Explaining and modeling the concentration and loading of Escherichia coli in a stream—A case study

Abstract

Escherichia coli (E. coli) level in streams is a public health indicator. Therefore, being able to explain why E. coli levels are sometimes high and sometimes low is important. Using citizen science data from Fall Creek in central NY we found that complementarily using principal component analysis (PCA) and partial least squares (PLS) regression provided insights into the drivers of E. coli and a mechanism for predicting E. coli levels, respectively. We found that stormwater, temperature/season and shallow subsurface flow are the three dominant processes driving the fate and transport of E. coli. PLS regression modeling provided very good predictions under stormwater conditions (R = 0.85 for log (E. coli concentration) and R = 0.90 for log (E. coli loading)); predictions under baseflow conditions were less robust. But, in our case, both E. coli concentration and E. coli loading were significantly higher under stormwater condition, so it is probably more important to predict high-flow E. coli hazards than low-flow conditions. Besides previously reported good indicators of in-stream E. coli level, nitrate-/nitrite-nitrogen and soluble reactive phosphorus were also found to be good indicators of in-stream E. coli levels. These findings suggest management practices to reduce E. coli concentrations and loads in-streams and, eventually, reduce the risk of waterborne disease outbreak.

Factors influencing the persistence of enteropathogenic bacteria in wetland habitats and implications for water quality

“…Wang et al . (2018) conducted a study modelling the abundance of E. coli in stream environments and found that nitrate/nitrite and phosphorous were good indicators of in‐stream E. coli levels. The usefulness of increased phosphorus levels as an indicator of faecal coliform proliferation in water and wetland environments has previously been reported by Toothman et al .…”

Colloid transport through soil and other porous media under transient flow conditions—A review

“…Particles with an effective diameter of 1 nm to 10 μm are considered colloids (Chrysikopoulos & Sim, 1996; Gao, Cao, Dong, Luo, & Ma, 2011; Sirivithayapakorn & Keller, 2003a; Smith et al, 2007; Vasiliadou & Chrysikopoulos, 2011; Wan & Wilson, 1994b; Wang, Schneider, Parlange, Dahlke, & Walter, 2018). In the subsurface environment colloids comprise many naturally occurring substances including clays, metal oxides, mineral precipitates, and organic compounds as well as biological organisms such as pathogenic bacteria (Wang et al, 2017, 2018; Wang, Schneider, et al, 2018), viruses (Torkzaban, Hassanizadeh, Schijven, Bruijn, & Husman, 2006; Torkzaban, Hassanizadeh, Schijven, & van den Berg, 2006; Zhang, Hassanizadeh, Raoof, van Genuchten, & Roels, 2012), and protozoa (Bradford, Wang, Kim, Torkzaban, & Šimůnek, 2014; Sen, 2011). Many known environmental pollutants can attach to and move with colloids, a process referred to as colloid‐facilitated transport, which has been identified as one of the most important mechanisms responsible for the mobilization of reactive heavy metals in soils (Barton & Karathanasis, 2003; Gao et al, 2011; Grolimund & Borkovec, 2005; Kretzschmar & Schafer, 2005).…”

“…Particles with an effective diameter of 1 nm to 10 μm are considered colloids (Chrysikopoulos & Sim, 1996;Gao, Cao, Dong, Luo, & Ma, 2011;Sirivithayapakorn & Keller, 2003a;Smith et al, 2007;Vasiliadou & Chrysikopoulos, 2011;Wan & Wilson, 1994b;Wang, Schneider, Parlange, Dahlke, & Walter, 2018). In the subsurface environment colloids comprise many naturally occurring substances including clays, metal oxides, mineral precipitates, and organic compounds as well as biological organisms such as pathogenic bacteria (Wang et al, 2017, viruses (Torkzaban, Hassanizadeh, Schijven, Bruijn, & Husman, 2006;Torkzaban, Hassanizadeh, Schijven, & van den Berg, 2006;Zhang, Hassanizadeh, Raoof, van Genuchten, & Roels, 2012), and protozoa (Bradford, Wang, Kim, Torkzaban, & Šimu ˚nek, 2014;Sen, 2011).…”

Analysis of Escherichia coli and Enterococci Concentrations Patterns in a Pennsylvania Creek Using Empirical Orthogonal Functions

“…Many studies have explored the spatial and temporal variation of the microbial concentrations in freshwater sources and analyzed environmental factors that affect these variations. Wang et al (2018) found that stream flow conditions, temperature, and shallow subsurface flow were the dominant factors of temporal variation of the E. coli concentration in the stream. Tyner et al (2018) observed that distance from shore, wind speed, and recreational activity influenced spatial variation of the E. coli concentration in a lake.…”