The Swiss plate geophone is a bedload surrogate monitoring system that has been calibrated in several gravel-bed streams using direct sampling techniques.Past systematic flume experiments have highlighted the dependency of the signal response on the bed roughness and the flow velocity. To further develop the
The dimensional analysis of the backwater effect caused by debris jams results in the Froude number of the approach flow in the initial situation prior to debris jam formation and the debris density as decisive parameters. For the more precise detection of the influence of both parameters the results of different hydraulic model test series at the Laboratory of Hydraulic and Water Resources Engineering of the Technical University of Munich concerning debris jams at spillways as well as at racks for the retention of wooden debris were uniformly evaluated. On the one hand a significant increase of the backwater effect with a rising Froude number of the approach flow could be shown. This is in good correlation to recent test results for debris jams at retention racks at the Laboratory of Hydraulics, Hydrology and Glaciology of the Swiss Federal Institute of Technology Zurich. On the other hand a significant increase of the backwater effect could also be shown for a rising debris density. However, the test results also show that significantly different backwater effects can occur in different test runs with identical test conditions. These differences are a result of the randomness of debris jam development, and therefore, a more exact quantification of the dependence of the backwater effect on the Froude number of the approach flow and on the debris density is not considered useful for the present results.
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 despite isolating elements. 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.
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