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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 275–291, 2015
https://doi.org/10.5194/hess-19-275-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 19, 275–291, 2015
https://doi.org/10.5194/hess-19-275-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 Jan 2015

Research article | 16 Jan 2015

The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models

M. C. Demirel et al.
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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 (19 Jul 2014) by Kerstin Stahl
AR by Mehmet Cüneyd Demirel on behalf of the Authors (21 Aug 2014)  Author's response
ED: Referee Nomination & Report Request started (23 Sep 2014) by Kerstin Stahl
RR by Renata Romanowicz (03 Oct 2014)
RR by Anonymous Referee #2 (04 Oct 2014)
RR by Stefanie Jörg-Hess (08 Oct 2014)
ED: Publish subject to minor revisions (Editor review) (24 Oct 2014) by Kerstin Stahl
AR by Mehmet Cüneyd Demirel on behalf of the Authors (03 Nov 2014)  Author's response    Manuscript
ED: Publish subject to minor revisions (Editor review) (23 Nov 2014) by Kerstin Stahl
AR by Mehmet Cüneyd Demirel on behalf of the Authors (02 Dec 2014)  Author's response    Manuscript
ED: Publish subject to technical corrections (23 Dec 2014) by Kerstin Stahl
AR by Mehmet Cüneyd Demirel on behalf of the Authors (23 Dec 2014)  Author's response    Manuscript
Publications Copernicus
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Short summary
This paper investigates the skill of 90-day low-flow forecasts using three models. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.
This paper investigates the skill of 90-day low-flow forecasts using three models. From the...
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