The dataset includes subsurface stratigraphic picks of the Milk River 'shoulder' in the Alberta Plains (Townships 1 to 73, Ranges 1W4 to 2W6) made from wireline geophysical well logs. The Milk River 'shoulder' is an informal term often used to refer to a distinctive 'shoulder' (deflection) on resistivity, sonic, density, and porosity logs. The Milk River 'shoulder' corresponds to the top of the Milk River Formation in southernmost Alberta, where it represents juxtaposition between paralic deposits of the underlying Deadhorse Coulee Member of the Milk River Formation and overlying marine shale of the Pakowki Formation. It is characterized by a leftward deflection (decreasing resistivity) upwards across the contact, forming the distinctive 'shoulder signature'. To the north, the Milk River 'shoulder' represents the boundary between the Alderson Member (lower Lea Park Formation) and the upper Lea Park Formation (Pakowki equivalent). In these areas, silty sands and mudstones of the Alderson Member are overlain by shales of the upper Lea Park Formation. Well data were screened to detect errors resulting from deviated wells, as well as incorrect ground and kelly bushing elevation data. We used statistical methods to identify local and regional statistical outliers, which we examined individually.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

The dataset contains data for placer watersheds locations. The dataset covers 18 watersheds within the Yukon Territory. The following watersheds form the principle boundaries of the dataset: Big Creek, Big Salmon River, Forty Mile River Indian River, Klondike River, Mayo River McQuesten River, Nisutlin River, Nordenskiold River Pelly River, Sixty Mile River, Southern Lakes (Yukon) Stewart River, White River\*, Yukon River North Yukon River South, Alsek River, Liard River \*Note - A small portion of the headwaters of the Tanana River (Yukon) watershed is associated within the boundaries of the White River watershed .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)

Belly River Structure

The purpose of this dataset is to identify the location of river valley connections.

This dataset provides results obtained by Health Canada’s Canadian Radiological Monitoring Network (CRMN) for 90Sr activity in milk samples originating from various locations across Canada. More information about the CRMN network can be found on the Health Canada website (see link below). From 1984 to 1993, data was collected from 20 locations. After 1993, routine milk analysis for radio-strontium activity was discontinued for all monitoring stations, except the Ottawa location. The results provided here are 90Sr activity concentrations in units of becquerels per litre (Bq/L). Milk is an important matrix for environmental radioactivity assessment since many radionuclides of health concern exhibit efficient soil to milk uptake pathways. As such, the surveillance of milk provides a very good indication as to the severity of environmental impact following a nuclear event. Strontium-90 (90Sr) is a radionuclide of particular concern because it has a long radiological and biological half-life coupled with a high affinity for incorporation into human bone and teeth. Nuclear weapons testing and nuclear accidents have released such long-lived radionuclides into the atmosphere, which in turn have entered the biological life cycle. Nevertheless, a steady decline in the activity concentration of 90Sr in milk can be seen since most of the nuclear weapon testing was halted in the 1960s. The map shows the approximate sampling location for each monitoring station. Stations are found within the associated location range.

Waterbody types include: * Lake * River * Canal * Reservoir * Kettle lake * Pond * Beaver Pond * Ocean This product requires the use of geographic information system (GIS) software.

Locations of open water within river ice in Manitoba, Ontario, Quebec, and the Maritimes were discerned manually using publicly accessible optical satellite images spanning from 2013 to 2020. This initial effort has led to a dataset pinpointing potential sites for river hydrokinetic energy initiatives.A more comprehensive dataset encompassing the entirety of Canada’s major freezing rivers has also been developed entitled “Hydrokinetic Resource Mapping - Optical Satellite Imagery Analysis of Open Water Regions in Ice-Covered Canadian Rivers” and is available at (https://search.open.canada.ca/openmap/61b4e576-9f3a-49a1-9546-b29be14787a4). Disclaimer:The identification of open water locations within river ice in Manitoba, Ontario, Quebec, and the Maritimes, as described, was conducted manually through the analysis of publicly available optical satellite images. This dataset is subject to the following limitations:1- The manual identification method may introduce potential human error and subjectivity within the dataset. 2- The publicly accessible satellite images employed may not provide fully comprehensive or entirely accurate representations of the actual conditions in the identified locations due to image resolution constraints, cloud cover, or atmospheric interference. This dataset is intended for preliminary assessment and should not be the sole basis for making critical decisions or investments related to hydrokinetic energy projects. Further validation and in-depth analysis are strongly recommended, and users should conduct their own due diligence and additional research to verify the data accuracy and relevance for specific applications. By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.