As an alternative to the commonly used univariate flood frequency analysis, copula frequency analysis can be used. In latter case more than one variable can be considered in the analysis, while in the first case, in most cases, only peak discharge values are analysed. In this study, 58 flood events at the Litija gauging station on the Sava River in Slovenia were analysed, selected based on annual maximum discharge values. Corresponding hydrograph volumes and durations were considered. The Gumbel–Hougaard copula was selected as the most appropriate for the pair of peak discharge and hydrograph volume. The same copula was also selected for the pair hydrograph volume and duration, and the Student-t copula was selected as the most appropriate for the pair of peak discharge and duration of flood.
COBISS.SI-ID: 6468961
Trivariate 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.
COBISS.SI-ID: 6578273
The identification of statistical trends and seasonality is significant for understanding current global climate change. In this study, discharge data from the Litija gauging station on the Sava River were used to perform flood frequency and seasonality analyses and identify trends. A statistically significant decreasing trend was detected in the mean monthly discharge values; however, the magnitudes of extreme events increased for the Litija station. The results of the study showed that the identified trends and their statistical significance depended on how the samples were defined.
COBISS.SI-ID: 6601313
Flood frequency analysis can be made by using two types of flood peak series, i.e. the annual maximum and peaks-over-threshold series. This study presents a comparison of the results of both methods for data from the Litija 1 gauging station on the Sava River in Slovenia. The results showed a better performance for the method of L-moments when compared with the conventional moments and maximum likelihood estimation. The combination of the method of L-moments and the log-Pearson type 3 distribution gave the best results of all the considered AM cases. The POT method gave better results than the AM method.
COBISS.SI-ID: 6315617
Frequency analyses are a basis for designing discharge estimations. Univariate flood frequency analyses are usually applied in hydrological practice. Hydrological processes are multivariate, however multivariate analyses are needed. Copula function can be used for multivariate modelling. Classical univariate flood frequency analyses are a precondition for the copula analyses. Flood frequency analyses were made on the annual maximum series data from gauging station Litija on the Sava River. Three copulas from the Archimedean family were used; parameters were estimated with method of moments (based on the Kendall correlation coefficient). Some joint return periods were calculated and compared with the univarite return periods. Differences between return periods were not negligible. In the case of a flood event in 1990, which was the largest in the observed period, TAND was 92 years and TOR was 17 years. Univariate return periods lay between these two values. Statistical and graphical performance measures were used to choose the best fit copula function. Gumbel-Hougaard copula gave better results than Clayton and Frank copulas.
COBISS.SI-ID: 6617953