IMPACTS OF CLIMATE CHANGE ON HYDROLOGIC PROCESSES IN THE COLORADO RIVER BASIN

The clear evidence of human-induced hydroclimatic shifts in the western U.S., and especially 
within the Colorado River Basin (CRB), has motivated the research community to pursue 
reliable estimates of future climate change impacts on hydrological processes. Although the 
large body of literature in this field shows consensus on the future drying of the CRB, there 
are large uncertainties in the magnitude of hydrologic changes because of differences in 
experimental approaches. Hence, this work focuses on the effects of methodological choices, 
in particular those related to hydrologic modeling, on the portrayal of climate change 
impacts at three catchments located in the headwaters of the CRB.
A commentary on the current development of complex process-based hydrologic models is first 
presented. It is argued that the relatively poor performance of such models may occur due to 
restrictions on their ability to refine their portrayal of physical processes, and improving 
hydrological models requires integrating the strengths of prior knowledge of hydrologic 
processes with the strengths of data driven inference. An assessment of the effects of 
hydrologic model choice and parameter calibration on projected hydrologic changes follows. 
Here, it is demonstrated that the subjective selection of model structures may introduce 
large uncertainties to hydrologic projections. Based on this, the third part of this study 
compares the effects of hydrologic model choice and parameter estimation strategies on 
projected climate change impacts. The main finding here is that parameter estimation methods 
can provide similar or larger uncertainties in some hydrologic processes when compared to 
uncertainties coming from model choice. The fourth component of this study evaluates the 
effects of regional climate model (RCM) configuration and forcing scaling on projected 
hydrologic changes. The results illustrate the implications of RCM configuration on projected 
changes of the water cycle, and provide an integrated view of the interplay between forcings 
and hydrologic model structures in the portrayal of climate change impacts. Finally, a 
commentary on the main results of this study and possible ways to move forward is provided. 
It is asserted that a greater role of expert knowledge is required to improve model selection 
and parameter estimation, and also for incorporating non-stationarity in climate change 
impact studies.