Spatial Disaggregation for Studies of Climatic Hydrologic Sensitivity

Abstract

The use of deterministic atmospheric general circulation models (GCMs) to understand potential global climate change under doubled CO\d2 forcing has prompted a need for better understanding of local hydrologic impacts. Incongruities in model resolutions do not allow for GCM output to be directly used as forcing in the smaller-scale hydrologic models. In this work, daily spatial disaggregation techniques are applied to the upper Rio grande basin in Colorado, simulating local temperature and precipitation regimes, and preserving spatial covariance structures at all spatial scales. Canadian Climate Centre GCM output is disaggregated to site-specific locations within the study basin. The precipitation runoff modeling system is then used to examine hydrologic sensitivity under the disaggregated climate forcing. The results form this sensitivity indicate that under spatially disaggregated, site-specific, climatic forcing, significant snowpack-accumulation decreases occur. This results in total annual runoff decreases of, on average, 17.7%. A seasonal shift toward earlier in the year is observed in peak runoff, soil moisture storage, and evapotranspiration.