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Climate change is presently a widely discussed subject in relation to alterations in water storage capacity and the components of the hydrological balance within catchment areas. This research study was directed at two main objectives: 1. The indirect estimation of long-term mean annual runoff using an empirical model; 2. The determination of changes in the annual runoff regime of fifty Danube sub-basins. Monthly areal precipitation, discharges, and air temperature data from 1961 to 1990 were collected for selected headwater sub-basins of the Danube River. In the first part, Turc-type empirical equations for the estimation of the long-term average annual runoff R in the Danube basin were employed. The parameters of the empirical equations were determined through nonlinear regression. Given the underestimation of the actual (territorial, balance) evapotranspiration ET values determined from the balance equation, the precipitation totals were corrected by +10%. With a 10% increase in precipitation, the values of balance ET reached the values ET determined by the Budyko–Zubenok–Konstantinov method. In the second part, fifty equations for the estimation of changes in the average annual runoff, depending on increases in the air temperature and changes in the annual precipitation separately for each of the 50 sub-basins, were established. In conclusion, the results suggest that, on average, a 100 mm increase in the average annual rainfall in the Danube River headwater sub-basins, will cause a 50 mm increase in outflow, and a 1 °C increase in the average annual air temperature will lead to a 12 mm decrease in runoff.

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Combined visualizations of filamentous structures and surrounding volumetric objects are common in biological and medical applications. Often, the structures' spatial relationships remain unclear to the viewer. In this paper, we discuss and evaluate techniques to emphasize spatial relationships. We concentrate on the visualization of transparent objects and intersecting lines. Among various techniques, participants of an exploratory user study preferred coloring of lines, marking of line-surface intersections by glyphs, and the combination of both. These techniques were additionally evaluated in a confirmatory study in which participants were asked to judge whether a filament runs through a transparent structure. We found that the evaluated techniques significantly improve the participants' performance in terms of the number of correct responses and response time. The best performance was found for the combination of line coloring and intersection glyph display. [ABSTRACT FROM AUTHOR]

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.

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.

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.

The aim of the presented research is improvement of methodology for probability calculation of coinciding occurrence of historic floods and droughts in the same year. The original procedure was developed in order to determine the occurrence probability of such an extreme historic event. There are two phases in calculation procedure for assessment of both extreme drought and flood occurrence probability in the same year. In the first phase outliers are detected as indicators of extreme events, their return periods are calculated and series' statistics adjusted. In the second phase conditional probabilities are calculated: empirical points are plotted, and both extreme drought and flood occurrence probability in the same year is assessed based on the plot. Outlier detection is performed for the territory of Serbia. Results are shown as maps of regions (basins) prone to floods, hydrologic drought, or both. Step-by-step numeric example is given for assessing conditional probability of occurrence of flood and drought for GS Raska on the river Raska. Results of assessment of conditional probability in two more cases are given for combination of extreme flood and 30 day minimum flow.

River flooding in Serbia is a natural phenomenon which largely exceeds the scope of water management and hydraulic engineering, and has considerable impact on the development of Serbian society. Today, the importance and value of areas threatened by floods are among the key considerations of sustainable development. As a result, flood protection techniques and procedures need to be continually refined and updated, following innovations in the fields of science and technology. Knowledge of high flows is key for sizing hydraulic structures and for gauging the cost-effectiveness and safety of the component structures of flood protection systems. However, sizing of hydraulic structures based on computed high flows does not ensure absolute safety; there is a residual flood risk and a risk of structural failure, if a flood exceeds computed levels. In hydrological practice, such floods are often referred to as historic/loads. The goal of this paper is to present a calculation procedure for the objective identification of historic floods, using long, multiple-year series of data on high flows of natural watercourses in Serbia. At its current stage of development, the calculation procedure is based on maximum annual discharges recorded at key monitoring stations of the Hydro-Meteorological Service of Serbia (HMS Serbia). When applied, the procedure results in the identification of specific historic maximum stages/floods (if any) at all gauge sites included in the analysis. The probabilistic theory is then applied to assess the statistical significance of each identified historic flood and to classify the historic flood, as appropriate. At the end of the paper, the results of the applied methodology are shown in tabular and graphic form for various Serbian rivers. All identified historic floods are ranked based on their probability of occurrence (i.e., return period).

When providing hydrologic indicators needed for hydro power plant design, knowledge of mean monthly flows allows for estimation of majority of indicators. The paper deals with a problem of obtaining mean monthly flows at the location where flow observation data do not exist. The closest gauge station from the observation network is selected as an analogue location/basin. Since the selected gauge station observation period is rather short, the extension of the data set is achieved by generating synthetic mean monthly flow series by the nonlinear correlation method explained within the paper. Attention is paid to finding the best fit for correlation within the observation period. Four segmentation types of the correlation curve of transformed values are studied. Observed data are used for estimation of applied model quality i.e. spatial interpolation of surrounding gauge stations to the analogue station. At the selected hydro power plant location, synthetic series of mean monthly flow is calculated by scaling series from the analogue gauge station, using basin area ratio as scaling coefficient. Apart from mean annual flow and annual flow distribution, based on the synthetic mean monthly series, daily flow duration curve and maintenance flow were calculated.