Assessing the vulnerability of coastal systems to storms often rely on an accurate modelling of extreme events and the identification of their impacts that depend on their physical characteristics. This requires the development of an exhaustive numerical downscaling of extreme hydrodynamics from deep to shallow areas to enhance our ability to predict the risks induced by these events, which is of fundamental importance for coastal managers. This work aims at investigating the nearshore dynamics of extreme events and their evolution from the shelf seas of the English Channel to the Normandy Coasts by developing a new numerical field of wave and sea level simulations during a period of 40 years. This dataset has been explored for the classification of extreme events considering their severity, direction, and duration. The overall results highlighted that more than 90% of the storms are coming from the Atlantic Ocean with a substantial change in their amplitude and their duration along the Channel: storms with Northern component are more severe while those coming from the South last longer with higher energy. A detailed monitoring of three different storm events exhibited that their impact depends on their travelling direction, being more significant for hydrodynamic events propagating following the orientation of the Channel, of about 70 degrees to the North, with lower diffraction. Extreme events coming from South Atlantic experience a stronger wave modulation when they arrive nearshore.

This research was carried out in the framework of the Surface Water and Ocean Topography (SWOT) program of the French National Centre of Space Studies (CNES). In the context of global climate change, increases in frequency and intensity of extreme events are considered potential threats. Hence, many efforts have been devoted to acquiring a better understanding of the natural processes driving the hydrodynamics’ multiscale variability in order to produce a more accurate estimation of their fluctuations. In this situation, and in the framework of Normandy’s coastal risk management, the dynamics of extreme events were investigated from regional scales (the English Channel basin) to local scales (the Normandy beaches in Etretat and Hautot-sur-Mer). Offshore wave data were obtained and hourly wave data were simulated for two years using the SWAN (Simulating WAves till Nearshore) model, including ten highly energetic stormy events selected by their different physical characteristics. Spectral analysis was conducted to compare the transformation in frequencies of the wave spectra from the Channel to shallow waters. A special focus was given to the hydrodynamics close to Normandy during these extreme events depending on their duration, their strength, and the persistence of the maximum wave height.

This study delves into the morphodynamic changes of pebble beaches in response to storm events, employing a combination of observational and numerical approaches. This research focuses on three extreme events, meticulously examining morhological changes in intertidal topography on the beach of Etretat (Normandy, France). A robust dataset of daily beach topography, derived from video monitoring systems, validates a set of numerical simulations of cross-shore dynamics performed by the process-based model XBeach-G. Our study evaluates the model’s efficacy in estimating beach profile evolution under high-energy conditions and explores its sensitivity to the physical properties of pebbles, including permeability. The results underscore the significance of considering spatial and temporal variations in permeability during storms to enhance the numerical model’s accuracy in predicting pebble beach dynamics. Furthermore, this study advocates for the incorporation of grain size mapping techniques to refine numerical model implementations.

Since the early 1990s, satellite altimetry has significantly improved our understanding of coastal and estuarine dynamics. The Casamance estuary in Senegal exemplifies a tropical microtidal system with limited instrumentation despite pressing environmental, social, and navigational concerns. This study explores the potential of SWOT satellite data to support the calibration and validation of high-resolution hydrodynamic models. Multi-source dataset of in situ measurements and altimetry observations has been combined with numerical modelling to investigate the hydrodynamics in response to physical drivers. Statistical metrics were used to quantify model performance. Results show that SWOT accurately captures water level variations in the main channel (width 800 m to 5 km), including both tidal and non-tidal contributions, with high correlation (R = 0.90) and low error (RMSE < 0.25 m). Performance decreases in tributaries (R = 0.42, RMSE up to 0.34 m), due to interpolated bathymetry and complex local dynamics. Notably, Delft3D achieves R = 0.877 at Diogué (RMSE = 0.204 m) and R = 0.843 at Carabane (RMSE = 0.225 m). These findings highlight the strategic value of SWOT for improving hydrodynamic modelling in data-scarce estuarine environments.