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

Guo, Kaihua; Guan, Mingfu; Yu, Dapeng

doi:https://doi.org/10.5194/hess-25-2843-2021

Articles | Volume 25, issue 5

https://doi.org/10.5194/hess-25-2843-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-2843-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 5

Review article

|

27 May 2021

Review article |

| 27 May 2021

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

Kaihua Guo, Mingfu Guan, and Dapeng Yu

Download

Final revised paper (published on 27 May 2021)
Supplement to the final revised paper
Preprint (discussion started on 16 Dec 2020)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review of existing numerical models to assess the performance of existing and new sewer systems during flooding conditions', Anonymous Referee #1, 04 Jan 2021
- AC1: 'Reply on RC1', Mingfu Guan, 09 Mar 2021
RC2: 'comments on a review paper on urban surface water flood modelling', Anonymous Referee #2, 05 Jan 2021
- AC2: 'Reply on RC2', Mingfu Guan, 09 Mar 2021

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to minor revisions (further review by editor) (09 Mar 2021) by Nadia Ursino

AR by Mingfu Guan on behalf of the Authors (15 Mar 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (23 Mar 2021) by Nadia Ursino

AR by Mingfu Guan on behalf of the Authors (25 Mar 2021)

Short summary

This study presents a comprehensive review of models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. It explores the advantages and limitations of existing models 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.