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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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HESS | Articles | Volume 23, issue 1
Hydrol. Earth Syst. Sci., 23, 73-91, 2019
https://doi.org/10.5194/hess-23-73-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 23, 73-91, 2019
https://doi.org/10.5194/hess-23-73-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Jan 2019

Research article | 07 Jan 2019

A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers

Theano Iliopoulou 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: Publish subject to revisions (further review by editor and referees) (16 Jul 2018) by Louise Slater
AR by Theano Iliopoulou on behalf of the Authors (27 Aug 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (09 Sep 2018) by Louise Slater
RR by Anonymous Referee #1 (19 Sep 2018)
RR by Anonymous Referee #3 (24 Oct 2018)
ED: Publish subject to revisions (further review by editor and referees) (31 Oct 2018) by Louise Slater
AR by Theano Iliopoulou on behalf of the Authors (16 Nov 2018)  Author's response
ED: Publish as is (06 Dec 2018) by Louise Slater
AR by Theano Iliopoulou on behalf of the Authors (14 Dec 2018)  Author's response    Manuscript
Publications Copernicus
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Short summary
We investigate the seasonal memory properties of a large sample of European rivers in terms of high and low flows. We compute seasonal correlations between peak and low flows and average flows in the previous seasons and explore the links with various physiographic and hydro-climatic catchment descriptors. Our findings suggest that there is a traceable physical basis for river memory which in turn can be employed to reduce uncertainty and improve probabilistic predictions of floods and droughts.
We investigate the seasonal memory properties of a large sample of European rivers in terms of...
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