This polygon layer displays sub-basin-level average precipitation derived from the ECMWF (European Centre for Medium-Range Weather Forecasts) model. This layer helps hydrologists, forecasters, and planners see how much rainfall/snowfall is predicted or has occurred in each sub-basin, supporting medium-range water resource and flood management. We are intersested in the forecast period of 7 days.This layer aggregates ECMWF forecast precipitation over polygonal sub-basins. Each feature includes attributes for average accumulated precipitation, forecast run/valid times, and sub-basin identifiers. ECMWF is a leading global model offering medium-range (up to 10 days) forecasts at a high skill level. By focusing on sub-basins, this layer aids in local-scale decision-making—enabling more precise flood risk assessments, reservoir inflow estimates, and water resource planning across the region of interest.

This polygon layer depicts sub-basin average observed precipitation from the High Resolution Deterministic Precipitation Analysis (HRDPA). Offers insight into how much rain/snow actually fell across each watershed in the past observation period. Observation periods we are interested are for past 1 day, 3 days and 7 days.HRDPA is ECCC’s high-resolution precipitation analysis, merging gauge, radar, and HRDPS model data. This layer aggregates the final (or preliminary) HRDPA accumulations to sub-basin polygons. Each record indicates the average precipitation that truly occurred over each watershed, vital for verifying model forecasts, calibrating hydrological models, and conducting post-event analyses of flood or drought severity.

This polygon layer represents accumulated precipitation forecasts from the Global Forecast System (GFS), a global numerical weather prediction model operated by NOAA/NCEP. It provides global medium‑range precipitation forecasts, as a 168‑hour (7‑day) accumulation, to support a wide range of weather and hydrological applications.This polygon layer is generated by extracting the accumulated precipitation field from Global Forecast System (GFS) GRIB2 files. The raw data are converted into a TIF raster, then resampled, smoothed, and classified into discrete precipitation ranges. The resulting polygon features depict forecasted precipitation accumulations over a 7‑day (168‑hour) period, allowing users to monitor expected rainfall and snowfall patterns on a global scale.

Drainage basins of Manitoba.Hydrologic drainage basins found within Manitoba. The Assiniboine River basin is divided to indicate the Shellmouth Reservoir subbasin, to better illustrate local impacts and conditions. Basin names are in English and French. 

This polygon layer presents 7‑day and 10‑day accumulated precipitation forecasts from the Global Deterministic Prediction System (GDPS), aggregated by sub-basin. It is designed to help hydrologists, water resource managers, and emergency planners pinpoint watersheds facing higher rainfall or snowfall totals in the medium-to-long range, enabling proactive flood risk assessment, drought monitoring, and resource allocation.Developed by Environment and Climate Change Canada (ECCC), the GDPS is a global numerical weather prediction model running at approximately 15km resolution, updated twice daily (00Z and 12Z). This layer integrates 168-hour (7‑day) and 240-hour (10‑day) precipitation forecasts into sub-basin polygons, offering a comprehensive view of expected cumulative precipitation. By focusing on watershed boundaries, decision-makers can quickly gauge regional vulnerabilities to prolonged rainfall or snowfall events.Key highlights: Global Model Insight: Captures large-scale, multi-day weather systems (e.g., atmospheric rivers, persistent low-pressure systems). Sub-Basin Aggregation: Delivers averaged precip values per basin, simplifying hydrological analysis for flood or drought outlooks. Extended Outlook: Spanning from day 0 to day 10, covers both medium- and longer-term forecast horizons, essential for strategic planning and mitigation efforts. Typical Uses:Flood Forecasting – Identifying basins prone to heavy or prolonged precipitation. Water Resource Management – Adjusting reservoir release schedules or irrigation planning based on expected accumulations. Emergency Preparedness – Deploying resources or issuing advisories in vulnerable watersheds.

This polygon layer shows the spatial distribution of forecasted accumulated precipitation across watershed sub‑basins using data derived from the Regional Ensemble Prediction System (REPS). In other words, it aggregates precipitation amounts—computed from processed REPS forecast output (converted from GRIB2 files into raster [TIF] format)—over defined watershed boundaries to provide a detailed view of expected rainfall over a typical 72‑hour forecast period. This information supports regional hydrological forecasting, flood risk analysis, and water resource management.REPS forecast data are first processed to extract the accumulated precipitation field (APCP) and converted into high‑resolution raster images. These “REPS APCP rasters” represent the spatial distribution of forecast precipitation (in millimeters) over the region. Next, using pre‑defined watershed or sub‑basin boundaries, zonal statistics are applied to compute the average precipitation for each sub‑basin. The final layer displays these averaged values as polygon features, highlighting variations in forecasted rainfall across different drainage areas. This approach helps users pinpoint regions that may receive higher or lower rainfall, thereby enhancing hydrological assessments and emergency planning.

The dataset represents known concentration areas of harvested or unharvested Softshell clam (Mya arenaria) in the intertidal zone of the Estuary and the Gulf of St. Lawrence, Quebec region. The dataset was created for the National environmental emergencies centre (NEEC) for preparation and response in case of an oil spill. Concentration areas were defined using Fisheries and Oceans Canada (DFO) inventories conducted between 2000 and 2020.This layer is dependent on the inventories carried out and thus only represents known clam areas. For example, for the Haute-Côte-Nord, inventories have been limited to areas open to harvesting (with the exception of 4 sectors), but it is known that the Softshell clam is also present outside these areas. In addition, little information was available for the Moyenne and Basse-Côte-Nord.This data layer does not represent the general distribution of the species nor the extent to which fishing is allowed. The extent of shellfish beds may vary over time in response to, among others harvesting and the recruitment rates. The boundaries of polygons from inventory data may be underestimated relative to the actual size of the deposit since the inventories were conducted at the location where the resource is most abundant, without necessarily sampling the entire bed. However, the accuracy is sufficient for the protection and management needs of the resource in the event of an environmental incident. Data sources and references:Brulotte, S. 2011. Évaluation des stocks de mye commune des eaux côtières du Québec. Secr. can. de consult. sci. du MPO. Doc. de rech. 2011/044. x + 53 p.Brulotte, S. 2018. Évaluation de la mye commune (Mya arenaria) des eaux côtières du Québec en 2016 – méthodologie et résultats. Secr. can. de consult. sci. du MPO. Doc. de rech. 2018/004. ix + 60 p.Brulotte, S. 2020. Évaluation des stocks de la mye commune (Mya arenaria) des eaux côtières du Québec en 2019 – méthodologie et résultats. Secr. can. de consult. sci. du MPO. Doc. de rech. 2020/055. vii + 43 p.Brulotte, S. 2022. Résultats des inventaires de gisements de mye commune (Mya arenaria) réalisés de 2016 à 2020 et mise à jour des résultats de ceux effectués de 2001 à 2014 au Québec. Secr. can. de consult. sci. du MPO. Doc. de rech. 2022/xxx. (in progress)Brulotte, S. and M. Giguère. 2003. Évaluation d'un gisement de mye commune (Mya arenaria) de l'embouchure de la rivière Mingan, Québec, Rapp. can. ind. sci. halieut. aquat. No. 2511: xi + 58.Brulotte, S., M. Giguère, S. Brillon and F. Bourque. 2006. Évaluation de cinq gisements de mye commune (Mya arenaria) aux Îles-de-la-Madeleine, Québec, de 2000 à 2003. Rapp. tech. can. sci. halieut. aquat. 2640 : xii + 92 p.Brulotte, S., Giguère, M. and Duluc, C. 2015. Essais de techniques de captage du naissain de mye commune (Mya arenaria) sur la rive nord de l’estuaire et du golfe du Saint-Laurent. Rapp. tech. can. sci. halieut. aquat. 3084 : ix + 60 p.Giguère, M., S. Brulotte and F. Hartog.2007. Évaluation de quelques gisements de mye commune (Mya arenaria) de la rive sud de l'estuaire du Saint-Laurent en 2005 et 2006. Rapp. can. ind. sci. halieut. aquat. No. 2738: xi + 107.Giguère, M., S. Brulotte, M. Boudreau and M.-F. Dréan. 2008. Évaluation de huit gisements de mye commune (Mya arenaria) de la rive nord de l’estuaire du Saint-Laurent de 2002 à 2008. Rapp. tech. can. sci. halieut. aquat. 2821 : x + 91 p.Roy, I., M. Giguère, S. Brulotte and M. Gagnon. 2003. Évaluation de douze gisements de mye commune (Mya arenaria) du sud de la Gaspésie, Rapp. Tech. can. sci. halieut. aquat. 2469: xvi + 140 p.

In the hydrogeological unit, quantity of water that replenishes groundwater beneath the water table, expressed in mm/yr. Recharge is usually calculated using hydrology balance, integrating information from precipitation, hydrology data, drainage, soil properties, evapotranspiration, etc. The result is a raster dataset in which each cell has a given value for the recharge of the aquifer. It can be calculate using HELP software, developed by the US EPA. The methods used to create the dataset are described in the metadata associated with the dataset. The dataset represent a raster in which each cell has a mean value describing the global annual recharge of the hydrogeological unit.

This dataset comprises a map of inland water bodies in Canada and neighboring regions, as described by Ghayourmanesh et al. (2024). The data are mapped using the Lambert Conformal Conic (LCC) geographic projection with a spatial resolution of 250 meters. The LCC projection is frequently used as a standard projection at the Canada Centre for Remote Sensing (CCRS) (Trishchenko et al., 2016, Trishchenko, 2019). Each pixel value represents a code describing either the probability of inland water presence or land/ocean(sea) mask

The Drainage Areas dataset is largely based on the Water Survey of Canada (WSC) drainage area boundaries at the sub-sub-basin level. The data model supports the derivation, from the Fundamental Drainage Areas dataset (sub-sub-basin level), of the WSC and Atlas of Canada drainage area hierarchies and the data is available in all three schemes. Drainage area definitions for both WSC and Atlas of Canada boundaries were reviewed resulting in some modifications. Larger scale reference data sources were used for further manual boundary adjustments. This dataset has been integrated with other National Scale Frameworks hydrology datasets and is considered a component of the Hydrology Theme (see Supplemental Information for more details about the Atlas of Canada National Frameworks data at the 1:1,000,000 scale).The Atlas Frameworks are a set of integrated base map layers which form part of a larger National-Scale Frameworks data collection. These data have been compiled at a scale of 1:1 000 000 with the primary goal being to indicate correct relative positioning with other framework layers rather than absolute positional accuracy.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)