Improving the Calibration of Impact Plate Bedload Monitoring Systems by
Filtering Out Acoustic Signals from Extraneous Particle Impacts
Abstract
The spatio-temporal variability of bedload transport processes poses
considerable challenges for bedload monitoring systems. One such system,
the Swiss plate geophone (SPG), has been calibrated in several
gravel-bed streams using direct sampling techniques. The linear
calibration coefficients linking the signal recorded by the SPG system
to the transported bedload can vary between different monitoring
stations by about a factor of six, for reasons that remain unclear.
Recent controlled flume experiments allowed us to identify the
grain-size distribution of the transported bedload as a further
site-specific factor influencing the signal response of the SPG system,
along with the flow velocity and the bed roughness. Additionally, impact
tests performed at various field sites suggested that seismic waves
generated by impacting particles can propagate over several plates of an
SPG array, and thus potentially bias the bedload estimates. To gain an
understanding of this phenomenon, we adapted a test flume by installing
a partition wall to shield individual sensor plates from impacting
particles. We show that the SPG system is sensitive to seismic waves
that propagate from particle impacts on neighboring plates or on the
concrete bed close to the sensors. Based on this knowledge, we designed
a filter method that uses time-frequency information to identify and
eliminate these “apparent” impacts. Finally, we apply the filter to
four field calibration datasets and show that it significantly reduces
site-to-site differences between calibration coefficients and enables
the derivation of a single calibration curve for total bedload at all
four sites.