Grants and Contributions:

Title:
Towards an integrated hydro-chemical understanding of phosphorus transport from headwater agro-ecosystems
Agreement Number:
RGPIN
Agreement Value:
$135,000.00
Agreement Date:
May 10, 2017 -
Organization:
Natural Sciences and Engineering Research Council of Canada
Location:
Ontario, CA
Reference Number:
GC-2017-Q1-02900
Agreement Type:
Grant
Report Type:
Grants and Contributions
Additional Information:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Recipient's Legal Name:
Wellen, Christopher (University of Windsor)
Program:
Discovery Grants Program - Individual
Program Purpose:

Agricultural intensification is necessary to meet the food demands of the growing world population and economy. However, food production can cause water quality impairments through loss of nutrients, including phosphorus. Indeed, excessive algal growth caused by excessive phosphorus inputs are the primary water quality impairment in freshwater ecosystems around the world and around Canada. Watershed models are often used to understand the factors that control the loss of phosphorus in agroecosystems and to predict how long it will take for reduced nutrient inputs to translate into reduced nutrient outputs and water quality benefits. However, watershed models have been criticized for their simplistic representation of hydrology, which may strongly affect the lag time required to realize nutrient outputs. The ability of catchment water quality models to represent processes in cold regions has also been questioned. The focus of the proposed work is to understand how agricultural headwaters function to transport water and phosphorus in cold regions. Using watershed models designed specifically for cold regions as well as environmental tracers, I will quantify the lag times to realize improvements in stream water quality at the headwaters after changes to phosphorus inputs are made. These estimates are essential to crafting policy that can protect the environment while allowing the agricultural sector of the economy to grow, while integrating environmental tracers will ensure that the model estimates of lag times are robust.