Modeling the Impacts of Atmospheric Deposition on Water Quality in Lake Ontario Under Climate Change Scenarios

Water quality in urban areas in Canada is a major issue despite the fact that it has excessive resources of freshwater. Current methods of addressing the impacts of atmospheric deposition and climate change on water quality are inadequate. Physical methods are too complex and usually ignore the impacts of atmospheric deposition. Therefore, in this research two categories of data driven models have been developed using artificial neural networks to model the atmospheric deposition and water quality. These models were developed in three regions near Lake Ontario: Toronto, Cobourg, and Grimsby regions which have different characteristics of population and air contamination. The results showed in future, the atmospheric deposition contamination in summers and autumns will become higher than the present situation. However, the precipitation contamination in winters will be lower. Moreover, the atmospheric deposition can not influence the water quality of Lake Ontario considerably.