Temporal variation and persistence of bacteria in streams.

Better understanding of bacterial fate and transport in watersheds is necessary for improved regulatory management of impaired streams. Novel statistical time series analyses of coliform data can be a useful tool for evaluating the dynamics of temporal variation and persistence of bacteria within a watershed. For this study, daily total coliform data for the Little River in East Tennessee from 1 Oct. 2000 to 31 Dec. 2005 were evaluated using novel time series techniques. The objective of this study was to analyze the total coliform concentration data to: (i) evaluate the temporal variation of the total coliform, and (ii) determine whether the total coliform concentration data demonstrated any long-term or short-term persistence. For robust analysis and comparison, both time domain and frequency domain approaches were used for the analysis. In the time domain, an autoregressive moving average approach was used; whereas in the frequency domain, spectral analysis was applied. As expected, the analyses showed that total coliform concentrations were higher in summer months and lower in winter months. However, the more interesting results showed that the total coliform concentration exhibited short-term as well as long-term persistence ranging from about 4 wk to approximately 1 yr, respectively. Comparison of the total coliform data to hydrologic data indicated both runoff and baseflow are responsible for the persistence.

Efficacy of Bacteroides measurements for reducing the statistical uncertainty associated with hydrologic flow and fecal loads in a mixed use watershed.

This paper presents an analysis of the occurrence and uncertainty of source-specific Bacteroides and Escherichia coli in a stream in a mixed land-use watershed with human, cattle, and wildlife fecal inputs located in a karstic geologic region during baseflow conditions. The objectives of the study were to evaluate the occurrence, hydrologic significance, and source of fecal mass in the stream using assays for total Bacteroides (AllBac) and bovine-specific Bacteroides (BoBac), and then to compare these measurements with E. coli densities and loads. Samples were collected during baseflow conditions over several months at seven different main channel sites in the Stock Creek watershed, a 49.3 km2 basin located in Knoxville, TN (USA). We determined instantaneous loads for total fecal loads, bovine fecal loads, and E. coli from measured flow rates and the representative Bacteroides fecal masses and/or E. coli densities. The study indicated a strong correlation between total fecal load (kg d(-1)), bovine fecal load (kg d(-1)), E. coli load rate (CFU d(-1)), 7-d antecedent precipitation, and turbidity. The various datasets were used to establish parameter correlations and spatial dependencies throughout the watershed. The data analysis demonstrated two prevalent patterns throughout the watershed: (i) a runoff-dominated transport and occurrence; and (ii) potential groundwater-dominated transport and occurrence.

Escherichia coli loading at or near base flow in a mixed-use watershed.

This study analyzed the occurrence of Escherichia coli in a mixed land-use watershed with human, cattle, and wildlife fecal inputs located in a karstic geologic region using synoptic monitoring (samples taken throughout the watershed system) during base-flow conditions. The objective of the study was to evaluate the occurrence of E. coli during base-flow conditions for several months at seven different main channel and nine different tributary sampling sites in the Stock Creek watershed, a 49.3-km(2) basin located in Knoxville, TN. Escherichia coli densities were measured using the Colilert (Defined Substrate Technology) method. The instantaneous loads for E. coli were determined from measured flow rates and E. coli densities, with the highest loading rates observed in the late fall. The study indicated a strong correlation between E. coli load rate (colony-forming units [CFU]/d), 7-d antecedent precipitation, and turbidity. Water quality data, however, also exhibited a spatial dependency; for example, the E. coli load rate was better correlated with turbidity in the slower draining basin tailwater sampling sites than in the faster draining upstream headwater sampling sites. In the headwater sites, the E. coli load rate was better correlated with 7-d antecedent precipitation than turbidity.