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Natural Hazards

, Volume 79, Issue 2, pp 1059–1077 | Cite as

Flood risk assessment for urban water system in a changing climate using artificial neural network

  • M. Abdellatif
  • W. Atherton
  • R. Alkhaddar
  • Y. Osman
Original Paper

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.

Keywords

Artificial neural network Climate change Combined sewer system Downscaling Flooding 

Notes

Acknowledgments

This paper is part of a research project conducted at Liverpool John Moores University in collaboration with MWH UK Ltd and United Utilities Plc in Northwest England. The authors would like to extend their thanks to Innovyze UK, for providing the InforWorks CS license. The views expressed in the paper are those of the authors and not necessarily those of the collaborating bodies.

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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • M. Abdellatif
    • 1
  • W. Atherton
    • 1
  • R. Alkhaddar
    • 1
  • Y. Osman
    • 2
  1. 1.Peter Jost Centre, School of the Built EnvironmentLiverpool John Moores UniversityLiverpoolUK
  2. 2.Department of Civil and Built Environment, School of Engineering, Sports and SciencesUniversity of BoltonBoltonUK

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