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Flood Risk Assessment for Urban Drainage System in a Changing Climate Using Artificial Neural Network

Abdellatif, MEM and Atherton, W and Alkhaddar, R and Osman, Y (2015) Flood Risk Assessment for Urban Drainage System in a Changing Climate Using Artificial Neural Network. Natural Hazards, 79 (2). pp. 1059-1077. ISSN 0921-030X

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Abstract

Changes in rainfall patterns due to climate change are expected to have negative impact on urban drainage systems, causing increase in flow volumes entering the system. In this paper, two emission scenarios for greenhouse concentration have been used, the high (A1FI) and the low (B1). Each scenario was selected for purpose of assessing the impacts on the drainage system. An artificial neural network downscaling technique was used to obtain local-scale future rainfall from three coarse-scale GCMs. An impact assessment was then carried out using the projected local rainfall and a risk assessment methodology to understand and quantify the potential hazard from surface flooding. The case study is a selected urban drainage catchment in northwestern England. The results show that there will be potential increase in the spilling volume from manholes and surcharge in sewers, which would cause a significant number of properties to be affected by flooding.

Item Type: Article
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s11069-015-1892-6
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Divisions: Built Environment
Civil Engineering
Publisher: Springer Verlag
Date Deposited: 03 May 2016 09:21
Last Modified: 18 Nov 2016 11:22
DOI or Identification number: 10.1007/s11069-015-1892-6
URI: http://researchonline.ljmu.ac.uk/id/eprint/3550

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