National audienceSediment transport modelling in shallow coastal waters is a challenging topic, especially in macrotidal environments where large intertidal areas are subjected to rapid wave transformation and breaking, complex patterns of tidal currents, and dynamic bedforms. Quantifying the sediment fluxes from the inner shelf to the shoreface is crucial to understand the long-term evolution of such embayements. The bay of Somme, facing the English Channel in North- West France, is a particularly relevant environment to tackle these issues. Known for its megatidal range (up to 10m in spring tides), it is in front of a large subtidal sediment source known as the Picard prism. The intertidal area, more than 6 km-wide, features highly dynamic dune fields and tidal channels. The aim of the study is to evaluate the sediment fluxes between the Picard prism and Bay of Somme using numerical modelling and in-situ observations. The first step is to build a numerical configuration which combines the hydrodynamic model CR OC O, the spectral wave model Wave Watch-III and the USGS sediment transport model. Three nested grids have been created (100m, 30m, 10m) that are forced at the boundaries by tide, wind, wave spectra and river input. Numerical results were tested against ADCP and tidal gauge data. The main conclusions are: i) the flow velocity and the sea surface height are in agreement with observations with a mean RMSE around 0.1m/s and 0.17m for current velocity and sea surface height, respectively ii) a time delay varying between 10 and 30 minutes is observed at some locations, iii) the contribution of the Somme River has very little influence on the results due the low flow discharge for the considered period, iv) the longshore current is well simulated by the coupled model. One of the main limitations of our modeling is due to a bathymetry that was not recorded at the same time as the measurements. Prospects for future work will be to add the USGS sediment transport model in the coupling and to simulate sediment fluxes