Articles | Volume 25, issue 2
Research article
18 Feb 2021
Research article |  | 18 Feb 2021

A time-varying parameter estimation approach using split-sample calibration based on dynamic programming

Xiaojing Zhang and Pan Liu


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) (28 Sep 2020) by Dimitri Solomatine
AR by Pan Liu on behalf of the Authors (02 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (14 Oct 2020) by Dimitri Solomatine
RR by Anonymous Referee #1 (08 Nov 2020)
RR by Anonymous Referee #2 (22 Nov 2020)
ED: Publish subject to minor revisions (review by editor) (13 Dec 2020) by Dimitri Solomatine
AR by Pan Liu on behalf of the Authors (21 Dec 2020)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (22 Dec 2020) by Dimitri Solomatine
Short summary
Rainfall–runoff models are useful tools for streamflow simulation. However, efforts are needed to investigate how their parameters vary in response to climate changes and human activities. Thus, this study proposes a new method for estimating time-varying parameters, by considering both simulation accuracy and parameter continuity. The results show the proposed method is effective for identifying temporal variations of parameters and can simultaneously provide good streamflow simulation.