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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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HESS | Articles | Volume 23, issue 8
Hydrol. Earth Syst. Sci., 23, 3405–3421, 2019
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 3405–3421, 2019
https://doi.org/10.5194/hess-23-3405-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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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
Publications Copernicus
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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.
Understanding the projection performance of hydrological models under contrasting climatic...
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