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Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie

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Abstract

Lake Erie is biologically the most active lake among the Great Lakes of North America, experiencing seasonal harmful algal blooms (HABs). The early detection of HABs in the Western Basin of Lake Erie (WBLE) requires a more efficient and accurate monitoring tool. Remote sensing is an efficient tool with high spatial and temporal coverage that can allow accurate and timely detection of the HABs. The WBLE is heavily influenced by the surrounding terrestrial ecosystem via rivers such as the Sandusky River and the Maumee River. As a result, the optical properties of the WBLE are influenced by multiple color producing agents (CPAs) such as phytoplankton, colored dissolved organic matter (CDOM), organic detritus, and terrigenous inorganic particles. The diversity of the CPAs and their non-linear interactions makes these waters optically complex, and the task of optical remote sensing for retrieving estimates of CPAs more challenging. Chlorophyll a, which is the primary light harvesting pigment in all phytoplankton, is used as a proxy for algal biomass. In this study, several published remote sensing algorithms and band ratio models were applied to the reflectance data from the full resolution MERIS sensor to remotely estimate chlorophyll a concentrations in the WBLE. Efficiency of the sensor and the algorithms performance were tested through a least squares regression and residual analysis. The results indicate that, among the suite of existing bio-optical models, the Simis semi-analytical algorithm provided the best model results for measures of algal biomass in the optically complex WBLE with R 2 of 0.65, RMSE 0.85 μg/l, (n = 71, P < 0.05). The superior results of this model in detecting chlorophyll a are attributed to several factors including optimizing spectral regions that are less sensitive to CDOM and the incorporation of correction factors such as absorption effects due to pure water (a w), backscatter (b b) from suspended matter and interference due to phycocyanin (δ), a major accessory pigment in the WBLE.

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Acknowledgments

This research was supported by the NOAA-Ohio Sea Grant Program Grant R/ER-100-PD. Authors are thankful to Matt Thomas, Captain of the Stone Laboratory research vessels, and the Stone Laboratories, for access and research vessels required to collect the samples.

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Authors and Affiliations

  1. Department of Geology and Environmental Geosciences, College of Charleston, Charleston, SC, 29424, USA

    Khalid Ali

  2. Department of Geology, Kent State University, Kent, OH, 44242, USA

    Donna Witter & Joseph Ortiz

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  1. Khalid Ali
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  2. Donna Witter
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Correspondence to Khalid Ali.

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Ali, K., Witter, D. & Ortiz, J. Application of empirical and semi-analytical algorithms to MERIS data for estimating chlorophyll a in Case 2 waters of Lake Erie. Environ Earth Sci 71, 4209–4220 (2014). https://doi.org/10.1007/s12665-013-2814-0

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