We focused on the effect of two types of “downscaling” methods. Downscaling is the process of translating Global Climate Model (GCM) projections with scales of 1 -2 degrees latitude and longitude to a spatial resolution suitable for basin scale hydrologic modeling (e.g. 25 km). We compared the effects of statistical downscaling, a method based on historical observations, to a physics-based method that uses a regional climate model (dynamical downscaling).
We analyzed simulations of three Global Climate Models (GCM) selected for their accurate representation of historic climatology and prevailing precipitation-bearing synoptic conditions in the southwest US. An analysis of both statistically and dynamically downscaled simulations for these GCMs showed a projected increase in the frequency of dry winters during the mid-21st century (2020-2059). For the summer precipitation, the GCMs were inconclusive and yielded contradicting precipitation projections.
To assess the impact of the projected changes in precipitation on the hydrologic cycle, we developed a modeling framework that includes the following components: 1) a weather generator that produces realizations of likely to occur hourly precipitation events; 2) a hydrologic model that simulates the streamflow and 3) a water resources model. For the USCR Basin, we used a groundwater reservoir to estimate recharge and water storage. For the Bill William River Basin, we used a lake model with the existing Army Corps of Engineers recommended operational rules to simulate the water levels and outflow from Alamo Lake.
We assessed the projected future water deficit in the USCR Basin and the additional water storage and that is needed in order to ensure a reliable water supply in the region. We also examined the impact of the projected mid 21-century precipitation patterns on Alamo Lake on the frequency of large releases from the dam and low water level conditions.
For both case studies, the results from the dynamically downscaling procedure yield a larger range of impacts than those provided by statistical downscaling procedure. In addition to this larger variability, the dynamic downscaling simulations also showed increasing uncertainty by simulating contradicting trends among the selected climate projections for mid-21st Century.