Comparative Evaluation of Statistical and Mechanistic Models of Escherichia coli at Beaches in Southern Lake Michigan

Abstract

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term "tracer" transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.

Real‐Time Water Quality Monitoring at a Great Lakes National Park

“…Whether this physical obstruction indeed affected the bacterial inputs and the relationship between the measured endpoints, as noticed in this study, merits further investigation. Hydrodynamic modeling has been used at other Great Lakes locations to characterize this of type relationship (Safaie et al, 2016) and to determine if fluctuations are predictable (Nevers et al, 2007); such information could be useful for understanding the underlying process at SLBE.…”

Occurrence of Traditional and Alternative Fecal Indicators in Tropical Urban Environments under Different Land Use Patterns

“…Among the driving factors, environmental (e.g., pH, temperature, salinity, turbidity, UV, etc.) and hydrologic (rainfall runoff) conditions have been well studied, previously using empirical models to predict target microbial concentrations in marine and temperate freshwater systems (6,19,20). Predictive models have been applied in the Great Lakes to provide timely information in beach notification programs (21).…”

Evaluating a Coupled Phenology‐Surface Energy Balance Model to Understand Stream‐Subsurface Temperature Dynamics in a Mixed‐Use Farmland Catchment

“…Stream temperature is an important variable that affects ecosystem functioning and controls biogeochemical processes in aquatic systems (Allan & Castillo, ; Baranov et al, ; Folegot et al, ; Webb et al, ). Increased stream temperature can negatively impact water quality and the health of aquatic ecosystems (Calow & Petts, ; Folegot et al, ; Roth et al, ), while water temperature at the outlet of catchments controls water quality in receiving waters such as lakes and the coastal ocean (Safaie et al, ). Stream thermal regimes are primarily driven by climatic conditions and are also influenced by a host of other factors, including topographic conditions, stream discharge, riparian vegetation and land use near the stream, and interactions with the subsurface environment (Caissie, ; Hannah & Garner, ).…”