Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5491-2020
https://doi.org/10.5194/hess-24-5491-2020
Research article
 | 
23 Nov 2020
Research article |  | 23 Nov 2020

Two-stage variational mode decomposition and support vector regression for streamflow forecasting

Ganggang Zuo, Jungang Luo, Ni Wang, Yani Lian, and Xinxin He

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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: Publish subject to revisions (further review by editor and referees) (07 Aug 2020) by Dimitri Solomatine
AR by Ganggang Zuo on behalf of the Authors (25 Aug 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (04 Sep 2020) by Dimitri Solomatine
RR by Anonymous Referee #2 (14 Sep 2020)
RR by John Quilty (14 Oct 2020)
ED: Publish subject to technical corrections (14 Oct 2020) by Dimitri Solomatine
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Short summary
A two-stage variational mode decomposition and support vector regression is designed to reduce the influence of boundary effects without removing or correcting boundary-affected decompositions. The proposed model significantly reduces the boundary effect consequences, saves modeling time and computation resources, barely overfits the calibration samples, and forecasts monthly runoff reasonably well compared to the benchmark models.