GSA Connects 2021 in Portland, Oregon

Paper No. 185-7
Presentation Time: 2:30 PM-6:30 PM


LARSON, Eleanore, MALINA, Natalia and OJEDA, Ann, Department of Geosciences, Auburn University, 2050 Beard Eaves Coliseum, Auburn, AL 36849

In this study we explore statistically significant relationships between E. coli and human proxies to better trace and remediate fecal contamination. High concentrations of E. coli put the health and safety of communities at risk of bacterial infections and digestive illnesses. There are three possible human sources of E. coli in Choccolocco Creek: failing septic tanks, leaky sewer lines, and ineffective wastewater treatment plants (WWTPs). Natural inputs of E. coli include local wildlife and livestock. Two WWTPs discharge their effluent directly into the creek and there is a high density of onsite septic systems in the region. Residential septic systems are largely unregulated in the U.S. and could contribute significantly to E. coli loading in surface waters. We have defined source-specific proxies to better track contamination. Animal sterols including β -sitosterol serve as animal proxies, while the human sterol, coprostanol, and a series of pharmaceuticals (caffeine and ibuprofen) serve as human fecal markers. Our study explores the relationship between anthropogenic and animal markers, water quality parameters, and E. coli in Choccolocco Creek to trace contamination back to its source. We hypothesize that anthropogenic inputs contribute to the total pathogen loading.

We collected water samples once a month from April to September 2021 at nine sample sites throughout the creek. E. coli was measured in triplicate using Coliscan Easygel kits. Turbidity, pH, DO, temperature, and P and N were recorded for each site. The source-specific marker concentrations were determined by solid-phase extraction followed by gas-chromatography mass-spectrometry. Collection of this high dimensional data should allow us to better understand the occurrence of E. coli and source-specific markers in the creek.

Spearman correlations, multiple linear regressions and principal component analysis will be used to identify significant relationships and clusters within the data. Using these analyses, we will will examine the overall watershed along with each individual site. Spatial data including the location of septic tanks, sewer lines, and wastewater outfall will be integrated into our assessment of contamination source. We expect distinct signatures for each of the anthropogenic sources within the watershed which will advance our understanding of fecal contaminant tracing.