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Hydrologic design of storm sewers, culverts, retention/detention basins and other components of storm water management systems are typically performed based on specified design storms derived from the rainfall intensity-duration-frequency (IDF) estimates and an assumed temporal distribution of rainfall. Use of inappropriate data or design storms could lead to malfunctions of the infrastructure systems: over-estimation may result in costly over-design or under-estimation may be associated with risk and human safety. One of the expected hydroclimatic impacts of climate change for London is the increase in the magnitude and frequency of extreme rainfalls which can have serious impact on the design, operation and maintenance of existing municipal water infrastructure.
This study presents a methodology for updating the rainfall IDF curves for the City of London incorporating various uncertainties associated with the assessment of climate change impacts on a local scale. Overall, two objectives have been achieved: first, an extensive investigation of the possible realizations of future climate from 29 scenarios developed from Atmosphere-Ocean Global Climate Models (AOGCM) and scenarios are performed using a downscaling based disaggregation approach. Annual maximum series of rainfall are fitted to Gumbel distribution to develop IDF curves for 1, 2, 6, 12 and 24 hour durations for 2, 5, 10, 25, 50 and 100 years of return periods. Next, the associated uncertainties are estimated using nonparametric kernel estimation approach and the resultant IDF curve is developed based on a probabilistic approach.
The results indicate that rainfall patterns in the City of London will most certainly change in future due to climate change. The use of the multi-model approach, rather than a single scenario is encouraged. Inherent uncertainties associated with different AOGCMs are quantified by a kernel based plug-in estimation approach. The resultant scenario indicates approximately 20- 40% changes in different duration rainfalls for all return periods. Use of a probability based intensity-duration-frequency curve is encouraged in order to apply the updated IDF information with higher level of confidence.
Department of Civil and Environmental Engineering, The University of Western Ontario
London, Ontario, Canada
Civil and Environmental Engineering
Solaiman, Tarana A. and Simonovic, Slobodan P., "Development of Probability Based Intensity- Duration-Frequency Curves under Climate Change" (2011). Water Resources Research Report. Book 34.