Great Lakes monitoring results: Comparison of probability based and deterministic sampling grids

The Great Lakes may be viewed as a coastal environment, affected by the same meteorological and physical forces as the coastal ocean. The U.S. EPA, Great Lakes National Program Office (GLNPO) has monitored the open waters of the lakes, annually, since 1983. As part of the U.S. EPA Environmental Moni...

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Bibliographic Details
Published inEnvironmental Monitoring and Assessment Vol. 81; no. 1-3; pp. 63 - 71
Main Authors WARREN, Glenn J, HORVATIN, Paul J
Format Conference Proceeding Journal Article
LanguageEnglish
Published Dordrect Springer 01.01.2003
Springer Nature B.V
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Summary:The Great Lakes may be viewed as a coastal environment, affected by the same meteorological and physical forces as the coastal ocean. The U.S. EPA, Great Lakes National Program Office (GLNPO) has monitored the open waters of the lakes, annually, since 1983. As part of the U.S. EPA Environmental Monitoring and Assessment Program (EMAP), a pilot study was performed in Lake Michigan to compare the existing GLNPO deterministic sampling grid with the EMAP probabilistic grid. Results of chemical analyses of trophic status indicators (total phosphorus and chlorophyll a) as well as nutrients and conventional limnological measurements, from spring and summer surveys in 1992 indicate little difference between the grids in the offshore region of the lake. The few statistically significant differences may be due to station distribution throughout the lake, or simple chance. This might be expected due to the well mixed nature of the open waters of Lake Michigan. The detection of a long-term trend for total phosphorus in Lake Michigan benefits from an annual program: viewing cumulative frequency distributions based on a four year EMAP interval does not convey information on the decrease in phosphorus in the lake. If the EMAP sampling grid were to be used in the Great Lakes, pilots in each of the lakes would be necessary for utilization of the existing long-term record as a basis for trend detection.
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ISSN:0167-6369
1573-2959
DOI:10.1023/A:1021304403117