Faculty Articles
Using probabilities of enterococci exceedance and logistic regression to evaluate long term weekly beach monitoring data.
Publication Title
Journal of water and health
ISSN
1477-8920
Publication Date
2-1-2016
Keywords
bacterial contamination, beach management, beach monitoring, environmental parameters, exceedance probability, logistic regression, multiple linear regression, recreational water quality, south florida beaches, tidal influence, water quality modeling, beach closure, public health, predictive modeling, risk assessment, environmental surveillance, rainfall correlation, hurricane impact, probability analysis, coastal water management
Abstract
Recreational water quality surveillance involves comparing bacterial levels to set threshold values to determine beach closure. Bacterial levels can be predicted through models which are traditionally based upon multiple linear regression. The objective of this study was to evaluate exceedance probabilities, as opposed to bacterial levels, as an alternate method to express beach risk. Data were incorporated into a logistic regression for the purpose of identifying environmental parameters most closely correlated with exceedance probabilities. The analysis was based on 7,422 historical sample data points from the years 2000-2010 for 15 South Florida beach sample sites. Probability analyses showed which beaches in the dataset were most susceptible to exceedances. No yearly trends were observed nor were any relationships apparent with monthly rainfall or hurricanes. Results from logistic regression analyses found that among the environmental parameters evaluated, tide was most closely associated with exceedances, with exceedances 2.475 times more likely to occur at high tide compared to low tide. The logistic regression methodology proved useful for predicting future exceedances at a beach location in terms of probability and modeling water quality environmental parameters with dependence on a binary response. This methodology can be used by beach managers for allocating resources when sampling more than one beach.
DOI
10.2166/wh.2015.030
Volume
14
Issue
1
First Page
81
Last Page
9
Disciplines
Medical Specialties | Medicine and Health Sciences | Osteopathic Medicine and Osteopathy
NSUWorks Citation
Lopez, J V.; Solo-Gabriele, H M.; Fleisher, Jay M.; and Fleisher, Jay M., "Using probabilities of enterococci exceedance and logistic regression to evaluate long term weekly beach monitoring data." (2016). Faculty Articles. 1446.
https://nsuworks.nova.edu/hpd_com_faculty_articles/1446