 4.2 million wells across the contiguous USA and show that nearly two-thirds (64 per cent) of them lie below nearby stream surfaces, implying that these streamwaters will seep into the subsurface if it is sufficiently permeable. A lack of adequate permeability data prevents us from quantifying the magnitudes of these subsurface flows, but our analysis nonetheless demonstrates widespread potential for streamwater losses into underlying aquifers. These potentially losing rivers are more common in drier climates, flatter landscapes and regions with extensive groundwater pumping. Our results thus imply that climatic factors, geological conditions and historic groundwater pumping jointly contribute to the widespread risk of streams losing flow into surrounding aquifers instead of gaining flow from them. Recent modelling studies 10 have suggested that losing streams could become common in future decades, but our direct observations show that many rivers across the USA are already potentially losing flow, highlighting the importance of coordinating groundwater and surface water policy. Direct observations of 4.2 million wells across the USA indicate that many streams are potentially losing water to underlying aquifers.

Microbe-mediated reactions remove nitrogen from river water as it flows through sediments. Simulations of the Mississippi River network suggest that denitrification due to flow through small-scale river bedforms exceeds that along channel banks. Increasing nitrogen concentrations in the world’s major rivers have led to over-fertilization of sensitive downstream waters 1 , 2 , 3 , 4 . Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions 5 , 6 , 7 , 8 , 9 , 10 . However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater—hyporheic zones 8 , 11 , 12 . Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed—and thus vertical hyporheic exchange—would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering.

The permeability of sediments at the sediment–water interface is an important control on several stream ecosystem services. It is well known that streambed permeability varies over several orders of magnitude, however, the environmental processes influencing this variation have received little attention. This review synthesizes the state-of-art knowledge and gaps in our understanding of the key physical and biological processes which can potentially modify the streambed permeability. These processes include—(a) physical clogging due to fine sediments, (b) biological clogging due to microbial biomass, and (c) sediment reworking by in-stream fauna. We highlight that the role of biotic processes (bioclogging and sediment reworking processes) in modifying the streambed permeability has not been investigated in detail. We emphasize that complex feedback mechanisms exist between these abiotic and biotic processes, and an interdisciplinary framework is necessary to achieve a holistic understanding of the spatio-temporal variability in streambed permeability. To this end, we propose to develop a conceptual model for streambed evolution after a disturbance (e.g. floods) as this model could be valuable in comprehending the dynamics of permeability. We also outline the challenges associated with developing a widely applicable streambed evolution model. Nonetheless, as a way forward, we present a possible scenario for the evolution of a streambed following a high flow event based on the trajectory of responses of the above-mentioned environmental processes. Finally, we suggest future research directions that could assist in improving the fundamental understanding of the clogging and sediment reworking processes and consequently of the dynamics of streambed permeability.

Streambed biogeochemical processes strongly influence riverine water quality and gaseous emissions. These processes depend largely on flow paths through the hyporheic zone (HZ), the streambed volume saturated with stream water. Boulders and other macroroughness elements are known to induce hyporheic flows in gravel‐bed streams. However, data quantifying the impact of these elements on hyporheic chemistry are lacking. We demonstrate that, in gravel‐bed rivers, the amount of dissolved oxygen (DO) in the bed depends chiefly on changes in bed shape, or morphology, such as the formation of scour and depositional areas, caused by the boulders, among other factors. The study was conducted by comparing DO distributions across different bed states and hydraulic conditions. Our experimental facility replicates conditions observed in natural gravel‐bed streams. We instrumented a section in the bed with DO sensors. Results generally indicate that boulder placement on planar beds has some effects, which are significant at high base flows, on increasing hyporheic oxygen amount compared to the planar case without boulders. Conversely, boulder‐induced morphological changes noticeably and significantly increase the amount of oxygen in the HZ, with the increase depending on sediment inputs during flood flows able to mobilize the sediment. Therefore, streambeds of natural, plane‐bed streams may have deeper oxic zones than previously thought because the presence of boulders and the occurrence of flood flows with varying sediment inputs induce streambed variations among these elements.

Local thermal nonequilibrium (LTNE) effects in heterogeneous media can affect subsurface temperature distributions, as well as the capacity of the heat transport model to solve the inverse problem of estimating groundwater fluxes. We present a synthetic coupled flow and heat transport numerical model with five scenarios to analyze the influence of subsurface hydraulic and thermal property variations on heat transport in heterogeneous streambed sediments, while also evaluating the role of LTNE effects in heat transport processes within heterogeneous streambed sediments and their impact on streambed fluxes estimation. Heterogeneous streambed sediments with varying sand‐gravel‐clay fractions are stochastically generated using a Markov Chain model. Synthetic streambed temperature‐time series are produced to estimate effective thermal diffusivity and thermal front velocity using a heat transport model based on homogeneous and local thermal equilibrium assumptions, and these estimates were compared to known values from numerical models of flow fields analogous to losing streams. Results show that neglecting thermal heterogeneity in streambed sediments leads to significant errors in streambed fluxes estimation, where the effective thermal diffusivity can be underestimated by about 40%, while the thermal front velocity can be overestimated by more than two times. In addition to the effects of streambed heterogeneity, LTNE effects further amplify these errors. Furthermore, the influences of streambed heterogeneity on LTNE effects are primarily influenced by flow velocity, with higher clay content reducing Darcian velocity and weakening LTNE effects.

Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined. Plain Language Summary Streambed grain sizes control river hydro‐biogeochemical function by modulating the resistance, speed of water exchange, and nutrient transport at water‐sediment interface. Consequently, quantifying grain sizes and size‐dependent hydro‐biogeochemical parameters is critical for predicting river's function. In natural streams, measuring these sizes and parameters, however, is challenging because grain sizes vary from millimeters to a few meters, change from small creeks to big streams, and could be concealed by complex non‐grain materials such as water, ice, mud, and grasses. All these factors make the size measurements a time‐consuming and high‐uncertain task. We address these challenges by demonstrating a workflow that combines computer vision artificial intelligence (AI), smartphone photos, and new uncertainty quantification theories. The AI performs well across various sizes, locations, and stream environments as indicated by an accuracy metric of 0.98. We apply the AI to extract the grain sizes and their characteristic percentiles for 1,999 photos. These characteristic grain sizes are then input into existing and our new theories to derive the quantities, distributions, and uncertainties of hydrobiogeochemical parameters. The high accuracy of the AI and the success of extracting grain sizes and hydro‐biogeochemical parameters demonstrate the potential to advance river science with computer vision AI and mobile devices. Key Points Stream sediments bigger than 44 microns can be detected from smartphone photos by You Only Look Once with a Nash–Sutcliffe efficiency of 0.98 Quantities, distributions, and uncertainties of streambed grain sizes can be determined from photos Impact of grain size uncertainty on hydrobiogeochemical parameters is examined

Quantification of groundwater (GW) and surface water (SW) interactions is crucial for effective water resource allocation and management. Immense progress has been made in the past few decades to address the different aspects of GW–SW exchanges. These have resulted in a large volume of literature. This work reviews in detail the mechanism of interaction and the applications of different field and modelling techniques. The review of flux quantification methods identifies the streambed and the aquifer beneath as two major components affecting the interactions. It is observed that the streambed is highly idealised in modelling studies, and the significance of aquifer properties in the flux quantification is found to be less emphasised. Therefore, attempts are made to highlight the potential significance of both streambed and the aquifer properties through a 2D numerical experiment. Using a superimposed GW–SW system and appropriately grouping the system parameters (as hydraulic and geometric), the experiment shows that the aquifer properties can dominate exchanging flux under certain conditions, e.g., at higher streambed conductance. The work provides suggestions to modify the widely used Darcy’s approach to include aquifer properties.