Spring 2009

The Newsletter of the Minnesota GIS/LIS Consortium

Table of Contents

MN GIS/LIS Consortium

From the Chair
Conference Planning
Volunteer Opportunities
Scholarship Winners

Drive to Excellence Update
USNG in Minnesota
Mn/DOT GIS Portal
LCC-GIS and Redistricting

Governor's Council
CTU and USNG standards out for review
Next Generation 9-1-1

Services Forum Results
Address Point Synchronization

Tracking Utility Trucks
Watershed E. coli Study

Mapping Floods
Improvng Flood Maps
Height Modernization

URISA Skills Survey
MHS Map Exhibit

Randy Johnson, ESRI GIS Hero

Other Places
Web 2.0 for Local Government
Economics and Place



Little CannonRiver E. coli Assessment
By Beau Kennedy, Goodhue County SWCD
In 2008, the Goodhue County Soil and Water Conservation District was awarded a Clean Water Legacy Grant to conduct a watershed assessment on the Little Cannon River in east-central Minnesota. The grant was written based on preliminary data collected by the Cannon River Watershed Partnership in 2007. The assessment is investigating the potential sources of E. coli throughout the Little Cannon River Watershed.
Data Collection
We divided the Little Cannon River Watershed into 10 different subwatersheds. A rating was applied to all the active feedlots and septic systems in each subwatershed. For feedlots we used the standard FLEval and MinnFarm methods. This required a site visit to every feedlot within the Little Cannon River Watershed (approximately 120). For septic systems we developed a rating system which was based on the age of the system weighted for its proximity to a water source.
At the outlet of each subwatershed, water samples were taken and sent to the lab for E. coli analysis, except for several subwatersheds that were dry whenever we tried to sample. E.coli is measured in MPN/100ml of sample (MPN = most probable number of colonies).
We were able to give a pollution potential rating to each subwatershed and compare that to the water quality data.
The findings of the study are not completed yet, since we still have another season of stream sample collection.
Once the data from 2008 was compiled, we entered our lab results and ratings into an Arc table where they could be manipulated. To portray the commonalities and differences we sorted the subwatershed by using the basic symbology tool. See Figure 1. The map colors represent E. coli numbers – red indicates a higher number of bacteria in the stream samples and green indicates a lower number of bacteria. The white (or dashed) watershed had no samples taken. The numbers are watershed labels.
We utilized the ArcGlobe application for this study as well. We found that ArcGlobe can demonstrate the findings of this study in a way that most programs cannot. By utilizing the track/fly tool, the audience gets a 3D image of where feedlots or septic systems are located in the subwatershed as well as the pollution potential rating. See Figure 2 for a snapshot taken from ArcGlobe. The column symbols are silos, representing a feedlot present at that site. The pushpin symbols are stream sample locations.
Preliminary Findings
Our preliminary E. coli results seem to correlate pretty well with the feedlot assessments done in the subwatersheds. One subwatershed (labeled “4” in the graphic) had the highest FLEval rating AND the highest geometric mean of bacteria in the stream.
On the other hand, the subwatershed labeled “5” had the highest rating for septic assessments, and yet the lowest E. coli numbers. This could be due to the subwatershed’s land use. It is by far the most wooded of the subwatersheds and has the lowest stream temperatures.
After the 2009 sampling season is complete, we should be able to determine which subwatersheds are contributing the most fecal to streams. This way we can concentrate our cost/share and technical assistance efforts in these impaired areas.
The Goodhue County SWCD would like to thank the Goodhue County GIS Department for their leadership and dedication to the Goodhue County Users Group. The GIS Department provided the SWCD with various layers we needed for this study including 2’ contours, parcel information, zoning, roads, and high resolution aerial photos. They also provided ArcGIS licensing and the Spatial Analyst extension for our staff. None of these applications would have been possible if it weren’t for the SWCD’s participation in the Users Group.
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