| description abstract | Accurate measurement of bedload is challenging, considering its spatial and temporal variability. Various indirect acoustic techniques are often used for estimating the bedload rate and total bedload mass. Estimating the grain size distribution for a bedload event of relatively short duration, taking the smaller bedload particles into account, is difficult. In the current study, an impact plate with two sensors, namely, an accelerometer and a geophone, is tested in a laboratory flume. Available bedload grains are sorted into different grain size classes, and two sets of experiments are conducted. Single-grain/multigrain particles and mixed-grain particles are considered in the single-class and multiclass experiments, respectively. Three different grain mixtures with variable fineness are fed to the plate in the mixed-grain experiment. The present setup can detect bedload grains from 2.36 to about 150 mm, which is an improvement over other indirect methods. A hybrid analysis methodology to predict the grain size distribution using signals from both sensors is developed. The grain size distributions (GSDs) are estimated with a maximum deviation of 22%, which is expected to improve further with data from longer bedload events. | |
