This project implemented novel approaches to assess the source, age, concentration and mobility of fecal indicator microorganisms within a karst groundwater system. Research was conducted in the well-characterized Blue Hole Spring karst groundwater basin in Versailles, Woodford County, Kentucky. At this site the AC/TC ratio and fecal coliform (FC) bacteria counts were used to delineate sources of fecal inputs and determine relative age of the fecal matter. An aging experiment using indicator bacteria (total coliform (TC) and atypical colonies (AC)), which approximated subsurface conditions, indicated that changes in the AC/TC ratio are likely to be retarded during bacterial transport through karst conduits. Decreases in the AC/TC ratio during the monitoring period appear to be the result of sewage releases. Multiple logistic regression (MLR) modeling was performed to examine correlations between physiochemical parameters and FC concentrations. MLR models using physiochemical parameters correctly predicted “safe for contact” (< 200 cfu/100 mL FC) conditions 65.6% of the time and “unsafe for contact” (> 200 cfu/100 mL FC) conditions 69.2% of the time at Blue Hole Spring. Modeling using other indicators (TC and AC) predicted “safe for contact” conditions 87.5% of the time and “unsafe for contact” conditions 61.5% of the time. A series of tracer tests were performed to compare transport of solute and abiotic particle tracers (rhodamine WT fluorescent dye, bromide and fluorescent bacteria-sized microspheres) and bacteria (15N-enriched wild-type E. coli) within the karst system. The surrogate tracers did not suitably mimic microbial mobility within the basin. Solutes and 15N-enriched E. coli arrived concurrently during storm flow to Blue Hole Spring, whereas microsphere breakthrough corresponded with maximum solute concentrations. The 15Nenriched E. coli exhibited slightly more tailing during storm-flow recession than solute tracers, none of which exhibited remobilization. Microspheres demonstrated remobilization within the conduits that correlated with later increases in discharge related to secondary storm events.

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.

The City of Georgetown, Kentucky relies on a vast karst spring network as a drinking water source. This karst feature has several inputs from sinkholes and streams in the Cane Run Watershed: a watershed associated with a variety of land uses in the recharge area. The recharge area encompasses the area from North Lexington to Georgetown and is composed of urban, suburban, agricultural and industrial usage. A serious water quality issue exists with respect to the impact of fecal contamination within the spring recharge area. Identification of fecal contamination is quantified by microbial indicators adapted from surface water applications: fecal load (E. coli), fecal source (two human-host specific Bacteroides DNA markers) and fecal age (AC/TC ratio). These three criteria are used in a categorical Microbial Source Tracking (MST) model to assign a Sanitary Category Value (SCV) between 0 and 3 for each sample location. Low SCVs (1.5) are associated with high values of fecal load, low fecal age and detectable concentration of human-specific markers. SCV measured during dry weather conditions are indicative of potentially leaking human sewers. Due to retention and conservation of fecal load (E. coli) and age (AC/TC) microbial indicators in the karstic environment, ambiguous SCV model results cannot pinpoint, with statistical confidence, fecal sources in a karstic environment. Human-host specific genetic markers (HF183 and HuBac) were also detected at all sample sites above limits of detection, indicating steady inflow of fecal material during all sample events. By adding a flow multiplier and expressing HF183 and HuBac values as a load, it was strongly indicated that a human fecal source was entering the groundwater conduit and impacting Royal Spring independent from other upstream fecal sources. Interpretation of these trends, while strongly indicated, cannot be supported with statistical evidence.