Articles

A WWAO collaboration has published a new paper on how to use next-generation satellite snow data to improve seasonal water supply forecasts using machine learning.

Does the public sector need the private sector’s help to address the freshwater crisis? 

Using remote-sensing data and machine learning, a team from NASA and beyond finds that switching to lower-intensity crops can reduce water consumption in California’s Central Valley by 93%, but this requires adopting uncommon crop types.

Resurrected for the first time in decades by an epic deluge of winter rain and snow, by spring the lake covered more than 100,000 acres, stretching over cotton, tomato and pistachio fields and miles of roads.

Remote-sensing data is becoming crucial to solve some of the most important environmental problems, especially those related to agricultural applications and food security.

As the world looks for sustainable solutions, a system tapping into NASA satellite data for water management has passed a critical test.

Rapid declines are most common in aquifers under croplands in drier regions, including California, the most extensive analysis of groundwater trends so far shows.

Though the Sacramento Valley has relatively abundant surface-water supplies, groundwater is also key for many of its communities and farms.

Almost one-third of American potatoes are grown in the Snake River Plain, a belt of low-lying land in the southern part of the state.

Much recent attention towards groundwater sustainability has focused on the heavily overdrafted San Joaquin Valley. However, the Sacramento Valley also needs to bring its groundwater basins into balance and avoid significant undesirable results of pumping.