In permafrost dominated regions, a gap persists in our understanding of water resources, the influence of groundwater, and the impact of climate change at the regional scale. Regional scale modelling can help to advance the understanding of these impacts by integrating with regional climate models. For regional modelling to be tenable, ongoing development of modelling methods and conceptualizations is required. By developing a fully integrated numerical groundwater-surface water climate model using HydroGeoSphere (HGS) (Aquanty 2021) for a gauged basin within the discontinuous permafrost zone, this dataset allows the verification of existing numerical methods and the testing of various conceptualizations of integrated groundwater-surface water flow in permafrost regions at the regional scale. This work informs future modelling and forecasting of regional water resources in permafrost regimes.

This model is derived from geological, geophysical and other forms of geodata. Feature extraction used deep learning. Predictive modelling made use of the deep ensemble method. Displayed is a Pan-Canadian probability map of mineral potential of graphite. This map was generated using known graphite deposits and occurrences and their associated features. Higher probability values highlight areas with an increased probability of graphite mineral systems.

11 tagged Blue whales (Balaenoptera musculus) were tracked during the daytime movements as well as the feeding behaviour in the St. Lawrence River estuary. Kernel density was applied to derminate the high density feeding areas of all individuals combined (30, 40, 50, 60, 75, 95 %).Doniol-Valcroze T, Lesage V, Giard J, Michaud R, 2012. Challenges in marine mammal habitat modelling: evidence of multiple foraging habitats from the identification of feeding events in blue whales. Endang Species Res, Vol. 17 : 255–268, doi : 10.3354/esr00427(English version only)

__The link: *Access the data directory* is available in the section*Dataset Description Sheets; Additional Information*__.**Slope classes** express the slope of the terrain in a relatively homogeneous area with a minimum area of 0.5 ha. They are generated from a numerical model that groups terrain slopes into six classes:+ 0-3% zero + Low by 4-8% + 9-15% soft + Moderate by 16-30% + 31-40% strong + Steep by 41% or moreThese data cover almost all of Quebec south of the 52nd parallel. This map is presented in two groups: grouping at the provincial level and grouping at the scale of 1/250,000. Each grouping represents an assembly of sheets produced on a scale of 1/20,000.The datasets were originally produced in 2005 and then updated in 2006. In 2010, they were enhanced with slope information for the northernmost part. No updates have been made since then.__For more information, please refer to the document: [Products presenting the concept of slope] (https://diffusion.mffp.gouv.qc.ca/Diffusion/DonneeGratuite/Foret/DONNEES_FOR_ECO_SUD/Classes_pente/01-Documentation/Produits_presentant_la_notion_de_pente.pdf)____ ⚠️ Notes: __ The numerical terrain model is prepared from the level curves and altitude points that come from the topographic map at a scale of 1/20,000 and 1/50,000 from the Quebec Topographic Database (BDTQ). This geographic database was produced in 2010 and has never been updated.__ 🕰️ Former names:__ Numerical slope classes, Slope class**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).

The Global Deterministic Prediction System (GDPS) is a coupled atmosphere (GEM), ocean and sea ice (NEMO-CICE) deterministic numerical weather prediction model. Forecasts are carried out twice a day for 10 days lead time. The geographical coverage is global at 15 km horizontal resolution. Data is available on some thirty vertical levels and interpolated on a global latitude-longitude uniform grid with 0.15 degree horizontal resolution. Variables availability in number and time frequency is a function of forecast lead time.

A hydrogeological unit is defined as any soil or rock unit or zone that by virtue of its hydraulic properties has a distinct influence on the storage or movement of groundwater. It is considered the main dataset from the GGP point of view. Hydrogeological units are ranked into five levels (from largest to smallest): 1) hydrogeological region, 2) hydrogeological context, 3) aquifer system, 4) hydrostratigraphic unit, and 5) aquifer. Here are formal definitions for these different types of hydrogeologic units. - Hydrogeological region Hydrogeological regions are areas in which the properties of sub-surface water, or groundwater, are broadly similar in geology, climate and topography. There are 9 such regions identified in Canada (ref?). - Hydrogeological context Hydrogeological contexts are units of reporting, conceptually narrower than regions, and are additionally delineated by physiographic and hydrogeological aspects. - Aquifer system ""A heterogeneous body of intercalated permeable and poorly permeable material that functions regionally as a water-yielding hydraulic unit; it comprises two or more permeable beds [aquifers] separated at least locally by aquitards [confining units] that impede groundwater movement but do not greatly affect the regional hydraulic continuity of the system"" (Poland et al., 1972). - Hydrostratigraphic unit (HSU) ""Body of sediment and/or rock characterized by ground water flow that can be demonstrated to be distinct under both unstressed (natural) and stressed (pumping) conditions, and is distinguishable from flow in other HSUs"" (Noyes et al.) - Aquifer ""A formation, group of formations, or part of a formation that contains sufficient saturated permeable material to yield significant quantities of water to wells and springs"" (Lohman et al, 1972, p. 21). The rank attribute is used to specify the scope of the described unit. The general principle behind this specification is to allow the same data structure to apply to various types of hydrogeological units, from the local aquifer to the almost continental hydrogeological region. The dataset includes properties such as identification, physiography, geology, aquifer description and properties, water balance, groundwater use and risk. It features numerical values or a general description when no values are available. The description can also be used to add context to the numerical values. For each property, metadata identifying the source of the original data, links to similar data in GIN, and description of the processes, algorithms or methodology used to obtain these datasets will be available to complement the data. This dataset is designed to capture and represent a set of synthesized information pertaining to hydrogeological units through maps and succinct table reports. Some attributes (or properties) of the dataset are irrelevant depending of the rank of the unit. In general, this dataset is organised to include multiple properties associated with aquifers and larger hydrogeologic units. These properties are grouped into categories, which include identification, physiography, geology, aquifer description, water balance, groundwater use and risk. The numerical values associated with each of the properties can be used to create thematic maps; hence, the importance of using standardized units of measurement and definitions for these properties. When numerical values are not available, a general description may be supplied instead. The description can also be used to add context to the numerical values. Because this dataset is the cornerstone of the national view on groundwater, supplemental contextual information (metadata) must be part of the data. Thus, for each property, metadata identifying the source of the original data, links to similar data in GIN, and a description of the processes, algorithms or methodology used to obtain these datasets will be available to complement the data.

The Regional Deterministic Precipitation Analysis (RDPA) produces a best estimate of precipitation amounts that occurred over a period of 6 hours. The estimate integrates data from in situ precipitation gauge measurements, weather radar, satellite imagery and numerical weather prediction models. Geographic coverage is North America (Canada, United States and Mexico). Data is available at a horizontal resolution of 10 km. The 6 hour analysis is produced 4 times a day and is valid at 00, 06, 12 and 18 UTC. A preliminary analysis is available approximately 1 hour after the end of the accumulation period and a final one is generated 7 hours later in order to assimilate more gauge data.

The High Resolution Deterministic Prediction System (HRDPS) carries out physics calculations to arrive at deterministic predictions of atmospheric elements from the current day out to 48 hours into the future. Atmospheric elements include temperature, precipitation, cloud cover, wind speed and direction, humidity and others. This product contains raw numerical results of these calculations. Geographical coverage of the system is most of Canada. Data is available over specific areas in the MSC Datamart and the whole coverage is available in the MSC GeoMet web services. Data is available at a horizontal resolution of about 2.5 km up to 31 vertical levels. Predictions are performed up to four times a day.

The Regional Deterministic Precipitation Analysis (RDPA) produces a best estimate of precipitation amounts that occurred over a period of 24 hours. The estimate integrates data from in situ precipitation gauge measurements, weather radar, satellite imagery and numerical weather prediction models. Geographic coverage is North America (Canada, United States and Mexico). Data is available at a horizontal resolution of 10 km. The 24 hour analysis is produced twice a day and is valid at 06 and 12 UTC. A preliminary analysis is available approximately 1 hour after the end of the accumulation period and a final one is generated 7 hours later in order to assimilate more gauge data.