IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v79y2015i2p1059-1077.html
   My bibliography  Save this article

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

Author

Listed:
  • M. Abdellatif
  • W. Atherton
  • R. Alkhaddar
  • Y. Osman

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. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • M. Abdellatif & W. Atherton & R. Alkhaddar & Y. Osman, 2015. "Flood risk assessment for urban water system in a changing climate using artificial neural network," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(2), pages 1059-1077, November.
    • Handle: RePEc:spr:nathaz:v:79:y:2015:i:2:p:1059-1077
    DOI: 10.1007/s11069-015-1892-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11069-015-1892-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11069-015-1892-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Al-Subaihi, Ali A., 2002. "Variable Selection in Multivariable Regression Using SAS/IML," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i12).
    2. D.I. Smith, 1999. "Urban Flood Damage and Greenhouse Scenarios - The Implications for Policy: An Example from Australia," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 4(3), pages 331-342, September.
    3. P. C. D. Milly & R. T. Wetherald & K. A. Dunne & T. L. Delworth, 2002. "Increasing risk of great floods in a changing climate," Nature, Nature, vol. 415(6871), pages 514-517, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nanda Khoirunisa & Cheng-Yu Ku & Chih-Yu Liu, 2021. "A GIS-Based Artificial Neural Network Model for Flood Susceptibility Assessment," IJERPH, MDPI, vol. 18(3), pages 1-20, January.
    2. Chenghao Zhong & Wengao Lou & Chuting Wang, 2022. "Neural Network-Based Modeling for Risk Evaluation and Early Warning for Large-Scale Sports Events," Mathematics, MDPI, vol. 10(18), pages 1-16, September.
    3. Helena M. Ramos & Mohsen Besharat, 2021. "Urban Flood Risk and Economic Viability Analyses of a Smart Sustainable Drainage System," Sustainability, MDPI, vol. 13(24), pages 1-13, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. P. V. Timbadiya & K. M. Krishnamraju, 2023. "A 2D hydrodynamic model for river flood prediction in a coastal floodplain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1143-1165, January.
    2. Berlemann, Michael, 2015. "Hurricane Risk, Happiness and Life Satisfaction. Some Empirical Evidence on the Indirect Effects of Natural Disasters," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113073, Verein für Socialpolitik / German Economic Association.
    3. Álvarez, Xana & Gómez-Rúa, María & Vidal-Puga, Juan, 2019. "Risk prevention of land flood: A cooperative game theory approach," MPRA Paper 91515, University Library of Munich, Germany.
    4. Abedifar, Pejman & Kashizadeh, Seyed Javad & Ongena, Steven, 2024. "Flood, farms and credit: The role of branch banking in the era of climate change," Journal of Corporate Finance, Elsevier, vol. 85(C).
    5. Teodor Kitczak & Heidi Jänicke & Marek Bury & Ryszard Malinowski, 2021. "The Usefulness of Mixtures with Festulolium braunii for the Regeneration of Grassland under Progressive Climate Change," Agriculture, MDPI, vol. 11(6), pages 1-20, June.
    6. Zbigniew Kundzewicz & Nicola Lugeri & Rutger Dankers & Yukiko Hirabayashi & Petra Döll & Iwona Pińskwar & Tomasz Dysarz & Stefan Hochrainer & Piotr Matczak, 2010. "Assessing river flood risk and adaptation in Europe—review of projections for the future," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(7), pages 641-656, October.
    7. Michael Bernardi & Christa Hainz & Paulina Maier & Maria Waldinger, 2023. "A “Green Revolution” for Sub-Saharan Africa? Challenges and Opportunities," EconPol Policy Brief 54, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    8. Weili Duan & Bin He & Daniel Nover & Jingli Fan & Guishan Yang & Wen Chen & Huifang Meng & Chuanming Liu, 2016. "Floods and associated socioeconomic damages in China over the last century," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 82(1), pages 401-413, May.
    9. Pratyush Tripathy & Teja Malladi, 2022. "Global Flood Mapper: a novel Google Earth Engine application for rapid flood mapping using Sentinel-1 SAR," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(2), pages 1341-1363, November.
    10. Sechindra Vallury & Bryan Leonard, 2022. "Canals, climate, and corruption: The provisioning of public infrastructure under uncertainty," Economics and Politics, Wiley Blackwell, vol. 34(1), pages 221-252, March.
    11. repec:fpr:2020cp:5(5 is not listed on IDEAS
    12. Jan Skála & Radim Vácha & Pavel Čupr, 2018. "Which Compounds Contribute Most to Elevated Soil Pollution and the Corresponding Health Risks in Floodplains in the Headwater Areas of the Central European Watershed?," IJERPH, MDPI, vol. 15(6), pages 1-16, June.
    13. David Ocio & Christian Stocker & Ángel Eraso & Arantza Martínez & José María Sanz Galdeano, 2016. "Towards a reliable and cost-efficient flood risk management: the case of the Basque Country (Spain)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 617-639, March.
    14. Yun Xing & Huili Chen & Qiuhua Liang & Xieyao Ma, 2022. "Improving the performance of city-scale hydrodynamic flood modelling through a GIS-based DEM correction method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2313-2335, July.
    15. David Marcolino Nielsen & Marcio Cataldi & André Luiz Belém & Ana Luiza Spadano Albuquerque, 2016. "Local indices for the South American monsoon system and its impacts on Southeast Brazilian precipitation patterns," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 909-928, September.
    16. Andrew C. Ross & Raymond G. Najjar, 2019. "Evaluation of methods for selecting climate models to simulate future hydrological change," Climatic Change, Springer, vol. 157(3), pages 407-428, December.
    17. Berlemann, Michael & Vogt, Gerit, 2007. "Kurzfristige Wachstumseffekte von Naturkatastrophen," Working Paper 69/2007, Helmut Schmidt University, Hamburg.
    18. Dandan Zhang & Juqin Shen & Pengfei Liu & Fuhua Sun, 2020. "Allocation of Flood Drainage Rights Based on the PSR Model and Pythagoras Fuzzy TOPSIS Method," IJERPH, MDPI, vol. 17(16), pages 1-19, August.
    19. Jian Fang & Feng Kong & Jiayi Fang & Lin Zhao, 2018. "Observed changes in hydrological extremes and flood disaster in Yangtze River Basin: spatial–temporal variability and climate change impacts," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(1), pages 89-107, August.
    20. Grames, Johanna & Prskawetz, Alexia & Grass, Dieter & Viglione, Alberto & Blöschl, Günter, 2016. "Modeling the interaction between flooding events and economic growth," Ecological Economics, Elsevier, vol. 129(C), pages 193-209.
    21. Jungmin Lim & Mark Skidmore, 2019. "Flood Fatalities in the United States: The Roles of Socioeconomic Factors and the National Flood Insurance Program," Southern Economic Journal, John Wiley & Sons, vol. 85(4), pages 1032-1057, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:79:y:2015:i:2:p:1059-1077. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.