Stevan Prohaska

Stochastic structure of annual discharges of large European rivers

Abstract Water resource has become a guarantee for sustainable development on both local and global scales. Exploiting water resources involves development of hydrological models for water management planning. In this paper we present a new stochastic model for generation of mean annul flows. The model is based on historical characteristics of time series of annual flows and consists of the trend component, long-term periodic component and stochastic component. The rest of specified components are model errors which are represented as a random time series. The random time series is generated by the single bootstrap model (SBM). Stochastic ensemble of error terms at the single hydrological station is formed using the SBM method. The ultimate stochastic model gives solutions of annual flows and presents a useful tool for integrated river basin planning and water management studies. The model is applied for ten large European rivers with long observed period. Validation of model results suggests that the stochastic flows simulated by the model can be used for hydrological simulations in river basins.

Multiple-coincidence of flood waves on the main river and its tributaries

This paper addresses the definition of multiple coincidences of flood waves on the main river and its tributaries. Contrary to previous studies of partial coincidences of various flood parameters (Prohaska 1999) for the main river and one of its tributaries, this procedure allows for the definition of complex (multiple) coincidences of a single parameter for the main river and several of its tributaries. In particular, coincidence is defined for the major parameter which characterizes a flood (i.e., the flood wave volume). The paper gives a practical example of the analysis of simultaneous flood waves on the Danube and its main tributaries in Serbia: the Tisa and the Sava rivers. The procedure for potential use of the established coincidence functions in applied water management and forecasting is also described in the paper.

Identification of long-term high-flow regime changes in selected stations along the Danube River

Abstract The aim of the paper is to study spatial and temporal changes in the magnitude, duration and frequency of high flows in the Danube basin. A hydrological series of the mean daily discharges from 20 gauging stations (operated minimally since 1930) were used for the analysis of changes in the daily discharges. The high flow events were classified into three classes: high flow pulses, small floods, and large floods. For each year and for each class, the means of the peak discharges, the number and duration of events, and the rate of changes of the rising and falling limbs of the waves were determined. The long-term trends of the annual time series obtained were analyzed and statistically evaluated. The long-term high flow changes were found to be different in three individual high flow classes. The duration of the category of high flow pulses is decreasing at 19 stations on the Danube and is statistically significant at the Linz, Vienna, Bratislava and Orsova stations. The frequency of the high flow pulses is increasing in all 20 stations. Also, the rising and falling rates of the high flow pulse category are increasing at the majority of the stations. The long-term trends of the selected characteristics of the small floods are very similar to the trends of the high flow pulses, i.e., the duration of small floods is decreasing, and their mean number per year is increasing. In the category of large floods the changes were not proved.

Coincidence of Flood Flow of the Danube River and Its Tributaries

The flood coincidence methodology within this contribution gives a statistically sound analysis concerning an important feature of flood genesis. The whole Danube reach is covered by such research, which reveals flood behaviour along the Danube impressively. The practical results could serve as a tool for experts and decision-makers, and aid in determining how to improve flood control and flood plain management and how to arrange this task for the greatest benefit. The fact that, more or less, no significant trends in flood behaviour were detected along the Danube River is worth mentioning. It should be considered that human action and climate change as well could change this substantially. Besides other flood characteristics, this could well change the coincidence behaviour of the Danube and its tributaries. To judge this, the evaluation of historical data is of great importance.

Annual and seasonal discharge prediction in the middle Danube River basin based on a modified TIPS (Tendency, Intermittency, Periodicity, Stochasticity) methodology

Abstract The short-term predictions of annual and seasonal discharge derived by a modified TIPS (Tendency, Intermittency, Periodicity and Stochasticity) methodology are presented in this paper. The TIPS method (Yevjevich, 1984) is modified in such a way that annual time scale is used instead of daily. The reason of extracting a seasonal component from discharge time series represents an attempt to identify the long-term stochastic behaviour. The methodology is applied for modelling annual discharges at six gauging stations in the middle Danube River basin using the observed data in the common period from 1931 to 2012. The model performance measures suggest that the modelled time series are matched reasonably well. The model is then used for the short-time predictions for three annual step ahead (2013–2015). The annual discharge predictions of larger river basins for moderate hydrological conditions show reasonable matching with records expressed as the relative error from −8% to +3%. Irrespective of this, wet and dry periods for the aforementioned river basins show significant departures from annual observations. Also, the smaller river basins display greater deviations up to 26% of the observed annual discharges, whereas the accuracy of annual predictions do not strictly depend on the prevailing hydrological conditions.

Estimation of flood frequencies from data sets with outliers using mixed distribution functions

ABSTRACT In this paper the estimation of high return period quantiles of the flood peak and volume in the Kolubara River basin are carried out. Estimation of flood frequencies is carried out on a data set containing high outliers which are identified by the Rosner’s test. Simultaneously, low outliers are determined by the multiple Grubbs–Beck. The next step involved the usage of the mixed distribution functions applied to a data set from three populations: floods with low outliers, normal floods and floods with high outliers. The contribution of the data set with low outliers is neglected, since it should underestimate the flood quantiles with large return periods. Consequently, the best fitted mixed distribution from the applied types (EV1, GEV, P3 and LP3) was determined by using the minimum standard error of fit.