HydroGEN Project Awarded $5 Million to Model National Water Resources Using Machine Learning

Sept. 16, 2021
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Dr. Laura Condon, College of Science

Image: UArizona College of Science

Congratulations to HAS Assistant Professor Laura Condon for her newly funded $5 million NSF grant, the HydroGEN Project, which will model national water resources using machine learning. 

You can read the original article by Mikayla Mace Kelly, University Communications, here (excerpted material follows).

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Willow Creek Entering the Taylor Reservoir in Colorado ©-Drew-Bennett-DJI_0946_web.jpg

Image: Willow Creek Entering the Taylor Reservoir in Colorado © Drew-Bennett-DJI_0946_web.jpg


As extreme weather events such as flooding and drought become more common in a climate impacted by humans, understanding and predicting water resources and systems becomes more important than ever.

Condon's new project, dubbed HydroGEN for or Hydrologic Scenario Generation, will put the best hydrologic science directly in the hands of landscape managers, resource managers and policymakers so that they can make informed decisions.

Condon is principal investigator of the project, which is part of the National Science Foundation's Convergence Accelerator program, which aims to support interdisciplinary efforts to solve real-world problems quickly.

Advanced hydrological models capable of simulating rapidly changing ecosystems are often only used in an academic setting because they are time consuming and expensive to build and require extensive expertise. Many of the tools used by decision-makers rely on simplifications and assumptions based on past observed behaviors.

HydroGEN bridges that gap by using machine learning to allow any user to build models that are fast-running but scientifically rigorous.

"Our team has expertise in building really advanced hydrological models that cover everything from the bedrock to the treetops, over a national scale," Condon said. "We model hydrological systems that are changing and evolving really well, but these are hard to build and require huge computational resources."

Congratulations, Laura! 

Contacts
Laura Condon