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.

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.

Accumulated precipitation represents the amount of total precipitation in mm (solid and/or liquid) which has been recorded over a given month or ISO week.Accumulation of precipitation values serve to inform users about the total amount of precipitation that has fallen in a specific region during a set time period. The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.

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.Several use cases of GeoAI data for change detection have been created. To view them, please follow the links below:- Iqaluit: https://open.canada.ca/data/en/dataset/ef29513d-a007-408c-beba-65f86e7b5b01- Calgary: https://open.canada.ca/data/en/dataset/bd07b597-5166-4b62-ae9c-245b3c62ea03- Québec City: https://open.canada.ca/data/en/dataset/4026720e-f7fb-478e-a58f-c62ebe20005d- Winnipeg: https://open.canada.ca/data/en/dataset/a6874aac-cfcd-4b92-bb3f-6031eedb5b57- Victoria: https://open.canada.ca/data/en/dataset/f011c7b9-f79e-42f8-9481-9bf9788bb189- Trois-Rivières: https://open.canada.ca/data/en/dataset/2b11a323-52c2-43d5-9c09-bc4b15b1bcc8

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).

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

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.

Percent of average precipitation represents the total amount of precipitation for a particular location over a specific time period, divided by the long-term average precipitation (1991-2020) for the same period and location, expressed as a percentage.Percent of average precipitation is to provide a clear and standardized way to compare how much precipitation has fallen during a specific time period relative to the long-term average for the same location and time period. Time periods calculated for monthly precipitation percentiles are 1, 2, 3, 6, 9, 12, 18, 24 months. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. Long-term average is 1991-2020.The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.