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.