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Open Engineering

formerly Central European Journal of Engineering

Editor-in-Chief: Ritter, William

CiteScore 2018: 0.91

SCImago Journal Rank (SJR) 2018: 0.211
Source Normalized Impact per Paper (SNIP) 2018: 0.655

ICV 2018: 121.06

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Monitoring the future behaviour of urban drainage system under climate change: a case study from north-western England

Yassin Z. Osman
  • Corresponding author
  • Department of Civil Engineering and Construction, ESS Group, University of Bolton, Deane Road, Bolton, BL3 5AB, UK
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Published Online: 2014-11-25 | DOI: https://doi.org/10.1515/eng-2015-0003


Catchments hydrological conditions and responses are anticipated to be affected by the changes in weather patterns, increasing in climate variability and extreme rainfall. Thus, engineers have no choice but to consider climate change in their practices in order to adapt and serve the public interests. This paper is an exploration of the impacts of climate change on the hydrology that underlies the hydraulic design of urban drainage system. Future rainfall has been downscaled from the Global Climate Model (GCM) employing a hybrid Generalised Linear Model (GLM) and Artificial Neural Network (ANN) downscaling techniques under different greenhouse emission scenarios. The output from this model is applied to a combined sewer system of an urban drainage catchment in the Northwest of England during the 21st Century to monitor its future behaviour in winter and summer seasons. Potential future changes in rainfall intensity are expected to alter the level of service of the system, causing more challenges in terms of surface flooding and increase in surcharge level in sewers. The results obtained demonstrate that there is a real chance for these effects to take place and therefore would require more attention from designers and catchment managers.

Keywords : Urban drainage; Climate change; Combined Sewer System; Artificial Neural Network; Storm water; InfoWorks CS


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About the article

Received: 2014-08-03

Accepted: 2014-09-02

Published Online: 2014-11-25

Citation Information: Open Engineering, Volume 5, Issue 1, ISSN (Online) 2391-5439, DOI: https://doi.org/10.1515/eng-2015-0003.

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© 2015 A. S. Sayyad et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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