Date Awarded

2011

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.)

Department

Virginia Institute of Marine Science

Advisor

Carl H. Hershner

Abstract

The collection of fecal coliform (FC) monitoring data in shellfish growing waters is primarily to assess public health risks from consumption of contaminated product. The data is also commonly used to assess the potential sources and loads of bacteria entering the aquatic system. This project is intended to extend traditional methods of developing these assessments, by applying an inverse modeling approach to improve the estimation of FC loads in the small watersheds typically contributing to shellfish growing waters in Virginia. Many fecal contamination studies in lower Chesapeake Bay, Virginia, have conveniently focused on analyses over relatively small spatial and temporal scales. The potential sources of bacteria are numerous and the magnitude of their contributions is commonly unknown (Hyer and Moyer, 2004). The effects of stochastic events merely complicate the already difficult task of quantifying sources and loads in an inherently variable system (White et al., 2008). Instead of identifying and quantifying individual fecal bacteria sources, like deer or raccoons or domestic animals, it is herein proposed to analyze spatial and temporal patterns of fecal contamination on relatively large scales and quantify FC loadings based on land cover. The result would make it easier for managers to assign land-cover-based accountability to restore fecal contaminated environments. Monitoring of FC concentrations throughout Virginia by the Division of Shellfish Sanitation (DSS) provided an opportunity to analyze FC levels from 1984 to the present and quantify FC loadings by type of land cover. There are three aspects in this study---spatial analysis of FC data, temporal analysis of FC data, and FC loadings quantification based on the findings from spatial and temporal analyses. GIS tools and a variety of statistical methods are used in combination with an inverse modeling approach. The modeling method was based on some basic concepts incorporated in the Watershed Management Model and the Tidal Prism Model currently used to develop Total Maximum Daily Load (TMDL) models for Virginia waters. The core contributions of this dissertation are: (1) This study provided a thorough examination of FC monitoring data in Virginia coastal waters and described how contamination levels are expressed at different spatial and temporal scales. Analyses examined tidal effects, regional effects, land condition effects, and climate effects. Results not only inform management decisions, but also provide guidance for the subsequent quantification of fecal bacteria loadings. (2) Fecal bacteria loadings are quantified as a function of land cover. The model developed in this study avoids the problems associated with using highly varied and poorly documented FC production rates and population numbers. Although the model is simple, the magnitude of Fecal Coliform Event Mean Concentration (FCMC) values based on land covers effectively distinguished the seasonal FC loadings.

DOI

https://dx.doi.org/doi:10.25773/v5-t4n1-cv18

Rights

© The Author

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