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Grant: Alliance Grants

University of Waterloo

$138,000.00

From data to knowledge: Designing user-driven nutrient loading observatories across the Great Lakes Basin

EF 2022-23

Résumé
The health of the Great Lakes has been an ongoing concern for decades. The Great Lakes are vital to the well-being of Canadians as they contain almost 20% of the world's surface freshwater, creating billions of dollars in economic activity, and providing drinking water for 1 in 4 Canadians. One of the greatest threats to water quality in the lower Great Lakes is the increasing frequency and severity of algal blooms. These occur in response to excess nutrients, such as phosphorus, that enter our waterways from agricultural and urban land uses. Binational targets have been developed to address water quality challenges, such as those driven by the 2012 Great Lakes Water Quality Agreement (GLWQA), which resulted in a commitment by Canada and the U.S. to reduce phosphorus loads to Lake Erie by 40%. For Canada to meet such goals, it is crucial to know the hotspots where nutrients are entering waterways. This is challenging, given water quality monitoring is limited and there are large gaps in data, resulting in a lack of the knowledge needed to make informed decisions. Our project will address this gap by developing a web-based tool WATERSCAPES that will use current sparse concentration and daily discharge data, and use sophisticated statistical and machine learning models to predict daily concentrations and loads across the Great Lakes basin. Water quality datasets will be provided by our partners (Federal government, Provincial government, Credit valley Conservation Authority, DataStream), and the research team will use this along with a suite of predictor variables such as temperature, slope, precipitation and land use for model development. The portal will be free and accessible to all and provide conservation authorities and regulatory agencies the critical information they need to prioritise additional monitoring, as well as design targeted and cost-effective measures for reducing pollution in watersheds. The new knowledge generated using this tool will not only help inform how Canada can meet its water quality targets, but will also contribute to the actions required to engage and empower communities, provide access to safe, high-quality drinking water, support healthy habitats, and allow for recreational use of the lakes.
Programme
Alliance Grants
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
571718-2021
Name nom
Basu, Nandita NB
Department département
Civil & Environmental Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2021
Award amount
138000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1002
Area of application group en
Northern development
Area of application group fr
Développement du nord
Area of application en
Environment
Area of application fr
Environnement
Research subject code
1501
Research subject group en
Environmental engineering
Research subject group fr
Génie de l'environnement
Research subject en
Water quality, pollution
Research subject fr
Qualité de l'eau, pollution
Installment
inst:1
Partie
1
Nb partie
1
Application title
From data to knowledge: Designing user-driven nutrient loading observatories across the Great Lakes Basin
Application summary
The health of the Great Lakes has been an ongoing concern for decades. The Great Lakes are vital to the well-being of Canadians as they contain almost 20% of the world's surface freshwater, creating billions of dollars in economic activity, and providing drinking water for 1 in 4 Canadians. One of the greatest threats to water quality in the lower Great Lakes is the increasing frequency and severity of algal blooms. These occur in response to excess nutrients, such as phosphorus, that enter our waterways from agricultural and urban land uses. Binational targets have been developed to address water quality challenges, such as those driven by the 2012 Great Lakes Water Quality Agreement (GLWQA), which resulted in a commitment by Canada and the U.S. to reduce phosphorus loads to Lake Erie by 40%. For Canada to meet such goals, it is crucial to know the hotspots where nutrients are entering waterways. This is challenging, given water quality monitoring is limited and there are large gaps in data, resulting in a lack of the knowledge needed to make informed decisions. Our project will address this gap by developing a web-based tool WATERSCAPES that will use current sparse concentration and daily discharge data, and use sophisticated statistical and machine learning models to predict daily concentrations and loads across the Great Lakes basin. Water quality datasets will be provided by our partners (Federal government, Provincial government, Credit valley Conservation Authority, DataStream), and the research team will use this along with a suite of predictor variables such as temperature, slope, precipitation and land use for model development. The portal will be free and accessible to all and provide conservation authorities and regulatory agencies the critical information they need to prioritise additional monitoring, as well as design targeted and cost-effective measures for reducing pollution in watersheds. The new knowledge generated using this tool will not only help inform how Canada can meet its water quality targets, but will also contribute to the actions required to engage and empower communities, provide access to safe, high-quality drinking water, support healthy habitats, and allow for recreational use of the lakes.