Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
The Royal Institution for the Advancement of Learning/McGill University
$290,750.00
Seasonal prediction of ice conditions in the St. Lawrence Seaway using AI
EF 2021-22 · 2021-09-01
Résumé
Knowledge of ice conditions from freeze-up to break-up is critical for hydrological forecasting and monitoring, as well as for safe operation of ships in icy waters. However, forecasts of ice conditions are almost nonexistent for the St-Lawrence Seaway, a major shipping channel in Canada. This project will develop a forecast model for the (sub-) seasonal evolution of ice conditions in the St-Lawrence River based on Machine Learning. The purpose of these predictions is to aid stakeholders in decision-making and risk analysis for their activities. Ideally, the forecasts will have a lead-time of 30 to 60 days and will be updated daily. First, the model will focus on forecasting ice conditions in the St-Lawrence Seaway, since there is currently a lack of ice forecasts in this region. The model will then be extended to the Estuary/Gulf of the St-Lawrence River if the forecasts for the Seaway are shown to be skillful.
Ministère
Programme
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Emplacement
Montreal|Montréal, Quebec, Canada
Type de bénéficiaire
Academia
Numéro d'entreprise
119128981
Type
Grant
Source
Proactive Disclosure - Grants and Contributions
Modifications
Chaque version de l'entente telle que publiée, de la plus ancienne à la plus récente, avec son total à cette version. Le montant ci-dessus est le plus récent.
| Modification | Date | Exercice financier | Total |
|---|---|---|---|
| 0 | 2021-09-01 | 2021-22 | $290,750.00 |
| 1 | 2021-09-01 | 2021-22 | $290,750.00 |
Tel que publié
Additional Information
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 365 days.
Additional Information (French)
Cet accord a été modifié 1 fois. La date de fin du présent accord a été changé de 365 jours.
Agreement End Date
2025-08-31
Agreement Number
978108
Agreement Start Date
2021-09-01
Agreement Title
Seasonal prediction of ice conditions in the St. Lawrence Seaway using AI
Agreement Title (French)
Prévisions saisonnières de l’état de la glace sur la voie maritime du Saint-Laurent à l’aide de l’intelligence artificielle
Agreement Type
Grant
Agreement Value
$290,750.00
Amendment Date
2024-08-26
Amendment Number
1
Description
Knowledge of ice conditions from freeze-up to break-up is critical for hydrological forecasting and monitoring, as well as for safe operation of ships in icy waters. However, forecasts of ice conditions are almost nonexistent for the St-Lawrence Seaway, a major shipping channel in Canada. This project will develop a forecast model for the (sub-) seasonal evolution of ice conditions in the St-Lawrence River based on Machine Learning. The purpose of these predictions is to aid stakeholders in decision-making and risk analysis for their activities. Ideally, the forecasts will have a lead-time of 30 to 60 days and will be updated daily. First, the model will focus on forecasting ice conditions in the St-Lawrence Seaway, since there is currently a lack of ice forecasts in this region. The model will then be extended to the Estuary/Gulf of the St-Lawrence River if the forecasts for the Seaway are shown to be skillful.
Description (French)
Prévisions saisonnières de l’état de la glace sur la voie maritime du Saint-Laurent à l’aide de l’intelligence artificielle
Expected Results
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
Ville-Marie--Le Sud-Ouest--Île-des-Soeurs
Federal Riding (French)
Ville-Marie--Le Sud-Ouest--Île-des-Soeurs
Federal Riding Number
24077
NAICS Code
541710 - R&D in the physical, engineering and life sciences
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
Program Purpose
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
119128981
Recipient City
Montreal|Montréal
Recipient Country
CA
Recipient Legal Name
The Royal Institution for the Advancement of Learning/McGill University
Recipient Postal Code
H3A 2M7
Recipient Province or Territory
QC
Recipient Type
S
Reference Number
172-2021-2022-Q2-978108
