Two statistical downscaling models were used to downscale regional climate change scenarios, on the basis of the outputs of three general circulation models (GCMs) and three emission scenarios. Driven by these climate change scenarios, a distributed macro-scale hydrological model (the Variable Infiltration Capacity (VIC) model) was applied to assess the impact of climate change on hydrological processes in the headwater catchment (HC) of the Tarim River basin, China. The results showed that the HC tends to experience warmer and drier conditions under the combined climate change scenarios. The predictions show a decreasing trend of the runoff in the HC, driven by the combined climate change scenarios. The results predicted an increasing trend for winter runoff however, which was consistent with the forecasts from most previous studies on other locations such as the region of St Lawrence tributaries (Quebec, Canada) and the Willamette River Basin (Oregon, USA). There was an inconsistent intra-annual distribution of the changes in precipitation and runoff in the HC; these inconsistencies may be explained by increasing snowmelt runoff resulting from higher air temperature. It was concluded that uncertainties within different GCM outputs are more significant than emission scenarios in the assessment of the potential impact of climate change.