Crowd-Sourced Water Quality Monitoring

To further the intent of state and federal clean water laws and reduce pollution crises on beaches and in streams, harbors and lakes, why don’t we set up crowd-sourced monitoring?  

It would involve video and audio recordings, viewable (along with related crowd-sourced data) on a public website maintained by the U.S. Environmental Protection Agency (EPA), the Michigan Department of Environmental Quality (MDEQ) or an environmental non-profit.

There could be pages on the website to display routine monitoring (data and visual conditions) and, separately, emergency data and visuals.  

Routine monitoring might include depth, turbidity, color, surface sheen or scum, debris, dead or dying fish or other wildlife, and field test results indicating the presence of toxins or pathogens. It wouldn’t have to be scientifically pure to be useful.  Different people could contribute from various locations at irregular times.

Videos and audios of developing water quality emergencies, supplementing a phone call, likely would influence the speed and nature of agency (e.g. police, health department or environmental) responses.

The severity of the fish kill in the Black River following manure runoff in August 2009; the extent of the July 2010 oil spill in the Kalamazoo River after a corroded pipeline owned by Enbridge Energy ruptured; and the size of the silt runoff from a hundred acres or more stripped of vegetation for a huge construction project on East Grand Traverse Bay in September and October 2014, all could have been recognized and dealt with sooner, had there been routine crowd-sourced monitoring.

See earlier post:

http://detroitwatersewerblog.blogspot.com/2015/07/whos-minding-our-rivers-part-2.html

UPDATE 9-11-15:

Note that "The University of Michigan is investing $100 million into a new project to analyze ‘big data.’ Big data refers to the collection of intensely complex and vast information ...  ’big data’ also refers to how fast information can be collected and how many different types of information can be analyzed together. The university will hold an all-day symposium next month to showcase the new ‘Data Science Initiative’."

http://wdet.org/posts/2015/09/08/81451-u-m-invests-100-million-in-data-service-initiative/