In the last few decades global climate is apparently changing. To understand the global climate changes it is important to identify statistical trends.
The thesis presents the statistical analysis of streamflow trends and their significant indices for the chosen water gauging stations in Slovenia on a yearly base, the analysis of distinctive streamflow trends and their indices for the chosen water gauging stations in individual seasons, the assessment of the influence of the water gauging station locations on the variation of streamflows, the assessment of the influence of the length of the time data series on the analysis results and the overview of streamflow trends and their indices according to the individual river basins in Slovenia. 40 water gauging stations with a daily mean discharge time series of 52 years was carried out in the analysis. The analysis was carried using R and Hydrospect software. The Mann-Kendall test was applied for the estimation of the trends in the discharge data series and their indices. The used streamflow indices for the estimation of the variation of the streamflows in time were annual/seasonal mean discharge, annual/seasonal maximum daily discharge, extreme annual/seasonal discharge defined by peak-over-threshold method (POT1 and POT3) and two low flow annual/seasonal discharge indices describing the different duration duration of low flows (7 and 30 days).
The analysis confirmed decreasing of mean annual discharges all over the country, decreasing of the low discharges in the Black Sea catchment area and decreasing of the low discharges at half of the stations in the Adriatic catchment area. The comparison of the trends confirms the landscape diversity of Slovenia, as they differ for the streams in the Eastern part of the country, the upper Sava River and the Adriatic catchment area. The influence of the length of the time data series on the analysis results was also demonstrated in the research.