We examine the response of streamflow to long-term rainfall variability under climate change by coupling downscaled global climate model precipitation to a distributed hydrologic model. We use daily output of the coupled global climate model ͑CGCM2͒ of the Canadian Centre for Climate Modelling and Analysis corresponding to the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios B2 scenario. The B2 scenario envisions slower population growth ͑10.4 billion by 2100͒ with

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... a more rapidly evolving economy and more emphasis on environmental protection. We use the Hydrologic Modeling System of the Hydrologic Engineering Center for distributed hydrologic modeling. Because of the incongruence between the spatial scale of the CGCM2 output and that of the hydrologic model, a new space-time stochastic random cascade model was implemented in order to downscale the CGCM2 precipitation. The downscaling model accounts for the observed spatial intermittency of precipitation as well as for the self-similar scaling structure of its spatial distribution. For the South Platte basin, results show that the distribution of peak flow rate is more sensitive to the spatial variability of rainfall than total runoff volume. Results also show that the relative impact of long-term rainfall variation associated with climate change on total runoff and peak flow can be much greater than the magnitude of the rainfall variation itself, and that the magnitude of the impact depends strongly on the magnitude of the associated change in evapotranspiration.