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In this study we investigate the effect of different downscaling methods on the hydrologic cycle of a Mediterranean catchment in Sardinia (Italy) that is prone to extreme flooding. To this aim, we use an ensemble of four combinations of GCM - RCM projections (see Deidda et al., 2013, and Langousis et al., 2016), statistically downscaled using: a) the parametric statistical scheme of Mamalakis et al. (2017), and b) its widely used non-parametric variant based on empirically derived Q-Q (quantile-quantile) correction relationships. In particular, we analyze differences in the climate projections of the available downscaled climate model outputs, considering or not the elevation factor (in the latter case by re-projecting outputs at the mean elevation of the basin). We further quantify the impact of these differences on modeled hydrologic variables. The hydrologic impact of climate change is evaluated during five 30-year periods (1951-1980, 1981-2010, 2011-2040, 2041-2070, 2071-2100), focusing on a set of variables that characterize the water balance, including precipitation, air temperature, discharge, leakage, and actual evapotranspiration. The response of the basin is quantified at the outlet and also at 33 subcatchments, analyzing the influence of features such as the area and mean elevation of the subcatchments. The results show that the choice of climate model and downscaling method leads to variations in the simulated hydrologic response of the basin, and that this effect varies also by subwatershed. Notwithstanding these differences, the reduction in precipitation predicted by the climate models is more pronounced as the watershed area increases, and as the altitude decreases. References:Deidda, R., M. Marrocu, G. Caroletti, G. Pusceddu, A. Langousis, V. Lucarini, M. Puliga, and A. Speranza (2013). Regional climate models' performance in representing precipitation and temperature over selected Mediterranean areas, Hydrol. Earth Syst. Sci., 17(12), 5041-5059, doi:10.5194/hess-17-5041-2013.Langousis, A., A. Mamalakis, R. Deidda and M. Marrocu (2016). Assessing the relative effectiveness of statistical downscaling and distribution mapping in reproducing rainfall statistics based on climate model results, Water Resour. Res., 52, doi:10.1002/2015WR017556.Mamalakis, A., A. Langousis, R. Deidda, and M. Marrocu (2017). A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall, Water Resour. Res., 53, doi:10.1002/2016WR019578. [ABSTRACT FROM AUTHOR]

Assessment of the impacts of climate change on hydrological regime is important for sustainable water resources management. The objective of this study is to assess the impacts of future climate changes on the hydrological regime of the headwater catchment of the Vistucky Creek (area 9.8 km2) in south-western Slovakia. Changes in climatic characteristics (i.e., precipitation and air temperature) for periods 2022-2060 and 2062-2100 were prepared by two regional climate models KNMI and MPI using the A1B emission scenario (average related to fossil carbon production). Both climatic scenarios assume increase in the air temperature and precipitation (higher in winter than in summer). A lumped conceptual rainfall-runoff model (the HBV-based TUW model) was used to simulate the catchment hydrological behaviour. The TUW model was calibrated for the reference period of 1982 – 2008. The calibration of the model was performed 50 times with a differential evolution algorithm. After obtaining the collection of the 50 parameter sets, the best set (in terms of Nash-Sutcliffe efficiency and the volume error) was chosen. This set of model parameters was used for the simulation of long-term mean monthly runoff for the three periods (i.e., 1982-2008, 2022-2060, and 2062-2100).The results show that changes in the long-term runoff seasonality and extremality of hydrological cycle could be expected in the future if the climate changes as the scenarios assume. The runoff should increase in autumn and winter months (i.e., from September to February) and decrease in spring and summer months (i.e, from April to August) compared to the reference period. Peakflows should increase in period 2062-2100 while discharge minima should slightly decrease (only for the climatic data from the KNMI model). It indicates possible increase in flow extremality. Catchment water storage as expressed by the soil moisture index and baseflow should decrease in period 2062-2100, especially according to climatic data from the KNMI model. Our contribution will discuss these changes in hydrological regime in the climate change context.AcknowledgmentThis work was supported by the Slovak Research and Development Agency under the contract No. APVV-15-0497. [ABSTRACT FROM AUTHOR]