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AI-Powered Dissolved Oxygen Forecasting for Atlantic Estuaries

Ecology · Planning & Decision-making

What it collects

About a measurement
Anonymized data
  • Environmental sensor readings from North Atlantic estuaries — including water quality measurements such as dissolved oxygen levels, temperature, salinity, and related oceanographic parameters used as model inputs.
About a place
Anonymized data
  • Spatial data describing the characteristics and locations of North Atlantic estuary sites, including highly degraded sites referenced in model training and evaluation.
Run by
National Research Council Canada (NRC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

EcologyPlanning & Decision-making

This system uses machine learning to predict dissolved oxygen levels in North Atlantic estuaries days in advance, helping environmental managers detect low-oxygen events before they harm marine life. It is operated by the National Research Council Canada and is currently in development. It does not collect or process personal information, and users of the system are not currently informed of the AI's role in generating predictions.

What it collects and what happens to it

Data taken in

About a measurement
Anonymized data
  • Environmental sensor readings from North Atlantic estuaries — including water quality measurements such as dissolved oxygen levels, temperature, salinity, and related oceanographic parameters used as model inputs.
About a place
Anonymized data
  • Spatial data describing the characteristics and locations of North Atlantic estuary sites, including highly degraded sites referenced in model training and evaluation.

Processing

Classification & Prediction
  • Machine learning models (described as outperforming traditional deep learning methods) that predict dissolved oxygen concentrations and forecast low-oxygen events in estuary water bodies based on historical and real-time environmental data.

What it does

Deciding (Analytical AI)
Human decides
  • The system predicts and scores dissolved oxygen levels from environmental sensor data, producing forecasts that environmental managers use to make resource management decisions. Humans decide how to act on the predictions.

Outputs

About a measurement
Anonymized data
  • Predicted dissolved oxygen level values and forecasts of low-oxygen events in estuary waters, produced days in advance to support environmental monitoring and management decisions.
A recommendation or prediction
Anonymized data
  • Forecasts of upcoming eutrophication events or harmful algal blooms provided to environmental managers as advisories for proactive intervention in coastal ecosystem management.

Run by

National Research Council Canada (NRC)
  • NRC Canada is the federal science and technology organization responsible for developing and deploying this dissolved oxygen prediction system for Atlantic estuary ecosystems.

Government of Canada AI Register — 2526-NRC-CNRC-008

Built by

Government of Canada
  • The system was developed internally by the Government of Canada — no third-party vendor is identified in the register entry.

Government of Canada AI Register — 2526-NRC-CNRC-008

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs (dissolved oxygen predictions and forecasts) are available to GC employees identified as the primary users. The register does not indicate broader public access to model outputs.

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.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Algorithmic TransparencyThe register notes that AI use is not currently disclosed to users (GC employees). As the system moves toward operational deployment, users should be informed that predictions are AI-generated. For more information, contact the National Research Council Canada.

Risks and safeguards

  • Civil liberties harmThe system is currently in development and AI use is not disclosed to users (GC employees), which may limit informed oversight of automated predictions.Safeguard: The system does not involve personal information and its outputs are advisory, reducing risk of direct civil liberties impact. Disclosure practices should be reviewed before operational deployment.