The state-of-the-art in depth-averaged mathematical modelling of 3-D coastal morphology is described for the medium-term morphodynamic model type, in which constituent models of waves, currents and sediment transport based on first physical principles are linked together to describe the time-evolution of the bed topography. Various aspects of the combined system of equations are discussed, such as its mathematical character, its inherent stability and its equilibrium state. The results of an intercomparison of different models are shown for two test cases and the potentials and limitations of the model concept are discussed.
As a part of the MAST2 GS-M Coastal Morphodynamics project, the predictions of four sediment transport models have been compared with detailed laboratory data sets obtained in the bottom boundary layer beneath regular waves, asymmetrical waves, and regular waves superimposed co-linearly on a current. Each data set was obtained in plane bed, sheet flow, conditions and each of the four untuned numerical models has provided a one-dimensional vertical (lDVj, time-varying, representation of the various experimental situations. Comparisons have been made between the model predictions and measurements of both time-dependent sediment concentration, and also wave-averaged horizontal velocity and concentration. For the asymmetrical waves and for the combined wave-current flows, comparisons have been made with vertical profiles of the cycle-averaged sediment flux, and also with the vertically-integrated net sediment transport rate. Each of the turbulence diffusion models gives an accurate estimate of the net transport rate (invariably well within a factor of 2 of the measured value). In contrast, none of the models provides a good detailed description of the time-dependent suspended sediment concentration, due mainly to the inability of conventional turbulence diffusion schemes to represent the entrainment of sediment into suspension by convective events at flow reversal. However, in the cases considered here, this has not seriously affected the model predictions of the net sediment flux, due
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.