Within the framework of marine resource management, a common knowledge base is being developed on the distribution, composition and dynamics of various geological resources. Focus is on data from the Belgian part of the North Sea, being representative of a typical sandbank sedimentary system. To ensure harmonised seabed mapping over large, supraregional areas and to facilitate the exchange of information, special attention was paid to compatibility with marine geodatabases from the adjacent Netherlands territory. With reference to the seabed and its subsurface, two main databases are being compiled: one comprising all available lithological descriptions and one with all numerical grain-size information. To enable standardisation of the data and make them easily query-able, non-numerical descriptions are being coded to an international standard (EU FP7 Geo-Seas; www.geoseas.eu), of which the Udden-Wentworth scale is the main classifier. Several other parameters were derived, such as percentages mud, sand, gravel, shells and organic material. For the sediment database, cumulative grain-size-distribution curves were compiled, enabling calculations of any desired granulometry parameter, such as percentages of the grain-size fractions (fine, medium, coarse sand) and percentiles that are relevant in seabed-habitat mapping or sediment-transport modelling (D35, D50, D84). For both databases, the completeness and accuracy of the metadata were considered highly important. Information about sampling and coring techniques, analytical methods, horizontal and vertical positioning accuracy, and the exact timing of data acquisition is pivotal in uncertainty analyses, which are an increasingly important element of seabed mapping. The time of seabed mapping is critical to convert measured water depths to a common datum such as TAW in Belgium, facilitating integration of sample data in bathymetry data and thus their incorporation in 4D-modelling studies on morphodynamic change. For Belgium, the geological databases will be imbedded in the data infrastructure of the Belgian Marine Data Centre (www.bmdc.be), ensuring compatibility with international standards and providing easy access to a wide user community. Following processing to generate data products such as resource-related subsurface models, visualisation is foreseen through Subsurface Viewer (GmbH INSIGHT). Applied maps and models thus disseminated are crucial in decision making, and invaluable for outreach and educational purposes. The newly developed database and its associated data products will contribute to the objectives of the projects TILES (Belspo Brain-be), EMODnet-Geology (EU DG MARE), and ZAGRI (private revenues from the marine-aggregate industry).
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RBINS Staff Publications 2016
In case of maritime pollution, man-overboard, or objects adrift at sea, national maritime authorities of the 9 countries bordering the European North West Continental Shelf (NWS) rely on drift model simulations in order to better understand the situation at stake and plan the best response strategy. So far, the drift forecast services are mainly managed at national levels with almost no integration at the transnational level. Designed as a support service to the national drift forecasting services, NOOS-Drift has the ambition to change this paradigm. NOOS-Drift is a distributed transnational multi-model ensemble system to assess and improve drift forecast accuracy in the European North West Continental Shelf. Developed as a one-stop-shop web service, the service allows registered users (national drift model operators or trained maritime authorities) to submit on-demand drift simulation requests to be run by all the national drift forecasting services connected to NOOS-Drift. Within 15 minutes after activation, the NOOS-Drift users shall get access to the drift simulation results of the individual ensemble members, as well as the results of a multi-models joint analysis assessing the ensemble spread and delineating risk areas to locate possible maritime pollution. This operation of such a distributed multi-models service is to our knowledge a world premiere. In this communication, we will present the technical and scientific developments that had to be done to make this service possible, including: - a robust, secure and latency-free communication system that coordinates the execution of the different national models - a strategy to build the multi-model ensemble - a definition of drift forecast accuracy - the joint multi-model analysis tools - the standard file formats and visualisation means. Finally we will illustrate on an example how the NOOS-Drift service could change the decision making process.
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RBINS Staff Publications 2020
