Large-watershed flood forecasting with high-resolution distributed hydrological model

Chen, Yangbo; Li, Ji; Wang, Huanyu; Qin, Jianming; Dong, Liming

doi:https://doi.org/10.5194/hess-21-735-2017

Articles | Volume 21, issue 2

https://doi.org/10.5194/hess-21-735-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Modeling hydrological processes and changes

https://doi.org/10.5194/hess-21-735-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 21, issue 2

Research article

|

03 Feb 2017

Research article |

| 03 Feb 2017

Large-watershed flood forecasting with high-resolution distributed hydrological model

Yangbo Chen, Ji Li, Huanyu Wang, Jianming Qin, and Liming Dong

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Final revised paper (published on 03 Feb 2017)
Preprint (discussion started on 26 Sep 2016)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'referee report', Anonymous Referee #1, 29 Sep 2016
- AC1: 'Reply to the comments of Referee # 1', Y. Chen, 08 Dec 2016
RC2: 'Suggestions for the authors', Anonymous Referee #2, 02 Dec 2016
- AC2: 'Reply to the comments of Referee # 2', Y. Chen, 08 Dec 2016

Peer-review completion

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

ED: Publish as is (07 Jan 2017) by Qiuwen Chen

AR by Yangbo Chen on behalf of the Authors (08 Jan 2017) Manuscript

Short summary

The distributed hydrological model has not yet been applied in large watershed flood forecasting due to some limitations. By proposing a method for estimating channel cross section size with remote sensing data, employing the PSO algorithm optimize model parameters and running the model on high-performance supercomputer with parallel computation technique, this article successfully applied the Liuxihe model in a larger watershed flood forecasting in southern China at high resolution.