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Recreational Beach Bacteria Modeling and Forecasting and the Consequences to Public Health and Economic Vitality A partnership involving: University of South Carolina Raytheon, Inc. University of Maryland Center for Environmental Science SC


  1. Recreational Beach Bacteria Modeling and Forecasting and the Consequences to Public Health and Economic Vitality A partnership involving: University of South Carolina Raytheon, Inc. University of Maryland Center for Environmental Science SC Department of Health and Environmental Control NOAA Center for Coastal Environmental Health and Biomolecular Research NOAA National Estuarine Research Reserve System NC/SC RCOOS SECOORA NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  2. Outline: • Setting the stage • Water quality concerns • Implications of swimming advisories • Beach advisory modeling • Outcomes of integrative efforts NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  3. Setting the stage In response to water quality concerns and associated public health concerns • State health agency routinely (weekly, post rain event, repeat) samples water quality at ocean beaches • Results used to inform public of potential health risk Marissa Reilly, DHEC Region 7 NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  4. Setting the stage • Enterococcus – Direct measurement of pathogens is difficult and expensive – High Enterococcus counts = greater chance of human pathogens being present • 24-hr incubation NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  5. Setting the stage Swimming advisories are issued if Enterococcus levels • >500 MPN/100mL – Issue advisory • >104 MPN/100mL – Resample Today’s advisory is based on yesterday’s water quality NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  6. Setting the stage Day 2 Bacteria Concentration (log) Day 1 Bacteria Concentration (log) NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  7. Setting the stage Implications of swimming advisories • Error of commission • Issue advisory when water quality is good • Poor image / revenue loss (i.e. the Chamber of Commerce is not happy) • Error of omission • Fail to issue advisory when water quality is poor • Public health risk NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  8. Beach advisory modeling A potential improvement offered up to public health officials was that • Enterococcus concentrations can be predicted with an accuracy adequate to assist decision-makers in the preemptive advisory process NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  9. Beach advisory modeling Perceived bottlenecks preventing prediction or timely response to critical public health and environmental events: • Access and integrated use of distributed, heterogeneous data • Insufficient density of appropriate data observations • Insufficient predictive model development NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  10. Beach advisory modeling NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  11. Beach advisory modeling NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  12. Beach advisory modeling Parameter Source Bacteria density Monitoring Programs Air temperature Monitoring Programs / Observing Systems/ Remote Sensing Water temperature Monitoring Programs / Observing Systems/ Remote Sensing Salinity Monitoring Programs / Observing Systems Tide stage NOAA Weather conditions Weather Service/ Observing Systems/ Remote Sensing Wind direction Weather Service/ Observing Systems/ Remote Sensing Precipitation Weather Service/ Observing Systems/ Remote Sensing Solar radiation Observing Systems/ Remote Sensing River Flow River Forecasting Centers / USGS Soil Moisture Remote Sensing NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  13. Beach advisory modeling Modeling techniques used include • Multiple Linear Regression (MLR) • Classification and Regression Trees (CART) • Ensemble Models NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  14. Beach advisory modeling NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  15. Beach advisory modeling Level 1 Level 2 Level 3 Model complexity is Cumulative Cumulative Cumulative dependent upon Rainfall Rainfall Rainfall Rain Intensity Rain Intensity Rain Intensity Preceding Dry Preceding Dry Preceding Dry • Location Days Days Days • Availability of data Weather Weather Weather • Acceptable error Tidal Range Tidal Range Tidal Range Lunar Phase Lunar Phase Lunar Phase Station Station Station Wind Speed Wind Speed Wind Wind Direction Direction Current Salinity NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  16. Beach advisory modeling Focusing on model validation and … Level 1 Level 2 Level 2 Level 1 Percent Misclassification Percent Misclassification 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC Level 3 Level 3 Percent Misclassification 60% 50% Model 40% 30% Validation 20% 10% 0% NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  17. Beach advisory modeling Error assessment Level 1 Level 2 60 60 50 50 40 40 30 30 20 20 10 10 0 0 NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC Level 3 60 50 40 30 20 10 0 NMB2 NMB3 MB1 MB2 MB3 MB4 SS GC % Type I Error (i.e. upsetting the Chamber of Commerce) % Type II Error (i.e. potential for increased health risks) NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  18. Beach advisory modeling • Models are now being used in support of issuing beach advisories • Decreased decision error • Increased support from local government • Improved public health protection • One of first/few marine/ Enterococcus models • One of first to use CART models NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  19. Outcomes of integrative efforts • Improving understanding of the role of technologies in addressing priority environmental and public health issues • New observation infrastructure of additional real-time, continuous observations • Improved knowledge of the data that exist to address coastal zone management issues in the region • Rapid access to local data for managers, researchers, and the public via the interactive website ____________________________________________________________________________________________________ • Development of inter-agency “rapid response” efforts addressing priority health and management issues • Improved coordination and communication among diverse, complimentary group of coastal agencies and organizations supporting proactive efforts rather than reactive response NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  20. Acknowledgements • USC – Madilyn Fletcher, Dwayne Porter, Dan Ramage, Jay Poucher, Jeremy Cothran, Jeff Jefferson, James Hibbert, Virginia Shervette, Emily McDonald, Erica Johnson • Raytheon, Inc. – Carroll Hood • University of Maryland – Heath Kelsey • SCDHEC – Shannon Berry, Sean Torrens • UNCW – Lynn Leonard, Jen Dorton • Partners - NC/SC RCOOS, NI-WB NERR, NC NERR, ACE Basin NERR, SECOORA • Funding: NOAA Geodetic Surveys and Services NFRA Regional Products Workshop Ann Arbor, MI 17-19 May 2010

  21. GeoRSS

  22. Marine Weather Portal Jennifer Dorton, UNC Wilmington Dwayne Porter, Univ. of South Carolina Vembu Subramanian, Univ of South Florida Charlton Galvarino (??)

  23. MWP Project Goals • Provide 24/7 access to critical marine information for the commercial & recreational marine communities. • Make NOAA data and other data provider information more widely accessible on one website. – With a consistent look and feel • Support NOAA’s Mission Goals of: – Serving Society's Needs for Weather and Water Information – Supporting the Nation's Commerce with Information for Safe, Efficient, and Environmentally Sound Transportation.

  24. Carolinas Coast was a joint effort by NWS, CORMP & Caro- COOPS to consolidate observing data & NWS products for the public.

  25. 2007 NOAA IOOS award allowed the project to expand from the Carolinas throughout the SE.

  26. Data Acquired from: • NWS • NDBC Buoys and CMAN stations – R-COOS stations – Federal & state agencies • NOS – Water level stations – PORTS – Tide Predictions • NCEP – Storm Prediction Center & Tropical Prediction Center

  27. Data Acquired from: • OPC and National Hurricane Center (offshore waters forecasts) • National Estuarine Research Reserves • USGS – stream gauge station • USACE – Field Research Facility stations • MADIS Ship Observations

  28. MWP Technology

  29. General Architecture USC USF • Servers at USC and USF – Collect data NWS – Collect hazards HQ – Create maps Webfarm – Package information as HTML and PNG • Webfarm at NWS HQ – Pulls packaged information from USC and USF – Serves the data & maps as webpages to the public

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