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Szolgay, Ján; Gaál, Ladislav; Bacigál, Tomáš; Kohnová, Silvia; Hlavčová, Kamila; Výleta, Roman; Blöschl, Günter (2016)
Publisher: Copernicus Publications
Languages: English
Types: Article
Subjects: GE1-350, QE1-996.5, Environmental sciences, Geology
Recent research on the bivariate flood peak/volume frequency analysis has mainly focused on the statistical aspects of the use of various copula models. The interplay of climatic and catchment processes in discriminating among these models has attracted less interest. In the paper we analyse the influence of climatic and hydrological controls on flood peak and volume relationships and their models, which are based on the concept of comparative hydrology in the catchments of a selected region in Austria. Independent flood events have been isolated and assigned to one of the three types of flood processes: synoptic floods, flash floods and snowmelt floods. First, empirical copulas are regionally compared in order to verify whether any flood processes are discernible in terms of the corresponding bivariate flood-peak relationships. Next the types of copulas, which are frequently used in hydrology are fitted, and their goodness-of-fit is examined in a regional scope. The spatial similarity of copulas and their rejection rate, depending on the flood type, region, and sample size are examined, too. In particular, the most remarkable difference is observed between flash floods and the other two types of flood. It is concluded that treating flood processes separately in such an analysis is beneficial, both hydrologically and statistically, since flood processes and the relationships associated with them are discernible both locally and regionally in the pilot region.

However, uncertainties inherent in the copula-based bivariate frequency analysis itself (caused, among others, also by the relatively small sample sizes for consistent copula model selection, upper tail dependence characterization and reliable predictions) may not be overcome in the scope of such a regional comparative analysis.