New research reveals that "foundation models" trained on vast, general time-series data may be able to forecast river flows accurately, even in regions with little or no local hydrological records.

Rather than relying on passive slides and outdated examples, Amber Book develops courses around real engineering challenges - helping engineers apply lessons immediately on the job: strengthening ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

The Beaver Watershed Alliance (“BWA”) announced an acquisition of a Clean Water Act Section 319 Grant for use in the Beaver Lake Watershed to: ...