Home > About GLERL > Contact Information

Eric Anderson

Eric Anderson


Phone: (734) 741-2293
Fax: (734) 741-2055
e-mail:
Curriculum Vitae


List of all GLERL Researchers


List of publications and presentations

Education

Ph.D., Case Western Reserve University, Mechanical & Aerospace Engineering, 2007
B.S., Case Western Reserve University, Mechanical Engineering, 2003

Research Interests

My research focuses on hydrodynamics in the Great Lakes and connecting channels. Numerical models and a network of observations, including meteorological conditions, water levels, and flows, are used to predict the physical environment of lakes, rivers, and coastal zones including three-dimensional currents, temperatures, and water levels. These predictions are used in several areas such as navigation, search and rescue, water quality, spill transport, and beach forecasting.

An Interview with Eric Anderson

1. How would you describe your job?

A big part of what I do in my job deals with hydrodynamic modeling, which makes me a “hydrodynamicist.” In this capacity, I study the physical nature of Great Lakes waters and how they respond to natural forces, which means predicting things like currents, temperature, water levels and waves. An example of a hydrodynamic event is the affect of wind in pushing water towards one end of the lake, stacking it up, resulting in a storm surge. If the wind dies down, this absence of force will cause the water to slosh within the lake resulting in a seiche effect, much like water in a bathtub. Hydrodynamics differs from hydrology in that it studies the dynamics or the motion of the water and the transfer of energy, where as hydrology tends to focus on aspects related to the water budget and quality.

In my hydrodynamics research, I use computer modeling to predict how forcing conditions, such as meteorological (weather) events, affect the motion and energy of a body of water. Observations of natural conditions, meteorology and other environmental factors serve as data in hydrodynamic models to make predictions on the Great Lakes and other bodies of water. For example, predictions from our hydrodynamic models are used by the U.S. Coast Guard for search and rescue operations. To help locate missing persons who have been out boating, circulation models can predict where the missing person may drift based on the location last seen in the boat at a certain time. The same modeling technique can be applied in tracking contaminants, the presence of bacteria, oil spills and other toxic chemicals.

2. What is the most interesting thing you’ve accomplished in your job?

I have been very interested in contaminant spill work on the St. Clair River. Through the use of current circulation models, we can determine the potential effects of contaminant spills on drinking water supplies. These models can predict travel time of certain substances, where the substances are going to land and in what concentrations.

3. What do you feel is the most significant challenge in your field today?

One of the biggest challenges in Great Lakes hydrodynamics is overcoming the lack of fine scale (high detail) observational data that is needed to predict and validate (confirm for accuracy) processes at small scales. For instance, if we’re interested in the physical environment at a particular beach, such as the waves, temperature, or even bacteria, we need information or observations at this scale. If there were only one beach of interest in the Great Lakes, maybe this wouldn’t be such an issue. However, when we need to predict these processes throughout the Great Lakes, we can’t possibly collect observations in all the areas of interest. Essentially, although we can solve equations that work effectively for offshore conditions or large-scale processes, when the area of interest becomes finer in scale, such as a particular beach or harbor, the observation demands increase dramatically.

For example, we can predict hydrodynamic processes in open lake areas using models that are large in scale (2 km) based on our current observation network. However, the observational data may be inadequate to validate model predictions of nearshore beach processes that are smaller in scale (10 meters). This impedes efforts to make beach modeling forecasts on a small scale. As a result, it is more challenging to make sound decisions on issues such as beach closures for incidences with high bacteria counts.

4. Where do you find inspiration? Where do your ideas come from in your research or other endeavors in your job?

The source of my inspiration comes from going out on the water and observing what’s going on around me on the lake. I am also inspired by working with a diverse group of colleagues, learning about other researchers’ work as well as our interaction in the investigative process. I think that my observations on the water help stimulate new, creative ideas on modeling. My sense is that a computer modeler who works in the field and experiences what it looks like and feels like to be on the water would have a different feel for the system than someone just working behind a computer. Taking time to observe the water in-person has raised my awareness for the finer details or even details that were unknown before, and as a result improves the work I do at the computer.

5. How would you advise high school students interested in science as a career path, or someone interested in your particular field?

Initially, I did research on the fluid dynamics inside bone tissue. However, when I became more interested in the environmental hydrodynamics, I was able to transfer this fundamental understanding of fluid dynamics to a new area, and I began work on the Great Lakes. It’s important for students to understand the core subjects and keep an open-mind in exploring as many different experiences as possible in science. You don’t need to put yourself on set path from the start as long as you equip yourself with a fundamental base. Then, when you do focus on a particular area, you will have the benefit of bringing different perspectives from many fields to your specific research area.