Initiative #99
Improved freshwater runoff modelling in Eastern Canada to drive ocean models
Listed in the registry Pilot Original language : English
About the initiative
Description of the initiative
Use Neural Networks to post-process streamflow simulations from the WRF-Hydro model, improving their agreement with observational data. These neural networks are applied as a downstream calibration step. Builds synergy between traditional calibration methods and modern AI techniques in hydrologic modeling.
AI family
Automation and Decision Support
- AI sub-category
- Predictive Analytics
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Lifecycle
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Ideation
Stage status : Completed
June 1, 2025
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Assessment
Stage status : Completed
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Approved
Stage status : Completed
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Development
Stage status : Completed
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Pilot
Stage status : In progress
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Production
Stage status : Upcoming
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Archived
Stage status : Upcoming
Schedule for this initiative
- Completed
- In progress
- Planned
- Not applicable
- Today
- Ideation
A similar need?
Nobody has come forward yet. If your team faces the same problem, say so: it helps bring initiatives together and share a solution.
Contacts
- Requester
- Smith, Melannie
- Sector contact
- Smith, Melannie
- Subject matter expert
- Winegardner, Amanda
- Smith, Melannie
Data and tools
- Sector
- Ecosystems and Oceans Science
- Region
- National Capital Region
- Could this initiative be shared with the Treasury Board Secretariat?
- Yes
- Submitted on
- June 1, 2025
Primary users
- Departmental employees
Government priorities and declaration
Declared to TBS Recorded as transmitted to TBS; not editable here.
- Declared name of the AI system
- Improving Streamflow Simulations with Neural Network Post-Processing
- TBS registry identifier
- 2526-DFO-MPO-016
- Status declared to TBS
- Pilot
- Sent to TBS on
- October 10, 2025
- Purpose of the system, as declared
- This project applied neural networks to post-process streamflow outputs from the WRF-Hydro model, improving alignment with observational data. The approach serves as a downstream calibration step, building synergy between traditional hydrologic calibration methods and modern AI techniques.