A definição de áreas para extração e dragagem de materiais inertes no leito das águas do mar advem da necessidade de regular o aproveitamento económico do mar territorial da Região e, ao mesmo tempo, criar uma disciplina indispensável a garantir a gestão sustentável dos recursos hídricos existentes num contexto de estabilidade económica e de desenvolvimento sustentado dos setores de atividade.

Structural framework limits (with uncertainties) and units in the Roer-to-Rhine area of interest. Compiled and harmonised from datasets of WP3 partners Royal Belgian Institute of Natural Sciences – Geological Survey of Belgium, Netherlands Organisation for Applied Scientific Research, Flemish Institute for Technological Research and Geological Survey of North Rhine‐Westphalia.

Structural framework limits (with uncertainties) and units in the Pannonian Basin area of interest. Compiled and harmonised from datasets of WP4 partners Mining and Geological Survey of Hungary, Geological Survey of Federation of Bosnia and Herzegovina, Croatian Geological Survey, Geological Institute of Romania, Geological Survey of Serbia, State Geological Institute of Dionyz Stur, Geological Survey of Slovenia and State Information Geological Fund of Ukraine.

This data product is an R Shiny application that discloses the data collected by the Institute of Oceanography and Fisheries (IZOR) in Croatia, in the Middle Adriatic (Skejic et al., 2015). A time series has been built of observations on the species composition of the plankton. The application shows the evolution over time of abundance of major groups of species, as well as the most frequent species (or other taxonomic units) in the dataset. There is also a multivariate representation based on a PCA of abundances of the most frequent species, which shows the seasonal (monthly) fluctuations and the long-term (yearly) trend, and the contribution of each individual species to the temporal evolution of the community.

This data product is a series of gridded abundance maps for 40 zooplankton species from 2007 to 2013 in the Baltic Sea, based on a neural network analysis. As input data a combination of EMODnet Biology datasets were used, together with the environmental variables dissolved oxygen, salinity, temperature, chlorophyll concentration bathymetry and the distance from coast. Additionally the position (latitude and longitude) and the year are provided to the neural network. DIVAnd (n-dimensional Data-Interpolating Variational Analysis) and the neural network library Knet were used in this analysis.

Modelling areas of the different 3DGEO-EU workpackages.

Geomanifestations in the Roer-to-Rhine area of interest. Compiled and harmonised from datasets of WP3 partners Flemish Planning Bureau for the Environment and Spatial Development, Royal Belgian Institute of Natural Sciences – Geological Survey of Belgium, Flemish Institute for Technological Research and Netherlands Organisation for Applied Scientific Research.

Geomanifestations in the Pannonian Basin area of interest. Compiled and harmonised from datasets of WP4 partners Mining and Geological Survey of Hungary, Geological Survey of Federation of Bosnia and Herzegovina, Croatian Geological Survey and Geological Survey of Slovenia.

Simulated change in mean groundwater head between the future (1 degree warming, minimum precipitation change) and past (1998-2018) for Drava-Mura aquifer, Croatia. Simulated by a 100 m by 100 m grid. Unit: Meters.

Simulated change in mean groundwater head between the future (1 degree warming, maximum precipitation change) and past (1998-2018) for Drava-Mura aquifer, Croatia. Simulated by a 100 m by 100 m grid. Unit: Meters.