Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5519-2020
https://doi.org/10.5194/hess-24-5519-2020
Research article
 | 
23 Nov 2020
Research article |  | 23 Nov 2020

On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment

Maxime Jay-Allemand, Pierre Javelle, Igor Gejadze, Patrick Arnaud, Pierre-Olivier Malaterre, Jean-Alain Fine, and Didier Organde

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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) (20 Jan 2020) by Véronique Ducrocq
AR by Maxime Jay-Allemand on behalf of the Authors (03 Apr 2020)  Author's response   Manuscript 
ED: Referee Nomination & Report Request started (13 Apr 2020) by Véronique Ducrocq
RR by Anonymous Referee #3 (20 May 2020)
RR by Anonymous Referee #2 (26 May 2020)
RR by Anonymous Referee #4 (27 May 2020)
ED: Publish subject to minor revisions (review by editor) (07 Jun 2020) by Véronique Ducrocq
AR by Maxime Jay-Allemand on behalf of the Authors (17 Jun 2020)  Manuscript 
ED: Publish as is (31 Jul 2020) by Véronique Ducrocq
AR by Maxime Jay-Allemand on behalf of the Authors (06 Aug 2020)  Author's response   Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Maxime Jay-Allemand on behalf of the Authors (13 Oct 2020)   Author's adjustment   Manuscript
EA: Adjustments approved (19 Nov 2020) by Véronique Ducrocq
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Short summary
This study contributes to flash flood prediction using a hydrological model. The model describes the spatial properties of the watersheds with hundreds of unknown parameters. The Gardon d'Anduze watershed is chosen as the study benchmark. A sophisticated numerical algorithm and the downstream discharge measurements make the identification of the model parameters possible. Results provide better model predictions and relevant spatial variability of some parameters inside this watershed.