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Downscaling of atmosphere-ocean general circulation models (AOGCMs) is necessary to transfer predictions of potential climate change scenarios to local levels. This is of special interest in dry mountainous areas, which are particularly vulnerable to climate change due to risks of reduced freshwater availability. These areas play a key role in hydrology, since they usually receive the highest local precipitation amounts, which are then stored in the form of snow and glaciers. The performance and ability to simulate extreme events of a statistical downscaling model (SDSM) were tested in the arid Upper-Elqui watershed, Chile. Thereafter, future temperature and precipitation seasonal trends along with agro-hydrological indices were analysed for the HadCM3 A2a and B2a scenarios. Maximum and minimum temperatures for both linear trends and extreme events were simulated accurately. However, the results show that SDSM was not a very robust method for the simulation of precipitation. Nevertheless, future trends and indices indicate possible strong inter-seasonal perturbations.