Abstract
Copyright: © 2013 Liserra T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Loads acting on urban drainage systems are intrinsically uncertain and often known with limited details given their physical complexity. External loads include climate variables (rain, snow, temperature ...), which have a naturally mutable behaviour, exacerbated by climate change. Other system variables, such as roughness of surfaces and soil permeability, are normally unknown and only partially measurable. Additional sources of uncertainty derive from the transposition of the physical system into numerical models, routinely used to make predictions about real systems and their design and management.
Highlights
In urban drainage systems, aleatory uncertainty mainly affects external forcing: e.g., one cannot predict exactly the maximum rainfall intensity that will occur year, even when sufficient data are available
The design of storm and combined drainage systems is based on rainfall intensity and involves the determination of the size of the conduits necessary to achieve the design hydraulic conveyance
While the overall effect of climate change on sewer design is yet to be ascertained, it should be noted that all the aforementioned approaches to the selection of rainfall design data are based on the usage of historical data as an indication of future conditions, with an assumption of statistical stationarity
Summary
External loads include climate variables (rain, snow, temperature ...), which have a naturally mutable behaviour, exacerbated by climate change. Additional sources of uncertainty derive from the transposition of the physical system into numerical models, routinely used to make predictions about real systems and their design and management. Probabilistic analyses of civil structures [1] distinguish two types of uncertainty: aleatory and epistemic. The former is inherent in a nondeterministic phenomenon due to its randomness, and originates from variability in known or observable data. Aleatory uncertainty mainly affects external forcing: e.g., one cannot predict exactly the maximum rainfall intensity that will occur year, even when sufficient data are available. We provide a review on the main sources of uncertainty in urban water systems and the related design and management issues
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