Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework

Pan, Zhengke; Liu, Pan; Gao, Shida; Xia, Jun; Chen, Jie; Cheng, Lei

doi:https://doi.org/10.5194/hess-23-3405-2019

Articles | Volume 23, issue 8

https://doi.org/10.5194/hess-23-3405-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-23-3405-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 8

Research article

|

19 Aug 2019

Research article |

| 19 Aug 2019

Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework

Zhengke Pan, Pan Liu, Shida Gao, Jun Xia, Jie Chen, and Lei Cheng

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Final revised paper (published on 19 Aug 2019)
Supplement to the final revised paper
Preprint (discussion started on 04 Feb 2019)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review of the paper "Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework"', Anonymous Referee #1, 22 Feb 2019
- AC1: 'Responses to Referee #1:', Pan Liu, 01 Apr 2019
RC2: 'Review of 'Improving hydrological projection performance under contrasting climatic conditions using spatial coherence through a hierarchical Bayesian regression framework'', Anonymous Referee #2, 22 Feb 2019
- AC2: 'Responses to Referee #2:', Pan Liu, 01 Apr 2019

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (16 Apr 2019) by Fabrizio Fenicia

AR by Pan Liu on behalf of the Authors (16 May 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (24 May 2019) by Fabrizio Fenicia

RR by Anonymous Referee #1 (19 Jun 2019)

RR by Anonymous Referee #2 (22 Jun 2019)

ED: Publish subject to minor revisions (review by editor) (01 Jul 2019) by Fabrizio Fenicia

AR by Pan Liu on behalf of the Authors (10 Jul 2019) Author's response Manuscript

ED: Publish as is (17 Jul 2019) by Fabrizio Fenicia

AR by Pan Liu on behalf of the Authors (22 Jul 2019) Manuscript

Short summary

Understanding the projection performance of hydrological models under contrasting climatic conditions supports robust decision making, which highlights the need to adopt time-varying parameters in hydrological modeling to reduce performance degradation. This study improves our understanding of the spatial coherence of time-varying parameters, which will help improve the projection performance under differing climatic conditions.