The MGWA Spring conference was held virtually on April 25th, 2024 and focused on artificial intelligence, and machine learning and its integration into groundwater science. The conference included a variety of presentations with applications outside and within Minnesota.
Christoper Olivares from the University of California Irvine School of Engineering was the keynote speaker and discussed how his research group used machine learning to complement PFAS monitoring in the state of California’s groundwater. Sean Donegan and Allan Adams from the company, Satelytics, presented their work on using artificial intelligence to develop algorithms for a variety of applications, such as assessing legacy PFAS or phosphorus in the Lake Okeechobee area. Evan Christianson, a vice President and senior hydrogeologist at Barr Engineering, gave an overview of machine learning and explained how this can complement process-based groundwater flow models like MODFLOW. Chris Gerrits from Crozier Consulting Engineers showed how machine learning was used to determine the maintenance schedule for a Canadian wellfield.
Several speakers gave presentations focused on work specifically within the state of Minnesota. Ben Heile and Sean Buchanen from Seequent and Ben Kroll from AECOM gave a presentation on 3D visualization tools that are used for subsurface data. Some of these technologies are being used as part of the 3M settlement work in the eastern Twin Cities Metropolitan Area. Chris Thielsen from the Itasca Consulting Group described a machine learning model that was developed to predict the stratigraphic codes associated with wells in the state’s County Well Index with 90 percent accuracy. Tarek Tomes, the Commissioner for MNIT, closed the conference by describing how the state of Minnesota is responsibly incorporating artificial intelligence into state government operations.
Click the link below to access all of the conference videos.
Spring Conference Presentation Videos Available (mgwa.org)
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