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Urban surface water flood modelling – a comprehensive review of current models and future challenges

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journal contribution
posted on 09.04.2021, 10:29 by Kaihua Guo, Mingfu Guan, Dapeng YuDapeng Yu
Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

Funding

Early Career Scheme from Hong Kong Research Grant Council (Grant number: 27202419)

History

School

  • Social Sciences and Humanities

Department

  • Geography and Environment

Published in

Hydrology and Earth System Sciences

Volume

25

Pages

2843-2860

Publisher

Copernicus Publications

Version

VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Copernicus Press under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

23/03/2021

Publication date

2021-05-27

Copyright date

2021

ISSN

1027-5606

eISSN

1607-7938

Language

en

Depositor

Prof Dapeng Yu. Deposit date: 7 April 2021