Abstract

In recent years, there has been a growing interest to understand how climate change will affect the management of urban drainage systems. The performance assessment of urban stormwater infrastructure re-quires precipitation data on a spatial scale of tens of square kilometres and on a range of time scales from 15 min to 24 h. However, the spatial and temporal averaging methods that are used by global climate models (GCMs) to predict precipitation are typically of the order of a few hundred square kilometers, and of months or seasons respectively. This mismatch of spatial and temporal scales has prompted research to bridge the gap and produce rainfall intensity-duration-frequency (IDF) relationships that can be used to assess the impacts of climate change on stormwater infrastructure.

In this chapter, a method is presented that takes a different approach to address this gap. Instead of looking at the effects of climate change on the return period (frequency) of different intensity-duration rainfall events, the effects of climate change on component reliability are examined. This is accomplished by relating component reliability to intensity-duration values using the hydraulic risk function, the extreme value (type I) distribution (EVD-I), and historical rainfall data. To examine the effects of climate change on component reliability, historical rainfall data are used to ascertain the mean and standard deviation of the EVD-I for hourly rainfall extremes and then a correction factor, based on physical constraint governed by the Clausius-Clapeyron rela-tion, is applied to these distributions to determine the change in component reliability. With these correlations and the intensity-duration-reliability functions, one can examine how changes in climate parameters, which are provided by GCMs, influence changes in compo-nent reliability. This is demonstrated using hourly rainfall data from five cities on the Canadian prairies.

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