A predictive model for microbial counts on beaches where intertidal sand is the primary source

Zhixuan Feng, Ad Reniers, Brian K Haus, Helena M Solo-Gabriele, John D. Wang, Lora E. Fleming

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Human health protection at recreational beaches requires accurate and timely information on microbiological conditions to issue advisories. The objective of this study was to develop a new numerical mass balance model for enterococci levels on nonpoint source beaches. The significant advantage of this model is its easy implementation, and it provides a detailed description of the cross-shore distribution of enterococci that is useful for beach management purposes. The performance of the balance model was evaluated by comparing predicted exceedances of a beach advisory threshold value to field data, and to a traditional regression model. Both the balance model and regression equation predicted approximately 70% the advisories correctly at the knee depth and over 90% at the waist depth. The balance model has the advantage over the regression equation in its ability to simulate spatiotemporal variations of microbial levels, and it is recommended for making more informed management decisions.

Original languageEnglish (US)
Pages (from-to)37-47
Number of pages11
JournalMarine Pollution Bulletin
Volume94
Issue number1-2
DOIs
StatePublished - May 15 2015

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Keywords

  • Beach advisory
  • Fecal indicator bacteria
  • Microbial mass balance
  • Multivariable linear regression
  • Nonpoint source beach
  • Water quality model

ASJC Scopus subject areas

  • Aquatic Science
  • Oceanography
  • Pollution

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