[1] The contamination of riverbeds by solutes derived from the surface flow has recently received increasing attention. Channel morphological features such as bed forms are important characteristics of the stream-subsurface interface and represent one control on the rate of solute delivery from the stream to the bed. Generally, larger bed forms are expected to produce greater rates of stream-subsurface exchange. However, the longitudinal dimension (wavelength) of the bed form is also important, and this effect can produce penetration patterns that may be unexpected from a visual observation of the bed surface. Experimental tests in a recirculating flume demonstrate these effects. Commonly used mathematical models do not consider the bed form geometry explicitly and depend on the availability of calibration data to derive exchange parameters for each stream reach. More detailed models that consider the effect of bed form shape are capable of simulating some of the observed experimental results. However, existing physically based models are shown to be insufficient for some bed form geometries that may occur in real streams.INDEX TERM: 1871 Hydrology: Surface water quality; KEYWORDS: solute transport, hyporheic, river contamination Citation: Marion, A., M. Bellinello, I. Guymer, and A. Packman, Effect of bed form geometry on the penetration of nonreactive solutes into a streambed, Water Resour.

River ecosystems are influenced by contaminants in the water column, in the pore water and adsorbed to sediment particles. When exchange across the sediment‐water interface (hyporheic exchange) is included in modeling, the mixing coefficient is often assumed to be constant with depth below the interface. Novel fiber‐optic fluorometers have been developed and combined with a modified EROSIMESS system to quantify the vertical variation in mixing coefficient with depth below the sediment‐water interface. The study considered a range of particle diameters and bed shear velocities, with the permeability Péclet number, PeK between 1000 and 77,000 and the shear Reynolds number, Re*, between 5 and 600. Different parameterization of both an interface exchange coefficient and a spatially variable in‐sediment mixing coefficient are explored. The variation of in‐sediment mixing is described by an exponential function applicable over the full range of parameter combinations tested. The empirical relationship enables estimates of the depth to which concentrations of pollutants will penetrate into the bed sediment, allowing the region where exchange will occur faster than molecular diffusion to be determined.

[1] An awareness of mixing processes is imperative in understanding the transport of pollutants in open channel flows, important for environmental impact studies. To date, controlled laboratory studies of the effects of vegetation on mixing processes have used simulated plants. This may neglect some of the important variables introduced by the presence of natural vegetation. In this study natural vegetation was planted within a laboratory channel, and a series of experiments quantifying velocity, turbulence, and longitudinal mixing were conducted over a time period sufficient to allow growth of the vegetation to impact on the mixing processes. In emergent conditions the results generally confirmed previous artificial vegetation and modeling studies, showing that vegetation reduces the magnitude of longitudinal shear dispersion. Additionally, measureable change in longitudinal mixing was observed primarily as a function of flow depth but also of plant age. Normalization using previously suggested parameter combinations failed to yield predictive trends. Submerged tests uniquely covered natural vegetation with a significant wake zone, and from this it was observed that longitudinal mixing is primarily a function of the degree of submergence. Overall, this paper presents a new data set quantifying the effects of natural vegetation on longitudinal mixing processes and illustrating deficiencies in previous understanding and predictive expressions based on idealized artificial vegetation.

[1] Prediction of the physical transport and mixing of pollutants or other soluble material is crucial for effective river management. Although well established methods exist which describe mixing processes in open channel flow, the presence of vegetation has a significant impact on mixing and few existing techniques account for this. To date, existing models which predict longitudinal dispersion coefficients in vegetated open channel flow have been derived and verified based on experiments conducted in simulated vegetation. This paper presents observations of longitudinal dispersion coefficients in a channel featuring living vegetation and tests against both an existing and a newly proposed model for longitudinal dispersion coefficient in submerged vegetated open channel flow. A model based on a mathematical technique of predicting dispersion in plain shear flow is shown to be capable of predicting longitudinal dispersion coefficients to within 20%.

Understanding solute mixing within real vegetation is critical to predicting and evaluating the performance of engineered natural systems such as storm water ponds. For the first time, mixing has been quantified through simultaneous laboratory measurements of transverse and longitudinal dispersion within artificial and real emergent vegetation. Dispersion coefficients derived from a routing solution to the 2‐D Advection Dispersion Equation (ADE) are presented that compare the effects of vegetation type (artificial, Typha latifolia or Carex acutiformis) and growth season (winter or summer). The new experimental dispersion coefficients are plotted with the experimental values from other studies and used to review existing mixing models for emergent vegetation. The existing mixing models fail to predict the observed mixing within natural vegetation, particularly for transverse dispersion, reflecting the complexity of processes associated with the heterogeneous nature of real vegetation. Observed stem diameter distributions are utilized to highlight the sensitivity of existing models to this key length‐scale descriptor, leading to a recommendation that future models intended for application to real vegetation should be based on probabilistic descriptions of both stem diameters and stem spacings.

Water Distribution Networks (WDNs) are critical infrastructures that ensure safe drinking water. One of the major threats is the accidental or intentional injection of pollutants. Data collection remains challenging in underground WDNs and in order to quantify its threat to end users, modeling pollutant spread with minimal sensor data is can important open challenge. Existing approaches using numerical optimisation suffer from scalability issues and lack detailed insight and performance guarantees. Applying general data-driven approaches such as compressed sensing (CS) offer limited improvements in sample node reduction. Graph theoretic approaches link topology (e.g. Laplacian spectra) to optimal sensing locations, it neglects the complex dynamics.In this work, we introduce a novel Graph Fourier Transform (GFT) that exploits the low-rank property to optimally sample junction nodes in WDNs. The proposed GFT allows us to fully recover the full network dynamics using a subset of data sampled at the identified nodes. The proposed GFT technique offers attractive improvements over existing numerical optimisation, compressed sensing, and graph theoretic approaches. Our results show that, on average, with nearly 30-40% of the junctions monitored, we are able to fully recover the dynamics of the whole network. The framework is useful beyond the application of WDNs and can be applied to a variety of infrastructure sensing for digital twin modeling.

A small-scale physical modelling method was developed to study the movement of clay during pile installation. The clay was simulated using a mixture of amorphous silica and mineral oil, which becomes almost transparent when the refractive indices of the oil and the silica are well matched. After adding reflective particles and consolidating the mixture in a transparent container, cylindrical model piles were driven vertically at the centre. A vertical section aligned with the pile centreline was illuminated by a laser light sheet, and a sequence of digital images was recorded. These were analysed using particle image velocimetry, and the complete displacement distribution during the pile installation was obtained. Notwithstanding some discrepancies at shallow depths, the observed displacements generally showed fairly good agreement with the theoretical predictions of the shallow strain path method (SSPM) once the effect of some soil trapped beneath the flat pile tip was taken into account. Normalisation of the horizontal and vertical components of movement employing both the pile length and radius, based on SSPM theory, was shown to be valid. The normalised vertical displacement contours were similar to those published by previous researchers. The results of this study could be used to assess the impact of disturbance due to pile installation on, for example, buried services or archaeology.

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