Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.

Zhiqun (Daniel) Deng, Lab Fellow at PNNL, has been named a fellow of the American Society of Mechanical Engineers, an honor that recognizes outstanding engineering achievements.

Researchers at PNNL advised elementary and middle school student teams with their problem-solving research for the FIRST® LEGO® League robotics competitions.

A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.

PNNL's Alison Colotelo receives award from the National Hydropower Association on behalf of Salmon Summit team at the 2024 Clean Currents conference.

Although climate change may bring increased precipitation to many parts of the United States, some areas may face drier conditions and lower streamflow, resulting in decreased hydropower generation.

A new mini-acoustic transmitter and tagging procedure is able to provide data on small, sensitive fish species like the American shad.

The first-of-its kind vessel will allow researchers to transport large equipment and take measurements in near-silence with reduced impact on wildlife.

New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.

PNNL researchers are working to provide the technical assistance and expertise needed for communities to shape their clean energy future.

New research identifies the most important factors in successful fish passage, pointing toward new options for flexible dam operations.

Three scientists at PNNL are lending more than 50 years of expertise to lead efforts to advance the nation’s Blue Economy.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

PNNL signs memorandum of understanding with Oregon State University to support marine science and technology advancements.