Transport Of Fecal Indicator Bacteria Research Articles

Utilization of multiple microbial tools to evaluate efficacy of restoration strategies to improve recreational water quality at a Lake Michigan Beach (Racine, WI)

Hydro-meteorological conditions facilitate transport of fecal indicator bacteria (FIB) to the nearshore environment, affecting recreational water quality. North Beach (Racine, Wisconsin, United States), is an exemplar public beach site along Lake Michigan, where precipitation-mediated surface runoff, wave encroachment, stormwater and tributary outflow were demonstrated to contribute to beach advisories. Multiple restoration actions, including installation of a stormwater retention wetland, were successfully deployed to improve recreational water quality. Implementation of molecular methods (e.g. human microbial source tracking markers and Escherichia coli (E. coli) qPCR) assisted in identifying potential pollution sources and improving public health response time. However, periodic water quality failures still occur. As local beach managers reassess restoration measures in response to climatic changes, use of expanded microbial methods (including bacterial community profiling) may contribute to a better understanding of these dynamic environments. In this 2-year study (2015 and 2019), nearshore/offshore Lake Michigan, stormwater, and tributary samples were collected to determine if, 1) the constructed wetland (~50 m from the shoreline) continued to provide stormwater separation/retention and 2) mixing between onshore sources, Root River and Lake Michigan, was increasing due to rising precipitation/lake levels. Monthly rainfall totals were 1.5× higher in 2019 than 2015, coinciding with a 0.63 m lake-level rise. The prevalence of more intense, onshore winds also increased, facilitating interaction between potential reservoirs of FIB with nearshore water through wind driven waves and lake intrusion, e.g. beach sands and the adjacent Root River. While a strong relationship existed between wet weather wetland and North Beach nearshore E. coli concentrations (all sites), bacterial communities were strikingly different. Conversely, bacterial community overlap existed between the Root River mouth and nearshore/offshore sites. These results suggest the constructed wetland can accommodate the climate-related changes observed in this study. Future restoration activities could be directed towards upstream tributary sources in order to minimize microbial contaminants entering Lake Michigan.

Modeling the Impact of Land Use Change on Basin‐scale Transfer of Fecal Indicator Bacteria: SWAT Model Performance

Land use change from annual crops to commercial tree plantations can modify flow and transport processes at the watershed scale, including the fate and transport of fecal indicator bacteria (FIB), such as . The Soil and Water Assessment Tool (SWAT) is a useful means for integrating watershed characteristics and simulating water and contaminants. The objective of this study was to provide a comprehensive assessment of the impact of land use change on microbial transfer from soils to streams using the SWAT model. This study was conducted for the Houay Pano watershed located in northern Lao People's Democratic Republic. Under the observed weather conditions, the SWAT model predicted a decrease from 2011 to 2012 and an increase from 2012 to 2013 in surface runoff, suspended solids, and transferred from the soil surface to streams. The amount of precipitation was important in simulating surface runoff, and it subsequently affected the fate and transport of suspended solids and bacteria. In simulations of identical weather conditions and different land uses, fate and transport was more sensitive to the initial number of than to its drivers (i.e., surface runoff and suspended solids), and leaf area index was a significant factor influencing the determination of the initial number of on the soil surface. On the basis of these findings, this study identifies several limitations of the SWAT fertilizer and bacteria modules and suggests measures to improve our understanding of the impacts of land use change on FIB in tropical watersheds.

Effect of Low Energy Waves on the Accumulation and Transport of Fecal Indicator Bacteria in Sand and Pore Water at Freshwater Beaches

Elevated fecal indicator bacteria (FIB) in beach sand and pore water represent an important nonpoint source of contamination to surface waters. This study examines the physical processes governing the accumulation and distribution of FIB in a beach aquifer. Field data indicate E. coli and enterococci can be transported 1 and 2 m, respectively, below the water table. Data were used to calibrate a numerical model whereby FIB are delivered to a beach aquifer by wave-induced infiltration across the beach face. Simulations indicate FIB rapidly accumulate in a beach aquifer with FIB primarily associated with sand rather than freely residing in the pore water. Simulated transport of E. coli in a beach aquifer is complex and does not correlate with conservative tracer transport. Beaches with higher wave-induced infiltration rate and vertical infiltration velocity (i.e., beaches with higher beach slope and wave height, and lower terrestrial groundwater discharge) had greater E. coli accumulation and E. coli was transported deeper below the beach face. For certain beach conditions, the amount of FIB accumulated in sand over 5-6 days was found to be sufficient to trigger a beach advisory if eroded to surface water.

Storm loads of culturable and molecular fecal indicators in an inland urban stream

Elevated concentrations of fecal indicator bacteria in receiving waters during wet-weather flows are a considerable public health concern that is likely to be exacerbated by future climate change and urbanization. Knowledge of factors driving the fate and transport of fecal indicator bacteria in stormwater is limited, and even less is known about molecular fecal indicators, which may eventually supplant traditional culturable indicators. In this study, concentrations and loading rates of both culturable and molecular fecal indicators were quantified throughout six storm events in an instrumented inland urban stream. While both concentrations and loading rates of each fecal indicator increased rapidly during the rising limb of the storm hydrographs, it is the loading rates rather than instantaneous concentrations that provide a better estimate of transport through the stream during the entire storm. Concentrations of general fecal indicators (both culturable and molecular) correlated most highly with each other during storm events but not with the human-associated HF183 Bacteroides marker. Event loads of general fecal indicators most strongly correlated with total runoff volume, maximum discharge, and maximum turbidity, while event loads of HF183 most strongly correlated with the time to peak flow in a hydrograph. These observations suggest that collection of multiple samples during a storm event is critical for accurate predictions of fecal indicator loading rates and total loads during wet-weather flows, which are required for effective watershed management. In addition, existing predictive models based on general fecal indicators may not be sufficient to predict source-specific genetic markers of fecal contamination.

Hydrometeorological and physicochemical drivers of fecal indicator bacteria in urban stream bottom sediments.

High levels of fecal indicator bacteria (FIB) are the leading cause of surface water quality impairments in the United States. Watershed-scale models are commonly used to identify relative contributions of watershed sources and to evaluate the effectiveness of remediation strategies. However, most existing models simplify FIB transport behavior as equivalent to that of dissolved-phase contaminants, ignoring the impacts of sediment on the fate and transport of FIB. Implementation of sediment-related processes within existing models is limited by minimal available monitoring data on sediment FIB concentrations for model development, calibration, and validation purposes. The purpose of the present study is to evaluate FIB levels in the streambed sediments as compared to those in the water column and to identify environmental variables that influence water and underlying sediment FIB levels. Concentrations of and enterococci in the water column and sediments of an urban stream were monitored weekly for 1 yr and correlated with a variety of potential hydrometeorological and physicochemical variables. Increased FIB concentrations in both the water column and sediments were most strongly correlated with increased antecedent 24-h rainfall, increased stream water temperature, decreased dissolved oxygen, and decreased specific conductivity. These observations will support future efforts to incorporate sediment-related processes in existing models through the identification of key FIB relationships with other model inputs, and the provision of sediment FIB concentrations for direct model calibration. In addition, identified key variables can be used in quick evaluation of the effectiveness of potential remediation strategies.

Comparison of numerical schemes for improved prediction model of fecal indicator bacteria in a riverine system

ABSTRACT Different numerical schemes for the fate and transport models of fecal indicator bacteria (FIB) were used to predict the concentration of FIB in a creek, which were then compared to a steady state model (QUAL2E). Escherichia coli (EC) and enterococci bacteria (ENT) were selected as representative FIB to compare the model performance under different flow and weather conditions in the Gwangju Creek in Korea. The results revealed that model accuracy of the forward time centered space (FTCS) scheme is the highest compared to the upstream, Dufort-Frankel, Crank-Nicolson methods and steady state model (QUAL2E) under dry weather conditions. In wet weather conditions, however, the upstream scheme shows the best performance among the five models. The upstream scheme thus represented a potential method for predicting the fate and transport of FIB originating from nonpoint sources during the rainy season. This study demonstrates that prediction results could vary in response to different numerical schemes a...