Forecasting contrasting coastal and estuarine hydrodynamics with OPENCoastS

Anabela Oliveira (1) , André B Fortunato (1) , Marta Rodrigues (1) , Alberto Azevedo (1) , João Rogeiro (1) , Samuel Bernardo (2) , Laura Lavaud (3) , X. Bertin (3) , Alphonse Nahon (1) , Gonçalo de Jesus (1) , Miguel Rocha (1) , Pedro Lopes (1)

1 LNEC - Laboratório nacional de engenharia civil [Lisboa] = National Laboratory for Civil Engineering [Lisbon] = Laboratoire national de génie civil [Lisbonne]
2 LIP - Laboratório de Instrumentačão e Física Experimental de Partículas
3 LIENSs - LIttoral ENvironnement et Sociétés

Robust and accurate coastal forecasts require models to represent the relevant processes, prediction computational tools and reliable computational resources. OPENCoastS is a free, open-source WebGIS platform to develop on-demand hydrodynamic forecast systems that started as a simple 2D engine. OPENCoastS provides a visualization and download interface with in-situ and Sentinel satellite data comparison. 2D tidal, 2D wave & current interaction and 3D baroclinic flows are now included, forced by several atmospheric, oceanic and riverine forcings. Four applications demonstrate OPENCoastS’ capacity. The prediction of the 2020 typhoon season in Taiwan illustrates the use of the service using only large-scale public data. An application to the Bay of Biscay shows the importance of waves on extreme water levels during storms. A nearshore deployment in Figueira da Foz harbor assesses the impact of bathymetry on coupled wave and current circulation. 3D baroclinic circulation forecasts in Tagus estuary are validated by independent data.

Mots clés: SCHISM; Forecast systems; Unstructured grids; cross-scale; EOSC; Wave and currents modeling; Baroclinic modeling

Domaines: Interfaces continentales, environnement; Ingénierie de l'environnement

Anabela Oliveira, André B Fortunato, Marta Rodrigues, Alberto Azevedo, João Rogeiro, et al.. Forecasting contrasting coastal and estuarine hydrodynamics with OPENCoastS. Environmental Modelling and Software, 2021, 143, pp.105132. ⟨10.1016/j.envsoft.2021.105132⟩. ⟨hal-03454644⟩