Predicted Soil Great Group class as defined by the The Canadian System of Soil Classification (third edition).

A vector representation of stream networks is a crucial dataset for the modelling the surface water and groundwater components of the hydrologic cycle. For many usages a crucial attribute of the drainage network is a digital topology and hierarchal stream order attribute (e.g., Strahler stream order). In Canada jurisdictional stream networks are available for the provinces and territories and nationally for Canada in the National Hydrological Network (NHN) dataset. Unfortunately, the NHN data lacks the same topological and attribute information that is available for numerous provinces due to standardization for the entire country. For Canada1Water it was also necessary to have a harmonized dataset with the United States, for both the southern transboundary watersheds and the Alaskan watersheds. This report documents the processes completed to upgrade the topological and graph network support for NHN and provide continuous connectivity with US datasets. It also highlights and corrects a number of stream density and stream order issues that occur within Canada across provincial and territorial borders and NTS tiles. All vector processing was completed in RivEX software extension for ArcMap. Following complete topological correction stream classification was assigned and a table of the node graph network developed. Additional work was then completed to normalize stream density particularly amongst low-order streams between British Columbia and the Yukon and amongst local NTS tiles in Quebec and Ontario. Corrected NHN Strahler stream order assignment was validated against a number of provincial and watershed datasets, all of which already have Strahler stream order attributed. These datasets are the same underlying digitized vector data, so there are no differences in node or polyline positions. Strahler stream order assignment validation was only done by visual comparison as due to differences in vector segments a statistical comparison is complicated. The transboundary integrated C1W stream network with complete classification provides a seamless national dataset to support transdisciplinary studies (fisheries, wildlife, health, pesticide and nutrient issues, mining impact, ecosystem restoration, numeric modelling) that involve a knowledge of stream distribution and ranking.

This dataset comprises all of the feature classes in the Alberta Provincial Electoral Divisions profiles. This data is derived from the Census of Canada and the National Household Survey from Statistics Canada from 2011 and 2016. This does not constitute an endorsement by Statistics Canada of this product.

All stops in the public transport network managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Breakdown of the electoral districts of the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Priority for snow removal on the road network according to three service levels (1, 2 and 3) or under provincial jurisdiction (MTQ) .attributs:ID - Unique IdentifierPriority - Service Level or Provincial Jurisdiction (MTQ)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This data set comprises all of the current feature classes in the Alberta Provincial Electoral Divisions profiles. This data is derived from the 2021 Census of Canada.

Electoral division of the 2017 election.**Collection context** Creation of districts in collaboration with the legal services and the electoral data of the Chief Electoral Officer (DGE). Balancing of districts according to anthropogenic constraints and number of voters.**Collection method** Computer-aided mapping.**Attributes*** `ID_SEC_DIS` (`long`): Identifier* `NAME_DISTRI` (`varchar`): District name* `NO` (`long`): District number* `AREA` (`varchar`): Area* `ADVISORY_NAME` (`varchar`): Name of the advisor* `SOURCE` (`varchar`): Source* `DATE_CREAT` (`date`): Creation date* `DATE_MODIF` (`date`): Date of modification* `USER_MODIF` (`varchar`): Modified byFor more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Historical hydrometric data are standardized water resource data and information. They are collected, interpreted and disseminated by the National Hydrological Services (NHS) in partnership with the provinces, territories and other agencies through the National Hydrometric Program. These data sets include daily mean, monthly mean, annual maximum and minimum daily mean and instantaneous peak water level and discharge information for over 2700 active and 5100 discontinued hydrometric monitoring stations across Canada.

PURPOSE:This Archer fiord data is associated with a larger program ArcticCORE, which was created to fulfill knowledge gaps and develop long term protection in the extremely remote Tuvaijuittuq region. The main objectives of this expedition were to improve our comprehension of the key drivers for productive capacity, diversity and ecosystem structure in areas connected to Baffin Bay and Tuvaijuittuq, including Archer fiord.DESCRIPTION:ArcticCORE is a 5-year broader program aiming to characterize Tuvaijuittuq’s unique ecosystem and its influence and connectivity with the adjacent ecosystems to inform sustainable management and conservation initiatives in Tuvaijuittuq and the eastern Arctic. In an Arctic Ocean with rapidly declining sea ice, Tuvaijuittuq area retains the oldest and thickest sea ice, and can act as a refuge for ice-dependent species. This program aims to characterize the Arctic marine ecosystem and establish baseline measurements for future comparisons in the region. From 2023, water collection was carried out at four stations throughout Archer Fiord and analyzed for primary productivity, chlorophyll a, phytoplankton flow cytometry and phytoplankton taxonomy down to the lowest identifiable level. These data will contribute to a better understanding of the key drivers for productive capacity, diversity and ecosystem structure in Archer fiord. Characterization of these upstream areas are relevant for an ecosystem-based approach to fisheries management in Baffin Bay, a priority for DFO and an intrinsic part of mandated activities, as they influence the ecosystem and fisheries resources downstream.