With the exception of a few areas, Lake Michigan (LM) is an oligotrophic clear water body. It is predominantly in its littoral zone where ecology-relevant processes unfold due to a variety of natural and anthropogenic forcings arising from the watershed. However, the bottom influence there is strong enough to contaminate the at-satellite signal, thus impeding the remote sensing of water quality parameters within the coastal zone.

A new bio-optical retrieval algorithm, based on a forward radiation transfer model, LM specific hydro-optical model and the multivariate optimization technique is developed for operational retrieval from satellite data of water quality parameters in lakes optically shallow areas. The retrieval output encompasses the concentrations of major Color Producing Agents (CPAs), viz. phytoplankton chlorophyll, total suspended matter and yellow substance in transparent coastal waters with a variety of cover types: sand, silt, stands of Chara, and Cladophora, and limestone pebble.

The sensitivity of both forward and inverse models was tested for hydro-optical conditions inherent in LM. By means of forward simulations, the spectral signature variations of subsurface remote sensing reflectance, R_rswthe modifications of the upwelling signal (controlled by the bottom type and depth). It is shown that at very low concentrations of CPAs (less than 0.01 in respective unit) the optical influence of the bottom becomes indiscernible if the bottom depth, H approaches 20 m. In waters loaded with higher quantities of total suspended matter (TSM) and phytoplankton chlorophyll, CHL, the bottom influence ceases at H ~ 10 m.

The noise sensitivity has shown that the shallower the water column and higher bottom albedo the more significant in the ensuing error in CPA retrievals. E.g. for a sandy bottom and water column  of 5 m, a 10% error in determining of albedo leads to a 18%, 28% and 10% error in retrieving, respectively, CHL, TSM and colored dissolved organic matter, CDOM.

Albert, A., and Gege, P. 2006. Inversion of radiance and remote sensing reflectance in shallow water between 400 and 800 nm for calculations of water and bottom properties. Applied Optics. 2006. Vol. 45, no. 10. P. 2331-2343.

Bukata, R., Jerome, J., Kondratyev, K., and Pozdnyakov, D. Optical Properties and Remote Sensing of Inland and Coastal Waters. Boca Raton: CRC Press. 1995. 362 p.

Chapra, S.C. and Dobson, H.F.H. Quantification of the Lake Trophic Typologies of Naumann (Surface Quality) and Thienemann (Oxygen) with Special Reference to the Great Lakes. International Association for Great Lakes Research. 1981. Vol. 7, no. 2. P. 182-193.

Clark, R., Fay, T., and Walker, C. Bathymetry calculations with Landsat 4 TM imagery under a generalized ratio assumptions. Applied Optics. 1987. Vol. 26. P. 4036-4038. doi: 10.4319/lo2003.48.1 part2.0431

Dekker, A., Phinn, S., Anstee, J., Bissett, P., Brando, V., Casey, B., Fearns, P., Hedley, J., Knlonowski, W., Lee, Zhong, Lynch, M., Lyons, M., and Mobley, C. Intercomparison of shallow water bathymetry, hydro-optics, and benthos mapping techniquesin Australian and Caribbean coastal environments. Limnology and Oceanography: Methods. 2011. Vol. 9. P. 396-425.

EEGLE ship-collected data archive. 2003. 1, 2. CD-ROM.

Effler, S., Peng, F., O’Donnell, D., Strait, C. The backscattering coefficient and its components in the Great Lakes: A review and synthesis. Journal of Great Lakes Research. 2013. Vol. 39 (supplement 1). P. 108-122.

Gillespie, R., Harrison III, W. B. and Grammer, G. M. Geology of Michigan and the Great Lakes. Western Michigan University Publ. 2008. 37 p.

GITHUB: https://github.com/nansencenter/boreali

Gordon, H., and Brown, O. Influence of bottom depth and albedo on the diffuse reflectance of a flat homogeneous ocean. Applied Optics. 1974. Vol. 13, no. 9. P. 2153-2159.

Greb, S., Garrison, P., Pfeiffer, S. Cladophora and water quality of Lake Michigan: a systematic survey of Wisconsin nearshore areas. In: Bootsma, H. A., Jensen, E. T., Young, E.B., Berges, J. A. (Eds.), Cladophora Research and Management in the Great Lakes. Special Report 200501. Great Lakes Water Institute, University of Wisconsin, Milwaukee. 2004. 7380 p.

Hu, C. Ocean color reveals sand ridge morphology on the West Florida Shelf. IEEE Geoscience and Remote Sensing Letters. 2008. Vol. 5, no. 3. P. 443 -447.

Hu, C., Hackett, K., Callahan, M., Andrfout, Wheaton, J., Porter, J., Mueller-Karge, F. The 2002 ocean colour anomaly in the Florida Bight: A cause of local coral reef decline? Geophysical Research Letters. 2003. Vol. 30, no. 3, doi: 10.1029/2002GL016479.

Hu, C., Mueller-Karge, F., Vargo, G., Neely, M., and Johns, E. Linkages between coastal runoff and the Florida Keys ecosystem: A study of a dark plume event. Geophysical Research Letters. 2004. Vol. 31. L15307, doi: 10.1029/2004GL020382.

Hu, C., Nelson, J., Johns, E., Chen, Z., Weisberg, R., and Mueller-Karge, F. Mississipi River water in the Florida Straits in the gulf Stream off Georgia in summer 2004. Geophysical Research Letters. 2005. Vol. 32. L14006, doi: 10.1029/2005GL022942.

IOCCG. Atmospheric correction for remotely-sensed ocean colour products. Wang, M. (Ed.). Reports of the International Ocean-Colour Coordination Group. 10, IOCCG Publ. Dartmouth, Canada. 2010.

Jerome, J. H, Bukata, R. P., Miller, J. R. Remote sensing reflectance and its relationship to optical properties of natural water. International Journal of Remote Sensing. 1996. Vol. 17, no. 1. P. 43-52.

Kirk, J.T.O. Dependence of relationship between inherent and apparent optical properties of water on solar altitude. Limnology and Oceanogaphy. 1984. Vol. 29. P. 350-356.

Korosov, A.A., Pozdnyakov, D.V., Folkestad, A., Pettersson, L.H., SГёrensen, K., Shuchman, R. Semi-empirical Algorithm for the Retrieval of Ecology-Relevant Water Constituents in Various Aquatic Environments. Algorithms. 2009. Vol. 2. P. 470–497.

Lee, Z., Carder, K., Arnone, R. Deriving inherent optical proprerties from water color: a multiband quasi-analytical algorithm for optically deep waters. Applied Optics. 2002. Vol. 41, no. 27. P. 5755-5772.

Lyzenga, D. Passive remote sensing techniques for mapping water depth and bottom features. Applied Optics. 1978. Vol. 17, no. 3. P. 379-383.

Mida, J. L., Scavia, D, Fahnenstiel, G. L., Pothoven, S. A., Vanderploeg, H. A., Dolan, D.M. Long-term and recent changes in southern Lake Michigan water quality with implications for present trophic status, Journal of Great Lakes Research. 2010. Vol. 36 (Supplement 3). P. 42-49. doi:10.1016/j.jglr.2010.03.010

Maritorena, S., Morel, A., Gentili, B. Diffuse reflectance of oceanic shallow waters: Influence of water depth and bottom albedo. Limnology and Oceanography. 1994. Vol. 39, no. 7. P. 1689-1703.

Mobley, C. D., Sundman, L. K, Boss, E. Phase Function Effects on Oceanic Light Fields. Applied Optics. 2002. Vol. 41, no. 6. P. 1035-1050 (2002) [10.1364/AO.41.001035].

More, J. J., Sorensen, D. C., Hillstrom, K. E., Garbow, B. S. The MINPACK Project, in Sources and Development of Mathematical Software, W. J. Cowell, ed., Prentice-Hall. 1984. P. 88-111.

Nalera, T. F. and Scholoesser, D. W. (Eds.). Quagga and zebra mussels: biology, impacts and control. Boka Raton. CRC Press. 2014. 761 p.

O’Reilly, J.E., S.Maritorena, D.Siegel, M.O ’Brien,D.Toole, B.Greg Mitchell, M.Kahru F.Chavez, P.Strutton, G.Cota, S.Hooker, C.McClain, K.Carder, F.Muller-Karger L.Harding, A.Magnuson, D.Phinney, G.Moore, J.Aiken, K.Arrigo, R.Letelier, M.Culver, Ocean color chlorophyll a algorithms for SeaWiFS, OC2, and OC4: Version 4. In: O’Reilly, J.E., and 24 Coauthors. SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3. NASA Tech. Memo. 11, S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Center, Greenbelt, Maryland. 2000. P. 9-23

Philpot, W. D. Bathymetric mapping with passive multispectral imagery. Applied Optics. 1989. Vol. 28, no. 8. P. 1569-1578.

Pozdnyakov, D.V. H. Grassl, Colour of Inland and Coastal Waters: a methodology for its interpretation. Chichester: Springer-Praxis. 2003. 170 p.

Press, W., S. Teukolsky, W. Vettering, B. Flannery. Numerical Recipes in C: The Art of Scientific Computing. 2nd ed. New York: Cambridge University Press. 1992.

Shuchman, R. A., Leshkevich, G., Sayers, M. J. Johengen, T. H., Brooks, C. N., Pozdnyakov, D. An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data. Journal of Great Lakes Research. 2013a. Vol. 32. P. 14-33.

Shuchman, R. A., Sayers, M. J., Brooks, C. N. Mapping and monitoring the extent of submerged aquatic vegetation in the Laurentian Great Lakes with multi-scale satellite remote sensing. Journal of Great Lakes Research. 2013b. Vol. 39. P. 78-89.

Shuchman, R., Korosov, A., Hatt, C., Pozdnyakov, D., Means, J., Meadows, G. Verification and application of a bio-optical algorithm for Lake Michigan using SeaWIFS: a 7-year inter-annual analysis. Journal of Great Lakes Research. 2006. Vol. 32. P. 258-279.