Saudi Arabia produces a majority of its fruits and vegetables locally in small-scale production farms. These farms utilize groundwater as the main source of irrigation water. The water-regulating authorities in Saudi Arabia rely on traditional culturing methods to monitor coliforms as indicators of microbial contamination. These methods are time-consuming, do not address the sources of contamination, and do not permit assessment on the associated health risk. To address these knowledge gaps, the study investigates the sources of contamination in eight wells northeast of Mecca, Saudi Arabia. The study focuses on the potential impact on groundwater quality due to a nearby chicken farm and urban runoffs from human residential areas. Besides performing conventional methods to determine nutrient content and to enumerate coliforms, quantitative PCR using four host-associated primer sets were used to distinguish microbial contamination from humans and livestock. High-throughput sequencing was also performed to determine the relative abundance of several genera associated with opportunistic pathogens. Bacterial isolates were cultivated from the vegetable samples harvested from these farms, and were characterized for their phylogenetic identities. Lastly, the study collates the information to perform quantitative microbial risk assessment due to ingesting antibiotic-resistant Listeria monocytogenes, Pseudomonas aeruginosa and Enterococcus faecalis in these vegetable samples.

The field of molecular fecal source tracking in the water environment has developed rapidly since the first PCR assays for general and host-­‐specific Bacteroides 16s rRNA markers were published. Numerous host-­‐specific molecular markers and PCR assays have been developed, adding greater specificity, sensitivity and quantitative methods to the array of options. The public demand for readying methods for transfer to the commercial lab, so that they may be used to generate data for public utilities, citizen action groups and regulatory agencies, has fueled the development of an entire new research community. These methods, however plentiful, have not found community agreement and there is no consensus concerning the appropriate implementation of molecular fecal source tracking in the field. Some issues plaguing the implementation include imperfect marker specificity, environmental variability, DNA extraction variability, PCR inhibition and high cost of molecular analysis. This thesis presents an approach for locating hot spots of human fecal pollution in an urban watershed by using published methodologies for the collection of molecular fecal source tracking data along with a tiered watershed screening tool for cost reduction and two data normalization techniques which ameliorate several known sources of error and strengthen the efficacy of watershed application.

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