Water quality observations in the Great Lakes using an optimized satellite bio-optical algorithm

Document Type

Conference Paper/Presentation

Publication Date



The Color Producing Agent Algorithm (CPA-A) is a semi-analytical inverse radiative transfer bio-optical model to retrieve water quality parameters from satellite observed reflectance. The CPA-A requires knowledge of the inherent optical properties of a given water body to produce accurate retrievals of the primary color producing agents (CPA) namely chlorophyll (CHL), suspended matter (SM), and CDOM. An optimized set of inherent optical properties, known as a hydro-optical (HO) model, has been generated for Lakes Michigan, Superior, and Huron that produce robust retrievals annually and intraannually for the MODIS mission (2002-2013). The optimized HO model was used to generate long term time series estimates of several water quality parameters including CHL, SM, CDOM, DOC, attenuation, absorption, backscatter, and photic depth. The diffuse attenuation coefficient (Kd) and photic depth are functions of CPA concentration and are therefore inherently retrievable with the CPA-A. Retrieved concentrations of CPA-A derived water quality parameters compare favorably with in situ measurements in the upper three Lakes. This complete set of water quality parameters provides unique observations of the lower food web including primary production to help better understand ecological changes due to anthropogenic forcing and climate change.

Publisher's Statement

© 2015 The authors.

Publication Title

IAGLR 58th Annual Conference on Great Lakes Research