This paper analyses the bivariate relationship between flood peaks and corresponding flood event volumes modelled by empirical and theoretical copulas in a regional context, with a focus on flood generation processes in general, the regional differentiation of these and the effect of the sample size on reliable discrimination among models. A total of 72 catchments in North-West of Austria are analysed for the period 1976-2007. From the hourly runoff data set, 25 697 flood events were isolated and assigned to one of three flood process types: synoptic floods (including long- and short-rain floods), flash floods or snowmelt floods (both rain-on-snow and snowmelt floods). The first step of the analysis examines whether the empirical peak-volume copulas of different flood process types are regionally statistically distinguishable, separately for each catchment and the role of the sample size on the strength of the statements. The results indicate that the empirical copulas of flash floods tend to be different from those of the synoptic and snowmelt floods. The second step examines how similar are the empirical flood peak-volume copulas between catchments for a given flood type across the region. Empirical copulas of synoptic floods are the least similar between the catchments, however with the decrease of the sample size the difference between the performances of the process types becomes small. The third step examines the goodness-of-fit of different commonly used copula types to the data samples that represent the annual maxima of flood peaks and the respective volumes both regardless of flood generating processes (the traditional engineering approach) and also considering the three process-based classes. Extreme value copulas (Galambos, Gumbel and Hüsler-Reiss) show the best performance both for synoptic and flash floods, while the Frank copula shows the best performance for snowmelt floods. It is concluded that there is merit in treating flood types separately when analysing and estimating flood peak-volume dependence copulas; however, even the enlarged dataset gained by the process-based analysis in this study does not give sufficient information for a reliable model choice for multivariate statistical analysis of flood peaks and volumes.
The objective of this study is to analyse the spatial variability of seasonal flood occurrences in the Upper Danube region for the period 1961-2010. The analysis focuses on the understanding of the factors that control the spatial variability of winter and summer floods in 88 basins with different physiographic conditions. The evaluation is based on circular statistics, which compare the changes in the mean date and in the seasonal flood concentration index within a year or predefined season. The results indicate that summer half-year and winter half-year floods are dominant in the Alps and northern Danube tributaries, respectively. A comparison of the relative magnitude of flood events indicates that summer half-year floods are on average more than 50% larger than floods in winter. The evaluation of flood occurrence showed that the values of seasonal flood concentration index (median 0.75) in comparison to the annual floods (median 0.58) shows higher temporal concentration of floods. The flood seasonality of winter events is dominant in the Alps; however, along the northern fringe (i.e. the Isar, Iller and Inn River) the timing of winter half-year floods is diverse. The seasonal concentration of summer floods tends to increase with increasing mean elevation of the basins. The occurrence of the three largest summer floods is more stable, i.e. they tend to occur around the same time for the majority of analysed basins. The results show that fixing the summer and winter seasons to specific months does not always allow a clear distinction of the main flood generation processes. Therefore, criteria to define flood typologies that are more robust are needed for regions such as the Upper Danube, with large climate and topographical variability between the lowland and high elevations, particularly for the assessment of the effect of increasing air temperature on snowmelt runoff and associated floods.