AI-Powered Inland Water Quality Monitoring and Change Detection
Ecology · Environmental Health
What it collects
- Synthetic Aperture Radar (SAR) data from Copernicus Sentinel-1 satellites — microwave backscatter imagery used to detect surface water conditions regardless of cloud cover or daylight.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Multispectral imagery from Planet Labs satellites, capturing visible and near-infrared spectral bands to assess water surface characteristics such as turbidity and algal presence.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Hyperspectral imagery from Wyvern, providing fine-grained spectral resolution across hundreds of bands to identify specific water quality parameters and contaminants.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- In-situ water quality readings from ECCC monitoring buoys, providing ground-truth physical and chemical measurements (e.g. temperature, dissolved oxygen, conductivity) to calibrate and validate model outputs.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Run by
- Environment and Climate Change Canada (ECCC)
- Where
- No fixed location
- Kept
- Not stated by the Helpful Places.
- Shared with
- Accountable organization
- Your copy
- You cannot see the data it holds about you. What you can do
What it is for
Ecology
Environmental HealthThis system uses artificial intelligence applied to satellite and sensor data to automatically detect when the quality of inland water bodies is degrading. It is developed by Environment and Climate Change Canada and is currently in development — not yet in live operation. The system does not collect or process any personal information about members of the public; its outputs are intended for Government of Canada employees responsible for water quality oversight.
What it collects and what happens to it
Data taken in
- Synthetic Aperture Radar (SAR) data from Copernicus Sentinel-1 satellites — microwave backscatter imagery used to detect surface water conditions regardless of cloud cover or daylight.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Multispectral imagery from Planet Labs satellites, capturing visible and near-infrared spectral bands to assess water surface characteristics such as turbidity and algal presence.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Hyperspectral imagery from Wyvern, providing fine-grained spectral resolution across hundreds of bands to identify specific water quality parameters and contaminants.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- In-situ water quality readings from ECCC monitoring buoys, providing ground-truth physical and chemical measurements (e.g. temperature, dissolved oxygen, conductivity) to calibrate and validate model outputs.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
Processing
- Machine learning classifiers and probabilistic models process remote sensing and buoy data to produce predictions of water quality degradation events and classify their severity or type.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- The system flags unusual departures from baseline water quality signatures in remote sensing data, identifying change events that warrant further scientific investigation.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
What it does
- Machine learning and probabilistic modelling are used to classify and score remote sensing observations for water quality change, producing outputs reviewed by Government of Canada environmental scientists.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- The system ingests raw satellite imagery (SAR, multispectral, hyperspectral) and converts pixel signals into structured water quality indicators for downstream analytical processing.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
Outputs
- Water quality change detection alerts and scores assigned to inland water body locations, indicating the presence, type, or severity of detected degradation events for review by GC employees.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Geospatially located outputs identifying which inland water bodies have been flagged for quality changes, enabling targeted follow-up monitoring and response by environmental scientists.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
Run by
- The federal department responsible for developing and deploying this AI system, operating through its Digital Service Branch — Emerging Technology and Experimentation Division.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
Built by
Not stated by the Helpful Places.
Kept for
Not stated by the Helpful Places.
Shared with
- The system does not involve personal information. Outputs are remote sensing analysis results and are not accessible to members of the public as individual records. The system's use of AI has not been disclosed to users (noted as 'N' in the register).
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Detection outputs are available to Government of Canada employees, specifically scientific and operational staff at Environment and Climate Change Canada responsible for water quality oversight.
Government of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
Stored
Not stated by the Helpful Places.
How to read the colours
Can it identify you?
- Anonymized data
- Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
- Pseudonymous data
- Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
- Identifiable data
- The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.
Who completes the loop?
- Human decides
- This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
- Human executes
- This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
- Autonomous
- This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.
Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)Environment and Climate Change Canada, Government of Canada AI Register entry 2526-ECCC-010.
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- AI registerGovernment of Canada AI Register — Water Quality Change Detection (2526-ECCC-010)
- Register entryPublished by the Helpful Places. Reference 9486908d. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
What you can do
Ask about this system
Questions go to the Helpful Places, not the vendor.
Your rights
- Right to Algorithmic TransparencyThis system does not process personal information and currently does not disclose its use of AI to users (noted as 'N' in the official register). As the system matures toward production, members of the public and Government of Canada employees may seek information about how it works through the Directive on Automated Decision-Making transparency provisions or by contacting Environment and Climate Change Canada.
Risks and safeguards
- Reputational harmRisk of false positive or false negative detections that could mislead environmental management decisions — for example, failing to detect an actual contamination event or flagging clean water bodies unnecessarily.Safeguard: the system is in development and outputs are reviewed by GC scientists before any action is taken; probabilistic modelling is used to characterize uncertainty in detections; ground-truth buoy data is used for calibration and validation.