Publication Date

2014-05-03

Availability

Open access

Embargo Period

2014-05-03

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PHD)

Department

Applied Marine Physics (Marine)

Date of Defense

2014-04-04

First Committee Member

Ad Reniers

Second Committee Member

Brian K. Haus

Third Committee Member

Helena M. Solo-Gabriele

Fourth Committee Member

John D. Wang

Fifth Committee Member

Lora E. Fleming

Abstract

To comply with federal law Beach Environmental Assessment and Coastal Health Act (BEACH Act), and the U.S. Environmental Protection Agency guidelines, beach monitoring programs have been adopted and implemented to protect beachgoers from health risks caused by harmful microorganisms. Present monitoring programs around the United States heavily rely on sparse water sampling (usually daily to weekly) with time-consuming microbial laboratory analysis, thereby potentially causing unnecessary beach closures or human health risks for beaches that remain open. The objective of this dissertation is to use both field observations and numerical models to investigate the linkages between microbiological, hydrological, and morphological processes at nonpoint source beaches. The scales cover intra-day to inter-annual variations, and from a single case study beach to hundreds of beaches in the State of Florida. This objective is accomplished through three studies. In the first study, a coupled microbe-hydrodynamic-morphological model is developed. The unique feature of this model is its capability of simulating the release of microbes attached to beach sands as a result of combined wave and tidal forcing. The microbe transport-decay equation, coupled to the nearshore process model XBeach, includes source functions that account for microbial release from mobilized sand, groundwater flow, entrainment through pore water diffusion, rainfall-runoff loading, and a fate function that accounts for solar inactivation effects. The model has skills in simulating observed temporal patterns of enterococci levels at a municipal beach in Miami, FL through an intensive 10-day field experiment, including the reproduction of diel cycles due to solar inactivation and patterns associated with semidiurnal tides. The spatial patterns are shown as rapid decreases of enterococci levels from the shoreline to offshore. The second study develops a new numerical mass balance model for enterococci levels on nonpoint source beaches. This is a model similar to more general horizontal grid numerical models, but simplified as it is limited to calculation of transient cross-shore microbial distributions for a beach with fairly alongshore uniform source and environmental conditions. The inputs to the model are readily-available environmental factors (i.e., wind, tide, wave, solar radiation, and precipitation), which are used in the mass balance considerations of source loading, transport, and biological decay. The significant advantage of this model is its easy implementation and a detailed description of the cross-shore distribution of enterococci which should be useful for beach management purposes. The performance of the balance model is evaluated by comparing predicted exceedances of a beach advisory threshold value to field data, and to a traditional regression equation model. Both the balance model and regression equation predicted approximately 70% the advisories correctly at the knee depth and > 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 is recommended for making more informed beach management decisions. In the third study, decade-long weekly monitored indictor bacteria levels (enterococci and fecal coliform) at 262 Florida recreational beaches, provided by the Florida Healthy Beaches Program, are analyzed to examine spatiotemporal patterns of microbial levels and microbial responses to hydrological and hydrometeorologic fluctuations (i.e., wave height, water temperature, solar radiation, and precipitation). Results showed that low-wave-energy beaches exceed the EPA thresholds significantly more than high-wave-energy ones (p < 0.01), and Gulf of Mexico beaches also exceed the thresholds significantly more than Atlantic ones (p < 0.01). Percent exceedances negatively correlate with both long-term mean wave height and beach slope, suggesting that beach wave energy level is an important factor in determining water quality. In general, the higher wave energy, the better beach water quality is. In addition, we found that seasonal bacterial variations in Atlantic and Gulf of Mexico beaches are generally out of phase. There are opposite correlations in seasonal mean log-transformed bacterial levels and environmental variables (i.e., wave height, water temperature, solar radiation, and precipitation) between Atlantic versus Gulf of Mexico beaches. Microbial variations on each of Florida coasts are likely controlled by different mechanisms, which would require different beach management strategies to minimize microbial water quality exceedances. In summary, this dissertation explores innovative modeling techniques and highlights physical and biological interactions in controlling nearshore microbial water quality. The new model tools and knowledge can be applied in beach management practice, water quality assessment, and decision support across the United States.

Keywords

beach; water quality; fecal indicator bacteria; XBeach; microbial mass balance; exceedance

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