Quantification and control of microbial pollution from agriculture: a new policy challenge?

environmental science & policy 11 (2008) 171–184

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Quantification and control of microbial pollution from agriculture: a new policy challenge? D. Kay a,*, J. Crowther b, L. Fewtrell a, C.A. Francis c, M. Hopkins a, C. Kay a, A.T. McDonald d, C.M. Stapleton a, J. Watkins c, J. Wilkinson e, M.D. Wyer a a

Catchment and Coastal Research Centre, River Basin Dynamics and Hydrology Research Group, IGES, University of Wales, Aberystwyth, Ceredigion, SY23 3DB, UK b CREH, University of Wales, Lampeter, Ceredigion, SA48 7ED, UK c CREH Analytical, Hoyland House, Horsforth, Leeds LS18 4RS, UK d School of Geography, University of Leeds, Leeds LS2 9JT, UK e Cawthron Institute, Private Bag 2, Nelson, New Zealand

article info Published on line 24 January 2008 Keywords: Faecal indicator Water Framework Directive Clean Water Act Best management practice Coliform Catchment

abstract Faecal indicator organisms (FIOs) are commonly used to quantify pollution of public health significance. Health protection, as indexed by FIO control, is a central aim of new ‘catchment-scale’ water quality management required in the USA by the Clean Water Act and in the European Union (EU) by the Water Framework Directive (WFD). Experience of the former, after a decade of implementation, suggests that the most significant reason for water quality ‘impairment’ is elevated FIO concentrations, mainly in recreational and shellfish harvesting waters. This provides an early warning of possible problems which the EU regulatory authorities are likely to face. To date, however, a surprising lack of EU attention has been given to prediction and control of catchment fluxes of this key parameter. This is likely to prove embarrassing if the experience of the US regulatory community is not acted upon with some urgency. There is a growing, though still partial, body of empirical science to form the ‘evidence-base’ for good regulatory practice. However, adoption of ‘best management practices’ (BMPs) to effect remediation of impacted waters will require close integration of water policy with policies on financial support for the farming community. This is likely to require enhanced communication and integration within the discrete policy communities addressing the agricultural sector through the Common Agricultural Policy and water regulation through the Water Framework Directive. # 2007 Elsevier Ltd. All rights reserved.

1.

Introduction

1.1.

The Water Framework Directive (WFD)

The WFD is the most significant piece of environmental legislation so far produced by the European Union (EU) (Anon, 2000). It defines a new context and approach for water quality regulation based on the concept of ‘drainage

basins’, within which EU Member States are required to manage both point and diffuse sources of pollution to achieve ‘good’ ecological status and water quality by 2015. The approach represents a radical change from traditional point-source effluent-quality regulation towards environmental water quality control at the point where the water is used for ecosystem maintenance, water supply, recreation and/or fisheries.

* Corresponding author. Tel.: +44 1570 423565; fax: +44 1570 423565. E-mail address: [email protected] (D. Kay). 1462-9011/$ – see front matter # 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.envsci.2007.10.009

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Correction of poor effluent quality in sewage-related pointsource discharges can be addressed through traditional ‘engineered’ solutions at treatment plants and within the sewerage infrastructure, but achievement of both good water quality and ecological status of water bodies requires that diffuse sources are addressed through integrated river basin management involving a much wider community of stakeholders, including, for example, planners and urban managers, industrial dischargers, the farming community and land managers. Consultation with stakeholders and the wider public is required by the WFD, thereby presenting further challenges for those involved in its implementation. Thus, engineers, social scientists and environmental professionals throughout Europe face new challenges and opportunities as the implications of the new approach become apparent. A recent review of WFD implementation issues in Austria Achleitner et al. (2005) defined seven principal requirements that the WFD places on EU Member States, namely: 1. achievement of good ecological status (and/or potential) in all water bodies within the EU by 2015 through integrated catchment management with no deterioration of the current status; 2. establishment of coordinated river basin management in the EU across borders for transboundary catchments (e.g. the Danube, Rhine and Elbe); 3. development of a full-cost recovery system for water supply and wastewater services, which applies the ‘polluter pays’ principle and covers environmental and resource costs (although there may be a divergence between investments required by the regulator to treat ‘all flows’ and the charge based on ‘actual flows’ to the polluter by the water and sewage undertaker); 4. formulation of river basin management plans which will be periodically updated; 5. integrated point- and diffuse-source pollution control; 6. reduction and subsequent elimination of defined priority hazardous substances; and 7. development of a legally binding ‘programme of measures’ and water quality and quantity monitoring programmes to underpin management programmes for control and planning.

1.2. The United States Environmental Protection Agency (USEPA) Clean Water Act Parallel developments in the United States of America (USA) are seen in the Federal Water Pollution Control Act (Anon, 2002a) (known as the Clean Water Act) and the ‘Total Maximum Daily Load’ (TMDL) concept. These encapsulate very similar principles of public consultation and catchmentwide management to those in the WFD (Anon, 2000). Section 303(d) of the Federal Water Pollution Control Water Act (page 103) requires that States identify ‘impaired’ water bodies that do not meet defined water quality standards. The TMDL process investigates these water quality problems and designs actions, in consultation with stakeholders, to effect remediation (i.e. similar to a WFD ‘programme of measures’). In defining how much of a pollutant a water body can tolerate, whilst complying with water quality standards, a TMDL

investigation should quantify all pollutant fluxes, i.e. including effluent discharges from wastewater treatment facilities, diffuse-source pollution from agriculture and surface drainage from streets or highways. Some 64,628 water quality ‘impairments’ were reported between January 1996 and 25 June 2007 and 25,255 TMDLs were approved by USEPA over the same period (Elshorbagy et al., 2005). The top five reasons for water quality impairment leading to an agreed TMDL have been: ‘microbial pollutants and pathogens’ (in fact, FIOs impacting on bathing and shellfish harvesting waters) (5111 TMDLs); heavy metal pollution (5072 TMDLs); nutrients (3521 TMDLs); sediments and siltation (2682 TMDLs); and organic enrichment and low dissolved oxygen (DO) (1425 TMDLs). Some 4525 TMDLs, for all impairment causes, were approved by USEPA in the single fiscal year to 30 September 2006 (Hyer and Moyer, 2004; Kay et al., 2006). Thus, in the US, where ‘pressure and impacts’ on water resources similar to the EU are evident, the principal ‘impairment’ cause leading to a TMDL is ‘pathogens’ (the pathogens themselves are rarely measured but are indexed by FIOs). The TMDL procedure defines ‘allocations’ which specify the amount (or concentration) of a pollutant that can be discharged to a water body such that standards are attained in both the receiving water body and all downstream waters’. This policy driver underpins the need for—information on: (i) the fluxes of catchment-derived point- and diffuse-source microbial loadings and (ii) the likely remediation efficacy of alternative control measures applied to the sewerage infrastructure and/or agricultural diffuse pollution sources (Ferguson et al., 2003; Jamieson et al., 2003, 2004a; Kay et al., 2001, 2005c,d,e, 2007a,b; Lewis et al., 2005; Wither et al., 2005).

2.

A case study: Tomales Bay, California

2.1.

The ‘problem statement’

In Tomales Bay, California, the principal ‘beneficial uses’ are recreation and shellfish harvesting. The Bay has been defined as ‘impaired by pathogens’ due to diffuse-source pollution from agriculture and a range of other sources, including human effluents, wildlife, recreational boating, horses, urban storm drainage and septic tanks (Anon, 2003b, 2004b). Although the ten small sewage treatment works and sewage holding ponds within the Bay’s catchment were not permitted to discharge to the Bay directly, effluents were spread onto fields, with the attendant risk of accidental spills. This combined loading had caused a ‘threatened’ classification under the State Shellfish Protection Act and a prohibition on commercial harvesting during rainfall periods by the California Department of Health Services. In addition, the Bay’s shellfish have been implicated in an illness outbreak (Anon, 2003b).

2.2.

FIO sources

A source analysis suggested that agricultural diffuse pollution generated the principal FIO loading to the Bay. The TMDL process sought to rectify this through targeted development of

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non-point pollution control strategies, including on-farm ‘best management practices’ (BMPs), together with an education and outreach programme driven by a catchment-wide stakeholder participation exercise, including shellfishery and watershed user groups. The principal nonpoint-source control measures for FIOs were outlined in a Basin Plan amendment of September 2005 (Anon, 2005). This identified the three main tributaries for the Bay as ‘impaired’, producing four clearly impaired locations: (i) Tomales Bay itself, (ii) Laquntas Creek, (iii) Walker Creek and (iv) Olema Creek.

2.3.

sources of human waste have an allocation of zero. Nonpoint source runoff containing coliform bacteria of animal and wildlife origin, at levels that do not result in exceedances of water objectives, does not constitute wastewater with particular characteristics of concern to beneficial uses. Therefore, animal and wildlife-associated discharges, in compliance with the conditions of this TMDL, do not constitute a violation of applicable discharge prohibitions.’’ (Anon, 2005). The concentration-based pollutant wasteload allocations for Tomales Bay are outlined in Table 1. Approximately 3 years have been allocated to operators of waste management facilities, dairies, equestrian areas, urban wastewater schemes and managers of dairy farms to submit plans for FIO flux remediation through compliance with appropriate ‘Waste Discharge Requirements’ to achieve the limits identified in Table 1. The Agricultural Water Quality control programme required on the Tomales Bay watershed has been costed, as required by the California Water Code, at between $0.9 and $2.0 million per year for the next 10 years. This cost derives from technical assistance and evaluation, provision of water troughs and on-farm measures (e.g. stock exclusion from stream banks), and is shared between the grazing lands operators, which number approximately 150. The operators may be eligible for state and federal water quality grants and federal agricultural support grants, although the extent of grant aid is not specified. A 5-year rolling review of water quality monitoring data is required to track improvement achieved in response to these measures and to:

Numeric targets

The targets are an interpretation of water quality standards. Those set for the Bay were: i. <30 shellfish harvest closures per year; ii. median faecal coliform (FC) <14,100 ml 1 and 90%ile <43,100 ml 1 in the Bay; and iii. geometric mean FC <200,100 ml 1 and 90%ile <400,100 ml 1 in the three tributaries.

2.4.

Load allocations

The load allocations set the highest FIO concentrations allowable in specified tributaries to ensure that the numeric targets are achieved in the receiving waters. These relate to contributions from ‘discharging entities’ and intermittent wildlife discharges are not accommodated through this mechanism. The pathogen TMDL states: ‘‘Discharging entities will not be held responsible for uncontrollable coliform discharges originating from wildlife. If wildlife contributions are determined to be the cause of exceedances, the TMDL targets and allocation scheme will be revisited as part of the adaptive implementation program. The discharge of human waste is prohibited. All

 evaluate spatial and temporal water quality trends in the Bay and its tributaries;  further identify significant pathogens source areas;  evaluate coliform levels and loadings to the Bay at the terminus of major tributaries;

Table 1 – Concentration-based pollutant load allocations for dischargers of pathogens in Tomales Bay watershed Pollutant source

Waste load allocation faecal coliform 100 ml For direct discharge to the Bay

Onsite sewage disposal systems Small wastewater treatment facilities Boat discharges Grazing land Dairies Equestrian facilities Municipal runoff Municipal runoff open space lands (terrestrial wildlife) In-Bay background (marine wildlife)

Median

90th percentile

0 0 0 <14 <14 <14 <14 <14 <14

0 0 0 <43 <43 <43 <43 <43 <43

Pollution load allocations for Tomales Bay tributaries as a geometric mean faecal coliform 100 ml Walker Creek Laqunitas Creek

1

For discharge to tributaries Geometric meana 0 0 N/A <200 <200 <200 <200 <200 N/A

1

95 95

a Geometric mean, percentile and mean values are based on no less than five samples collected in a 30-day period and no more than 10% of samples are to exceed the 90th percentile value.

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 collect sufficient data to calibrate and validate the Bay hydrodynamic model to observed coliform levels; and  collect sufficient data to prioritize implementation efforts and assess the effectiveness of implementation actions.

assist EU authorities with implementation of WFD policies in relation to ‘protected areas’.

3. It is envisaged that these data will allow the quinquennial review process to answer the following questions (Anon, 2005): 1. Are the Bay and the tributaries progressing toward TMDL targets as expected? If progress is unclear, how should monitoring efforts be modified to detect trends? If there has not been adequate progress, how might the implementation actions or allocations be modified? 2. What are the pollutant loads for the various source categories (including naturally occurring background pathogen contributions and the contribution from open space lands), how have these loads changed over time, how do they vary seasonally, and how might source control measures be modified to improve load reduction? 3. Is there new, reliable and widely accepted scientific information that suggests modifications to targets, allocations, or implementation actions? If so, how should the TMDL be modified? 4. The allocations assume a conservative bacterial die-off rate of 0.02/h. This value is based on rates reported for San Francisco Bay in 1970. If bacterial die-off is found to be higher, higher allocations may be considered. What are bacterial die-off rates in the water column and stream sediments? Do they vary by season? What are bacteria transport times from sources to the Bay? 5. How does estuarine mixing and dilution of tributary waters vary by flow and season? 6. What is the relationship between precipitation, runoff, tributary loads, Bay coliform levels, and water quality exceedances and shellfish harvesting closures? 7. Are there bacteria in Tomales Bay sediments that enter the water column during storm events? If yes, how should this process be accounted for? A baseline faecal coliform water quality monitoring programme for the tributaries and the Bay was also planned from January 2006, with weekly sampling intervals for 5 weeks, thence monthly, sampling from March–December. Clearly, this sample acquisition regime would not be adequate to address the questions above and further investigations would be required to clarify the detailed scientific issues implied in these questions.

2.5.

Lessons for WFD implementation

There are many parallels between TMDLs and WFD ‘programmes of measures’: both require significant stakeholder engagement, they operate at the catchment or drainage basin scale, and commence by defining the ‘pressures and impacts’ (WFD) or ‘problem statement’ (TMDL). The existing TMDL studies provide lessons for the implementation of WFD ‘programmes of measures’ in the area of FIO control, but at this early stage they do not appear to have developed a set of process-based operational tools to

The United Kingdom (UK) context

The most significant policy challenge presented by the implementation of the WFD is the quantification and management of diffuse-source pollution from the farming community and urban sources (Anon, 2002d, 2003a). Examination of the available policy instruments for diffuse-pollution control have been undertaken in the UK by the Department for Environment, Food and Rural Affairs (Defra) and others, and cost estimates have been published (Anon, 2004a). Tackling diffuse water pollution from agriculture (DWPA) in England and Wales is been taken forward through the Catchment-Sensitive Farming (CSF) programme and current CSF Delivery Initiative (SFDI) within Defra. Some £21.8 m million is being spent over 2 years on a network of CSF Officers for collective and individual engagement with farmers in priority catchments where the problems are most acute. Assessment of priority catchments includes, amongst other parameters, catchments where failures in bathing water criteria have been recorded due to DWPA. In parallel, Defra is also working to identify the most cost-effective additional policy options likely to be required to meet WFD objectives. Options being considered include the extension of existing Defra policies as well as the development of new approaches for tackling DWPA and investigation of the principal DWPA problems (Haygarth et al., 2005). To date, the nutrient parameters have received by far the most coordinated EU attention within both the policy and academic communities, with major EU projects such as EUROHARP (Borgvang and Bar, 2005) developing a ‘toolkit for nutrient management and assessments of nutrient mobility in river basin districts’ (Neal and Heathwaite, 2005; Neal and Jarvie, 2005; Neal et al., 2006). In the UK, nutrient pressure ‘risk maps’ for controlled waters have been produced by the UK Environment Agency using an approach reported by Heathwaite et al. (2005). The analysis outlined in Haygarth et al. (2005) provide a provisional inventory of diffuse pollution losses in England and Wales. They reinforce this assessment and conclude: ‘‘Nitrogen, because of its sheer volume of usage and early legislative controls (The Nitrates Directive), is the most researched and understood pollutant. However, its impact in some regions is now thought to be of less importance than phosphorus, which controls the productivity of many inland freshwater lakes and waterways. Sediment and pathogen transfers (sic. i.e. in fact faecal indicators) represent the ‘newer’ challenge for the 21st century.’’ They also suggest the following forward strategy for Defra:  ‘‘Modelling to be at the centre of a future research strategy (termed a ‘model centric’ approach by Haygarth et al. (2005), but this needs to be backed up with long term and well coordinated platform catchments. Scenario testing (including climate change) to quantify effects of measures is most

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Fig. 2 – Pie chart representation of faecal coliform flux into St. Aubins Bay of the Island of Jersey (Kay et al., 1999).

Fig. 1 – Faecal indicator organism source–apportionment studies conducted in the UK.

cost-effectively done using appropriate policy models. We have identified that these exist (albeit better for some contaminants than others).  There is still a need for field/catchment-scale experimentation to address some issues. We suggest that the best way forward is to assess what models are now capable of achieving in support of programmes of measures. Where a lack of knowledge limits progress (e.g. the effectiveness of mechanism of a mitigation method), then experiments should then be commissioned to provide the data.  This integrated, multi-pollutant ‘model centric’ approach, that attempts to integrate all previous models that have previously focussed on the individual final goal of a robust policy model for diffuse pollution’’. To address the suggested ‘21st century challenge’ of microbial modelling, source–apportionment studies and some empirical black-box models predicting FIO concentration and flux from land use parameters have been reported for UK catchments. Most recently, the UK’s sentinel catchment for WFD research, the Ribble catchment, was modelled in this manner (Kay et al., 2005d). Additionally, empirical studies seeking to quantify the remediation potential of on-farm

measures to reduce diffuse pollution have been completed in Scotland (Dickson et al. (2005) and Kay et al. (2005c)). Other interventions to reduce FIO fluxes in UK catchments have been reported, e.g. flood retention wetlands (Kay et al. (2005e)) and ‘natural treatment systems’ for effluents, including reed beds, lagoons and integrated constructed wetlands (ICWs) (Harrington et al., 2005; Kay et al., 2005e). One of the most promising interventions reported to date is the on-farm ICW, which is used in Ireland for treating contaminated water from farm hardstanding areas and roofs (Edwards et al., 2008; Harrington et al., 2005). Initial nutrient and FIO removal efficiencies seem promising and the systems appear more robust to flow alterations than engineered ‘natural treatment’ systems such as reed beds (Kay et al., 2005a). However, regulatory concerns have been expressed concerning the downward translocation of pollutants to groundwater and these are the subject of current investigation with EU support in Ireland and the UK. The conclusions of Haygarth et al. (2005) identify key research requirements for the policy community. There is a particular need to progress the field of catchment microbial and sediment modelling. To date, the microbial component has received more international attention in Canada, Australia and the USA (i.e. via the TMDL approach outlined above) than in the UK and EU as part of the WFD implementation. When this emerging area has a similar science base to the nutrient parameters, the identification and development of the type of multi-parameter model needed to inform the

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Fig. 3 – Temporal (hourly) flux plot representation for Irvine Bay, Scotland for an 8-week sampling campaign.

policy community should be possible. There is a need, however, for pan-European coordination. This might be implemented through amendments to the current remits of the WFD ‘Common Implementation Strategy’ and, in the UK, through attention to microbial and sediment modelling needs by the UK Technical Advisory Groups addressing WFD implementation. Detailed examination of this area will be required if ‘protected areas’, such as bathing and shellfish harvesting waters, are to be managed effectively through the implementation of the principles enshrined in the WFD as clearly envisaged in early drafts (Anon, 2002c) of the new Bathing Water Directive (Anon, 2006). Whilst US regulatory approaches exemplified in the TMDL concept have sought to set water quality criteria in ‘inputs’, as

specified in Table 1, there is little evidence to date that US studies have progressed to the stage of distributed white-box modelling which could underpin evidence-based advice on remediation strategies to the farming community. Current criteria (Table 1) are little more than ‘ambient’ water quality criteria for recreational and shellfish harvesting waters. This ‘precautionary’ approach is understandable, but only serves to illustrate the basic lack of hard scientific information on catchment microbial dynamics. This suggests that Haygarth et al.’s (2005) definition of microbial dynamics as the 21st century challenge is just as appropriate to the agencies and research scientists responsible for TMDL application as it is to EU policy makers designing programmes of measures for WFD implementation.

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Fig. 4 – Bathing water faecal indicator concentrations and riverine inputs to the bathing waters adjacent to Irvine beach in Ayrshire, Scotland (Wyer et al., 2000).

Fig. 5 – Schematic diagram of the Ribble estuary catchments (Stapleton et al., 2002).

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4.

The current evidence-base

4.1.

Studies to quantify FIO fluxes

A series of FIO source–apportionment studies has been undertaken for UK catchments to address non-compliance with the 1976 Bathing Water Directive (Anon, 1976). Fig. 1 shows the locations of these investigations throughout the British Isles and in the States of Jersey (Crowther et al., 2001, 2002, 2003; Kay et al., 1999, 2001; Stapleton et al., 2002; Wyer et al., 1994, 1997, 1998, 2001). These studies have provided a data resource for characterising base- and high-flow FIO concentrations during the summer (May–September) bathing season in rivers and streams draining catchments which encompass the range of land uses present, including affor-

ested plantations, upland rough grazing, improved lowland pasture, arable and urban. These studies have developed a number of representational tools used to communicate the key lessons derived to date. Fig. 2 shows a simple pie chart of FIO flux measured during an 8-week sampling period generated for the Island of Jersey (Wyer et al., 1994). This illustrates the importance of high-flow events in total flux assessment. These commonly occupy less than 10% of the time period during the temperate north European summer bathing period, but they can account for the bulk of FIO delivery. A slightly more complex, but useful, representation of FIO flux is seen in the temporal flux sequence for Irvine Bay, Ayrshire (Fig. 3), again for an 8-week sampling campaign (Wyer et al., 2001). At the time of this investigation the sewage

Fig. 6 – Temporal (hourly) flux plot representation for the catchments draining to the Ribble estuary, UK (Wyer et al., 2003).

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discharged to the coastal recreational waters underwent preliminary treatment (screening) before being discharged via a long sea outfall (1500 m). Fig. 3 illustrates the importance of this input during dry periods when the adjacent bathing beach generally exhibited compliant conditions (see Fig. 4). However, following rainfall events, the FIO flux increased dramatically in absolute terms and the contribution to this flux of riverine sources derived from diffuse agricultural catchment sources was proportionally much more important. It was during these episodes of peak flux that the adjacent bathing water was at risk of non-compliance (‘impairment’ in US terms). Many riverine discharges to bathing waters have upstream point-source discharges of treated effluents and combined sewage overflows (CSOs) which add to the diffuse loading. In the Irvine catchment investigation, a sewer modelling study facilitated quantification of these anthropogenic point-source discharges. These were found to comprise only 11% of the high-flow riverine flux, which further illustrates the importance of diffuse agricultural sources in catchments that include both urban and livestock farming areas. The Irvine catchment offers perhaps the most generically transferable model of FIO delivery in which the long periods of low flow during the summer are associated with relatively low fluxes. During this period, FIOs from sewage effluents dominate the delivery pattern and, if the beach or shellfish harvesting area is non-compliant, this probably indicates poor design and operation of sewage treatment processes and/or inappropriate discharge locations for the treated effluent. Following rainfall events, stream flows will be elevated and there is a risk of spills from CSOs. During these short episodes, FIO fluxes from agricultural diffuse sources increase rapidly and can dominate the total episodic delivery during the key periods when non-compliance is most likely to be experienced. This simple model of FIO delivery has been shown not to operate in more urbanised UK catchments, such as the Ribble system (Stapleton et al., 2008; Wither et al., 2005; Wyer et al., 2003). Fig. 5 shows a schematic representation of this system. The hourly flux diagram in Fig. 6 shows how these inputs change in response to rainfall and illustrates the dominance of the River Douglas in terms of total input to the Ribble estuary. Partly in response to these data, ultra-violet (UV) disinfection was installed on the largest streams of treated sewage effluent discharging to the River Douglas. It is still the case, however, that diffuse sources are important during episodic events, as characterised by the flux at location 101 (the Ribble at Samlesbury). However, it is Fig. 8 which really illustrates the divergence of this catchment system from the characteristic pattern of the Irvine system described earlier. The total inputs to the estuary are quantified in the two bars on the right hand side of Fig. 7. These clearly suggest that untreated spills of diluted raw sewage from CSOs and storm tank overflows (STOs) contribute the majority of the flux observed in this 7-week period in the bathing season. Fig. 8 also illustrates the impact of UV disinfection on the total inputs. This intervention reduces the ‘final effluent’ flux but, in consequence, has the effect of increasing the ‘proportion’ of the untreated ‘spills’ to the post-UV reduced overall flux.

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Fig. 7 – Temporal (hourly) flux plot representation for the catchments draining to the Ribble estuary, UK (This map is based on CEH 1990 Landcover data, Ordnance Survey profile and 1:50,000 raster data. Environment Agency, 100026380, (2005)).

4.2.

Remediation and management of FIO fluxes

The evidence-base in this area is sparse when compared to the nutrient-related parameters. However, there have been a relatively small number of investigations worldwide (see reviews by Kay et al. (2007b) and Ferguson et al. (2003)). In the UK, the Scottish Executive has initiated a series of investigations to quantify the effects of certain remedial measures in livestock farming areas (Dickson et al., 2005; Kay et al., 2005c). These have centred on stream bank fencing to generate riparian filter strips and ensure stock exclusion from water courses; farm dirty water control; and the installation of constructed wetlands (Decamp and Warren, 2002; Harrington et al., 2005; Kay et al., 2005e) to treat FIO fluxes from farm hardstandings and roof surfaces (Edwards et al., 2008). Preliminary findings of these investigations suggest that fencing of approximately 30% of stream bank length within areas of improved pasture is required before any improvement in high-flow FIO flux can be observed, but that the measures do produce significant FIO flux reductions at sub-catchment outlets of over 50% (Kay et al., 2007a). The studies have also uncovered significant seasonal variability in FIO flux, with a distinct summer peak in temperate livestock rearing areas which seems to be related to the period when stock is grazing the open fields and not housed, as would be the case in the winter (Rodgers et al., 2003). This observation has significance for future study design and suggests problems will be encountered where a longitudinal (i.e. before and after) design is adopted without suitably chosen ‘control’ catchments (Kay et al., 2007a).

4.3.

Predictive modelling of FIO fluxes

FIOs represent a highly non-conservative water quality parameter. It is for this reason that any credible quantification of this pollutant must specify the sample handling procedures and have samples analysed within prescribed

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Fig. 8 – Satellite acquired land use data used for modelling faecal indicator flux in the Ribble catchment, UK (Wyer et al., 2003). The land cover presented is a combination of satellite-derived data (i.e. CEH 1990 data) and OS map data (digital 1:50,000 maps used to extract woodland and urban).

time periods (Anon, 2002b). In the environment, these gutderived bacterial are subject to temperature and nutrient stress because they have evolved to thrive at body temperatures with a rich nutrient supply in the alimentary canal. In environmental waters, they are in a low-nutrient environment, but their metabolism is slowed by the generally lower temperatures. These conditions accelerate or slow the rate at which these organisms become nonviable outside the gut of warm-blooded animals. There is a significant literature on the rate of this decay in marine waters because of their traditional use as receiving environments for sewage effluents (Kay et al., 2005b; Sinton et al., 2002). However, such information for the different catchment components, which would require characterisation for a truly process-based and white-box modelling approach, is not available. Because of this, process-based modelling

efforts to date have been somewhat rudimentary (Ferguson, 2005; Jamieson et al., 2003, 2004b, 2005a,b; Kay et al., 2007b; Tong and Chen, 2002). Simple black-box regression models have been developed to predict base- and high-flow FIO concentrations in the UK catchments identified in Fig. 1, using land use data from field mapping and/or a combination of satellite data and Ordnance Survey 1:50,000 digital map information (Crowther et al., 2002, 2003) (Fig. 8). These models, which are study-specific (i.e. relate to the study catchment and monitoring period), have been used to identify those monitoring points where the actual FIO concentrations exceed predicted concentrations (i.e. positive anomalies) for more detailed FIO-source investigation (Kay et al., 2005d). Data from some of these studies are presently being used to develop generic models for predicting summer bathing season base- and high-flow FIO concentrations in the

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UK and their apportionment to urban and rural sources. However, these generic models must be regarded as provisional at this stage because: (i) urban areas are rather poorly represented in many of the study catchments on which the models are based and (ii) the effects of antecedent rainfall upon FIO concentrations, which need to be taken into account when combining data from different studies, are still poorly understood. It is interesting to note that the statistical correlation predicting FIO concentration from land use in such regression models is much stronger for high-flow conditions than for low flows. In the case of the former, explained variances of >60% have often been reported, which would seem acceptable given the imprecision associated with FIO enumeration (Anon, 2002b). There are some surprising but important information gaps which hamper model development in relation to FIOs. There is, for example, very little empirical peer-reviewed information on FIO concentrations in treated sewage effluent to underpin any scenario analysis of treatment options (Kay et al., 2008b). Equally crucial information, needed by the diffuse-source modelling community, is empirically derived data on expected catchment-scale export coefficients for FIOs. Some UK data have been collated by Kay et al. (2008a), but a literature comparable to nutrient parameters, such as phosphorus, simply does not exist.

4.4.

Microbial-source tracking

Bacterial-source tracking is an emerging tool which can provide a qualitative assessment of the likely FIO sources in environmental waters. It has been employed by Hyer and Moyer (2004) to inform TMDL studies in the USA, and Pond et al. (2004) provide an excellent overview of the potential for the source-tracking methods currently available to contribute to FIO source apportionment. These methods use either: (i) species and or sub-species of organisms thought to be associated with faecal matter from humans or defined animal groups, or (ii) chemical markers indicative of human sewage. There is currently no single and definitive approach with which to quantify the exact proportions of human and animal derived FIOs, but this area is developing rapidly and may provide operationally useful data in the medium term. However, parallel testing of source tracking, where traditional source–apportionment data are available, suggests that qualitative tracking information does not provide additional explanatory power (Stapleton et al., 2007).

5.

Conclusions

Established protocols are emerging from the peer-reviewed literature to underpin FIO flux quantification for catchment systems. This ‘quantitative source apportionment’ is the first step in the design of control measures to remediate impaired or non-compliant waters. It is possible to develop and deploy generic black-box modelsi to ‘predict’ FIO fluxes using empirical data from past UK studies, though it should be noted that the present models must be regarded as provisional, especially because urbanised catchments may be under-represented in the present data set.

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The potential for remediating FIO fluxes through specific land management measures in areas of improved pasture has been established in studies conducted in Scotland. However, the international evidence on the individual impact of different forms of management intervention is inconsistent (Kay et al., 2007b). Additionally, the process-based understanding of FIO fate and transport at the catchment-scale is, at best, rudimentary. Further empirical understanding of microbial dynamics in terrestrial ecosystems is required to underpin credible white-box process-based model development. Such models are required to design and predict the impacts of different policy scenarios at both the catchment- and farmscale. Previous remediation studies have provided a broad indication of beneficial outcomes, but they have been insufficiently widespread or detailed to separate out the impacts of the various intervention policy mixes which would be possible. Very basic questions still need to be answered by the research community in addressing the needs of the policy maker and regulator. In a putative rank order, these include: 1. What are the FIO concentrations and fluxes in faecal matter from a range of species including livestock, wildlife and humans? 2. What FIO concentrations may be expected in sewage effluents produced by different treatment regimes? 3. What are the rates of export of FIOs from catchments of specific land use under base- and high-flow conditions? 4. How do in-stream processes of sedimentation, bio-film development and re-entrainment affect and determine event-based fluxes of FIOs? 5. How do the available interventions (e.g. riparian filter strips, integrated constructed wetlands, farm dirty water control and sewage treatment) reduce FIO delivery at the catchment-scale, and how do mixtures of these strategies perform? 6. How long do FIOs remain viable in the principal catchment compartments (e.g. faecal matter on the land surface, soil horizons, soil throughflow waters, field drain flow, groundwaters, rivers, lakes and impoundments); and in nearshore marine environments, some UK empirical data are emerging (Oliver et al., 2005a, 2005b, 2006) but the whole area of faecal indicator fate and transport in terrestrial systems is under-researched? 7. The associated question of potential environmental regrowth of the FIOs has been raised in semi-tropical environments (Fujioka, 2001; Fujioka et al., 1981; Fujioka and Yoneyama, 2002). In temperate studies, for example, prolonged survival in-stream bed sediments has been observed (McDonald et al., 1982), but the implications of these observations for the generally accepted modelling assumption of first order kinetics decay are, as yet, unclear. Beyond these essential scientific questions remains a series of important information gaps concerning the policy design of remedial measures, the appropriate balance between ‘enforcement’ by environmental regulators and ‘encouragement’ through farm support policies, and the cost-benefit of alternative intervention scenarios.

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FIO dynamics in catchment systems is a young but developing area of environmental science which will need rapid progress if the scientific community is to provide the policy insights needed to address the present pattern of water quality ‘impairments’ in the US and likely non-compliance against Water Framework Directive requirements.

Acknowledgements Elements of this analysis were presented at the joint SEPA/SAC meeting in 2006 on Diffuse Pollution from Agriculture. We are grateful for helpful advice from US scientists involved in TMDL investigations, including David J. Lewis, Peter Krottje and Farhad Ghodrati. Any errors of fact or interpretation are, however, the authors’ responsibility.

references

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sources. She is currently working on health impact assessment (with an emphasis on using quantitative approaches) of aspects of water supply, stormwater and wastewater management and also flooding under a series of EPSRC projects. Carol Francis is a graduate microbiologist with 20 years experience of environmental microbiology applied to recreational waters, catchment flux studies and potable water investigations. She is expert in analytical quality control systems and their application with microbiological laboratories. Matthew Hopkins is a Clinical Research Associate for a global Clinical Research Organisation specialising in the set up, clinical monitoring, data collection, safety monitoring, and close out of phase II–IV clinical trials. He has considerable experience in water chemistry. Chris Kay is a graduate environmental scientist who has managed field teams acquiring water quality and hydrological information on investigations in the UK and the Channel Islands. Completed studies and reports have spanned policy questions relevant to recreational and shellfish harvesting waters set in a Water Framework Directive Context. Adrian McDonald is Professor of Environmental Management at the University of Leeds. Adrian has been advisor to the House of Lords report on Water Management and the Inter Ministerial Forum on Water Management in The Hague. He is a Founding Trustee of the Yorkshire Dales Rivers Trust, a co-director of CREH – a specialist analytical company – and has extensive consultancy experience with the water industry in the UK and overseas. Carl Stapleton is a Senior Research Fellow within CREH at the University of Wales, Aberystwyth. He has published widely on faecal indicator and nutrient fluxes in catchment systems as well as nearshore environments, hydrodynamics and ecology. He has managed projects throughout the UK and Channel Islands. John Watkins has 40 years experience in environmental microbiology including the analysis of samples for Cryptosporidium parvum including involvement in external proficiency schemes. He is a member of the Standing Committee of Analysts and chairs the current UK committee revising the Blue Book methods for environmental microbiology relevant to recreational waters. He has worked on projects for the Overseas Development Administration and the British Council.

John Crowther is a Reader in Environmental Science of the University of Wales with specialist expertise in the development of statistical models to predict faecal indicator organism concentrations in rivers and coastal bathing waters from catchment land use data and antecedent weather conditions. He also undertakes archaeology-related soils analysis and reporting.

Jeremy Wilkinson works for Cawthron in New Zealand on major environmental assessments. His background is in environmental sciences and faecal indicator as well as, hydrochemistry and rainfall-runoff modelling. He has worked at the Centre for Ecology and Hydrology (Wallingford), Centre for Research Into Environment and Health, and Flinders University Adelaide on issues such as faecal contamination, forestry impacts on water quality, coastal contamination, influences of development and population on storm and wastewater discharges and the impacts on seagrass.

Lorna Fewtrell is a Senior Research Fellow within the Centre for Research into Environment and Health at the University of Wales, Aberystwyth. She has built on a background of biochemistry and toxicology by extending into the health and environment field and specialises in drawing together information from a wide range of

Mark Wyer is a Senior Research Fellow within CREH at the University of Wales, Aberystwyth. He has published widely on faecal indicator and nutrient fluxes in catchment systems. He has studied in the UK and Canada and managed projects throughout the UK and Channel Islands.