Articles | Volume 22, issue 5
https://doi.org/10.5194/hess-22-2891-2018
https://doi.org/10.5194/hess-22-2891-2018
Research article
 | 
16 May 2018
Research article |  | 16 May 2018

Hydro-stochastic interpolation coupling with the Budyko approach for prediction of mean annual runoff

Ning Qiu, Xi Chen, Qi Hu, Jintao Liu, Richao Huang, and Man Gao

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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) (18 Dec 2017) by Erwin Zehe
AR by Xi Chen on behalf of the Authors (14 Jan 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (17 Jan 2018) by Erwin Zehe
RR by Mirko Mälicke (13 Feb 2018)
RR by Jon Olav Skøien (13 Mar 2018)
ED: Publish subject to revisions (further review by editor and referees) (13 Mar 2018) by Erwin Zehe
AR by Xi Chen on behalf of the Authors (14 Mar 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (15 Mar 2018) by Erwin Zehe
RR by Jon Olav Skøien (06 Apr 2018)
ED: Publish subject to minor revisions (review by editor) (09 Apr 2018) by Erwin Zehe
AR by Xi Chen on behalf of the Authors (18 Apr 2018)  Author's response    Manuscript
ED: Publish as is (24 Apr 2018) by Erwin Zehe
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Short summary
The spatial runoff is decomposed into a deterministic trend and deviations from it caused by stochastic fluctuations which are described by Budyko method and stochastic interpolation. This coupled method is applied to spatially interpolate runoff in the Huaihe River basin of China. Results show that the coupled method reduces the error in overestimating low runoff and underestimating high runoff suffered by the other two methods, so it improves the prediction accuracy of the mean annual runoff.