2007 EPA Region III Volunteer Monitoring Conference
AGENDA
VOLUNTEER MONITORING IN THE MID ATLANTIC:
CITIZEN SCIENTISTS INVOLVED IN THE WATERSHED
“Using Monitoring Data to Protect and Restore Water Quality”
Tracks - A) Using Watershed Data
B) Managing and collecting data
C) What is the story behind the data?
FRIDAY, October 12, 2007
| 7:30 - 9:00 am | Registration, continental breakfast (poster setup) | ||
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| 9:00 - 10:00 | Plenary (Henkel Hall Auditorium) Emcee - George L. Ohrstrom - Friends of the Shenandoah River (5 min) Welcome - Dr. Tracy Fitzsimmons, Senior Vice President, Shenandoah University (15 min) Keynote speaker - EPA Speaker Mike Haire - The importance of Volunteer Monitoring from an EPA Perspective (30 min) |
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| 10:15 - 11:45 Concurrent Session 1 (sponsored by VWMC) | CSI-A Using volunteer monitoring data at the local, watershed, state, regional levels Panel members from Region 3 states discussing different models of collaboration with volunteers and success stories. |
CSI-B Associating water quality data with land use and BMP performance Presentations on how volunteer monitoring can help track BMP and TMDL performance. |
CSI-C Understanding Water Quality Standards
Topics range from how states classify streams and new or upcoming water quality standards. |
| 12:00 - 1:00 pm | Lunch (Allen Dining Hall) Speaker - David K. Paylor, Director of Virginia Department of Environmental Quality |
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| 1:15 - 2:45 Concurrent Session 2 (sponsored by VWMC) | CSII-A Relaying Results: sending your data in regional, state, and federal databases Participants will receive an overview of various water quality and volunteer monitoring databases to store and access monitoring data. |
CSII-B Unconventional Water Quality Monitoring
Presentations showcasing methods to determine water quality using inexpensive and unconventional methods. |
CSII-C Community Outreach & Successful Collaborations
Learn how monitoring groups can work together with local and state government. Topics include the dos and don'ts of collaboration. |
| 2:45 - 3:00 | Break | ||
| 3:00 - 4:15 | Communicating your needs - Breakout groups where participants explain what they would like to see in the volunteer monitoring movement. |
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| 4:20 - 5:00 | Wrap up - Common themes from the breakout session and where do we go from here. |
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| 5:00 - 6:00 | Poster Session and Raffle | ||
SATURDAY, October 13, 2007
| 8:00 - 9:00 am | Continental breakfast | |||||
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| 9:00 - 12:00 pm Sponsored by Virginia Citizens for Water Quality | FT1 Cave Field Trip |
FT2 SOS Modified Habitat Assessment |
FT3 Rain Barrel Workshop |
Lab 1 Coliscan Easygel |
Lab 2 GIS Workshop |
Lab 3 Data to Information Workshop |
Saturday Event Summary
FT1 Cave Field Trip- Travel to a local cave to learn about Karst topography and how it can impact water quality. Please bring clothes that can get dirty and sturdy shoes.
FT2 SOS Modified Habitat Assessment- Participants can learn about the Modified Habitat Assessment Method used by Save Our Streams volunteers in a local stream. Stream walking may be included so please bring waders or hip boots.
FT3 Rain Barrel Workshop- Participants can build a rain barrel to store rainwater (a $100.00 value). Participants must take the barrel they build with them when they leave the training. Barrels are approximately 30 inches wide by 60 inches tall and can usually fit in the back seat of a non-compact sized car.
Lab 1 Coliscan Easygel- Learn how to use Coliscan Easygel® to detect E. coli bacteria in water. The 2½ hour workshop will go through the necessary steps from collecting samples to counting the E. coli colonies. Participants will receive a free Coliscan kit (a $25.00 value) to take home with them for analysis.
Lab 2 GIS Workshop- Learn how to use free Geographic Information System (GIS) software to analyze and present your monitoring data more effectively.
Lab 3 Data to Information Workshop- Do you have several years of monitoring data? Are you interested in understanding what your data mean? This session will be an opportunity for you to learn basic statistical analysis to find the "story" in your data.