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Modeling pathogens for oceanic contact recreation advisories in the New York City area using total event simulations

Author

Listed:
  • Wen, Bin
  • Georgas, Nickitas
  • Dujardins, Charles
  • Kumaraswamy, Anand
  • Cohn, Alan

Abstract

A simulation of transport and fate of pathogen indicators for the New York City open waters was completed using a coupled numerical model. Modeled concentrations for Enterococci in receiving waters were extracted from the model and compared with NYC beach observations and NYC Harbor Surveys to validate and bias-correct the result. Results, both before and after bias-correction, were then used to calculate model-based contact recreation advisories and compare to existing advisories: NYC DEP advisory guidance for waterbodies, and NYC DOHMH advisory guidance for NYC beaches. The model was able to simulate the transport and fate of Enterococci. Receiving water Enterococci concentrations grew responsively to rainfall, and decreased notably after rainfall. The model showed the ability to take complexity of natural effects into account, and was conservative in most cases after bias-correction. Based on an exceedance criterion of 110cfu/100mL, simulated Enterococci concentrations exceeded that criterion 54% (109%) of the total advisory days that existing NYC DOHMH guidance would suggest throughout all NYC beaches, on average, before (after) bias-correction. The model exceeded that criterion 217% (246%) of the total advisory days that existing NYC DEP guidance would suggest throughout all NYC waterbodies, on average, before (after) bias-correction. Simulation results were provided to NYC DEP and NYC DOHMH for the refinement of existing advisories.

Suggested Citation

  • Wen, Bin & Georgas, Nickitas & Dujardins, Charles & Kumaraswamy, Anand & Cohn, Alan, 2017. "Modeling pathogens for oceanic contact recreation advisories in the New York City area using total event simulations," Ecological Modelling, Elsevier, vol. 365(C), pages 93-105.
    • Handle: RePEc:eee:ecomod:v:365:y:2017:i:c:p:93-105
    DOI: 10.1016/j.ecolmodel.2017.09.021
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