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This paper aims to reveal the annual regime, time series, and long-term water temperature trends of the Danube River at Bratislava, Slovakia, between the years 1926 and 2005. First, the main factors affecting the river's water temperature were identified. Using multiple regression techniques, an empirical relationship is derived between monthly water temperatures and monthly atmospheric temperatures at Vienna (Hohe Warte), Austria, monthly discharge of the Danube, and some other factors as well. In the second part of the study, the long-term trends in the annual time series of water temperature were identified. The following series were evaluated: 1) The average annual water temperature (To) (determined as an arithmetic average of daily temperatures in the Danube at Bratislava), 2) the weighted annual average temperature values (To ) (determined from the daily temperatures weighted by the daily discharge rates at Bratislava), and 3) the average heat load (Zt) at the Bratislava station. In the long run, the To series is rising; however, the trend of the weighted long-term average temperature values, To , is near zero. This result indicates that the average heat load of the Danube water did not change during the selected period of 80 yr. What did change is the interannual distribution of the average monthly discharge. Over the past 25 yr, an elevated runoff of "cold" water (increase of the December-April runoff) and a lower runoff of "warm" water (decrease of the river runoff during the summer months of June-August) were observed.

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Abstract:In this paper we focused on the history of floods and extreme flood frequency analysis of the upper Danube River at Bratislava. Firstly, we briefly describe the flood marks found on the Danube River in the region of Bratislava, Slovakia, and provide an account of the floods' consequences. Secondly, we analyzed the annual maximum discharge series for the period 1876-2012, including the most recent flood of June 2013. Thirdly, we compare the values of T-year design discharge computed with and without incorporating the historic floods (floods of the years 1501, 1682, and 1787 into the 138-year series of annual discharge peaks). There are unfortunately only a few historic flood marks preserved in Bratislava, but there are very important and old marks in neighbouring Hainburg and other Austrian cities upstream to Passau. The calculated T-year maximum discharge of the Danube at Bratislava for the period 1876-2010 without and with historic flood values have been compared. Our analysis showed that without incorporating the historic floods from the years 1501, 1682, and 1787 the 1000-year discharge calculated only with data from the instrumented period 1876-2013 is 14,188 m 3 s -1 , and it is lower compared to the 1000-year discharge of 14,803 m 3 s -1 when the three historic floods are included. In general, the T-year discharge is higher throughout the whole spectrum of T-year discharges (10, 20, 50, 100, 200, 500-year discharge) when the three historic floods are included. Incorporating historic floods into a time series of maximum annual discharge seems to exert a significant effect on the estimates of low probability floods. This has important implications for flood managements and estimation of flood design discharge.

The extent (determined by the repellency indices RI and RIc) and persistence (determined by the water drop penetration time, WDPT) of soil water repellency (SWR) induced by pines were assessed in vastly different geographic regions. The actual SWR characteristics were estimated in situ in clay loam soil at Ciavolo, Italy (CiF), sandy soil at Culbin, United Kingdom (CuF), silty clay soil at Javea, Spain (JaF), and sandy soil at Sekule, Slovakia (SeF). For Culbin soil, the potential SWR characteristics were also determined after oven-drying at 60°C (CuD). For two of the three pine species considered, strong (Pinus pinaster at CiF) and severe (Pinus sylvestris at CuD and SeF) SWR conditions were observed. Pinus halepensis trees induced slight SWR at JaF site. RI and RIc increased in the order: JaF < CuF < CiF < CuD < SeF, reflecting nearly the same order of WDPT increase. A lognormal distribution fitted well to histograms of RIc data from CuF and JaF, whereas CiF, CuD and SeF had multimodal distributions. RI correlated closely with WDPT, which was used to develop a classification of RI that showed a robust statistical agreement with WDPT classification according to three different versions of Kappa coefficient.

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Prediction of Water Quality in the Danube River Under extreme Hydrological and Temperature ConditionsOne of the requirements imposed by the Water Framework Directive (WFD, 2000/60/EC) is to analyze and predict how quality of surface waters will evolve in the future. In assessing the development of a stream's pollution one must consider all sources of pollution and understand how water quality evolves over time. Flow and water temperature regime of a stream or river are the main factors controlling the extent to which deterioration of a stream's water quality can propagate under constant input from pollution sources. In addition, there is ever increasing public concern about the state of the aquatic environment. Decision makers and scientists involved in water management call for studies proposing simulation models of water quality under extreme natural hydrologic and climatic scenarios. Also, human impact on water resources remain an issue for discussion, especially when it comes to sustainability of water resources with respect to water quality and ecosystem health. In the present study we investigate the long-term trends in water quality variables of the Danube River at Bratislava, Slovakia (Chl-a, Ca, EC, SO2-, Cl-, O2, BOD5, N-tot, PO4-P, NO3-N, NO2-N, etc.), for the period 1991-2005. Several SARIMA models were tested for the long-term prediction of selected pollutant concentrations under various flow and water temperature conditions. In order to create scenarios of selected water quality variables with prediction for 12 months ahead, three types of possible hydrologic and water temperature conditions were defined: i) average conditions - median flows and water temperature; ii) low flows and high water temperature; and iii) high flows and low water temperature. These conditions were derived for each month using daily observations of water temperature and daily discharge readings taken in the Danube at Bratislava over the period 1931-2005 in the form of percentiles (1th-percentile, median, 99th-percentile). Once having derived these extreme-case scenarios, we used selected Box-Jenkins models (with two regressors - discharge and water temperature) to simulate the extreme monthly water quality variables. The impact of natural and man-made changes in a stream's hydrology on water quality can be readily well simulated by means of autoregressive models.