Publication Date
12-5-2003
Abstract
It is widely known that micro-organisms such as bacteria (e.g., E. coli), Giardia (often associated with beaver), and Cryptosporidium (sometimes associated with pets, livestock, and wildlife) can enter streams during rain and snowmelt events. It is also known that transport of nutrients such as phosphorus and nitrogen, in addition to total and dissolved organic carbon (TOC/DOC), may be elevated during rain and snowmelt events. It is difficult, however, to accurately determine the type and quantity of these parameters transported during such events. In addition, accurately identifying the sources of these contaminants is a difficult task. Hence, organizations responsible for public water supplies, outdoor recreation, and environmental quality face substantial challenges in their efforts to protect public health. Work is currently underway to generate event transport and source identification data to improve water pollution detection, measurement, and protection methods for Massachusetts’ watersheds. With the voluntary cooperation of landowners, three field-measurement and sampling sites have been established for detailed sampling during rainfall events. These sites include a farm, a residential - commercial region, and a forested area. At each site, both an upstream and a downstream sampling transect have been established and instrumented to measure flow with a high level of accuracy. Both monthly and detailed event sampling occur at these transects. The constituents analyzed include several emerging pathogens and alternative source-specific indicator organisms, including Giardia cysts and Cryptosporidium oocysts, in addition to traditional water-quality and microbial analyses. It is anticipated that the final database will consist of transport data during twenty-four distinct storm-events in addition to monthly baseline data. The results of the study to date will be presented. Long-term goals include determining the relative contribution of contaminant loads during baseflow and storm events. These data, combined with land use information, will then be used to identify the most likely sources contamination. Storm event sampling strategies will also be optimized in terms of the number of samples to be collected, the timing of sample collection (including sample initiation), and the constituents to be measured. In particular, correlations of the resulting data with meteorological and hydrologic conditions will be explored to determine if an optimum time for sample collection can be identified.