Bayesian inference of historical streamflow changes suggests further stress in the Colorado River Basin

Study region

Colorado River Basin (CRB), North America

Study focus

Bayesian inference is used to analyze long-term streamflow in the CRB. Key parameters describing long-term hydroclimatic changes are integrated into a state-space model (SSM). Results from Global Climate Models (GCMs), coupled with downscaling and hydrologic modeling, are used by the SSM to inform these parameters, which are then updated based on historical observations. Multidecadal streamflow projections are made using the SSM and subsequently applied to the Colorado River Simulation System (CRSS) model to examine future river system conditions.

New hydrological insights for the region

The SSM projects a long-term decline (in both average and upper and lower confidence intervals) of annual streamflow in the CRB. Compared to some GCM-coupled modeling results, the SSM suggests a modest decrease of annual precipitation in the Upper Basin because of climate change (e.g., 2.3 % lower from the long-term average by 2050), a greater temperature sensitivity (reduction per unit temperature increase) of streamflow, and thus a larger streamflow decline. The observed averaged streamflow during 2000–2023 generally aligns with the decreasing trend in the SSM out-of-sample validations and is projected to become an average condition by ∼2040, along with further declines afterwards. Additional river system modeling from the CRSS suggests, despite extraordinary conservations in recent years, additional efforts may be necessary to sustain regional water supply amid climate change.