Human, Swine Waste Pose Dual Threats to Water Quality After Flooding
For Immediate Release
A study that monitored surface waters in the wake of 2018’s Hurricane Florence finds that waters contaminated by fecal bacteria were affected by both human and swine waste.
“We found that surface waters in eastern North Carolina were more likely to face dual contamination than to be contaminated by either human waste or swine waste by themselves,” says Angela Harris, corresponding author of the study and an assistant professor of civil, construction and environmental engineering at North Carolina State University.
“This means people are dealing with multiple hazards,” Harris says. “It also means there are two sources of fecal contamination that need to be addressed. It’s not just the swine industry, and it’s not just wastewater treatment plants or septic systems.”
For the study, researchers collected surface water samples at 40 sites across eastern N.C. Samples were collected one week after Hurricane Florence made landfall in September 2018, and again one month after landfall. These samples are referred to as Phase 1 and Phase 2, respectively.
The researchers tested the water samples for a variety of bacteria. Specifically, the samples were tested for: E. coli – an indicator species used to identify fecal contamination and the likelihood that there are pathogens present; pathogens such as Arcobacter butzleri and various Listeria species; and bacterial species associated specifically with either swine or humans, so that researchers could trace contamination back to its source.
“About 30% of the surface water sites we tested had levels of bacteria that would have made those waters unsafe for swimming,” Harris said.
The most commonly found pathogen was Arcobacter, a finding the research team published late last year. The new study reports that the presence of Arcobacter wasn’t associated with human or swine fecal markers. In other words, it’s not clear where the pathogen is coming from.
Another mystery was that the levels of E. coli in Phase 2 samples taken from permanent water channels (as opposed to floodplains) were actually higher than the levels of E. coli in the Phase 1 samples.
“We’re not sure why E. coli levels jumped in those Phase 2 samples,” Harris says. “It could be because water levels were decreasing, so there was less dilution. It could be due to temporary changes in regulatory requirements in the wake of the hurricane. It could be some other variable we haven’t identified. We need a lot more monitoring data to begin to tease that apart.
“A lot of post-flooding work has been done in urban areas,” Harris says. “This is one of the few studies that looks at post-flooding water quality impacts in rural, agricultural areas. And our findings suggest that this merits a much closer look. This work highlights the need for more routine water quality monitoring in these areas that tests for the bacteria we were looking at here. That could help us establish broader baseline measures for water quality.
“This is particularly important given concerns around antibiotic-resistant pathogens and the likelihood that we’ll be seeing more extreme wet weather events in the future.”
The study, “Microbial Contamination in Environmental Waters of Rural and Agriculturally-Dominated Landscapes Following Hurricane Florence,” is published in the journal ACS ES&T Water. The paper was co-authored by Emine Fidan, a Ph.D. student at NC State; Natalie Nelson and Mahmoud Sharara, assistant professors of biological and agricultural engineering at NC State; Ryan Emanuel, a professor of environmental resources at NC State; Theo Jass and Jeffrey Niedermeyer, former research assistants at NC State; Sophia Kathariou, professor of food, bioprocessing and nutrition sciences at NC State; Francis de los Reyes III, professor of civil, construction and environmental engineering at NC State; and Diego A. Riveros-Iregui and Jill R. Stewart of the University of North Carolina at Chapel Hill.
The study was done with support from the National Science Foundation, under grants 1901588 and 1901202; the North Carolina Policy Collaboratory; and the Institute for the Advancement of Food and Nutrition Sciences through an International Life Sciences Institute North America grant.
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Note to Editors: The study abstract follows.
“Microbial Contamination in Environmental Waters of Rural and Agriculturally-Dominated Landscapes Following Hurricane Florence”
Authors: Angela R. Harris, Emine N. Fidan, Natalie Nelson, Ryan Emanuel, Theo Jass, Sophia Kathariou, Jeffrey Niedermeyer, Mahmoud Sharara and Francis Lajara de los Reyes III, North Carolina State University; Diego A. Riveros-Iregui and Jill R. Stewart, University of North Carolina at Chapel Hill
Published: Aug. 23, ACS ES&T Water
DOI: 10.1021/acsestwater.1c00103
Abstract: Hurricane Florence brought unprecedented rainfall and flooding to Eastern North Carolina in 2018. Extensive flooding had the potential to mobilize microbial contaminants from a variety of sources. Our study evaluated microbial contaminants in surface waters at 40 sites across Eastern North Carolina one week after the hurricane made landfall (Phase 1) and one month later (Phase 2). High concentrations of Escherichia coli were detected in flowing channel and floodwater samples across both phases; however, channel samples during Phase 2 had higher concentrations of E. coli compared to Phase 1. Human- and swine-associated fecal markers were detected in 26% and 9% of samples, respectively, with no trends related to phase of sampling. Arcobacter butzleri, previously shown to be recovered from most (73%) samples, and detection of this pathogen was not associated with any source-associated fecal marker. Detection of Listeria spp. was associated with the swine-associated fecal marker. These results suggest that improved swine and human feces management should be explored to prevent microbial contamination in surface water, especially in regions where extreme rainfall may increase due to climate change. Sampling at higher frequency surrounding rainfall events would provide more detailed characterization of the risks posed by floodwater at different time scales and under different antecedent conditions.
