Rainfall-driven E. coli transfer to the stream-conduit network observed through increasing spatial scales in mixed land-use paddy farming karst terrain

Karst aquifers have distinctive hydrology and supply 25% of the world's population with drinking water, making them a critical geological setting for understanding and managing microbial water pollution. Rainfall causes elevated concentrations and loading of faecal microorganisms, e.g. E. coli, in catchment surface and groundwater systems, increasing the risk of human exposure to faecally-contaminated water. However, effective management of microbial water quality in complex karst catchments is constrained by limited understanding of E. coli - discharge responses to rainfall. We analysed how rainfall events of varying magnitude (2.4-100 mm) control E. coli-discharge dynamics at increasing spatial scales in a mixed land-use karst catchment in southwest China. During the wet season, hourly water sampling was undertaken throughout five storm events to characterise in high detail E. coli emergence with resulting flow across multiple sites of varying catchment area, stream order, and land-use. E. coli concentration was found to increase by 1-3 orders of magnitude following rainfall events. Maximum E. coli concentration and speed of E. coli recession were influenced by rainfall (amount, intensity), timing of agricultural activities, and position in the hydrological system. For high intensity events ∼90% of the cumulative E. coli export occurred within 48 h. E. coli concentration increased with increasing discharge at all sites. E. coli concentration at low discharge was higher in the headwaters than at the catchment outlet, while the rate of increase in E. coli concentration with increasing discharge appears to follow the opposite trend, being higher at the catchment outlet than the headwaters. This was attributed to the decreasing flow path gradient and increasing degree of development of the fissure network, but further event monitoring at varying catchment scales is required to confirm this relationship. The results provide novel insight into how rainfall characteristics combine with land-use and catchment hydrology to control E. coli export in karst landscapes.

High resolution characterisation of E. coli proliferation profiles in livestock faeces

Agricultural intensification can lead to high volumes of livestock faeces being applied to land, either as solid or liquid manures or via direct defecation, and can result in reservoirs of faecal indicator organisms (FIOs) persisting within farmland. Understanding the survival of FIOs, e.g. E. coli, in agricultural environments, and in particular within different livestock faeces, is key to developing catchment management practices for the protection of ecosystem services provided by clean water. Frequently, controlled laboratory studies, under constant temperature regimes, are used to determine the impact of environmental factors on E. coli persistence in livestock faeces; however, such studies oversimplify the diurnal variations and interactions of real world conditions. The aim of this study was to investigate the survival of E. coli using a controlled environment facility, which simulated diurnal variation of temperatures typically experienced during a British spring and summer. The approach provided a comparison of E. coli persistence profiles within faeces of sheep, beef cattle and dairy cattle to allow novel interpretations of E. coli regrowth patterns in contrasting livestock faeces in the period immediately post-defecation. Thus, the coupling of a tightly controlled environment facility with high resolution monitoring enabled the development of a new non-linear, asymptotic description of E. coli proliferation in livestock faeces, with increased potential for E. coli growth observed during warmer temperatures for all livestock types. While this study focused on temperatures typical of the UK, the occurrence of a phase of E. coli regrowth has implications for microbial water quality management worldwide.

Turbidity composition and the relationship with microbial attachment and UV inactivation efficacy

Turbidity in water can be caused by a range of different turbidity causing materials (TCM). Here the characteristics and attachment of bacteria to TCMs was assessed and the resultant impact on UV disinfection determined. TCMs represent potential vehicles for bacterial penetration of water treatment barriers, contamination of potable supplies and impact on subsequent human health. The TCMs under investigation were representative of those that may be present in surface and ground waters, both from the source and formed in the treatment process. The TCMs were chalk, Fe (III) hydroxide precipitate, kaolin clay, manganese dioxide and humic acids, at different turbidity levels representative of source waters (0, 0.1, 0.2, 0.4, 1, 2, and 5 NTU). Escherichia coli and Enterococcus faecalis attachment followed the order of Fe(III)>chalk, with little to no attachment seen for MnO₂, humic acids and clay. The attachment was postulated to be due to chalk and Fe(III) particles having a more neutral surface charge resulting in elevated aggregation with bacteria compared to other TCMs. The humic acids and Fe(III) were the TCMs which influenced inactivation of E. coli and E. faecalis due to decreasing UV transmittance (UVT) with increasing TCM concentration. The presence of the Fe(III) TCM at 0.2 NTU resulted in the poorest E. coli inactivation, with 2.5 log₁₀ reduction at UV dose of 10mJcm^-2 (k_d of -0.23cm²mJ^-1) compared to a 3.9 log₁₀ reduction in the absence of TCMs. E. faecalis had a greater resistance to UV irradiation than E. coli for all TCMs. Effective disinfection of drinking water is a priority for ensuring high public health standards. Uniform regulations for turbidity levels for waters pre-disinfection by UV light set by regulators may not always be appropriate and efficacy is dependent on the type, as well as the amount, of turbidity present in the water.

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

Effective management of diffuse microbial water pollution from agriculture requires a fundamental understanding of how spatial patterns of microbial pollutants, e.g. E. coli, vary over time at the landscape scale. The aim of this study was to apply the Visualising Pathogen &Environmental Risk (ViPER) model, developed to predict E. coli burden on agricultural land, in a spatially distributed manner to two contrasting catchments in order to map and understand changes in E. coli burden contributed to land from grazing livestock. The model was applied to the River Ayr and Lunan Water catchments, with significant correlations observed between area of improved grassland and the maximum total E. coli per 1km² grid cell (Ayr: r=0.57; p<0.001, Lunan: r=0.32; p<0.001). There was a significant difference in the predicted maximum E. coli burden between seasons in both catchments, with summer and autumn predicted to accrue higher E. coli contributions relative to spring and winter (P<0.001), driven largely by livestock presence. The ViPER model thus describes, at the landscape scale, spatial nuances in the vulnerability of E. coli loading to land as driven by stocking density and livestock grazing regimes. Resulting risk maps therefore provide the underpinning evidence to inform spatially-targeted decision-making with respect to managing sources of E. coli in agricultural environments.

Using spatial-stream-network models and long-term data to understand and predict dynamics of faecal contamination in a mixed land-use catchment

An 11year dataset of concentrations of E. coli at 10 spatially-distributed sites in a mixed land-use catchment in NE Scotland (52km²) revealed that concentrations were not clearly associated with flow or season. The lack of a clear flow-concentration relationship may have been due to greater water fluxes from less-contaminated headwaters during high flows diluting downstream concentrations, the importance of persistent point sources of E. coli both anthropogenic and agricultural, and possibly the temporal resolution of the dataset. Point sources and year-round grazing of livestock probably obscured clear seasonality in concentrations. Multiple linear regression models identified potential for contamination by anthropogenic point sources as a significant predictor of long-term spatial patterns of low, average and high concentrations of E. coli. Neither arable nor pasture land was significant, even when accounting for hydrological connectivity with a topographic-index method. However, this may have reflected coarse-scale land-cover data inadequately representing "point sources" of agricultural contamination (e.g. direct defecation of livestock into the stream) and temporal changes in availability of E. coli from diffuse sources. Spatial-stream-network models (SSNMs) were applied in a novel context, and had value in making more robust catchment-scale predictions of concentrations of E. coli with estimates of uncertainty, and in enabling identification of potential "hot spots" of faecal contamination. Successfully managing faecal contamination of surface waters is vital for safeguarding public health. Our finding that concentrations of E. coli could not clearly be associated with flow or season may suggest that management strategies should not necessarily target only high flow events or summer when faecal contamination risk is often assumed to be greatest. Furthermore, we identified SSNMs as valuable tools for identifying possible "hot spots" of contamination which could be targeted for management, and for highlighting areas where additional monitoring could help better constrain predictions relating to faecal contamination.

Predicting diffuse microbial pollution risk across catchments: The performance of SCIMAP and recommendations for future development

Microbial pollution of surface waters in agricultural catchments can be a consequence of poor farm management practices, such as excessive stocking of livestock on vulnerable land or inappropriate handling of manures and slurries. Catchment interventions such as fencing of watercourses, streamside buffer strips and constructed wetlands have the potential to reduce faecal pollution of watercourses. However these interventions are expensive and occupy valuable productive land. There is, therefore, a requirement for tools to assist in the spatial targeting of such interventions to areas where they will have the biggest impact on water quality improvements whist occupying the minimal amount of productive land. SCIMAP is a risk-based model that has been developed for this purpose but with a focus on diffuse sediment and nutrient pollution. In this study we investigated the performance of SCIMAP in predicting microbial pollution of watercourses and assessed modelled outputs of E. coli, a common faecal indicator organism (FIO), against observed water quality information. SCIMAP was applied to two river catchments in the UK. SCIMAP uses land cover risk weightings, which are routed through the landscape based on hydrological connectivity to generate catchment scale maps of relative in-stream pollution risk. Assessment of the model's performance and derivation of optimum land cover risk weightings was achieved using a Monte-Carlo sampling approach. Performance of the SCIMAP framework for informing on FIO risk was variable with better performance in the Yealm catchment (r_s=0.88; p<0.01) than the Wyre (r_s=-0.36; p>0.05). Across both catchments much uncertainty was associated with the application of optimum risk weightings attributed to different land use classes. Overall, SCIMAP showed potential as a useful tool in the spatial targeting of FIO diffuse pollution management strategies; however, improvements are required to transition the existing SCIMAP framework to a robust FIO risk-mapping tool.

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.

Opportunities and limitations of molecular methods for quantifying microbial compliance parameters in EU bathing waters

The debate over the suitability of molecular biological methods for the enumeration of regulatory microbial parameters (e.g. Faecal Indicator Organisms [FIOs]) in bathing waters versus the use of traditional culture-based methods is of current interest to regulators and the science community. Culture-based methods require a 24-48hour turn-around time from receipt at the laboratory to reporting, whilst quantitative molecular tools provide a more rapid assay (approximately 2-3h). Traditional culturing methods are therefore often viewed as slow and 'out-dated', although they still deliver an internationally 'accepted' evidence-base. In contrast, molecular tools have the potential for rapid analysis and their operational utility and associated limitations and uncertainties should be assessed in light of their use for regulatory monitoring. Here we report on the recommendations from a series of international workshops, chaired by a UK Working Group (WG) comprised of scientists, regulators, policy makers and other stakeholders, which explored and interrogated both molecular (principally quantitative polymerase chain reaction [qPCR]) and culture-based tools for FIO monitoring under the European Bathing Water Directive. Through detailed analysis of policy implications, regulatory barriers, stakeholder engagement, and the needs of the end-user, the WG identified a series of key concerns that require critical appraisal before a potential shift from culture-based approaches to the employment of molecular biological methods for bathing water regulation could be justified.