The project goal is to assist the Minnesota Pollution Control Agency (MPCA) with meeting the objectives of the Surface Water Assessment Grant (SWAG) to conduct field and water chemistry monitoring at MPCA specified lake sampling locations and stream locations. This will be accomplished by collecting water samples at seven lake sites and eight streams in the Kettle and Upper St. Croix Watersheds, as well as compiling and submitting the required data, information and reports.
The University of Minnesota will develop effective interview questions for community watershed assessments in the Rainy River basin and provide assistance in understanding the data collected through community interviews.
Approximately 70 percent of all Minnesotans rely on groundwater as their primary source of drinking water. Wells used for drinking water must be properly sealed when removed from service to protect both public health and Minnesota’s invaluable groundwater resources. The Minnesota Department of Health protects both public health and groundwater by assuring the proper sealing of unused wells.
Clean Water funds are being provided to well owners as a 50% cost-share assistance for sealing unused public water-supply wells.
This project will generate water quality data for 10 stream locations MPCA designated for their 2012 and 2013 open-water sampling seasons (8 by NRRI-UMD and 2 via subcontract to the North St. Louis SWCD). The overall project goal is to collect event-based physical and chemical data sets for 10 agency-prioritized stream sampling sites in NE Minnesota for calculating pollutant loads and for incorporation into the overall State database for MPCA assessment purposes.
Five locations will be monitored in support of the combined Vermilion Community College and Rainy River Community College 2016 – 2017 Minnesota Pollution Control Agency (MPCA) Watershed Pollutant Load Monitoring Network (WPLMN) Sampling Agreement. Water samples, field measurements, field images, and other observations will be obtained at each location during each sampling event.