Projection of Streamflow Change Using a Time-Varying Budyko Framework in the Contiguous United States
Abstract
Predicting future streamflow change is essential for water resources management and understanding the impacts of projected climate and land use changes on water availability. The Budyko framework is a useful and computationally efficient tool to model streamflow at larger spatial scales. This study predicts future streamflow changes in 889 watersheds in the contiguous U.S. based on projected climate and land use changes from 2040 to 2069. The temporal variability of surface water balance controls, represented by the Budyko ω parameter, was modeled using multiple linear regression, random forest, and gradient boosting. Results show that random forest is the optimal model and can explain >85% of the variance in most watersheds. Relative cumulative moisture surplus, forest coverage, crop land and urban land are the most important variables of the time-varying ω in most watersheds. There are statistically significant increases in mean annual precipitation, potential evapotranspiration, and ω in 2040-2069, as compared to 1950-2005. This leads to a statistically significant decrease in the runoff ratio (Q/P). Streamflow is projected to decrease in the central, southwestern, and southeastern United States and increase in the northeast. These projections of water availability which are based on future climate and land use change scenarios can inform water resources management and adaptation strategies.
