A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock

Forecasting acute rainfall driven E. coli impacts in inland rivers based on sewer monitoring and field runoff

Surface water quality is frequently impacted by acute rainfall driven pollutant sources such as sewer overflows. Understanding the risk of exposure from faecal pollution from short term impacts is challenging due to a paucity of high-resolution data from river systems. This paper proposes practical modelling approach for forecasting arrival time and durations of elevated E. coli levels based on hydrological routing of catchment source loadings, characterized by distributed and remote sensing techniques (including sewer overflow monitoring). The model is calibrated and validated using new high resolution E. coli datasets from a UK catchment featuring both diffuse field runoff and storm overflow impacts. Hourly/Bihourly sampling of E. coli was undertaken in the river following different rainfall events across a range of seasonal conditions. The model provides a good estimate of arrival times and durations of elevated E. coli periods following rainfall events. Model simulations suggest that key sources in the catchment are event specific, with sewer overflow spills being more significant following short, intense rainfall events.

Persistence of E. coli in Streambed Sediment Contaminated with Faeces from Dairy Cows, Geese, and Deer: Legacy Risks to Environment and Health

Legacy stores of faecal pollution in streambed sediments can result in delayed impacts on environmental quality and human health if resuspended into the overlying water column. Different catchment sources of faecal pollution can contribute to a legacy store of microbial pollutants, with size of stores influenced by microbial die-off and faecal accrual rates in the streambed. The aim of this study was to use a mesocosm experiment to characterise the persistence of E. coli derived from faeces of dairy cows, deer, and geese once introduced to streambed sediment under different temperature regimes. The settling rate of solid constituents of faecal material into streambed sediment once delivered into an aquatic environment was also quantified. The persistence patterns of E. coli in streambed sediment were found to vary as a function of faecal source and temperature; die-off of E. coli in sediment contaminated with goose faeces was more rapid than in sediments contaminated with dairy cow or deer faeces. Goose faeces also recorded a more rapid settling rate of faecal particles through the water column relative to dairy cow and deer faeces, suggesting a more efficient delivery of E. coli to streambed sediments associated with this faecal source. Our findings provide new evidence to improve understanding of the potential longer-term risks to both the environment and public health posed by sediments when contaminated with livestock, wildlife, and wildfowl faeces.

Escherichia coli runoff from sheep and dairy cow grazed pasture: A plot scale simulation

Animal agriculture is recognized as a key source of fecal microbial impacts on water quality and associated risks to human health. Most of the research effort has focused on losses of fecal microbes from cow/cattle feces with little research effort on sheep fecal risks. The literature on fecal microbial risks from pasture is complicated by the fact that experiments are carried out in different environments leading to difficulties in making direct comparisons between sheep and cow/cattle losses from pasture areas. In this study, a plot scale simulation was conducted on the same pasture plots, using simulated rainfall to generate comparable runoff conditions, and using simulated grazing to create similar relative stocking rates. The Escherichia coli concentrations in the runoff were similar from simulated or natural rainfall events. At an equivalent stocking rate, the E. coli runoff concentrations from the sheep grazed pastures were four times higher than the cow grazed pasture. These results show that at an equivalent stocking rate, the E. coli runoff risk from sheep grazed pasture is higher than for cow grazed pasture. Further research is needed to understand the relative impacts of different grazing species of animals as well as stocking rate or management effects on these relative risks to water quality.

Mobilization of Escherichia coli and fecal source markers from decomposing cowpats

In rural environments, the sources of fecal contamination in freshwater environments are often diffuse and a mix of fresh and aged fecal sources. It is important for water monitoring purposes, therefore, to understand the impacts of weathering on detection of the fecal source markers available for mobilization from livestock sources. This study targets the impacts of rainfall events on the mobilization of fecal source tracking (FST) markers from simulated cowpats decomposing in situ for five-and-a-half-months. The FST markers analysed were Escherichia coli, microbial source tracking (MST) markers, fecal steroids and a fecal ageing ratio based on the ratio between counts of river microflora and total coliforms. There was a substantial concentration of E. coli (10⁴/100 mL) released from the ageing cowpats suggesting a long-term reservoir of E. coli in the cowpat. Mobilization of fecal markers from rainfall-impacted cowpats, however, was markedly reduced compared with fecal markers in the cowpat. Overall, the Bacteroidales bovine-associated MST markers were less persistent than E. coli in the cowpat and rainfall runoff. The ten fecal steroids, including the major herbivore steroid, 24-ethylcoprostanol, are shown to be stable markers of bovine pollution due to statistically similar degradation rates among all steroids. The mobilizable fraction for each FST marker in the rainfall runoff allowed generation of mobilization decline curves and the derived decline rate constants can be incorporated into source attribution models for agricultural contaminants. Findings from this study of aged bovine pollution sources will enable water managers to improve attribution of elevated E. coli to the appropriate fecal source in rural environments.

Time since faecal deposition influences mobilisation of culturable E. coli and intestinal enterococci from deer, goose and dairy cow faeces

Mobilisation is a term used to describe the supply of a pollutant from its environmental source, e.g., soil or faeces, into a hydrological transfer pathway. The overarching aim of this study was to determine, using a laboratory-based approach, whether faecal indicator bacteria (FIB) are hydrologically mobilised in different quantities from a typical agricultural, wildlife and wildfowl source, namely dairy cattle, red deer and greylag goose faeces. The mobilisation of FIB from fresh and ageing faeces under two contrasting temperatures was determined, with significant differences in the concentrations of both E. coli and intestinal enterococci lost from all faecal sources. FIB mobilisation from these faecal matrices followed the order of dairy cow > goose > deer (greatest to least, expressed as a proportion of the total FIB present). Significant changes in mobilisation rates from faecal sources over time were also recorded and this was influenced by the temperature at which the faecal material had aged over the course of the 12-day study. Characterising how indicators of waterborne pathogens are mobilised in the environment is of fundamental importance to inform models and risk assessments and develop effective strategies for reducing microbial pollution in catchment drainage waters and associated downstream impacts. Our findings add quantitative evidence to support the understanding of FIB mobilisation potential from three important faecal sources in the environment.

Integrative Survey of 68 Non-overlapping Upstate New York Watersheds Reveals Stream Features Associated With Aquatic Fecal Contamination

Aquatic fecal contamination poses human health risks by introducing pathogens in water that may be used for recreation, consumption, or agriculture. Identifying fecal contaminant sources, as well as the factors that affect their transport, storage, and decay, is essential for protecting human health. However, identifying these factors is often difficult when using fecal indicator bacteria (FIB) because FIB levels in surface water are often the product of multiple contaminant sources. In contrast, microbial source-tracking (MST) techniques allow not only the identification of predominant contaminant sources but also the quantification of factors affecting the transport, storage, and decay of fecal contaminants from specific hosts. We visited 68 streams in the Finger Lakes region of Upstate New York, United States, between April and October 2018 and collected water quality data (i.e., Escherichia coli, MST markers, and physical–chemical parameters) and weather and land-use data, as well as data on other stream features (e.g., stream bed composition), to identify factors that were associated with fecal contamination at a regional scale. We then applied both generalized linear mixed models and conditional inference trees to identify factors and combinations of factors that were significantly associated with human and ruminant fecal contamination. We found that human contaminants were more likely to be identified when the developed area within the 60 m stream buffer exceeded 3.4%, the total developed area in the watershed exceeded 41%, or if stormwater outfalls were present immediately upstream of the sampling site. When these features were not present, human MST markers were more likely to be found when rainfall during the preceding day exceeded 1.5 cm. The presence of upstream campgrounds was also significantly associated with human MST marker detection. In addition to rainfall and water quality parameters associated with rainfall (e.g., turbidity), the minimum distance to upstream cattle operations, the proportion of the 60 m buffer used for cropland, and the presence of submerged aquatic vegetation at the sampling site were all associated based on univariable regression with elevated levels of ruminant markers. The identification of specific features associated with host-specific fecal contaminants may support the development of broader recommendations or policies aimed at reducing levels of aquatic fecal contamination.

Chronic urban hotspots and agricultural drainage drive microbial pollution of karst water resources in rural developing regions

Contamination of surface and groundwater systems with human and animal faecal matter leads to exposure of reliant populations to disease causing micro-organisms. This exposure route remains a major cause of infection and mortality in developing countries, particularly rural regions. To meet the UN's sustainable development goal 6: Ensure availability and sustainable management of water and sanitation for all, we need to identify the key controls on faecal contamination across relevant settings. We conducted a high-resolution spatial study of E. coli concentration in catchment drainage waters over 6 months in a mixed land-use catchment in the extensive karst region extending across impoverished southwest China. Using a mixed effects modelling framework, we tested how land-use, karst hydrology, antecedent meteorological conditions, agricultural cycles, hydrochemistry, and position in the catchment system affected E. coli concentrations. Land-use was the best predictor of faecal contamination levels. Sites in urban areas were chronically highly contaminated, but water draining from agricultural land was also consistently contaminated and there was a catchment wide pulse of higher E. coli concentrations, turbidity, and discharge during paddy field drainage. E. coli concentration increased with increasing antecedent rainfall across all land-use types and compartments of the karst hydrological system (underground and surface waters), but decreased with increasing pH. This is interpreted to be a result of processes affecting pH, such as water residence time, rather than the direct effect of pH on E. coli survival. Improved containment and treatment of human waste in areas of higher population density would likely reduce contamination hotspots, and further research is needed to identify the nature and distribution of sources in agricultural land.

Impact of Freeze-Thaw Cycles on Die-Off of E. coli and Intestinal Enterococci in Deer and Dairy Faeces: Implications for Landscape Contamination of Watercourses

Characterising faecal indicator organism (FIO) survival in the environment is important for informing land management and minimising public health risk to downstream water users. However, key gaps in knowledge include understanding how wildlife contribute to catchment-wide FIO sources and how FIO survival is affected by low environmental temperatures. The aim of this study was to quantify E. coli and intestinal enterococci die-off in dairy cow versus red deer faecal sources exposed to repeated freeze–thaw cycles under controlled laboratory conditions. Survival of FIOs in water exposed to freeze–thaw was also investigated to help interpret survival responses. Both E. coli and intestinal enterococci were capable of surviving sub-freezing conditions with the faeces from both animals able to sustain relatively high FIO concentrations, as indicated by modelling, and observations revealing persistence in excess of 11 days and in some cases confirmed beyond 22 days. Die-off responses of deer-derived FIOs in both faeces and water exposed to low temperatures provide much needed information to enable better accounting of the varied catchment sources of faecal pollution and results from this study help constrain the parameterisation of die-off coefficients to better inform more integrated modelling and decision-making for microbial water quality management.

An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 1: Background and model description

A new Model for the Agent-based simulation of Faecal Indicator Organisms (MAFIO) is developed that attempts to overcome limitations in existing faecal indicator organism (FIO) models arising from coarse spatial discretisations and poorly-constrained hydrological processes. MAFIO is a spatially-distributed, process-based model presently designed to simulate the fate and transport of agents representing FIOs shed by livestock at the sub-field scale in small (<10 km²) agricultural catchments. Specifically, FIO loading, die-off, detachment, surface routing, seepage and channel routing are modelled on a regular spatial grid. Central to MAFIO is that hydrological transfer mechanisms are simulated based on a hydrological environment generated by an external model for which it is possible to robustly determine the accuracy of simulated catchment hydrological functioning. The spatially-distributed, tracer-aided ecohydrological model EcH₂O-iso is highlighted as a possible hydrological environment generator. The present paper provides a rationale for and description of MAFIO, whilst a companion paper applies the model in a small agricultural catchment in Scotland to provide a proof-of-concept.

An agent-based model that simulates the spatio-temporal dynamics of sources and transfer mechanisms contributing faecal indicator organisms to streams. Part 2: Application to a small agricultural catchment

The new Model for the Agent-based simulation of Faecal Indicator Organisms (MAFIO) is applied to a small (0.42 km²) Scottish agricultural catchment to simulate the dynamics of E. coli arising from sheep and cattle farming, in order to provide a proof-of-concept. The hydrological environment for MAFIO was simulated by the "best" ensemble run of the tracer-aided ecohydrological model EcH₂O-iso, obtained through multi-criteria calibration to stream discharge (MAE: 1.37 L s^-1) and spatially-distributed stable isotope data (MAE: 1.14-3.02‰) for the period April-December 2017. MAFIO was then applied for the period June-August for which twice-weekly E. coli loads were quantified at up to three sites along the stream. Performance in simulating these data suggested the model has skill in capturing the transfer of faecal indicator organisms (FIOs) from livestock to streams via the processes of direct deposition, transport in overland flow and seepage from areas of degraded soil. Furthermore, its agent-based structure allowed source areas, transfer mechanisms and host animals contributing FIOs to the stream to be quantified. Such information is likely to have substantial value in the context of designing and spatially-targeting mitigation measures against impaired microbial water quality. This study also revealed, however, that avenues exist for improving process conceptualisation in MAFIO (e.g. to include FIO contributions from wildlife) and highlighted the need to quantitatively assess how uncertainty in the spatial extent of surface flow paths in the simulated hydrological environment may affect FIO simulations. Despite the consequent status of MAFIO as a research-level model, its encouraging performance in this proof-of-concept study suggests the model has significant potential for eventual incorporation into decision support frameworks.