AI-based techniques for multi-step streamflow forecasts:  application for multi-objective reservoir operation  optimization and performance assessment

Guo, Yuxue; Yu, Xinting; Xu, Yue-Ping; Chen, Hao; Gu, Haiting; Xie, Jingkai

doi:https://doi.org/10.5194/hess-25-5951-2021

Articles | Volume 25, issue 11

https://doi.org/10.5194/hess-25-5951-2021

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

https://doi.org/10.5194/hess-25-5951-2021

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

Articles | Volume 25, issue 11

Research article

|

18 Nov 2021

Research article |

| 18 Nov 2021

AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment

Yuxue Guo, Xinting Yu, Yue-Ping Xu, Hao Chen, Haiting Gu, and Jingkai Xie

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Final revised paper (published on 18 Nov 2021)
Preprint (discussion started on 16 Dec 2020)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Comments on manuscript (HESS-2020-617)', Anonymous Referee #1, 12 Jan 2021
- AC1: 'Reply on RC1', Yuxue Guo, 25 Mar 2021
RC2: 'AI-based techniques for multi-step streamflow forecasts: Application for multi-objective reservoir operation optimization and performance assessment', Anonymous Referee #2, 05 Mar 2021
- AC2: 'Reply on RC2', Yuxue Guo, 25 Mar 2021
EC1: 'Editor's final comment on hess-2020-617', Dimitri Solomatine, 05 Apr 2021

Peer-review completion

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

ED: Publish subject to revisions (further review by editor and referees) (05 Apr 2021) by Dimitri Solomatine

AR by Yuxue Guo on behalf of the Authors (06 Apr 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (15 Apr 2021) by Dimitri Solomatine

RR by Anonymous Referee #2 (24 May 2021)

RR by Anonymous Referee #1 (11 Jun 2021)

ED: Publish subject to revisions (further review by editor and referees) (16 Jun 2021) by Dimitri Solomatine

AR by Yuxue Guo on behalf of the Authors (10 Jul 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (18 Jul 2021) by Dimitri Solomatine

RR by Anonymous Referee #1 (31 Jul 2021)

ED: Publish subject to technical corrections (18 Oct 2021) by Dimitri Solomatine

AR by Yuxue Guo on behalf of the Authors (18 Oct 2021) Author's response Manuscript

Short summary

We developed an AI-based management methodology to assess forecast quality and forecast-informed reservoir operation performance together due to uncertain inﬂow forecasts. Results showed that higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts. Moreover, the relationship between the forecast horizon and reservoir operation was complex and depended on operating configurations and performance measures.