The Peak Over Threshold Method (POT) was used as an alternative technique to the traditional analysis of annual discharge maxima of the Danube River. The POT method was applied to a time-series of daily discharge values covering a period of 60 years (1931-1990) at the following gauge stations: Achleiten, Kienstock, Wien, Bratislava and Nagymaros. The first part of the paper presents the use of the POT method and how it was applied to daily discharges. All mean daily discharges exceeding a defined threshold were considered in the POT analysis. Based on the POT waves independence criteria the maximum daily discharge data were selected. Two theoretical log-normal (LN) and Log-Pearson III (LP3) distributions were used to calculate the probability of exceeding annual maximum discharges. Performance of the POT method was compared to the theoretical distributions (LN, LP3). The influence of the data series length on the estimation of the N-year discharges by POT method was carried out too. Therefore, with regard to later regulations along the Danube channel bank the 40, 20 and 10-year time data series were chosen in early of the 60-year period and second analysed time data series were selected from the end of the 60-year period. Our results suggest that the POT method can provide adequate and comparable estimates of N-year discharges for more stations with short temporal coverage. and Príspevok sa zaoberá analýzou extrémnych hydrologických udalostí na Dunaji metódou Peak Over Threshold (POT). Metóda POT sa používa ako alternatíva určovania N-ročných prietokov k metóde ročných maxím pri analýzach extrémnych hydrologických udalostí. Pre výskyt vrcholových prietokov sa zvyčajne predpokladá Poissonova distribúcia. Základnými vstupnými údajmi pre štatistickú analýzu sú 60-ročné časové rady priemerných denných prietokov a 60-ročné rady maximálnych ročných prietokov v nami zvolených staniciach: Achleiten, Kienstock, Viedeň, Bratislava a Nagymaros - za obdobie 1931-1990. Extrémne hydrologické udalosti na Dunaji boli analyzované metódou POT, ktorá zahŕňa všetky maximálne denné prietoky povodní za dané obdobie, presahujúce zvolenú prahovú hodnotu. Na zostavenie teoretickej čiary prekročenia boli vybrané dve teoretické rozdelenia pravdepodobnosti: logaritmicko-normálne rozdelenie (LN) a Pearsonovo rozdelenie III. typu (LP III). Druhým cieľom príspevku bolo analyzovať vplyv zmeny dĺžky časového radu na odhad N-ročných prietokov. V práci boli 60-ročné časové rady údajov skrátené na 40, 20 a 10-ročné rady. V závere sme porovnali a zhodnotili získané výsledky štatistických odhadov N-ročných prietokov vo zvolených staniciach. Z výsledkov analýzy vyplýva, že metóda POT dáva pomerne dobré odhady N-ročných prietokov aj pre krátke časové rady údajov.
Direct interpolation of daily runoff observations to ungauged sites is an alternative to hydrological model regionalisation. Such estimation is particularly important in small headwater basins characterized by sparse hydrological and climate observations, but often large spatial variability. The main objective of this study is to evaluate predictive accuracy of top-kriging interpolation driven by different number of stations (i.e. station densities) in an input dataset. The idea is to interpolate daily runoff for different station densities in Austria and to evaluate the minimum number of stations needed for accurate runoff predictions. Top-kriging efficiency is tested for ten different random samples in ten different stations densities. The predictive accuracy is evaluated by ordinary cross-validation and full-sample crossvalidations. The methodology is tested by using 555 gauges with daily observations in the period 1987-1997. The results of the cross-validation indicate that, in Austria, top-kriging interpolation is superior to hydrological model regionalisation if station density exceeds approximately 2 stations per 1000 km2 (175 stations in Austria). The average median of Nash-Sutcliffe cross-validation efficiency is larger than 0.7 for densities above 2.4 stations/1000 km2 . For such densities, the variability of runoff efficiency is very small over ten random samples. Lower runoff efficiency is found for low station densities (less than 1 station/1000 km2 ) and in some smaller headwater basins.