There is no doubt that the climate nowadays is changing and will most likely continue to change in the future. These changes, along with other negative impacts, cause alterations in many climate variables. For a better understanding of climate change, climate projections are in use, which enable us to assess the future climate based on the expected levels of greenhouse gases in the atmosphere. In this master's thesis, we focused on the estimation of trends in mean, high, and low annual flows at 52 gauging stations in Slovenia. For trend detection, we applied the Mann-Kendall test with a chosen significance level of α = 0,05. The input data for analysis consisted of projected river flows, which are the product of two or six climate models for the period 2011–2100. The models were selected by the Slovenian environmental agency with the goal of encompassing a wide range of potential flow changes in the future. We evaluated the statistical significance of trends as well as their directions (positive or negative). The proportion of statistically significant trends increased from RCP2.6 to RCP8.5. Mann-Kendall results presented diverse trends, rendering these findings inconclusive. To further assess the magnitude of trends, we used Sen’s slope method. The analysis of Sen’s slope results clearly illustrates that the most significant changes are correlated with high flow indices, while the smallest changes are associated with low flow indices. Across all flow indices, changes increased from RCP2.6 to RCP8.5. The results suggest that certain flow changes can be expected, particularly for the RCP4.5 and RCP8.5 scenarios. It is essential to acknowledge that climate projections entail uncertainties stemming from emission scenario uncertainties, input data, and natural climate variability. The latter is particularly relevant for Slovenia, as river flows continuously change, mainly due to fluctuations in precipitation.
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