Hydropower is a key contributor to the nation’s renewable energy portfolio, helping to fill in the gaps between traditional sources of electricity and intermittent renewable sources such as wind and solar. However, as climate change results in more extreme weather events across the United States — particularly droughts in the west — it is crucial to better understand and predict the conditions that impact sustainable hydropower electricity generation and what operational changes can be made to mitigate these impacts.
A new report released by the U.S. Department of Energy’s Oak Ridge National Laboratory details findings from its third climate change impact assessment for hydropower — part of a multi-year study directed by the SECURE Water Act of 2009 Section 9505.
In consultation with the federal power marketing administrations and other federal agencies, ORNL led a series of assessments for 132 federal hydropower plants across the United States to examine the potential effects of climate change on water available for hydropower generation and on the marketing of power from these federal facilities.
A spatially consistent assessment approach was designed to enable interregional comparisons. This approach used a series of models and methods with different spatial resolutions to gradually downscale global climate change signals into watershed-scale hydrologic projections to support hydropower impact assessments. In the first of three assessments, a variety of historic meteorologic and hydrologic observations, hydropower facility characteristics and geospatial data sets were collected to support model development, calibration and verification. The second assessment provided future seasonal and monthly hydropower projections to support long-term hydropower marketing planning. Finally, the third assessment adopted a multimodel assessment framework to better reveal the uncertainties in future hydrologic and hydropower projections. During each assessment, the latest climate projection information from the Coupled Model Intercomparison Project was used to support the modeling and analysis.