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Sediment transport controls the evolution of river channels, playing a fundamental role in physical, ecological, and biogeochemical processes across a wide range of spatial and temporal scales on the Earth surface. However, developing predictive transport models from first principles and understanding scale interactions on sediment fluxes remain as formidable research challenges in fluvial systems. Here we simulate the smallest scales of transport using direct numerical simulations (DNS) to explore the dynamics of bed-load and discover how turbulence and grain-scale processes influence transport rates, showing that their interplay gives rise to a critical regime dominated by fluctuations that propagate across scales. These connections are represented using a stochastic differential equation, and a statistical description through a path integral formulation and Feynman diagrams, thus providing a framework that incorporates nonlinear and turbulence effects to model the dynamics of bed-load across scales. [ABSTRACT FROM AUTHOR]

As tools and techniques to measure experimental granular flows become increasingly sophisticated, there is a need to rigorously assess the validity of the approaches used. This paper critically assesses the performance of particle image velocimetry (PIV) and particle tracking velocimetry (PTV) for the measurement of granular flow properties. After a brief review of the PIV and PTV techniques, we describe the most common sources of error arising from the applications of these two methods. For PTV, a series of controlled experiments of a circular motion is used to illustrate the errors associated with the particle centroid uncertainties and the linear approximation of particle trajectories. The influence of these errors is then examined in experiments on dry monodisperse granular flows down an inclined chute geometry. The results are compared to those from PIV analysis in which errors are influenced by the size of the interrogation region. While velocity profiles estimated by the two techniques show strong agreement, second order statistics, e.g. the granular temperature, display very different profiles. We show how the choice of the sampling interval, or frame rate, affects both the magnitude of granular temperature and the profile shape determined in the case of PTV. In addition, the determined magnitudes of granular temperature from PIV tends to be considerably lower when directly measured or largely overestimated when theoretically scaled than those of PTV for the same tests, though the shape of the profiles is less sensitive to frame rate. We finally present solid concentration profiles obtained at the sidewalls and and examine their relationship to the determined shear rate and granular temperature profiles. [ABSTRACT FROM AUTHOR]