For more than three decades, researchers have utilized the Snowmelt Runoff Model (SRM) to test the impacts of climate change on streamflow of snow-fed systems. In this study, the hydrological effects of climate change are modeled over three sequential years using SRM with both typical and recommended (parameter shift) methodology. We predict the impacts of climate change on water resources of the five most productive watersheds tributary to the Rio Grande.  These basins collectively supply more than 75% of the total river volume. Surface temperature and precipitation from atmosphere-ocean general circulation models (GCM) from the coupled model intercomparison project CMIP3 and CMIP5 multi-model data set are downscaled to weather stations used to force the SRM.  Period change analysis (1990-2000) vs. (2090-2100) is used to derive temperature and precipitation changes for 55 GCM simulations. However, for each basin we subsample the range of uncertainty characterized by these 55 GCMs into only four extreme mean states representing warmer/wetter, warmer/drier, hotter/wetter, and hotter/drier mean future projections. Results indicate an increase in temperature between 3.0-6.2 °C and an 18% decrease to 26% increase in precipitation. Following parameterization of SRM, the difference between measured and computed volume is 10% and Nash-Sutcliffe Efficiency is 0.87. Without modifications to the snow runoff coefficient (Cs), results range from a reduction in total volume of 21% to an increase in total volume of 4% ((hotter/drier (-21%); warmer/drier (-18%); hotter/wetter (3%); warmer/wetter (4%)). Despite an increase in precipitation in the hotter/wetter scenario, total volume decreased in three of five simulated basins.  Modifications to Cs resulted in a 0 to 16% difference in simulated annual volume. Results indicate future application of SRM should include a parameter shift representing the changed climate.