Articles | Volume 23, issue 8
https://doi.org/10.5194/hess-23-3279-2019
https://doi.org/10.5194/hess-23-3279-2019
Research article
 | 
09 Aug 2019
Research article |  | 09 Aug 2019

Replication of ecologically relevant hydrological indicators following a modified covariance approach to hydrological model parameterization

Annie Visser-Quinn, Lindsay Beevers, and Sandhya Patidar

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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) (04 Feb 2019) by Pierre Gentine
AR by Annie Visser-Quinn on behalf of the Authors (06 Feb 2019)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (15 Feb 2019) by Pierre Gentine
RR by Anonymous Referee #2 (20 Feb 2019)
RR by Anonymous Referee #1 (15 Mar 2019)
ED: Reconsider after major revisions (further review by editor and referees) (03 Apr 2019) by Pierre Gentine
AR by Annie Visser-Quinn on behalf of the Authors (03 May 2019)
ED: Referee Nomination & Report Request started (22 May 2019) by Pierre Gentine
RR by Anonymous Referee #2 (12 Jun 2019)
RR by Anonymous Referee #1 (18 Jun 2019)
ED: Publish subject to minor revisions (review by editor) (28 Jun 2019) by Pierre Gentine
AR by Annie Visser-Quinn on behalf of the Authors (28 Jun 2019)  Author's response   Manuscript 
ED: Publish as is (12 Jul 2019) by Pierre Gentine
AR by Annie Visser-Quinn on behalf of the Authors (12 Jul 2019)  Manuscript 
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Short summary
The ecological impact of changes in river flow may be explored through the simulation of ecologically relevant flow indicators. Traditional approaches to model parameterization are not well-suited for this. To this end, this paper considers the ability of a modified covariance approach, applied to five hydrologically diverse catchments. An overall improvement in consistency is observed, whilst timing and rate of change represent the best and worst replicated indicators respectively.