Articles | Volume 23, issue 1
https://doi.org/10.5194/hess-23-73-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-73-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jan 2019
Research article |
| 07 Jan 2019
| 07 Jan 2019
A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers
Department of Water Resources and Environmental Engineering,
School of Civil Engineering, National Technical University of Athens,
Zographou, 15780, Greece
Cristina Aguilar
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
of Earth System Research, University of Córdoba, Córdoba, 14071, Spain
Berit Arheimer
Swedish Meteorological and Hydrological Institute, 601 76
Norrköping, Sweden
María Bermúdez
Water and Environmental Engineering Group, Department of Civil
Engineering, University of A Coruña, 15071 A Coruña, Spain
Nejc Bezak
Faculty of Civil and Geodetic Engineering, University of Ljubljana,
Jamova 2, 1000 Ljubljana, Slovenia
Andrea Ficchì
Department of Geography and Environmental Science, University of
Reading, Reading, RG6 6AB, UK
formerly at: IRSTEA, Hydrology
Research Group (HYCAR), 92761, Antony, France
Demetris Koutsoyiannis
Department of Water Resources and Environmental Engineering,
School of Civil Engineering, National Technical University of Athens,
Zographou, 15780, Greece
Juraj Parajka
Vienna University of Technology, Institute of Hydraulic Engineering
and Water Resources Management, Karlsplatz 13/222, 1040 Vienna, Austria
María José Polo
Fluvial Dynamics and Hydrology Research Group, Andalusian Institute
of Earth System Research, University of Córdoba, Córdoba, 14071, Spain
Guillaume Thirel
IRSTEA, Hydrology Research Group (HYCAR), 92761, Antony,
France
Alberto Montanari
Department DICAM, University of Bologna, Bologna, 40136, Italy
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- Spatiotemporal clustering of streamflow extremes and relevance to flood insurance claims: a stochastic investigation for the contiguous USA K. Papoulakos et al. 10.1007/s11069-024-06766-z
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- Estimation of seasonal precipitation memory curves for major rivers in the Tibetan Plateau based on GRACE satellites data H. Gu et al. 10.1016/j.ejrh.2024.101942
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Latest update: 31 Jul 2025
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...
