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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-134
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Apr 2018

Research article | 03 Apr 2018

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

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

Theano Iliopoulou1, Cristina Aguilar2, Berit Arheimer3, María Bermúdez4, Nejc Bezak5, Andrea Ficchì6, Demetris Koutsoyiannis1, Juraj Parajka7, María José Polo2, Guillaume Thirel8, and Alberto Montanari9 Theano Iliopoulou et al.
  • 1Department of Water Resources and Environmental Engineering, School of Civil Engineering, National Technical University of Athens, Zographou, 15780, Greece
  • 2Fluvial dynamics and hydrology research group, Andalusian Institute of Earth System Research, University of Cordoba, Cordoba, 14071, Spain
  • 3Swedish Meteorological and Hydrological Institute, 601 76 Norrköping, Sweden
  • 4Water and Environmental Engineering Group, Department of Civil Engineering, Universidade da Coruña, 15071 A Coruña, , Spain
  • 5Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova 2, SI-1000 Ljubljana, Slovenia
  • 6Department of Geography and Environmental Science, University of Reading, Reading, RG6 6AB, United Kingdom; formerly, IRSTEA, Hydrology Research Group (HYCAR), F-92761, Antony, France
  • 7Vienna University of Technology, Institute of Hydraulic Engineering and Water Resources Management, Karlsplatz 13/222, A-1040 Vienna, Austria
  • 8IRSTEA, Hydrology Research Group (HYCAR), F-92761, Antony, France
  • 9Department DICAM, University of Bologna, Bologna, 40136, Italy

Abstract. The geophysical and hydrological processes governing river flow formation exhibit persistence at several timescales, which may manifest itself with the presence of positive seasonal correlation of streamflow at several different time lags. We investigate here how persistence propagates along subsequent seasons and affects low and high flows. We define the High Flow Season (HFS) and the Low Flow Season (LFS) as the three-month and the one-month periods which usually exhibit the higher and lower river flows, respectively. A dataset of 224 European rivers spanning more than 50 years of daily flow data is exploited. We compute the lagged seasonal correlation between selected river flow signatures, in HFS and LFS, and the average river flow in the antecedent months. Signatures are peak and average river flow for HFS and LFS, respectively. We investigate the links between seasonal streamflow correlation and various physiographic catchment characteristics and hydro-climatic properties. We find persistence to be more intense for LFS signatures than HFS. To exploit the seasonal correlation in flood frequency estimation, we fit a bivariate Meta-Gaussian probability distribution to peak HFS flow and average pre-HFS flow in order to condition the peak flow distribution in the HFS upon river flow observations in the previous months. The benefit of the suggested methodology is demonstrated by updating the flood frequency distribution one season in advance in real-world cases. Our findings suggest that there is a traceable physical basis for river memory which in turn can be statistically assimilated into flood frequency estimation to reduce uncertainty and improve predictions for technical purposes.

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Theano Iliopoulou et al.
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