Meredith B. Nevers
B.A. (Biology) Wittenberg University, 1994
M.S. (Marine Biology) University of North Carolina at Wilmington, 1996
This research will make advances toward lake-wide monitoring systems for recreational water quality. With the expansion of water quality predictions and the characterization of natural and human-derived bacterial populations, better assessments of public health risk can be made. Next research steps will include the continued expansion and refinement of predictive models with independent variables that incorporate dynamic biological and physical processes. Modeling will also incorporate new dependent variables that are better indicators of recent human sewage contamination and associated pathogens and disease-causing organisms.
There is a decided need for a rapid means of characterizing microbiological water quality and for distinguishing sources of these natural indicator bacteria populations and associated human health risk. Currently, all Great Lakes coastal beaches (and marine beaches) are monitored for fecal indicator bacteria to determine when there is human fecal sewage contamination that may be harmful to human health. In recent years, numerous problems with the currently accepted indicator have been recognized. Notably, the analytical assay for E. coli requires 24 hours of culturing, a time frame lengthier than the rate of potentially significant changes in E. coli concentration in natural waters. A strong need for rapid assessment of microbiological water quality has developed. Recent research has targeted several means of rapidly measuring water quality, among them faster analytical assays, a new indicator, and the use of empirical/statistical predictive models. Each possibility has advantages and disadvantages, many tied to specific situations at individual beaches. A clearer understanding of the application and implications of these rapid methods is needed so that beach managers can effectively manage their beaches to protect beachgoers. Different beaches may require different approaches to monitoring.