The use of sterol profiles, supported with other faecal source tracking methods, to apportion septic tanks contamination in rural catchments.

Identifying the origin of faecal pollution in water is needed for effective water management decisions to protect both human health and aquatic ecosystems. Traditionally used indicators of faecal contamination, such as E. coli, only indicate pollution from warm-blooded animals and not the specific source of contamination; hence, more source specific tracers are required. The study has focussed on separating the two main sources of contaminants within rural catchments in Ireland, agriculture and on-site wastewater treatment systems (predominantly septic tanks). While human-specific effluent tracers may assist in identifying potential pathways from individual septic tanks to surface waters, it is difficult to quantify the cumulative impact of such systems at a catchment scale. This study has investigated faecal sterols as a method to quantify such an impact on four small catchments in areas of low subsoil permeability with high densities of septic tanks. The results demonstrate the usefulness of faecal sterols which provide a quantitative evaluation of the respective impact between agricultural pasture inputs and on-site effluent showing differences between the four catchments. The study also highlights the need to derive more specific local reference sterol profile databases for specific countries or regions, using local source material of animal faeces and effluent. Two intensive sampling campaigns on the four catchments then used faecal sterols in parallel to fluorescent whitening compounds (FWCs), caffeine, artificial sweeteners and selected pharmaceuticals to gain further insights and confirmation about contamination hotspots as well as providing comparison between the different parameters. The combination of sterols, FWCs, caffeine, acesulfame and cyclamate has proven suitable to provide an estimate of the extent of human contamination in these rural catchments and has yielded additional information about potential pollution pathways and proximity of contamination. Overall, this methodology can help to facilitate a targeted and effective water management in such catchments.

Patterns of cyanobacterial abundance in a major drinking water reservoir: what 3 years of comprehensive monitoring data reveals?

The present study provides a detailed analysis of the factors influencing variation in cyanobacterial communities of a large shallow off-river drinking water reservoir on the east coast of Australia. Receiving multiple inflows from two unprotected mixed land-use catchments, the Grahamstown Reservoir is a model example of a reservoir which is highly vulnerable to adverse water quality issues, including phytoplankton blooms and the resulting filtration, toxin and taste and odour problems produced. The spatial and temporal distributions of cyanobacteria were assessed for a period of 3 years (January 2012-December 2014) based on samples collected from three monitoring stations within the reservoir. Relationships between cyanobacterial abundance and a range of environmental factors were evaluated by application of multivariate curve resolution-alternating least squares (MCR-ALS) analysis.Results of the analysis indicated that among the 22 physico-chemical variables and 14 cyanobacterial taxa measured, the vertical temperature gradient within the water column and nutrient availability were the most powerful explanatory factors for the observed temporal and spatial distribution patterns in the densities of cyanobacterial taxa. The abundance patterns of the dominant cyanobacterial taxa-Aphanocapsa, Aphanothece, Microcystis and Pseudanabaena-were strongly linked with rainfall and run-off patterns into the reservoir, while Coelosphaerium and Microcystis were the taxa most influenced by the apparent occurrence of thermal stratification. The findings demonstrate the capacity of rigorous multivariate data analysis to identify more subtle relationships between water quality variables, catchment factors and cyanobacterial growth in drinking water reservoirs.

Contamination of estuaries from failing septic tank systems: difficulties in scaling up from monitored individual systems to cumulative impact.

Aquaculture in many coastal estuaries is threatened by diffuse sources of runoff from different land use activities. The poor performance of septic tank systems (STS), as well as runoff from agriculture, may contribute to the movement of contaminants through ground and surface waters to estuaries resulting in oyster contamination, and following their consumption, impacts to human health. In monitoring individual STS in sensitive locations, it is possible to show that nutrients and faecal contaminants are transported through the subsurface in sandy soils off-site with little attenuation. At the catchment scale however, there are always difficulties in discerning direct linkages between failing STS and water contamination due to processes such as effluent dilution, adsorption, precipitation and vegetative uptake. There is often substantial complexity in detecting and tracing effluent pathways from diffuse sources to water bodies in field studies. While source tracking as well as monitoring using tracers may assist in identifying potential pathways from STS to surface waters and estuaries, there are difficulties in scaling up from monitored individual systems to identify their contribution to the cumulative impact which may be apparent at the catchment scale. The processes which may be obvious through monitoring and dominate at the individual scale may be masked and not readily discernible at the catchment scale due to impacts from other land use activities.

Distribution, abundance and activity of geosmin and 2-methylisoborneol-producing Streptomyces in drinking water reservoirs.

While cyanobacteria have been widely recognised as the most common cause of geosmin and 2-methylisoborneol related taste and odour (T&O) episodes in drinking water supplies, many reported occurrences could not be attributed to these organisms. The Streptomyces genus of soil bacteria also includes producers of these compounds, however their potential role in such occurrences is poorly understood and often disregarded on the basis that they are terrestrial rather than aquatic organisms, with their detection in water samples assumed to reflect the presence of dormant spores rather than metabolically active vegetative cells. Using qPCR and a differential cell lysis technique for DNA extraction, allowing distinction of spores from vegetative cells, the aim of this study was to determine the distribution, abundance and potential activity of Streptomyces species across a range of aquatic and marginal habitat zones in two drinking water reservoirs, including: exposed soil, submerged sediments, plant debris and emergent macrophytes at the margins; marginal and offshore surface waters; deep offshore waters; and offshore benthic sediments. Marginal substrates including soil, sediment and plant debris were identified as the dominant habitat zones for Streptomyces, (concentrations up to 1.1 × 107 cells g-1) supporting the concept of 'wash-in' from the margins due to run-off or water level rise following rainfall, as the likely pathway for Streptomyces induced T&O in reservoirs. However, vegetative cells were also found to comprise a substantial proportion of Streptomyces populations in the reservoir water mass itself (>90% in some surface and bottom water samples), suggesting the potential for these bacteria to be metabolically active in the water and therefore contribute to in situ production of T&O metabolites.

Evaluating potential applications of faecal sterols in distinguishing sources of faecal contamination from mixed faecal samples.

Faecal samples from humans, herbivores, carnivores and birds as well as samples from septic tanks and effluents from a sewage treatment plant (STP) were extracted and analyzed by gas chromatography-mass spectrometry for faecal sterols including coprostanol, epicoprostanol, cholestanol, cholesterol, stigmasterol, campesterol, 24-ethylcoprostanol and beta-sitosterol. Coprostanol was observed in the highest concentrations from the human derived samples, but it was also present in substantial quantities in a range of herbivores. There was no unique marker of human faecal contamination. Multivariate analyses revealed that the faecal sterol profiles were significantly different between the four groups of animals (Wilks' lambda=0.007, P<0.002), and coprostanol and 24-ethylcoprostanol were the major discriminant factors. However, when faecal samples were mixed, the confounding of faecal sterol levels prevented accurate identification of contributing species. Conversely, faecal sterol ratios were highly efficient at identifying which mixtures contained human contribution, but could not appropriately determine percentage contributions of sources.

Bacterial source tracking from diverse land use catchments by sterol ratios.

Water samples from sites potentially impacted by septic tanks, cattle, sewage treatment plant (STP) and natural forests were collected at regular monthly intervals and within 48 h of rainfall events between October 2004 and June 2006. All samples (n=296) were analysed for faecal coliforms and faecal sterols including coprostanol, epicoprostanol, cholestanol, cholesterol and 24-ethylcoprostanol. Faecal sterol ratios were used to assign human and/or herbivore contamination sources and to estimate their percentage relative contributions in water samples. The catchments had significantly different profiles of designated contamination origins (p<0.05), which were consistent with land use patterns. The STP impacted site had the highest incidence of human contamination assignations and the highest mean levels of coprostanol, whilst the forested site had the highest incidence of uncontaminated samples and the lowest mean concentration of coprostanol. Coprostanol concentrations were not always correlated with faecal coliform counts.

Comparisons of water quality parameters from diverse catchments during dry periods and following rain events.

In this study, 12 catchments sites located along the north coast of New South Wales in Australia were grouped into the four categories of septic, cattle, sewage treatment plant (STP) and forested sites via cluster analysis based on their land use patterns. Water samples from all these sites were collected between October 2004 and June 2006 at a regular monthly interval and within 48 h of rain events. The samples were analyzed for bacterial counts including faecal coliform and total coliform; faecal sterols including coprostanol, epicoprostanol, cholesterol, cholestanol, 24-ethylcoprostanol, campesterol, stigmasterol and beta-sitosterol; and the elements including Na, Rb, Sr, Ag, Cd, Sn, Cs, Ba, Hg, Tl, Pb, Bi, U, Mg, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, K, As, Se, P and Mo. Over the course of the sampling period, the STP site had the highest average coprostanol level of 1693+/-567 ng/L which was significantly higher (p<0.05) than the septic sites (190+/-71 ng/L), the cattle sites (163+/-94 ng/L) and forested sites (14+/-4 ng/L). As expected, the forested sites had significantly lower average level of faecal coliforms (373+/-87 cfu/100 mL) compared with the STP (1395+/-574 cfu/100 mL), septic (1243+/-494 cfu/100 mL) and cattle sites (535+/-112 cfu/100 mL). The concentrations of coprostanol were not correlated with the numbers of faecal coliform bacteria when the entire data set was evaluated. The forested sites generally had the lowest average levels of elemental compositions, with significantly lower levels noted for Na, U, Mg, V, Cu, Sr, K, As, P and Mo, whereas Fe was the only element notably higher in the forested sites. Temporal and rain events analyses of the data set revealed that elevated levels of both coprostanol and faecal coliforms were not exclusive to rain events. The average coprostanol levels in rain event samples at each site were not significantly different compared with the corresponding dry event samples. Conversely, faecal coliform numbers increased by 2-4 times in rain events samples from septic, cattle and forested sites, but did not alter in the STP site. Multivariate analyses identified coprostanol and Sr as major contributing factors for the discrimination of septic, cattle, STP and forested sites for both rain and dry events samples. It was clear that each land use type of catchment could be characterized by biochemical, bacteriological and elemental parameters.