DETAILED ANALYSIS OF PATHOGEN INDICATOR LOADINGS DURING SIX SUMMER STORMS AS DETERMINED VIA CULTURE-BASED AND GENETIC-BASED METHODS IN UPPER STROUBLES CREEK WATERSHED, VA, USA

Although intermittent contaminants from urban runoff are a major concern to many receiving waters in the United States, our understanding on microbiological stormwater quality remains incomplete. More detailed analyses of continuous time series FIB loadings during a storm event is essential for better stormwater management plans. This present study is unique in that both culture-based and genetic-based methods are used to test the FIB levels in time-series stromwater samples and the relationships between their results are investigated, which is essential as it is likely that genetic-based methods will eventually supplant culture-based methods as the monitoring mechanism of choice, and some studies suggested that the relationships between the results of culture-based and genetic-based methods may vary both spatially and temporally.

The main objective of the present study is to investigate the distribution of FIB loadings for several storms during the summer of 2013 in the Upper Stroubles Creek watershed in Blacksburg, VA (USA). Stroubles Creek is currently included on the Commonwealth of Virginia’s 303(d) impairment list due to elevated E. coli concentrations, with an associated total maximum daily load (TMDL) required. A segment of the creek is continuously monitored for a variety of hydrologic and water quality measures by the Virginia Tech Stream Research, Education And Management (StREAM) Lab. Grab samples were collected automatically via ISCO samplers every 15-30 minutes during six summer storms. Samples were immediately analyzed for concentration of E. coli and enterococci using IDEXX defined substrate methods, with a sub-aliquot preserved for later qPCR analysis for enterococci. Observations of FIB loadings during each storm were compared with various climatic, hydrologic, and physicochemical water- quality parameters collected in real-time by the StREAM Lab. Understanding patterns of microbial transport during storms will facilitate development of impending TMDL restoration plans to minimize the potential community health risks where possible. The detailed observations and conclusions from this study may provide a practical means for rapid problem identification and/or potential solutions to similar watershed with less available monitoring data.