Publications scientifiques

Submersion risks assessment requires different tools and methods from regional to coastal scales. The Shom’s strategy relies on numerical modelling and observational systems applied in a challenging multi-scale context. At regional scales, storm surge and wave models Hycom and Wavewatch III, bathymetric digital terrain models (DTMs) and observational tide/buoy networks used within the operational national storm surge service (Homonim project with Météo-France) are presented, as well as their applications in climatological 40-year hindasts.

Significant developments have been made in the observation systems and techniques of estimating sea level towards meeting the standard accuracy requirement of Global Climate Observation Systems (GCOS). This study undertakes a systematic review of the current advances in estimating sea level change in the context of the 4^th industrial revolution. Trends in the use of main observation systems such as tide gauges, satellite altimetry, and ancillary systems such as GNSS and Autonomous Surface Vehicles were explored.

Satellite altimetry and tide gauges are the two main techniques used to measure sea level. Due to the limitations of satellite altimetry, a high-quality unified sea level model from coast to open ocean has traditionally been difficult to achieve. This study proposes a fusion approach of altimetry and tide gauge data based on a deep belief network (DBN) method.

Sea-level rise due to anthropogenic climate change is projected not only to exacerbate extreme events such as cyclones and storms but also to cause more frequent chronic flooding occurring at high tides under calm weather conditions. Chronic flooding occasionally takes place today in the low-lying areas of the Petit Cul-de-sac marin (Guadeloupe, West Indies, French Antilles). This area includes critical industrial and harbor and major economic infrastructures for the islands.

Increasing our capacity to predict extreme storm surges is one of the key issues in terms of coastal flood risk prevention and adaptation. Dynamically forecasting storm surges is computationally expensive. Here, we focus on an alternative data-driven approach and set up a weather-type statistical downscaling for daily maximum storm surge (SS) prediction, using atmospheric hindcasts (CFSR and CFSv2) and 15 years of tidal gauge station measurements. We focus on predicting the storm surge at La Rochelle–La Pallice tidal gauge station.

Coastal facilities such as nuclear power plants (NPPs) have to be designed to withstand extreme weather conditions and must, in particular, be protected against coastal floods because it is the most important source of coastal lowland inundations. Indeed, considering the combination of tide and extreme storm surges (SSs) is a key issue in the evaluation of the risk associated with coastal flooding hazard. Most existing studies are generally based on the assumption that high tides and extreme SSs are independent.

Intertidal communities dominated by canopy-forming brown algae (Phaeophyceae) usually prove to be highly productive systems, based on short-term measurements. However, long-term metabolism (primary production and respiration) is sensitive to several factors acting on different time scales (e.g. tidal cycle, seasonality), making its assessment challenging. Here, we used mathematical modelling to investigate the metabolism of a Fucus serratus-dominated community on daily and annual time scales.

Sandy beaches are highly dynamic environments buffering shores from storm waves and providing outstanding recreational services. Long-term beach monitoring programs are critical to test and improve shoreline, beach morphodynamics and storm impact models. However, these programs are relatively rare and mostly restricted to microtidal alongshore-uniform beaches. The present 16-year dataset contains 326 digital elevation models and their over 1.635 × 106 individual sand level measurements at the high-energy meso-macrotidal rip-channelled Truc Vert beach, southwest France.

Earthquakes affect near-surface permeability, however temporal permeability evolution quantification is challenging due to the scarcity of observations data. Using thirteen years of groundwater level observations, we highlight clear permeability variations induced by earthquakes in an aquifer and overlaying aquitard. Dynamic stresses, above a threshold value PGV > 0.5 cm s⁻¹, were mostly responsible for these variations. We develop a new model using earth tides responses of water levels between earthquakes.