evaluate temporal variability and trends in RE across the CONUS
identify climatic and/or water-use factors driving changes in RE.
Methods:
Measured monthly runoff data for water-years 1951 through 2012 aggregated to HUC8’s.
Monthly precipitation (in mm) and temperature (in °C) from PRISM used as inputs to a monthly water balance model to simulate monthly runoff for each HU for comparison with the measured monthly runoff.
Regression and cluster analysis.
Reporting
Reporting
Extending their visualization
What have we learned?
Variability and trends in the time series of mean cluster runoff efficiency were examined and clustered
Several statistically significant (p < 0.05) positively and negatively trending domains were identified
All but one of these significant trends in runoff efficiency can be explained by trends and variability in climate (primarily precipitation); groundwater withdrawals hypothisized for the other.
McCabe, Gregory J., and David M. Wolock. 2016. “Variability and Trends in Runoff Efficiency in the Conterminous United States.”JAWRA Journal of the American Water Resources Association 52 (5): 1046–55. https://doi.org/10.1111/1752-1688.12431.