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| Titel |
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation |
| VerfasserIn |
B. Gräler, M. J. Berg, S. Vandenberghe, A. Petroselli, S. Grimaldi, B. Baets, N. E. C. Verhoest |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 4 ; Nr. 17, no. 4 (2013-04-02), S.1281-1296 |
| Datensatznummer |
250018838
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| Publikation (Nr.) |
 copernicus.org/hess-17-1281-2013.pdf |
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| Zusammenfassung |
| Most of the hydrological and hydraulic studies refer to the notion of a
return period to quantify design variables. When dealing with multiple design
variables, the well-known univariate statistical analysis is no longer
satisfactory, and several issues challenge the practitioner. How should one
incorporate the dependence between variables? How should a multivariate
return period be defined and applied in order to yield a proper design event?
In this study an overview of the state of the art for estimating
multivariate design events is given and the different approaches are
compared. The construction of multivariate distribution functions is done
through the use of copulas, given their practicality in multivariate
frequency analyses and their ability to model numerous types of dependence
structures in a flexible way. A synthetic case study is used to generate a
large data set of simulated discharges that is used for illustrating the
effect of different modelling choices on the design events. Based on
different uni- and multivariate approaches, the design hydrograph
characteristics of a 3-D phenomenon composed of annual maximum
peak discharge, its volume, and duration are derived. These approaches are
based on regression analysis, bivariate conditional distributions, bivariate
joint distributions and Kendall distribution functions, highlighting
theoretical and practical issues of multivariate frequency analysis. Also an
ensemble-based approach is presented. For a given design return period, the
approach chosen clearly affects the calculated design event, and much
attention should be given to the choice of the approach used as this depends
on the real-world problem at hand. |
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