### Lagrangian Observations of Transport Processes Facilitated via Novel Sensing Tools  
Flow sensing and transport processes monitoring and instrumentation have gained increasing attention following the relatively recent technological advancements in the field of micro-electromechanical sensors (MEMS) that make it possible to record Lagrangian observations of individual sediment particles [39; 40; 41; 42; 43; 44; 45] and shed light on the dynamics of sediment transport processes at an extraordinary resolution and with high precision fused inertial measurement units, IMUs (e.g., via the use of robust and accurate accelerometers, gyroscopes, and magnetometers) [46; 47; 48]. Instrumented particles with a range of such sensors can be placed on the riverbed surface to simulate the response of light natural pebbles, exposed to a flow field that can set these into motion downstream a river. The main data logged are the components of particle accelerations in the particle's local coordinate system as well as angular displacements around these. As with all electronics, limitations of such devices revolve around the duration; they can be autonomously powered before a need to recharge or change a power source. This has not been an issue for controlled lab experiments, but it may become a constraint for long periods of field deployment, affecting the useful logging durations that can be achieved or requiring a compromise in terms of the number and frequency of data being logged. Novel miniaturized instrumented particles equipped with high precision accelerometer and gyroscope sensors have also  
Figure 2: Demonstration of the dominant above-threshold hydrodynamic forcing modes for a particle hopping out of its pocket, leading to transport by saltation. Hydrodynamic impulse is defined as the temporal integral of the total force acting on the particle. This can primarily be the hydrodynamic drag (\(F_{D}\)), lift (\(F_{L}\)), or a combination of both forces, for the cases of a particle fully exposed, partially hidden, and buried in the bed surface (shown in green, orange, and red, respectively).  
been developed, recording time series of acceleration and angular displacement, finding application for the monitoring of bed surface destabilization [47; 49], and monitoring low mobility bedload transport conditions [48].  
Given the highly dynamic and relatively intermittent character of saltating particles inherited by turbulent flows just above the threshold of incipient motion and the randomness of particle properties (such as size and shape) and local microtopography properties (bed surface particles' arrangement and packing), as well as the complex particle/particle and fluid/particle interactions during transport by hopping [37]. The statistical description of sediment transport by using probability distributions is useful due to extensive temporal and spatial irregularity of the factors which control it, such as local grain geometry, relative grain exposure, friction angle, and bed surface packing conditions [37; 50]. Researchers [13; 37; 51; 52; 53; 54] have studied sediment transport in a probabilistic context and attempted to relate it to the hydrodynamic properties of turbulent flows, while considering sediment transport at the particle scale. As a universally accepted criterion that robustly explains this dynamical process and stochasticity does not yet exist, the stochastic description of sediment transport dynamics at a high resolution using MEMS appears to be attractive [48].