Advances in River Bedload Tracking Technology: Self-righting Radio Frequency Identification Tracers and an In-stream Automated Station
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Understanding of bedload transport rates in natural streams has been an area of focus for researchers for decades. Recently, researchers have begun to use Radio Frequency Identification (RFID) technology to track individual particles. The application of RFID technology allows for the classification of movement of individual clasts while increasing recovery rate of tracers particles. Small glass cylinders hold a copper coil around a ferrite rod which allows the tag to communicate a unique identification code to an antenna. The unique identification code allows researchers to analyze individual particle movement in a manner which was not possible prior to RFID technology. Despite the popularity, there are still improvements to be made to the technology and methodology of tracking RFID-tagged tracers. Existing tracking methods include manually walking the streambed between flood events with an antenna, while flagging and marking tracers which have been detected. This method only provides inter-flood data while also being extremely time consuming. Additionally, the detection range of RFID tags can be highly variable depending on the orientation of the tag. Vertical tags produce a circular detection range while horizontal tags have a much smaller detection range, shaped like a peanut with two lobes. Inconsistency in detection range limits the ability to accurately locate a tracer’s position while decreasing recovery rates. The goal of this research is to advance RFID technology in two manners: develop a customized system of tracking RFID tracers during a flood event and develop a method for ensuring consistent detection range in RFID tags. The first goal is accomplished by designing a stationary antenna array system to be installed into the bed of the stream to detect tracers as they move over-top during a flood event. The system automatically records the tracer movement allowing for in-depth analysis of the timing of particle movement during a flood event. The second goal is accomplished through the design of the “Wobblestone”, a unique and innovative product to ensure a consistent detection range while increasing the viability of smaller RFID tags for field studies. A case study was performed at Schneider Creek in Kitchener, Ontario. Schneider Creek was previously a concrete channel which was recently restored to a natural channel. This case study includes seeding and inter-flood tracking of RFID-tagged particles and field testing of the customized stationary antenna array.
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Christopher Muirhead (2018). Advances in River Bedload Tracking Technology: Self-righting Radio Frequency Identification Tracers and an In-stream Automated Station. UWSpace. http://hdl.handle.net/10012/13929