Revision of urban drainage design rules after assessment of climate change impacts on precipitation extremes at Uccle, Belgium

2013 ◽  
Vol 496 ◽  
pp. 166-177 ◽  
Author(s):  
P. Willems
2010 ◽  
Vol 62 (5) ◽  
pp. 1170-1176 ◽  
Author(s):  
V.-T.-V. Nguyen ◽  
N. Desramaut ◽  
T.-D. Nguyen

The main objective of the present study is to propose a method for estimating an optimal temporal storm pattern for urban drainage design in southern Quebec (Canada) in the context of climate change. Following a systematic evaluation of the performance of eight popular design storm models for different typical urban basins, it was found that the Canadian Atmospheric Environment Service (AES) storm pattern and the Desbordes model (with a peak intensity duration of 30 min) were the most accurate for estimating runoff peak flows while the Watt model gave the best estimation of runoff volumes. Based on these analyses, an optimal storm pattern was derived for southern Quebec region. The proposed storm pattern was found to be the most suitable for urban drainage design in southern Quebec since it could provide accurate estimation of both runoff peak flow and volume. Finally, a spatial-temporal downscaling method, based on a combination of the spatial statistical downscaling SDSM technique and the temporal scaling General Extreme Value distribution, was used to assess the climate change impacts on the proposed optimal design storm pattern and the resulting runoff properties.


2014 ◽  
Vol 119 (18) ◽  
pp. 10,799-10,812 ◽  
Author(s):  
Marc d'Orgeville ◽  
W. Richard Peltier ◽  
Andre R. Erler ◽  
Jonathan Gula

2013 ◽  
Vol 68 (1) ◽  
pp. 16-28 ◽  
Author(s):  
K. Arnbjerg-Nielsen ◽  
P. Willems ◽  
J. Olsson ◽  
S. Beecham ◽  
A. Pathirana ◽  
...  

A review is made of current methods for assessing future changes in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic-induced climate change. The review concludes that in spite of significant advances there are still many limitations in our understanding of how to describe precipitation patterns in a changing climate in order to design and operate urban drainage infrastructure. Climate change may well be the driver that ensures that changes in urban drainage paradigms are identified and suitable solutions implemented. Design and optimization of urban drainage infrastructure considering climate change impacts and co-optimizing these with other objectives will become ever more important to keep our cities habitable into the future.


2017 ◽  
Vol 21 (12) ◽  
pp. 6461-6483 ◽  
Author(s):  
Poulomi Ganguli ◽  
Paulin Coulibaly

Abstract. In Canada, risk of flooding due to heavy rainfall has risen in recent decades; the most notable recent examples include the July 2013 storm in the Greater Toronto region and the May 2017 flood of the Toronto Islands. We investigate nonstationarity and trends in the short-duration precipitation extremes in selected urbanized locations in Southern Ontario, Canada, and evaluate the potential of nonstationary intensity–duration–frequency (IDF) curves, which form an input to civil infrastructural design. Despite apparent signals of nonstationarity in precipitation extremes in all locations, the stationary vs. nonstationary models do not exhibit any significant differences in the design storm intensity, especially for short recurrence intervals (up to 10 years). The signatures of nonstationarity in rainfall extremes do not necessarily imply the use of nonstationary IDFs for design considerations. When comparing the proposed IDFs with current design standards, for return periods (10 years or less) typical for urban drainage design, current design standards require an update of up to 7 %, whereas for longer recurrence intervals (50–100 years), ideal for critical civil infrastructural design, updates ranging between  ∼ 2 and 44 % are suggested. We further emphasize that the above findings need re-evaluation in the light of climate change projections since the intensity and frequency of extreme precipitation are expected to intensify due to global warming.


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