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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.
Keywords
DESIGN-HYDROGRAPH ESTIMATION

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Chicago
Gräler, Benedikt, Andrea Petroselli, Salvatore Grimaldi, Bernard De Baets, and Niko Verhoest. 2016. “An Update on Multivariate Return Periods in Hydrology.” In Proceedings of the International Association of Hydrological Sciences (IAHS), ed. AH Schumann, G Bloschl, A Castellarin, J Dietrich, S Grimaldi, U Haberlandt, A Montanari, D Rosbjerg, A Viglione, and S Vorogushyn, 373:175–178 Gottingen, Germany: Copernicus.
APA
Gräler, B., Petroselli, A., Grimaldi, S., De Baets, B., & Verhoest, N. (2016). An update on multivariate return periods in hydrology. In AH Schumann, G. Bloschl, A. Castellarin, J. Dietrich, S. Grimaldi, U. Haberlandt, A. Montanari, et al. (Eds.), Proceedings of the International Association of Hydrological Sciences (IAHS) (Vol. 373, pp. 175–178 ). Presented at the 7th International Water Resources Management conference of ICWRS, Gottingen, Germany: Copernicus.
Vancouver
1.
Gräler B, Petroselli A, Grimaldi S, De Baets B, Verhoest N. An update on multivariate return periods in hydrology. In: Schumann A, Bloschl G, Castellarin A, Dietrich J, Grimaldi S, Haberlandt U, et al., editors. Proceedings of the International Association of Hydrological Sciences (IAHS). Gottingen, Germany: Copernicus; 2016. p. 175–8 .
MLA
Gräler, Benedikt, Andrea Petroselli, Salvatore Grimaldi, et al. “An Update on Multivariate Return Periods in Hydrology.” Proceedings of the International Association of Hydrological Sciences (IAHS). Ed. AH Schumann et al. Vol. 373. Gottingen, Germany: Copernicus, 2016. 175–178 . Print.
@inproceedings{8553276,
  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.},
  author       = {Gr{\"a}ler, Benedikt and Petroselli, Andrea and Grimaldi, Salvatore and De Baets, Bernard and Verhoest, Niko},
  booktitle    = {Proceedings of the International Association of Hydrological Sciences (IAHS)},
  editor       = {Schumann, AH and Bloschl, G and Castellarin, A and Dietrich, J and Grimaldi, S and Haberlandt, U and Montanari, A and Rosbjerg, D and Viglione, A and Vorogushyn, S},
  issn         = {2199-899X},
  keyword      = {DESIGN-HYDROGRAPH ESTIMATION},
  language     = {eng},
  location     = {Bochum, Germany},
  pages        = {175--178 },
  publisher    = {Copernicus},
  title        = {An update on multivariate return periods in hydrology},
  url          = {http://dx.doi.org/10.5194/piahs-373-175-2016},
  volume       = {373},
  year         = {2016},
}

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