Reliable estimates of expected extreme flood events are required for design and operation of vital infrastructure and also for more general flood risk management and planning, e.g. emergency planning, flood risk mapping. In practice, this information is obtained through the use of flood frequency estimation techniques based on the principle of analysing series of observed events to infer a probabilistic behaviour, which is then extrapolated to provide estimates of the likely magnitude of future extreme events. While the focus of the Project is to make scientific and technological advances, the systematic assessment of methods for flood frequency estimation will constitute a very important contribution to flood risk management in Europe, and thereby have a direct impact on economic and social development throughout large parts of Europe where flooding is a severe problem.
D.01 Chairing over/coordinating (international and national) projects
Copulas have been used in several scientific fields and also applications of copulas have increased in the last decade. Copulas can be used to model multidimensional processes, however many hydrological processes, like floods and droughts, are multidimensional and therefore copulas seem to be an interesting option to carry out different multivariate analysis or perform bivariate and trivariate frequency analysis using copulas, which can be done as alternative to still mostly used univariate frequency analysis, where just one variable is considered in analysis. Bivariate and trivariate analyses were carried out for the Litija and Gornja Radgona gauging stations, which are booth part of the Danube river basin (Sava and Mura rivers, respectively). Different variables, as e.g. peak discharge (Q), hydrograph volume (V), hydrograph duration (D), hydrograph time ratio (T) suspended sediment concentration (SSC) were analysed and a methodology to estimate monthly sums of SSC is presented.
B.03 Paper at an international scientific conference
COBISS.SI-ID: 6773857Flood frequency analyses are usually made by univariate distribution functions and in most cases only peaks are considered in analyses. However, hydrological processes are multidimensional, so it is reasonable to consider more than one variable in analyses. Copula function successfully models dependence between two or more depended variables and determination of marginal distributions and Copula selection are two separate processes. 58 years of annual maximums on the Litija station were used for analyses and three-points graphical method was used for base flow separation. Some frequently used Copula functions from the Archimedean (Gumbel-Hougaard, Frank, Joe, Clayton, BB1 and Ali-Mikhail-Haq), Elliptical (Student-t and Normal) and Extreme value (Galambos, Hüsler-Reiss and Tawn) families were applied to the data. Conditional return periods, including OR and AND cases, were determined as results of the study.
B.03 Paper at an international scientific conference
COBISS.SI-ID: 6234721Trivariate Frequency Analyses of Peak Discharge, Hydrograph Volume and Suspended Sediment Concentration Data Using Copulas. Copula functions are often used for multivariate frequency analyses, but discharge and suspended sediment concentrations have not yet been modelled together with the use of 3-dimensional copula functions. One hydrological station from Slovenia and five stations from USA were used for trivariate frequency analyses of peak discharges, hydrograph volumes and suspended sediment concentrations. We selected Gumbel–Hougaard copula as the most appropriate model for all discussed stations. We can conclude that copula functions are useful mathematical tool, which can also be used for modelling variables that are presented in this paper.
F.02 Acquisition of new scientific knowledge
COBISS.SI-ID: 6578273Copula functions have been used increasingly in several scientific fields, but applications of copulas in hydrology have increased in the last decade. In the paper the results of some useful case studies of copula application are presented Bivariate and trivariate analyses of flood variables (peak, volume, duration) were carried out. We analysed also the dependance of peak discharge, hydrograph volume and suspended sediment concentration and define the model for estimation of suspended sediment concentration values with the use of measured discharge and precipitation. Statistical tests show that copula model gave better results comparing to the often used regression models.
F.18 Transfer of new know-how to direct users (seminars, fora, conferences)
COBISS.SI-ID: 6474849