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Volume 14, issue 12 | Copyright

Special issue: Advances in statistical hydrology

Hydrol. Earth Syst. Sci., 14, 2465-2478, 2010
https://doi.org/10.5194/hess-14-2465-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 09 Dec 2010

Research article | 09 Dec 2010

Introducing empirical and probabilistic regional envelope curves into a mixed bounded distribution function

B. Guse1,2,*, Th. Hofherr2,3,4, and B. Merz1 B. Guse et al.
  • 1Deutsches GeoForschungsZentrum Potsdam GFZ, Section 5.4 – Hydrology, Telegrafenberg, 14473 Potsdam, Germany
  • 2Center for Disaster Management and Risk Reduction Technology (CEDIM), 76187 Karlsruhe, Germany
  • 3Institute for Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), 76128 Karlsruhe, Germany
  • 4Geo Risks Research, Münchener Rückversicherungs-Gesellschaft, 80791 Munich, Germany
  • *now at: Department of Hydrology and Water Resources Management, Christian-Albrechts-Universität zu Kiel, Olshausenstrasse 40, 24098 Kiel, Germany

Abstract. A novel approach to consider additional spatial information in flood frequency analyses, especially for the estimation of discharges with recurrence intervals larger than 100 years, is presented. For this purpose, large flood quantiles, i.e. pairs of a discharge and its corresponding recurrence interval, as well as an upper bound discharge, are combined within a mixed bounded distribution function. The large flood quantiles are derived using probabilistic regional envelope curves (PRECs) for all sites of a pooling group. These PREC flood quantiles are introduced into an at-site flood frequency analysis by assuming that they are representative for the range of recurrence intervals which is covered by PREC flood quantiles. For recurrence intervals above a certain inflection point, a Generalised Extreme Value (GEV) distribution function with a positive shape parameter is used. This GEV asymptotically approaches an upper bound derived from an empirical envelope curve. The resulting mixed distribution function is composed of two distribution functions which are connected at the inflection point.

This method is applied to 83 streamflow gauges in Saxony/Germany. Our analysis illustrates that the presented mixed bounded distribution function adequately considers PREC flood quantiles as well as an upper bound discharge. The introduction of both into an at-site flood frequency analysis improves the quantile estimation. A sensitivity analysis reveals that, for the target recurrence interval of 1000 years, the flood quantile estimation is less sensitive to the selection of an empirical envelope curve than to the selection of PREC discharges and of the inflection point between the mixed bounded distribution function.

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