A Mechanistic Phosphorus-Based Model for the Western Lake Erie Cyanobacteria Bloom

Session: 41a. - Great Lakes Harmful Algal Blooms Research from Watershed Influence to Ecosystem Effects

Richard Stumpf, NOAA, [email protected]
Erik Davenport, NOAA, [email protected]
Timothy Wynne, NOAA, [email protected]
Laura Johnson, Heidelberg University, National Ctr for Water Quality Res., [email protected]

Abstract

The core models used for examining the cyanobacterial blooms in Lake Erie are either statistical models or numerical simulation models.  For scenario testing, these models are effective, but, have some limitations (like all models).  Numerical simulations are computationally intense, and the statistical models are limited by the available time series or climatology of data.  Mechanistic models can provide another modeling strategy that can increase the options and flexibility of scenario testing and forecasting.   We have developed a mechanistic model that forecasts the bloom size directly from phosphorus sources, using simple bulk assumptions.  The model parameters have physical meaning and can be assigned or tuned with existing measurements or even with other models.  Components can be adjusted based on shifts in the lake due to management activities, but also factors resulting from lake response to external functions such as climate change. This model can allow closer examination of factors that cannot be explained under the current statistical models.  It describes the non-linear relationship between Maumee River load and bloom biomass, and it allows for some retrospective analysis of blooms. Having three classes of models (numerical, mechanistic, and statistical) will provide better control on analysis of future management and climate scenarios. 

1. Keyword
cyanophyta

2. Keyword
Lake Erie

3. Keyword
modeling

4. Additional Keyword
phosphorus

5. Additional Keyword
satellite