![]() ![]() This is particularly true for bedload transport formulae, where there is a scarcity of reliable field data to test them, as well as knowledge gaps around the dynamics of individual particles (particularly rolling dynamics) during bedload transport. However, they are primarily empirical and often have poor predictive performance when extended to conditions outside those to which they were ‘fit’. Over the last two centuries many sediment transport formulae have been developed. The accurate quantification of sediment transport processes is crucial for predicting river geometry, gravel resources, erosion, coastal replenishment, bridge integrity, flood hazards, substrate size distributions, instream habitats, reservoir sedimentation, and river evolution following restoration. In particular, sediment transport is responsible for the formation of alluvial plains and basins that provide terrain well suited to human habitation and agriculture. Tectonic activity, weathering, erosion, and sediment transport are key processes that shape the landscapes of the Earth. Although designed for measurement of coarse bedload transport and particle dynamics during floods, the sensors are equally applicable for deployment in other harsh environments, such as to study landslide and rockfall dynamics. This paper covers the technical development of the sensors, mounting them inside stones, and field recovery tests. Firmware to control the sensors and relay units was developed, as well as software for configuring the sensors and an android application for communicating with the sensors via the LoRa radio transmission module. Novel relay units and drone-based recovery systems were also developed for finding the sensors after field deployments. The sensors are enclosed in rugged waterproof housings for deployment in extreme conditions (i.e., bedload transport during floods). The sensors feature a 9-axis inertial measurement unit, 3-axis high-g accelerometer, 128 MB flash memory, and a 433 MHz LoRa radio transmission module for sensor recovery. To address this challenge rugged sensors (Kinematic Loggers) were developed for deployment inside stones (ranging in size from cobbles to boulders) during floods. ![]() Sensors must be waterproof and recoverable after being transported downstream and potentially buried by other sediment. A promising approach to address this knowledge gap is to use sensors embedded within stones. Discrete particle dynamics is one of the least understood aspects of river bedload transport, but in situ measurement of stone movement during floods poses a significant technical challenge. ![]()
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