Publications

Currier, WR; Wood, AW; Mizukami, N; Nijssen, B; Hamman, JJ; Gutmann, ED (2023). Vegetation Representation Influences Projected Streamflow Changes in the Colorado River Basin. JOURNAL OF HYDROMETEOROLOGY, 24(7), 1291-1310.

Abstract
Vegetation parameters for the Variable Infiltration Capacity (VIC) hydrologic model were recently up-dated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Previous work showed that these MODIS-based parameters improved VIC evapotranspiration simulations when compared to eddy covari-ance observations. Due to the importance of evapotranspiration within the Colorado River basin, this study provided a basin-by-basin calibration of VIC soil parameters with updated MODIS-based vegetation parameters to improve streamflow simulations. Interestingly, while both configurations had similar historic streamflow performance, end-of-century hydrologic projections, driven by 29 downscaled global climate models under the RCP8.5 emissions scenario, differed between the two configurations. The calibrated MODIS-based configuration had an ensemble mean that sim-ulated little change in end-of-century annual streamflow volume (10.4%) at Lees Ferry, Arizona, relative to the his-torical period (1960-2005). In contrast, the previous VIC configuration, which is used to inform decisions about future water resources in the Colorado River basin, projected an 11.7% decrease in annual streamflow. Both VIC configura-tions simulated similar amounts of evapotranspiration in the historical period. However, the MODIS-based VIC con -figuration did not show as much of an increase in evapotranspiration by the end of the century, primarily within the upper basin's forested areas. Differences in evapotranspiration projections were the result of the MODIS-based vege-tation parameters having lower leaf area index values and less forested area compared to previous vegetation esti-mates used in recent Colorado River basin hydrologic projections. These results highlight the need to accurately characterize vegetation and better constrain climate sensitivities in hydrologic models.

DOI:
10.1175/JHM-D-22-0143.1

ISSN:
1525-7541