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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 13, issue 9
Hydrol. Earth Syst. Sci., 13, 1699–1712, 2009
https://doi.org/10.5194/hess-13-1699-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 13, 1699–1712, 2009
https://doi.org/10.5194/hess-13-1699-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  29 Sep 2009

29 Sep 2009

Effects of intersite dependence of nested catchment structures on probabilistic regional envelope curves

B. Guse1,2, A. Castellarin3, A. H. Thieken1,4, and B. Merz1 B. Guse et al.
  • 1Deutsches GeoForschungsZentrum GFZ, Section Hydrology, Potsdam, Germany
  • 2Center for Disaster Management and Risk Reduction Technology (CEDIM), Karlsruhe, Germany
  • 3Dipartimento di Ingegneria delle Strutture, dei Trasporti, delle Acque, del Rivelamento, del Territorio (DISTART), Università di Bologna, Bologna, Italy
  • 4alpS – Centre for Natural Hazards and Risk Management, University of Innsbruck, Innsbruck, Austria

Abstract. This study analyses the intersite dependence of nested catchment structures by modelling cross-correlations for pairs of nested and unnested catchments separately. Probabilistic regional envelope curves are utilised to derive regional flood quantiles for 89 catchments located in Saxony, in the Southeast of Germany. The study area has a nested structure and the intersite correlation is much stronger for nested pairs of catchments than for unnested ones. Pooling groups of sites (regions) are constructed based on several candidate sets of catchment descriptors using the Region of Influence method. Probabilistic regional envelope curves are derived on the basis of flood flows observed within the pooling groups. Their estimated recurrence intervals are based on the number of effective sample years of data (i.e. equivalent number of uncorrelated data). The evaluation of the effective sample years of data requires the modelling of intersite dependence. We perform this globally, using a cross-correlation function for the whole study area as well as by using two different cross-correlation functions, one for nested pairs and another for unnested pairs. In the majority of the cases, these two modelling approaches yield significantly different estimates for the effective sample years of data, and therefore also for the recurrence intervals. The reduction of the recurrence interval when using two different cross-correlation functions is larger for larger pooling groups and for pooling groups with a higher fraction of nested catchments. A separation into nested and unnested pairs of catchments gives a more realistic representation of the characteristic river network structure and improves the estimation of regional information content. Hence, applying two different cross-correlation functions is recommended.

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