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The impact of climate change on sewer infrastructure performance in Toronto, Ontario, Canada

Congress: 2008
Author(s): Barry J. Adams, Ph.D, P.Eng
University of Toronto, Civil Engineering Department 35 St George St, Toronto, Canada Tel: 416-946-0164 E-mail: adams@ecf.utoronto.ca

Keyword(s): Climate Change, Stormwater System Performance, Analytical Probabilistic Models, Time Series Analysis
AbstractGiven the scientific consensus that global climate is changing, it is fundamental to determine potential impacts on local climate conditions and on urban drainage infrastructure. In recent years, several studies have focused on determining the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. Several methods are routinely employed, including regional climate models, statistical downscaling and mesoscale models. For this study, historical precipitation data from Toronto, Ontario, Canada is examined using time series analysis techniques in order to determine trends in runoff quantities and stormwater system performance indicators (annual runoff volume, annual number of overflows, annual overflow volume and annual fraction of runoff controlled) under the impact of climate change. The forecasted rainfall characteristics were then input to Analytical Probabilistic Models (APMs) developed at the University of Toronto to identify projected changes in stormwater performance indicators for a runoff control system with downstream storage and treatment. Trend analyses indicate that the annual number of rainfall events and annual mean event durations are increasing while the annual mean event intensities are decreasing. Further analyses revealed that much of the increase in precipitation exhibited in the historical record was the result of changes in small events (less than 2mm). With the removal of rainfall event less than 2mm, an increasing trend remained for the annual number of events and there were no significant trends found for the other rainfall event characteristics. These findings were corroborated by the time series analysis of extreme events and by other Canadian studies that all failed to detect significant trends in Canadian extreme weather events. Acknowledging the inherent uncertainty in extrapolating future weather patterns based on currents trends, a sensitivity analysis was also performed on the event characteristics. This analysis revealed that the stormwater system performance is most sensitive to changes in event volume and annual number of events, while event duration and interevent time has little impact on stormwater performance indicators. According to current trends and assuming no change in current design parameters (storage volume and treatment rate), there will be an increase in Toronto’s mean annual runoff volume over the next 30 years. APMs predict a 5% increase in the annual number of overflows and the overflow volume. However, removing events less than 2mm from the record results in a 30% increase in both the annual number of overflows and the overflow volume. This indicates that in order to maintain current levels of runoff control, more robust designs will be needed.
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