A key challenge for resource and land managers is predicting the consequences of climate warming on streamflow and water resources. Over the last century in the western US, significant reductions in snowpack and earlier snowmelt have led to an increase in the fraction of annual streamflow during winter, and a decline in the summer. This study explores the relative roles of snowpack accumulation and melt, and landscape characteristics or 'drainage efficiency', in influencing streamflow. An analysis of streamflow during 1950-2010 for 81 watersheds across the western US indicates that summer streamflows in watersheds that drain slowly from deep groundwater and receive precipitation as snow are most sensitive to climate warming. During the spring, however, watersheds that drain rapidly and receive precipitation as snow are most sensitive to climate warming. Our results indicate that not all trends in the western US are associated with changes in snowpack dynamics; we observe declining streamflow in late fall and winter in rain-dominated watersheds as well. These empirical findings have implications for how streamflow sensitivity to warming is interpreted across broad regions.
Provides an example of how to bring the flood of data and information on climate change together to prioritize conservation and management, using an example of a model for Bull trout in the Boise River basin.
Many new tools are becoming available to provide downscaled climate data and help us make management decisions. How do these tools perform when used in an excersize to examine real-world problems? See the example of an exercise done for Bull Trout.