New Mexico

Rivers like the Rio Grande and tributaries of the Colorado River deliver much of New Mexico’s usable water. However, river hydrology – the distribution and movement of water, along with its physical and chemical properties – can be hard to predict because environmental conditions are ever-changing and rivers can run through hard-to-reach, remote locations. Berkeley Lab scientists are using machine learning to learn from past observations and make predictions about hydrology at new locations with fewer observations. With more accurate predictions, jurisdictions can better manage dwindling freshwater resources as demand continues to rise.

Zanskar uses AI, big data, and advanced sensing to discover and unleash domestic geothermal energy resources. The startup graduated from Berkeley Lab’s science entrepreneur fellowship program, Cyclotron Road, in 2022. Now, its New Mexico-based Lightning Dock power plant houses the world’s most productive pumped geothermal well in the U.S., providing baseload power for people around the state. The company’s technology could help make geothermal energy a cheaper and more abundant source of electricity for all Americans. 

Devastating wildfires have become increasingly routine in the American West. Consumer-priced air monitors have become popular in recent years for checking the level of wildfire smoke exposure. Berkeley Lab scientists compared four such monitors against a research-grade instrument as a reference, and found that these accessible monitors can provide actionable information to help Americans understand how to protect themselves and their families from wildfire smoke.