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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.
Sapna Sharma;Usman Khan
Luke Moslenko
Pollution Probe
Biology
Professional, scientific and technical services
York University
Accelerate
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