The Lake Michigan Eutrophication Model, LM3-Eutro: Model Development and Calibration

Authors: Pauer, James J; Anstead, Amy M; Melendez, Wilson; Rossmann, Ronald; Taunt, Katherine W; Kreis, Russell G

Source: Water Environment Research, Volume 80, Number 9, September 2008 , pp. 853-861(9)

Publisher: Water Environment Federation

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Abstract:

A eutrophication model developed to generate primary-production estimates in Lake Michigan can simulate 17 state variables, including three plankton classes and several nutrients. The model, known as the Lake Michigan Eutrophication model (LM3-Eutro), has a high-resolution computational grid that enables good spatial description of spring temperature and phytoplankton concentrations, which have significant gradients in the lakes. The grid also allows the model to predict concentrations in nearshore areas and other regions of interest. The model provided more accurate estimates of algal light limitation based on three-hour intervals compared to daily averages that are used in most eutrophication models, especially during sunny summer days when algal photo-inhibition often occurs. Model output was compared to field data using statistical parameters such as squares of the correlation coefficients to determine the best model fit. The calibrated model output fit the field data reasonably well for nutrients and phytoplankton, which provided confidence in the framework, governing equations, and coefficients used.

Keywords: Mathematical model; Lake Michigan; eutrophication; carbon; light limitation

Document Type: Research article

DOI: http://dx.doi.org/10.2175/106143008X304686

Publication date: 2008-09-01

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  • Water Environment Research® (WER®) publishes peer-reviewed research papers, research notes, state-of-the-art and critical reviews on original, fundamental and applied research in all scientific and technical areas related to water quality, pollution control, and management. An annual Literature Review provides a review of published books and articles on water quality topics from the previous year.

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