HR: 14:30h
AN: OS23G-03    [Abstracts]
TI: Sensitivity Analysis of Factors Influencing the Fate and Transport of Fecal Indicator Bacteria in Southern Lake Michigan
AU: * Thupaki, P
EM: thupakip@msu.edu
AF: Michigan State University, Department of Civil & Environmental Engineering , East Lansing, MI 48864, United States
AU: Phanikumar, M S
EM: phani@msu.edu
AF: Michigan State University, Department of Civil & Environmental Engineering , East Lansing, MI 48864, United States
AU: Schwab, D J
EM: david.schwab@noaa.gov
AF: NOAA Great Lakes Environmental Research Laboratory (GLERL), 2205 Commonwealth Blvd., Ann Arbor, MI 48105, United States
AU: Whitman, R L
EM: rwhitman@usgs.gov
AF: USGS Great Lakes Science Center, Lake Michigan Ecological Research Station, Porter, IN 46304, United States
AU: Nevers, M B
EM: mnevers@usgs.gov
AF: USGS Great Lakes Science Center, Lake Michigan Ecological Research Station, Porter, IN 46304, United States
AU: Shively, D A
EM: dshively@usgs.gov
AF: USGS Great Lakes Science Center, Lake Michigan Ecological Research Station, Porter, IN 46304, United States
AB: To understand the factors that influence the fate and transport of fecal indicator bacteria (FIB) in the nearshore waters of the Great Lakes, we examined two southern Lake Michigan beaches (as well as the tributaries discharging into the lake in the vicinity of the beaches). A three-dimensional, σ-coordinate Princeton Ocean Model (POM) with a nested-grid was used to describe wind-driven circulation in Lake Michigan. A biological model coupled to the hydrodynamic and temperature fields in the lake was used to describe the observed FIB levels near the beaches. We report simulation results for the summers of 2004 and 2006. Inactivation of pathogens in the nearshore region is influenced by a complex set of factors including solar insolation, water temperature, settling of particulate matter, resuspension, turbulent diffusion, loading from tributaries etc. Efforts to systematically quantify the relative contributions of these complex and often inter-related processes are somewhat limited, especially for freshwater environments. Here we describe sensitivity analyses based on our numerical simulations with the objective of ranking the various processes involved in terms of their relative importance. We also examine the performance of different mathematical formulations of inactivation in order to identify their relative merits.
DE: 1871 Surface water quality
DE: 4217 Coastal processes
DE: 4255 Numerical modeling (0545, 0560)
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly