Modeling to Predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

Zimmerman, Tammy M.

doi:10.3133/sir20085039

Cited by 6 publications

(6 citation statements)

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“…23). This analysis is confirmation of past research at Presque Isle State Park that has shown a strong relation between turbidity and E. coli (Zimmerman, 2006(Zimmerman, , 2008Francy and others, 2013).…”

Section: June 24 2015supporting

confidence: 77%

Longshore water-current velocity and the potential for transport of contaminants—A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park beaches, Erie, Pennsylvania, June and August 2015

Hittle¹

2017

Open-File Report

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For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://store.usgs.gov/.Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. AcknowledgmentsThe author thanks the employees of the Erie County Department of Health and Human Services and the Regional Science Consortium for their assistance in collecting the nearshore samples. The author also thanks the U.S. Geological Survey Water Science Center office in Louisville, Kentucky, for use of the boat, Ed Puckett for excellence in driving the boat, and Lowell Abbadini for excellent assistance. Thanks also go to the Walnut Creek Marina for providing a boat slip during the synoptic surveys in June and August 2015. Supplemental InformationSpecific conductance is given in microsiemens per centimeter at 25 degrees Celsius (µS/cm at 25 °C).

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Section: June 24 2015supporting

confidence: 77%

Longshore water-current velocity and the potential for transport of contaminants—A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park beaches, Erie, Pennsylvania, June and August 2015

Hittle¹

2017

Open-File Report

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“…The goal of predictive models is to produce more accurate results than persistence models, using the previous day’s FIB measurement for current day decisions. Most models included in this review outperformed persistence models to varying degrees, in terms of sensitivity, specificity, and/or accuracy, supporting the use of predictive models in management decisions [ 27 , 35 , 64 , 70 , 80 ]. However even if models are used for management decisions, routine water sampling for FIB should still be conducted to ensure models remain valid, and are updated and refined as appropriate, across seasons.…”

Section: Discussionmentioning

confidence: 64%

Systematic review of predictive models of microbial water quality at freshwater recreational beaches

et al. 2021

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Monitoring of fecal indicator bacteria at recreational waters is an important public health measure to minimize water-borne disease, however traditional culture methods for quantifying bacteria can take 18–24 hours to obtain a result. To support real-time notifications of water quality, models using environmental variables have been created to predict indicator bacteria levels on the day of sampling. We conducted a systematic review of predictive models of fecal indicator bacteria at freshwater recreational sites in temperate climates to identify and describe the existing approaches, trends, and their performance to inform beach water management policies. We conducted a comprehensive search strategy, including five databases and grey literature, screened abstracts for relevance, and extracted data using structured forms. Data were descriptively summarized. A total of 53 relevant studies were identified. Most studies (n = 44, 83%) were conducted in the United States and evaluated water quality using E. coli as fecal indicator bacteria (n = 46, 87%). Studies were primarily conducted in lakes (n = 40, 75%) compared to rivers (n = 13, 25%). The most commonly reported predictive model-building method was multiple linear regression (n = 37, 70%). Frequently used predictors in best-fitting models included rainfall (n = 39, 74%), turbidity (n = 31, 58%), wave height (n = 24, 45%), and wind speed and direction (n = 25, 47%, and n = 23, 43%, respectively). Of the 19 (36%) studies that measured accuracy, predictive models averaged an 81.0% accuracy, and all but one were more accurate than traditional methods. Limitations identifed by risk-of-bias assessment included not validating models (n = 21, 40%), limited reporting of whether modelling assumptions were met (n = 40, 75%), and lack of reporting on handling of missing data (n = 37, 70%). Additional research is warranted on the utility and accuracy of more advanced predictive modelling methods, such as Bayesian networks and artificial neural networks, which were investigated in comparatively fewer studies and creating risk of bias tools for non-medical predictive modelling.

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“…Predictive modeling is a tool for assessing water quality in real-time using easily measured environmental and (or) water-quality variables-such as turbidity (water clarity) or rainfall-to make management decisions in 1 or 2 hours on whether to post beach advisories or closures. The USGS and collaborators have been investigating predictive modeling for more than a decade (Francy and Darner, 1998;Nevers and Whitman, 2005;Zimmerman, 2008). Nowcast systems that use predictive models to post advisories or closings are one means to provide realtime assessments of water quality.…”

Section: • Fecal Indicator Bacteria (Fib) Such Asmentioning

confidence: 99%

Real-time assessments of water quality: expanding nowcasting throughout the Great Lakes

2013

Fact Sheet

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The overall mission of this work is to provide science-based information and methods that will allow beach managers to more accurately make beach closure and advisory decisions, understand the sources and physical processes affecting beach contaminants, and understand how science-based information can be used to mitigate and restore beaches and protect the public. The U.S. Geological Survey (USGS), in collaboration with many Federal, State, and local agencies and universities, has conducted research on beach health issues in the Great Lakes Region for more than a decade. The work consists of four science elements that align with the USGS Beach Health Initiative Mission: real-time assessments of water quality; coastal processes; pathogens and source tracking; and data analysis, interpretation, and communication. The ongoing or completed research for real-time assessments of water quality is described in this fact sheet.

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Modeling to Predict Escherichia coli at Presque Isle Beach 2, City of Erie, Erie County, Pennsylvania

Cited by 6 publications

References 0 publications

Longshore water-current velocity and the potential for transport of contaminants—A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park beaches, Erie, Pennsylvania, June and August 2015

Longshore water-current velocity and the potential for transport of contaminants—A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park beaches, Erie, Pennsylvania, June and August 2015

Systematic review of predictive models of microbial water quality at freshwater recreational beaches

Real-time assessments of water quality: expanding nowcasting throughout the Great Lakes

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