PGMN Groundwater Level Observations
The groundwater level data along with the precipitation data is used to identify groundwater level trends over time. Groundwater levels are measured once per hour in PGMN wells using level loggers. The data is stored in the logger and then transmitted via telemetry to a program information system. For non-telemetry PGMN sites the data is uploaded manually from the level logger.
The Provincial Groundwater Monitoring Network (PGMN) is a partnership program between the Ontario Ministry of the Environment, Conservation and Parks and the province’s Conservation Authorities, as well as some municipalities in areas not covered by a Conservation Authority. There are almost 400 wells monitored across the province. The PGMN program began in 2000 and is designed to monitor ambient groundwater level and chemistry conditions across Ontario.
Toronto and Region Conservation Authority (TRCA) is responsible for maintaining the digital telemetry systems at 21 monitoring wells in our jurisdiction, collecting water level data and arranging for chemical analyses of water quality samples at dedicated wells.
This dataset includes water level observations for PGMN monitoring wells located within TRCA’s jurisdiction, including: seven wells in the Oak Ridges Moraine Aquifer Complex, five in the Thorncliffe Formation, six in the Scarborough Formation, one in the Lower Newmarket Till, and one in a bedrock unit. Wells are identified by PGMN Well No., coordinates, and aquifer.
Datasets available for download
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PGWMN_LevelObservationsFeature Layer
Layer 0 via ArcGIS REST API
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PGWMN_LevelObservations (Explore)HTML
Explore PGWMN_LevelObservations on ArcGIS Hub
Additional Info
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| Last Updated | May 19, 2026, 16:31 (UTC) |
| Created | May 19, 2026, 16:31 (UTC) |
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Domain / Topic
Domain or topic of the dataset being cataloged.
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Title
Title for the Dataset.
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PGMN Groundwater Level Observations |
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Description
A description of the dataset.
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The groundwater level data along with the precipitation data is used to identify groundwater level trends over time. Groundwater levels are measured once per hour in PGMN wells using level loggers. The data is stored in the logger and then transmitted via telemetry to a program information system. For non-telemetry PGMN sites the data is uploaded manually from the level logger. |
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Tags / Keywords
Keywords/tags categorizing the dataset.
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Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
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Dataset Size
Dataset size in megabytes.
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48.0 |
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Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
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Published Date
Published date of the dataset.
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2020-07-16 |
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Time Period Data Span (start date)
Start date of the data in the dataset.
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Time Period Data Span (end date)
End date of time data in the dataset.
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GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
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Access category
Type of access granted for the dataset (open, closed, service, etc).
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public |
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License
License used to access the dataset.
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Toronto and Region Conservation Authority (TRCA) Open Data Licence v1.0 - Toronto and Region Conservation Authority (TRCA) |
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Limits on use
Limits on use of data.
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Location
Location of the dataset.
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https://trca-camaps.opendata.arcgis.com/datasets/camaps::pgmn-groundwater-level-observations |
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Data Service
Data service for accessing a dataset.
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Owner
Owner of the dataset.
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trca_d.macleod |
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Contact Point
Who to contact regarding access?
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Conservation Ontario |
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Contact Point Email
The email to contact regarding access?
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[email protected] |
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Publisher
Publisher of the dataset.
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Conservation Ontario |
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Publisher Email
Email of the publisher.
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Author
Author of the dataset.
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trca_d.macleod |
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Author Email
Email of the author.
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Accessed At
Date the data and metadata was accessed.
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2023-04-28 |
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Identifier
Unique identifier for the dataset.
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36f742af97b44254b064216386801a6c |
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Language
Language(s) of the dataset
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English |
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Link to dataset description
A URL to an external document describing the dataset.
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https://trca-camaps.opendata.arcgis.com/datasets/camaps::pgmn-groundwater-level-observations |
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Persistent Identifier
Data is identified by a persistent identifier.
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Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
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Contains data about individuals
Does the data hold data about individuals?
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Contains data about identifiable individuals
Does the data hold identifiable data about individual?
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Contains Indigenous Data
Does the data hold data about Indigenous communities?
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Portal Type
Platform type of the source portal.
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Version
Version of the datatset
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None |
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Source
Source of the dataset.
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None |
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Version notes
Version notes about the dataset.
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Is version of another dataset
Link to dataset that it is a version of.
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Other versions
Link to datasets that are versions of it.
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Provenance Text
Provenance Text of the data.
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Conservation Ontario |
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Provenance URL
Provenance URL of the data.
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Temporal resolution
Describes how granular the date/time data in the dataset is.
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GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
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GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
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Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
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Community Permission
Community permission (who gave permission).
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The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
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Number of data rows
If tabular dataset, total number of rows.
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46 |
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Number of data columns
If tabular dataset, total number of unique columns.
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15 |
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Number of data cells
If tabular dataset, total number of cells with data.
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690 |
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Number of data relations
If RDF dataset, total number of triples.
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Number of entities
If RDF dataset, total number of entities.
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Number of data properties
If RDF dataset, total number of unique properties used by the triples.
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Data quality
Describes the quality of the data in the dataset.
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Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.
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