Using long-term science data to examine relationships of wastewater infrastructure and water quality

Sarah Williamson, a junior from Baylor University, worked with Denzell Cross in the lab of Dr. Krista Capps.  They used community-collected data to examine spatial and temporal changes in water quality in a local watershed.

Abstract:  The integrity of freshwater systems throughout the world is threatened by increasing concentrations of gut bacteria, such as E. coli. In urban watersheds, increases in bacterial concentrations are associated with intentional municipal wastewater discharge and aging and obsolete wastewater infrastructure (e.g., sewage leaks and failing septic systems). Tracing sources of bacterial contamination in surface waters is often difficult due to the need for long-term monitoring. Moreover, long-term monitoring can be time intensive and costly.
Community science organizations can be a cost-effective way to collect large amounts of environmental data across broad spatial and temporal scales. However, data collected by community scientists are often criticized due to concerns about scientific rigor, data fragmentation, and inaccuracy. Other work has demonstrated that groups employing robust protocols can produce data that align with data collected by professionals, and can be used reliably in decision-making processes pertaining to environmental health and watershed management. The purpose of this study was to examine spatial and temporal changes in water quality using data collected by community scientists of the Upper Oconee Watershed Network, and use community data to investigate relationships between water quality metrics and wastewater infrastructure in Athens-Clarke County (ACC). Specifically, we wanted to ask if water quality metrics (i.e., conductivity and turbidity) correlated to fecal bacteria concentrations in ACC surface waters and if there are relationships between site- and watershed-specific concentrations of E. coli and the proximity and density of wastewater infrastructure. We found that turbidity may be a strong predictor in bacteria concentrations however, the relationship between bacteria and conductivity was not clear. Our data also suggests that there may be important links between wastewater infrastructure and reduced water quality.