Grant: Strategic Projects - Group
Trent University
$98,265.00
Catchment-scale modelling of carbon fluxes in the Great Lakes basin
FY 2006-07
Summary
The purpose of this proposal is to develop a catchment-scale carbon model for the Great Lakes basin that can be used to predict dissolved organic carbon (DOC) fluxes from the Canadian portion of the terrestrial environment into the Great Lakes. This is important because the breakdown of DOC can lead to the production of significant quantities of greenhouse gases. We will focus on several large watersheds that will be selected to represent dominant land use categories; those draining into Lakes Erie and/or Ontario will be predominately agricultural while those draining into Huron and/or Superior will be primarily forested. Our intent is to extrapolate our results to other parts of the Great Lakes basin so that we can estimate total carbon flux. We plan to employ two very different modelling approaches in this study. Firstly, we will use a simple approach based on empirical relationships relating land use and dissolved organic carbon (DOC) flux from catchments, and relating water chemistry and partitioning of carbon between permanent storage in lake sediments and degradation to produce greenhouse gases. The latter pathway contributes to Canada's greenhouse gas emissions. This approach will allow us to estimate the organic carbon flux into the Great Lakes from the Canadian side. However, this is a steady-state model, and it cannot be used to make direct predictions about the impacts of changes in external factors, e.g. climate, on DOC flux. The second approach will utilize process-based dynamic modelling. We will start with two existing models, one a nutrient model (INCA) that has been widely used in the study of nitrogen, and the other (MAGIC) a catchment-scale biogeochemistry model that has been widely used in the study of soil and water acidification. Each of these models can be adapted to include a carbon. The former model is driven by land use and hydrologic data, while the latter utilizes hydrologic data, soil and water chemistry and information about anthropogenic stressors, particularly acid deposition. Each can and has been linked to climate change through both alterations to hydrology and through climate-related effects on processes such as mineralization rates.
Program
Strategic Projects - Group
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
336422-2006
Name nom
Dillon, Peter
Department département
Environmental and Resource Studies
Organization id
32
Institution établissement
Trent University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2006
Competition year année de concours
2006
Award amount
98265
Program id
STPGP
Program name en
Strategic Projects - Group
Program name fr
Projets stratégiques - De groupe
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1045
Committee name en
Strategic Projects Selection Panel - Environment
Committee name fr
Comité de sélection des projets stratégiques - Environnement
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
4201
Research subject group en
Geochemistry and geochronology
Research subject group fr
Géochimie et géochronologie
Research subject en
Environmental geochemistry
Research subject fr
Géochimie environnementale
Partie
1
Nb partie
3
Application title
Catchment-scale modelling of carbon fluxes in the Great Lakes basin
Keyword
NA
Application summary
The purpose of this proposal is to develop a catchment-scale carbon model for the Great Lakes basin that can be used to predict dissolved organic carbon (DOC) fluxes from the Canadian portion of the terrestrial environment into the Great Lakes. This is important because the breakdown of DOC can lead to the production of significant quantities of greenhouse gases. We will focus on several large watersheds that will be selected to represent dominant land use categories; those draining into Lakes Erie and/or Ontario will be predominately agricultural while those draining into Huron and/or Superior will be primarily forested. Our intent is to extrapolate our results to other parts of the Great Lakes basin so that we can estimate total carbon flux. We plan to employ two very different modelling approaches in this study. Firstly, we will use a simple approach based on empirical relationships relating land use and dissolved organic carbon (DOC) flux from catchments, and relating water chemistry and partitioning of carbon between permanent storage in lake sediments and degradation to produce greenhouse gases. The latter pathway contributes to Canada's greenhouse gas emissions. This approach will allow us to estimate the organic carbon flux into the Great Lakes from the Canadian side. However, this is a steady-state model, and it cannot be used to make direct predictions about the impacts of changes in external factors, e.g. climate, on DOC flux. The second approach will utilize process-based dynamic modelling. We will start with two existing models, one a nutrient model (INCA) that has been widely used in the study of nitrogen, and the other (MAGIC) a catchment-scale biogeochemistry model that has been widely used in the study of soil and water acidification. Each of these models can be adapted to include a carbon. The former model is driven by land use and hydrologic data, while the latter utilizes hydrologic data, soil and water chemistry and information about anthropogenic stressors, particularly acid deposition. Each can and has been linked to climate change through both alterations to hydrology and through climate-related effects on processes such as mineralization rates.