New York Nowcast, Recreational Beaches of New York

Science Center Objects

Problem – Currently, swim advisories or closings are issued by beach managers based on standards for concentrations of bacterial indicators such as Escherichia coli (E. coli). Standard culture methods for these bacteria take at least 18-24 hours before results are available. At most Great Lakes beaches, the beach is posted with an advisory or closing or is determined to be acceptable for sw...

Problem – Currently, swim advisories or closings are issued by beach managers based on standards for concentrations of bacterial indicators such as Escherichia coli (E. coli).   Standard culture methods for these bacteria take at least 18-24 hours before results are available.   At most Great Lakes beaches, the beach is posted with an advisory or closing or is determined to be acceptable for swimming on the basis of the previous day’s E. coli concentration.  Sanitary conditions may change overnight and even throughout the day (Boehm and others, 2002) making decisions made from previous days information incorrect.  Because of this time-lag issue, water-resource managers are seeking solutions that provide near real-time estimates of recreational water quality on which to base their decisions..  One solution to improve the timeliness and accuracy of recreational water-quality assessments is to use multi-variable predictive models.  Predictive models use environmental and water-quality variables that are easily and quickly measured in the field and obtained from on-line, third-party environmental databases to yield the probability that the state standard will be exceeded and to estimate concentrations of E. coli. 

The U.S. Environmental Protection Agency (USEPA) encourages the use of predictive models in new proposed regulatory criteria as an option to supplement culture-based analytical results to facilitate same-day public health decisions (U.S. Environmental Protection Agency, 2012a).  Predictive models are used routinely for beach closure or advisory decisions at a few locations within the Great Lakes such as to the Ohio Nowcast (https://pa.water.usgs.gov/apps/nowcast/).  The Ohio Nowcast has been shown to provide better estimates of public health risk than using the previous day’s E. coli concentration, the current method used by most beach managers, especially in regard to sensitivity (Francy and others, 2009). Sensitivity is the proportion of actual exceedances of the state standard that are predicted correctly. 

The U.S. Geological Survey (USGS) is working with local and state agencies to expand the use of operational predictive models throughout the Great Lakes. Data were collected during the recreational seasons of 2010-12 to develop beach-specific models for E. coli at 43 beaches (Francy and others, 2013).  For some beaches, data collected before 2010 were also used.   The best model for each beach was based on a unique combination of explanatory variables including most commonly, day of the year, wave height, turbidity, wind direction and speed, antecedent rainfall for various time periods, and change in lake level over 24 hrs.  Updated or new models were validated during an independent year (2012-14).  Model performance was compared to the current method for assessing recreational water quality at each beach to determine the potential for a public New York Nowcast in 2013-14.  At eleven beaches in New York, model results were reliable enough to begin using them in a New York Nowcast system developed in 2013-15 (https://pa.water.usgs.gov/apps/nowcast/). 

Objective – The overall objective is to provide beach manages with the ability to base beach-closure decisions on regression models versus currently used “logic” models.  Nowcasting is based on combining field-data collection in a management system with third-party Federal Agency (NOAA and USGS) daily data integration.  The Nowcast system allows the users to have a web-based ability to graphically display their decisions to the public.

Scope –We propose to continue the New York Nowcast system at eleven beaches that have been involved in Nowcasting over the past 2 years. The future intent is to accommodate all interested New York State recreational beaches and, potentially, other state beaches interested in public notification of beach conditions. 

A predictive model for each beach can be, or has been, developed for the recreational season using Virtual Beach software specifically designed by USEPA for beach model development (U.S. Environmental Protection Agency, 2012b).  The output from the model is the probability that the E. coli concentration will exceed the State bathing-water single-sample standard (235 colony forming units/100 mL).  A threshold probability is established for each model based on historical data, and the beach is posted with an advisory if the probability exceeds this threshold (Francy and Darner, 2006; Francy and Others, 2013).

Approach – USGS will improve and maintain the New York Nowcast system and refine and expand a data-management system to accommodate additional beaches in New York, the Great Lakes Region and recreational beaches in general. The new system will provide recreational water-quality notifications to the public in 2015 and will be called the New York Nowcast.  Provided that the growth is accepted by multiple water science centers and cooperators, the system name would adapt to a regional one as its acceptance and use grow beyond New York. 

Selected References

Boehm, A.B., Grant, S.B., Kim, J.H., Mowbray, S.L., McGee, C.D., Clark, C.D., Foley, D.M., Wellman, D.E., 2002,  Decadal and shorter period variability of surf zone water quality at Huntington Beach, California:  Environmental Science and Technology, v. 36, no. 18, p. 3885-3892.

Francy, D.S. and Darner, R.A., 2006, Procedures for developing models to predict exceedance of recreational water-quality standards at coastal beaches: U.S. Geological Survey Techniques and Methods 6-B5, 34 p. 

Francy, D.S., Bertke, E.E., and Darner, R.A., 2009, Testing and refining the Ohio Nowcast at two Lake Erie beaches—2008: U.S. Geological Survey Open-File Report 2009-1066, 20 p., accessed at http://pubs.usgs.gov/of/2009/1066/

Francy, D.S., Brady, A.M.G., Carvin, R.B., Corsi, S.R., Fuller, L.M., Harrison, J.H., Hayhurst, B.A., Lant, J., Nevers, M.B., Terrio, P.J., and Zimmerman, T.M., 2013, Developing and implementing predictive models for estimating recreational water quality at Great Lakes beaches: U.S. Geological Survey Scientific Investigations Report 2013–5166, 68 p., http://dx.doi.org/10.3133/sir2013/5166/.

U.S. Environmental Protection Agency,  2012a, Recreational Water Quality Criteria: Washington, D.C.,   EPA-820-D-11-002, accessed March 2012 at http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation/index.cfm, 66 p. 

U.S. Environmental Protection Agency, Center for Exposure Assessment Modeling, 2012b, Exposure Assessment Models—Virtual Beach, accessed March 2012 at http://www.epa.gov/ceampubl/swater/vb2/index.html 

Project Location by County

 

St. Lawrence County, NY, Jefferson County, NY, Oswego County, NY, Cayuga County, NY, Wayne County, NY, Monroe County, NY, Orleans County, NY, Niagara County, NY, Erie County, NY, Chautauqua County, NY