Long term average (LTA) Potential Groundwater Recharge (GWRpot) for the European domain at 1 km spatial resolution for the period 1981-2010. The LTA GWRpot data set i part of a series of gridded datasets established in the TACTIC project for estimating Potential Groundwater Recharge (GWRpot). The data available are AET, Effective precipitation (Peff=Precipitation-AET), Groundwater Recharge coefficient (Rcoef defined as the ratio: Peff / GWRpot ) The Potential Groundwater Recharge GWRpot = (Precipitation-AET)*Rcoef. The TACTIC series of gridded datasets for estimation of GWRpot included two versions of GWRpot. The current dataset is the GWRpot_biacorr= Peff_biascorr*Rcoef, adjusted to other Peff estimates from seven national pilots in Europe. The other is GWRpot =Peff*Rcoef. Urban areas are masked out and not represented in the gridded dataset. All units are mm/year for the period 1981-2010.

The data comprise unprocessed raw data (level 0 data) containing image and spectral data acquired by scanning of drillcores at SGU. Level 0 is typically the level at which raw hyperspectral data is captured during the scanning campaign and the data has not been processed i.e. no data correction, normalization or band subsetting has been performed on this data. The cameras in the scanner cover the visible-near infrared and short-wave infrared (VNIR-SWIR) and the long-wave infrared (LWIR). The combination of different infrared wavelength ranges increases the mineral detection capability. Objective information about the mineralogical composition of the drillcores is fundamental basics for interpretation and modeling of the rock and the geological evolution.

The data comprise image and spectral data acquired by scanning of drillcores at SGU. The cameras in the scanner cover the visible, short wavelength and long wavelength parts of the infrared spectrum. The combination of different infrared wavelength ranges increases the mineral detection capability. Objective information about the mineralogical composition of the drillcores is fundamental basics for interpretation and modeling of the rock and the geological evolution. Level 2 is a processing level where data has been prepared for further spectral processing and product generation. Note that mineral identification is not included in level 2. This requires further processing and interpretation of the data.

T layer represents topographical information, where calculation of the slope was effectuated and represented in rasterfile, reclassified into T index values. The highest values correspond to low slope areas (alluvial aquifers) and the highest values correspond to steepest areas in mountains.

Raster data of the geological map used for HOVER WP3 D3-5b Geology

MIN4EU DB consists of two parts: Minerals Inventory data and Minerals Yearbook data. Minerals Inventory covers mineral occurrences and mines in Europe (onshore). The European Union has identified security of supply, improving environmental management and resource efficiency as key challenges for the raw materials sector. Data on the location and spatial distribution of primary and secondary raw materials in relation to exploration, exploitation, production and trading activities form the basis for decision-making in government and industry. Given the dynamic nature of such data, regular updates of comprehensive, reliable and harmonized information across borders are required, as there are several sources of non-harmonized data with different coverages developed over the last decades by national and international projects for different purposes. Data have been prepared and collected in the projects Minerals4EU, EURare, ProSUM, ORAMA, RESEERVE and MINTELL4EU, and others and are shared in the European Geological Data Infrastructure (EGDI).

The GEOCR500 dataset was processed completely digitally in ArcGIS 9.1 and integrated within a regional geographic information system.

Base of negative bouyancy zone for 100% C02. Geographical site: Celtic Sea & French EEZ. References: Burnol, A. (2018). Roles of Gas Hydrates for CO2 Geological Storage Purposes. Gas Hydrates 2, 267-284. doi:https://doi.org/10.1002/9781119451174.ch13 Burnol, A., Thinon, I., Ruffine, L., & Herri, J. M. (2015). Influence of impurities (nitrogen and methane) on the CO2 storage capacity as sediment-hosted gas hydrates – Application in the area of the Celtic Sea and the Bay of Biscay. International Journal of Greenhouse Gas Control, 35, 96-109. doi:https://doi.org/10.1016/j.ijggc.2015.01.018

Gas analyses produced by IODP The International Ocean Discovery Program

Information about the heat flow and geothermal gradient represented as points. The data originally come from the global heat flow database of the International Heat Flow Commission in 2010. A description of the data and a literature list can be found on the website of the International Heat Flow Commission (https://ihfc-iugg.org/products/global-heat-flow-database)