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SNF Project: Sediment transport measurements with geophone sensor
To increase our understanding in bedload transport processes in steep streams, it is necessary to monitor it as accurate as possible. We can classify bedload monitoring methods in two main branches: direct and indirect methods. Typical direct methods include trapping sediment (i.e. retention basin), collecting moving particles (i.e. Helley-Smith samplers) and using tracer particles (i.e. Radio-frequency identification RFID). The promising advantage of indirect sensors (active and passive) is that they can provide high-resolution and continuous measurements of the transport intensity. The signal characteristics from these sensors can be related to the bedload. The registered signal depends firstly on the sensor’s type and sensitivity and secondly on the in-situ hydraulic conditions and the transported grain properties which mean that the calibration of these systems is necessary in order to obtain absolute bedload transport rates.
The Erlenbach stream in Alptal (figure 1 and 2) is one of the Swiss Federal
Research Institute WSL catchments were Bedload transport observations are
available since 1982. ObjectivesIn 1999 the piezoelectric bedload impact sensors (PBIS) were replaced by geophone sensors (fsampling = 10'000 [Hz]). Previous studies have demonstrated that the signal created by the kinetic impacts of bedload material registered by the geophone over an impact plate is a possible way to quantify bedload transport (The number of impulses per unit time being proportional to the total bedload volume of an event). The device calibration clearly depends on site specific variables such as the grain distribution, material density and flow characteristics.
The project aims to identify the main factors influencing the response of the geophone sensor and to determine which aspects of calibration can be generalized in un-calibrated field sites. Further on, the possibility to extract grain size information from the geophone measurements will be explored (acoustic signal analysis).
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