The Minnesota Stormwater Seminar Series provides an opportunity to learn about the most recent research, discoveries, and case studies around urban stormwater management specifically for an audience of stormwater practitioners, professionals, and researchers. Seminars include a presentation, panel discussion, and Q&A with participants.
2024 Seminars
- January 18: Capturing and quantifying coarse organic matter in urban stormwater - John Chapman, Univ. of MN
- February 22: Performance of Stormwater Products and Practices: Why it Matters - Seth Brown, NMSA
- March 14: Rethinking Green Stormwater Infrastructure in Place - Ashlynn Stillwell, Univ. of Illinois Urbana-Champaign
- April 18: Plants and vegetation in stormwater practices - John Bly
- May 16: Urban Long Term Ecological Restoration (LTER) Project - Sarah Hobbie
- June 20: Lauren McPhillips
Seminars
Plants for Stormwater Design, Interactive Selection Tool for Stormwater Professionals and the Public
Green infrastructure (rain gardens, bioinfiltration) requires choosing the correct plants for the site, soils, and situation. Join us for this seminar featuring the results of a recently completed research project - Plants for Stormwater Design, Interactive Selection Tool for Stormwater Professionals and the Public.
Rethinking Green Stormwater Infrastructure in Place
Green stormwater infrastructure can function reliably in combination with grey infrastructure under a wide range of conditions, with important environmental justice considerations in sustainable stormwater management.
Performance of Stormwater Products and Practices: Why it Matters.
This presentation will provide and update on Federal policies and national trends driving the stormwater sector today as well as share information on national-level initiatives that focus on developing, coordinating and planning for means to evaluate the efficacy of stormwater control measures in controlled environments as well as administering third-party testing efforts to provide users of stormwater infrastructure a high level of confidence in the performance of these control measures.