Developing a watershed approach to manage anthropogenic and environmental stressors in an eastern Lake Ontario watershed

Water quality in the watersheds of the Great Lakes are under ever-increasing pressures from population growth, urban expansion, economic development, nutrient enrichment, and climate change. We aim to develop a statistical model to understand the relative influence of anthropogenic stressors on water quality for the central Lake Ontario watershed surrounding the cities of Oshawa, Whitby, and Ajax. The project will: review potential ecological, water quality, climate, population, land cover, social, and economic data sources from global re-analysis data, open-access databases, government, industry, environmental networks, and scientific literature; and develop a basic prototype of a machine-learning data intensive watershed analytical approach to understand how anthropogenic stressors impact water quality. These models will be used to forecast water quality conditions under different scenarios of population growth and climate change. The results of this research will be useful for non-profit government organizations, conservation agencies, and urban planners to manage water quality in the Great Lakes watershed.

Intern: 
Luke Moslenko
Faculty Supervisor: 
Sapna Sharma;Usman Khan
Province: 
Ontario
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