The theme on physicochemical monitoring of rivers and rivers presents data from all stations in networks monitoring water quality in rivers in Quebec and the St. Lawrence River.The purpose of networks for monitoring general water quality is to characterize, using current physicochemical and bacteriological parameters, the quality of water in spatial terms and to monitor the evolution of this quality over time. For the regular monitoring of the general quality of river and river water, the parameters measured are: total phosphorus, total nitrogen, nitrites and nitrates, ammonia nitrogen, chlorophyll a, pheopigments, faecal coliforms, faecal coliforms, turbidity, suspended matter, pH, conductivity, dissolved organic carbon and temperature. This data is used to calculate the Bacteriological and Physicochemical Water Quality Index (IQBP), a water quality classification index.The data set on physicochemical monitoring of rivers and rivers also includes the drainage areas of some of the stations. The attribute table provides a compilation of land use by category for the last year available at the time the data was generated. Follow-up is carried out annually.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

These datasets provide information pertaining to sediment grain size, porosity, organic content, total carbon and nitrogen concentrations, trace element concentrations, chlorophyll and phaeopigment concentrations, and meiofauna and macrofaunal abundance in Simoom Sound between November, 2000, and February, 2001. Data formatting of files were performed by Meagan Mak.Sutherland et al (2023) covers the benthic component of a broader project investigating potential modification of marine ecosystems by shrimp trawling and trapping on the central coast of British Columbia. Sediment and infaunal samples were collected before and after fishing with commercial fishing gear consisting of otter-trawl, beam-trawl, and trap-lines. Simoom Sound was sampled in November 2000 and February 2001. Tabulated data of sediment characteristics that include sediment grain size, porosity, carbon and nitrogen content, trace-element, and chlorophyll concentrations are presented in this report. In addition, the infaunal data are comprised of both macrofaunal and meiofaunal communities.

The Versatile Soil Moisture Budget (VSMB) is a soil water budget model that is continuous and deterministic in nature and was developed by AAFC. It is based on the premise that the water available for plant growth is gained by precipitation or irrigation, and lost through evapotranspiration and runoff as well as lateral and deep drainage. The daily net loss or gain is added or subtracted from the water already present in the rooting zone. Water is withdrawn simultaneously, but at different rates, from different soil depths, depending on the potential evapotranspiration, the stage of crop development, the water release characteristics of each soil layer and the available water.

This map service provides access to most of the Resource Map datasets shown on the GeoAtlas application.**Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule. This map service is used by the GeoATLAS web application, sub-section Resource Map in the Mineral Exploration theme. It includes Base Metals Potential, Coal Potential, Gold Potential, Helium Potential, Bitumen (Oil Sands) Potential, Lithium Potential, Potash and Salt Resource Potential, Rare Earth Elements Potential and Uranium Potential schema in Production Data Warehouse. Note: Oil and Gas pools are found in the /Petroleum service.

GeoAI are buildings, hydrography, forests, and roads automatically extracted using Deep Learning models applied to a source dataset, typically aerial or satellite images. The primary aim of GeoAI is to increase Canada's availability of high-resolution foundational geospatial data for both spatial and temporal coverage.‌The infrastructure and expertise put in place by NRCan enables a rapid, efficient, and scalable data creation process through the use of leading-edge technology and Artificial Intelligence models. Published datasets for a given source can be revisited at a later date as more accurate models are developed and put into production. For now, only static files are available, but as the series develops, new products and services will be added.

The Air Quality Health Index (AQHI) is a scale designed to help quantify the quality of the air in a certain region on a scale from 1 to 10. When the amount of air pollution is very high, the number is reported as 10+. It also includes a category that describes the health risk associated with the index reading (e.g. Low, Moderate, High, or Very High Health Risk). The AQHI is calculated based on the relative risks of a combination of common air pollutants that are known to harm human health, including ground-level ozone, particulate matter, and nitrogen dioxide. The AQHI formulation captures only the short term or acute health risk (exposure of hour or days at a maximum). The formulation of the AQHI may change over time to reflect new understanding associated with air pollution health effects. The AQHI is calculated from data observed in real time, without being verified (quality control).

Regional Deterministic Air Quality Analysis (RDAQA) is an objective analysis of surface pollutants that combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) with hourly observations from various monitoring networks in North America, including the Canadian measurement networks operated by the provinces, territories and certain cities, as well as the various American networks in the context of the AIRNow program administered by US/EPA (US Environmental Protection Agency). RDAQA analysis provides the best description of current air quality conditions, and is used to inform the public, meteorologists in the various Environment and Climate Change Canada forecasting offices, Health Canada and other users about the distribution of air pollutants near the ground, and the performance of forecasting models. Each hour, a preliminary product is available approximately one hour after the observation measurement time, while final and Firework products are available approximately two hours after the measurement time. The preliminary and final products contain analysis of the chemical constituents O3, SO2, NO, NO2, PM2.5 (fine particles with diameters of 2.5 micrometers or less) and PM10 (coarse particles with diameters of 10 micrometers or less), while the Firework product contains analysis of PM2.5 and PM10.

Annual and five-year (5YA) average wet deposition maps for the ammonium ion are available. The file formats include geodatabase files (*.gdb) compatible with geospatial software (e.g. ESRI ArcGIS) and KMZ files compatible with virtual globe software (e.g. Google Earth™). Maps can also be viewed online via Open Maps and the ArcGIS online viewer. Annual deposition from each site was screened for completeness using the following criteria: (1) precipitation amounts were recorded for >90% of the year and >60% of each quarter, and (2) ammonium concentrations were reported for >70% of the precipitation measured over the year and for >60% of each quarter. Five-year average wet deposition values are averaged annual deposition values with a completeness criterion >60% for the five-year period. Units for wet deposition fluxes are in kg of NH4 per hectare per year (kg ha-1 y-1). Sources of measurement data and spatial interpolation method are described here: https://doi.org/10.18164/e8896575-1fb8-4e53-8acd-8579c3c055c2. Recommended citation: Environment and Climate Change Canada, [year published]. NH4 Wet Deposition Maps. Air Quality Research Division, Environment and Climate Change Canada, Toronto, Ontario, Canada. [URL/DOI], accessed [date].Recommended acknowledgement: The author(s) acknowledge Environment and Climate Change Canada for the provision of Canada-U.S. wet deposition kriging maps accessed from the Government of Canada Open Government Portal at open.canada.ca, and the data providers referenced therein.

The lithogeochemical data provides the chemical composition of rock samples. This data helps characterize the rocks and can be used to understand their mode of formation.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)

PURPOSE:To quantify impacts of nutrient and sediment loading to plant and animal communities and the environmental conditions that support them in estuaries of the Southern Gulf of St. LawrenceDESCRIPTION:The MEQ monitoring program is being implemented in 35-40 estuaries in the southern Gulf of St. Lawrence (sGSL) to support the development of a MEQ measure (threshold) to promote efforts to address nutrient enrichment in estuaries. The two main indicators included in the monitoring program are dissolved oxygen and eelgrass coverage which are used to assess the trophic status of estuaries within the region. The two factors most important for impacting the trophic status of estuaries are nitrogen loading and water residence time, i.e., water circulation. If water residence time is long and/or nitrogen loading is high, nutrient impacts are likely. A peer-reviewed manuscript has demonstrated that these two factors are predictive of the dissolved oxygen regime in the upper estuary and that publication successfully used dissolved oxygen to ascribe trophic status to estuaries. In a companion paper it was also determined that nitrogen loading was negatively correlated with eelgrass coverage. These two papers form the basis of the MEQ monitoring program (see attached). NOTES ON QUALITY CONTROL:Dissolved oxygen loggers require calibration prior to deployment and are checked for drift after retrieval (though drift isn't anticipated given optical sensor technology). In the event that dissolved oxygen loggers weren't cleared at a frequency sufficient to prevent data errors from occurring these data are removed prior to analysis. Additionally, data must be scrubbed of erroneous measurements which are relatively rare and very apparent. An error code of -888.88 is the primary error for dissolved oxygen loggers. Salinity probes rarely provide erroneous data and when they do it is typically the result of fouling.PHYSICAL SAMPLE DETAILS:Water is sampled bi-weekly to monthly using a Niskin water sampler at a depth of 0.5 m from the water surface, from May-November. Samples are processed in the laboratory in duplicate for chlorophyll a and seston within ~8 hours of being collected.SAMPLING METHODS:For each study estuary, dissolved oxygen is monitored continuously with optical dissolved oxygen loggers in the upper and mid-estuary. Tidal amplitude and salinity (NB and NS only) were also monitored at the upper estuary location only. Depth profiles for other water quality variables are taken at the bi-weekly or monthly scale as well as samples for seston (NB and NS only) and chlorophyll a (a proxy for phytoplankton). These parameters are monitored on a 3-year cycle except for two sites in PE and one site in NB and NS which are monitored annually: West and Wheatley, PE, Cocagne, NB and Pugwash, NS, respectively.Data is collected for eelgrass coverage by a collaborator between June-September, ideally during the same year we collect water quality data.Collaborators include the province of PEI’s Department of Environment, Water and Climate Change and the Southern Gulf of St. Lawrence Coalition on Sustainability.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.