Of Interest...
Michigan Bacteriological Research Laboratory (MI-BaRL)
The USGS Michigan Water Science Center Bacteriological Research Laboratory (MI-BaRL) in Lansing, MI provides a variety of modern analytical approaches to understand bacteriological contamination and microbial ecology in diverse aquatic environments. The MI-BaRL laboratory has examined beach microbiology, the occurrence of antibiotic-resistant bacteria in surface water, and the occurrence of microbial pathogens in surface water, ground water, and in drinking water supplies. In addition, several studies conducted in the MI-BaRL have examined the ecology of microbial communities in different settings, including sulfur rich springs, arsenic and hydrocarbon contaminated groundwater, and wastewater-contaminated surface and groundwater.
Featured Publication:
Pathogenic Bacteria and Microbial-Source Tracking Markers in Brandywine Creek Basin, Pennsylvania and Delaware, 2009–10
The City of Wilmington, Delaware, is in the downstream part of the Brandywine Creek Basin, on the main stem of Brandywine Creek. Wilmington uses this stream, which drains a mixed-land-use area upstream, for its main drinking-water supply. Because the stream is used for drinking water, Wilmington is in need of information about the occurrence and distribution of specific fecally derived pathogenic bacteria (disease-causing bacteria) and their relations to commonly measured fecal-indicator bacteria (FIB), as well as information regarding the potential sources of the fecal pollution and pathogens in the basin.
This study focused on five routinely sampled sites within the basin, one each on the West Branch and the East Branch of Brandywine Creek and at three on the main stem below the confluence of the West and East Branches. These sites were sampled monthly for 1 year. Targeted event samples were collected on two occasions during high flow and two occasions during normal flow.
Silver Lake Nutrient Loading Study (Oceana County, MI)
The Silver Lake Nutrient Loading Study began in August 2012 between the Silver Lake Improvement Board and project partners, which include the U.S. Geological Survey (USGS), the Annis Water Resources Institute (AWRI) , and Progressive AE. Recent persistent algal blooms, high phosphorus concentrations during summer months, as well as a decrease in water clarity underscore a need to characterize water and nutrient sources to Silver Lake (located in Oceana County, MI). The objective of the Silver Lake Nutrient study is to characterize the nutrient conditions and hydrologic inputs and outputs to Silver Lake in order to develop a water budget and nutrient budget for the lake. Once identified, information on nutrient sources can be used by the Silver Lake Improvement Board to implement management practices that best protect Silver Lake from potential negative effects associated with elevated nutrient concentrations.
In addition to the website (http://mi.water.usgs.gov/projects/silverlake/index.html), you can also follow project progress on Twitter at @USGS_Silverlake
Predicting Water Clarity Overview
The U.S. Geological Survey (USGS), in cooperation with the Michigan Department of Environmental Quality (MDEQ), has been monitoring the quality of inland lakes in Michigan through the Lake Water Quality Assessment monitoring program. This program is funded through the Michigan Clean Michigan Initiative, and the USGS Cooperative Program. However, only a portion of Michigan's inland lakes can be conventionally sampled each year. A technique was developed by USGS, modeled after Olmanson and others (2001), to predict water clarity and corresponding trophic state index (TSI) values based on the Carlson's Trophic State Index (TSI) in inland lakes greater than 20 acres using satellite remote sensing data.
By L.M. Fuller, R.S. Jodoin, and R.J. Minnerick
For the full report click here. |
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Chemicals of emerging concern in water and bottom sediment in Great Lakes areas of concern, 2010 to 2011-Collection methods, analyses methods, quality assurance, and data
2012, Lee, Kathy E.; Langer, Susan K.; Menheer, Michael A.; Foreman, William T.; Furlong, Edward T.; Smith, Steven G. USGS Data Series: 723
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