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
