Innovative Sensors for Measuring Large Wood (LW) Movement Dynamics in Rivers
Abstract
Large wood (LW) plays an import yet critical role in fluvial systems. The sudden occurrence of LW during floods often yields disastrous consequences. In order to better control for LW in transit, but also to mitigate the formation of massive accumulations at critical river cross-sections (e.g. bridges), a better understanding of LW movement dynamics is required. In the course of the SmartWood_3D research project at the Laboratory of Hydraulics, Hydrology and Glaciology ETH Zurich, innovative inertial measurement units (IMUs) are deployed in prototype wood logs, so called SmartWood. Each nine-degree of freedom (9-DoF) IMU comprises an accelerometer, gyroscope, and magnetometer that allow the capture of movement dynamics at high resolution. In addition, two external GPS-modules approximate the georeferenced location of SmartWood. The sensor-units function within an isolated Lagrangian system, storing measured data fully synchronized in time at an onboard memory. Communication with the sensors as well as data transfer takes place via WiFi-connection. Sensor dimensions are therefore dominated by the size of the reception antenna and battery, resulting in a total length of roughly 150 mm and 10 mm in diameter. Gained sensor data contain invaluable information about mobilization, transport and depositional processes. In combing all 9-DoF data by means of sensor fusion, SmartWood orientation and velocity can be calculated for any point in time. Thus, SmartWood shows great potential for allowing novel insights into LW movement dynamics, where traditional methods cannot yield satisfactory results, such as providing a fully resolved 3D transport trajectory of SmartWood on its journey downstream. Gained knowledge from SmartWood deployment in the field will help in the design of effective LW diversion and retention structures but also contribute to an improved process understanding of LW movement dynamics.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMEP55B1114S