Great Lakes modeling: Are the mathematics outpacing the data and our understanding of the system?

Session: 31. - Evaluation of the Current State of Ecological Modeling and Future Perspectives

James Pauer, USEPA/ORD Mid-Continent Ecology Division, [email protected]
Wilson Melendez, CSRA Inc., [email protected]
Lisa Lowe, CSRA Inc., [email protected]
Brenda Rashleigh, USEPA/ORD/NHEERL, [email protected]

Abstract

Mathematical modeling in the Great Lakes has come a long way from the pioneering work done by Manhattan College in the 1970s, when the models operated on coarse computational grids (often lake-wide) and used simple eutrophication formulations.  Moving forward 40 years, we are now running models on extremely fine computational grid resolutions and using tens if not hundreds of equations to describe the biogeochemistry.  Many will argue that today’s models enable a realistic representation of the transformation, transport and fate of nutrients and phytoplankton in the lakes. Here, we will show from our own work and from analyses of published models, the pitfalls of using such sophisticated models.  We will show how this level of sophistication can lead to a false sense of model accuracy, lack of transparency, and difficulty in estimating model uncertainty, resulting in a lack of faith and consensus in model results. We will discuss the need to compromise between the level of sophistication, required model observations, and model reality.  We will also offer an approach to developing models with better defined accuracy, improved transparency and credibility, and greater consensus among stakeholders, and we will discuss the advantages of using community models.

1. Keyword
ecosystem modeling

2. Keyword
eutrophication

3. Keyword
lake model

4. Additional Keyword
Model uncertainty

5. Additional Keyword
Model transparency