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Volume 373
Proc. IAHS, 373, 175-178, 2016
https://doi.org/10.5194/piahs-373-175-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Proc. IAHS, 373, 175-178, 2016
https://doi.org/10.5194/piahs-373-175-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  12 May 2016

12 May 2016

An update on multivariate return periods in hydrology

Benedikt Gräler1, Andrea Petroselli2, Salvatore Grimaldi3, Bernard De Baets4, and Niko Verhoest5 Benedikt Gräler et al.
  • 1Institute of Hydrology, Ruhr University Bochum, Bochum, Germany
  • 2Dipartimento di scienze agrarie e forestali (DAFNE Department), University of Tuscia, Tuscia, Italy
  • 3Dipartimento per la innovazione nei sistemi biologici agroalimentari e forestali (DIBAF Department), University of Tuscia, Tuscia, Italy
  • 4Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium
  • 5Laboratory of Hydrology and Water Management, Ghent University, Ghent, Belgium

Abstract. Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.

Moreover, we preliminary investigate the ability of the multivariate return period definitions to select maximal events from a time series. Starting from a rich simulated data set, we show how similar the selection of events from a data set is. It can be deduced from the study and theoretically underpinned that the strength of correlation in the sample influences the differences between the selection of maximal events.

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Many hydrological studies are devoted to the identification of events that are expected to occur on average within a certain time span. While this topic is well established in the univariate case, recent advances focus on a multivariate characterization of events based on copulas. Following a previous study, we show how the definition of the survival Kendall return period fits into the set of multivariate return periods.
Many hydrological studies are devoted to the identification of events that are expected to occur...
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