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Modeling water clarity in oceans and coasts
Citation:
Abdelrhman, M. Modeling water clarity in oceans and coasts. Estuarine and Coastal Modeling Conference (ECM14), Providence, RI, June 13 - 15, 2016.
Impact/Purpose:
Accurate modeling of light intensity in the water column is essential to understand and predict primary productivity in oceans and coastal systems. This paper provides a complete method to track the change in light intensity, as phytoplankton concentrations change in the water column, which can be included in existing water quality and ecological models.
Description:
In oceans and coastal waters, phytoplankton is the primary producer of organic compounds which form the base for the food chain. The concentration of phytoplankton is a major factor controlling water clarity and the depth to which light penetrates in the water column. The light intensity available at any depth is a major factor determining the health of phytoplankton populations. For example, there is a strong coupling between light intensity and phytoplankton concentration (e.g., self-shading of the cells), which reduces available light and in return affects the growth rate of the cells. Accurate modeling of light intensity in the water column is essential to understand and predict primary productivity in oceans and coastal systems. This paper provides a complete method to track the change in light intensity, as phytoplankton concentrations change in the water column, which can be included in existing water quality models. The methodology implements relationships from bio-optical models, which use phytoplankton chlorophyll a (Chl-a) concentration and other factors as a surrogate for light attenuation due to their effects on absorption and scattering. The mathematical algorithm presented estimates the reduction in water column light intensity due to absorption by pure water, Chl-a pigment, non-algal particles (NAPs), and colored dissolved organic matter (CDOM), as well as backscattering by pure seawater, phytoplankton particles, and NAPs. Since light is the fundamental factor supporting phytoplankton production, the method presented will facilitate studies of the effects of various environmental and management scenarios (e.g., global warming, altered precipitation patterns, greenhouse gases) on the wellbeing of phytoplankton in the oceans and coastal systems.