PNNL has published a report that sets the foundation for modeling gaps and technical challenges in optimizing hydropower operations for both energy production and water management.

California and other areas of the U.S. Southwest may see less future winter precipitation than previously projected by climate models, according to new research that corrects for a long-standing model error: the double-ITCZ bias.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

Culminating 10 years of study, researchers at PNNL’s Marine and Coastal Research Laboratory developed a new predictive framework for estuarine–tidal river research and management.

For decades, the Department of Energy's Pacific Northwest National Laboratory has played a role in establishing and maintaining sustainable hydropower for the region.