The realization of hydromorphologic laboratory experiments on the propagation of aggrading or degrading sediment fronts requires simultaneous measurements of the sediment feeding rate, the profile of the free surface, and the flume bed elevation. In this study, five action cameras and different image-processing techniques were employed to measure all the needed quantities automatically and with adequate temporal resolution. The measurement of the sediment feeding rate was determined by particle image velocimetry as a surrogate, correlated quantity: the surface velocity of the sediment flow along a vibrating channel was used as an upstream feeder. The profile of the free surface was measured by shooting an array of piezometers connected to the flume. Each piezometer pipe contained a buoyant black sphere that could be recognized by using tools for particle identification, thus determining the elevation of the free surface above the piezometric probe. Finally, the bed profile along the flume was measured at any instant by edge detection, locating the transition from a water layer to a sediment layer in images taken from the side of the flume. The paper describes the instrumentation and the methods, finally presenting the results obtained from a prototypal experiment. Potentialities and limitations of the proposed methods are discussed, together with some prospects on future use in systematic experimental campaigns.

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This communication explores the use of numerical modelling to simulate the hydro-morphologic response of a laboratory flume subject to sediment overloading. The numerical model calibration was performed by introducing a multiplicative factor in the Meyer–Peter and Müller transport formula, in order to achieve a correspondence with the bed and water profiles recorded during a test carried out under a subcritical flow regime. The model was validated using a second subcritical test, and then run to simulate an experiment during which morphological changes made the water regime switch from subcritical to supercritical. The “relationship” between physical and numerical modelling was explored in terms of how the boundary conditions for the two approaches had to be set. Results showed that, even though the first two experiments were reproduced well, the third one could not be modeled adequately. This was explained considering that, after the switch of the flow regime, some of the boundary conditions posed into the numerical model turned out to be misplaced, while others were lacking. The numerical modelling of hydro-morphologic processes where the flow regime is trans-critical in time requires particular care in the position of the boundary conditions, accounting for the instant at which the water regime changes.

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