CONNECT – Local coastal monitoring service for Portugal

CONNECT delivers a local, high-resolution, coastal monitoring service that seamlessly integrates model-based forecasts and observations to provide physical and water quality data on Portuguese estuaries and coastal systems to support environmental protection and the blue economy.

CONNECT's main features are: i) shelf-to-estuary-to-river, high-resolution, circulation and water quality operational modeling, downscaling Copernicus Marine Service regional forecasts to produce daily forecasts of physical, biogeochemical and fecal indicator bacteria variables; ii) real-time physical and biogeochemical data acquisition from in-situ observation networks, and remote sensing data from the Copernicus Marine Service; iii) a dedicated WebGIS portal, providing open access to the data and related physical and water quality indicators, and iv) seamless integration with Copernicus Marine Service regional models and Earth Observation data.

The strengthens the support of the implementation of the Water Framework Directive (WFD), the Marine Strategy Framework Directive (MSFD), the Floods Directive (FD), the Bathing Water Directive (BWD) and other EU policies, such as the Green Deal, by providing further and integrated historical and real-time information on physics and water quality.

CONNECT delivers a user-friendly service that seamlessly integrates and shares through a dedicated webGIS portal layers of blue and green data, aggregated at different spatial and temporal levels. The integrated service will be globally accessible, comprehensive, flexible, and modular, being easily customizable and transferable to other coastal systems anywhere. The service’s main features are:

• Shelf-to-estuary, high-resolution, circulation and water quality operational modeling with SCHISM operated by WIFF and OPENCoastS, downscaling CMEMS regional forecasts to produce daily forecasts of local physical and biogeochemical variables;
• Real-time physical and biogeochemical data acquisition from in-situ observation networks, and EO-based data from CMEMS (CoastNet);
• River flows at the models’ upstream boundaries predicted using Artificial Intelligence (AI);
• Automatic model-observations comparison, enhancing confidence in both;
• Water level extremes and water quality indicators based on model forecasts and observations;
• Weekly reports of the modeled and observed variables that summarize both the physical behavior and the water quality status of the coastal systems;
• A dedicated webGIS portal, providing web services and open access to the data;
• Seamless integration with CMEMS regional models and EO data.