An INCA model for pathogens in rivers and catchments: Model structure, sensitivity analysis and application to the River Thames catchment, UK
Graphical abstract
Schematic representing the sources, transport mechanisms and stores of pathogens in the environment.
Introduction
Pathogens are a generic name for the primary microbial agents that cause many illnesses and contagious diseases. These micro-organisms can be microscopic bacteria, sub-microscopic viruses or larger protozoa. In general, pathogens derive from warm blooded animals and humans and can originate from both diffuse sources in catchments, such as runoff from livestock, as well as point sources, such as sewage treatment works (STWs). Pollution of water resources by pathogens is a serious health risk, and pathogens are recognised as one of the primary pollutants of concern in the world (Domingo et al., 2007). Water bodies contaminated with pathogens are responsible for the spread of many contagious, water-borne diseases (Chapra, 2013). This is particularly of concern where water is used for municipal water supply, crop irrigation, and recreational purposes (Environment Agency, 2003, Amirat et al., 2012). Furthermore, the contaminants of wastewater can exacerbate biodiversity loss, such as invertebrates, fish and shellfish (European Commission, 2013).
The European Commission has highlighted the need for continual improvement of wastewater treatment in their seventh implementation report (2013) of the 1991 Urban Waste Water Treatment Directive. According to the most recent Water Framework Directive 2000/60/EC implementation report (2015), point source pollution from sewer overflows remain one of the main pollution sources in urban areas, requiring significant investment in the coming years across the EU. Diffuse pollution significantly affects 90% of river basin districts, 50% of surface water bodies, and 33% of groundwater bodies across the EU. The agricultural sector is the primary source of diffuse pollution. In England and Wales there have been many incidents associated with consumption of contaminated public and private drinking water (Nichols et al., 2009), with the implicated pathogens being Giardia spp., Cryptosporidium spp., Escherichia coli 0157, Salmonella typhi, Salmonella paratyphi, Campylobacter spp. and Streptobacillus moniliformis. Also the evidence suggested that both low and high river flow conditions can give rise to pathogen-associated drinking water problems, due to reduced dilution of point sources under low flows, and the flushing of pathogens from diffuse sources during high flows and rainfall events (Wilkinson et al., 1995a, Wilkinson et al., 2011). There is also growing evidence of microbial contamination of groundwater, which is often used as an untreated private supply among many communities in the developed world (Kay et al., 2007b, Feighery et al., 2013). For example, testing of private water supplies in England and Wales during 2014 shows that water supplies, in many cases, continues to be of unsafe microbiological quality, with 22.2% of samples (N = 12,885) containing coliform bacteria, 13.4% (N = 7829) containing enterococci, and 12.8% of samples (N = 13,828) containing E. coli (DWI, 2015). These results demonstrate that groundwater contamination with faecal matter from birds, animals or humans is widespread, and there is a high risk of private water supplies causing illness (DWI, 2015). There are well established methods of measurement of pathogens and the unit of measurement for bacteria using culturing methods is colony forming units (cfu) per 100 ml of sample. These numbers can be large from STWs with up to 100 million cfu/100 ml for effluents and even higher levels from manures and animal sources (Kay et al., 2008). Thus, filtration and chlorination of public water supplies are generally essential to ensure potable drinking water.
Future predictions of climate change, land-use change and population growth are likely to exacerbate existing pressures on the world's river systems (Alcamo et al., 2007, Whitehead et al., 2009). Climate change is predicted to increase the risks water-borne diseases with a very high confidence (IPCC, 2014). For example, temperature increases and precipitation pattern changes associated with climate change will affect the growth, survival and transport of enteric bacteria (Liu et al., 2013). In order to understand land-use, climate change, and population growth impacts on river pathogen concentrations, scientific and modelling studies on both point and diffuse pathogen sources, and their transport dynamics and survival at the catchment scale, are required. Models can be used to develop informed health risk assessments, evaluate policy reforms and land-use change options, as well as study management practices (Wilkinson et al., 1995a, Wilkinson et al., 1995b, Kay et al., 2008).
In this paper we consider the transport mechanisms and dynamic processes affecting pathogens in river catchments and develop a new generic version of the INtegrated CAtchment Model INCA (Whitehead et al., 1998, Whitehead et al., 2011, Wade et al., 2002a, Wade et al., 2002b). The model is subjected to an uncertainty analysis to evaluate the parameter sensitivity and is applied in a case study of the River Thames to investigate the transport, survival, and management of the indicator species total coliforms (TC). Lastly, the potential impacts of land-use change are investigated to assess future potential changes in total coliforms in the River Thames catchment.
Section snippets
Pathogen sources, modelling and die-off dynamics
An understanding of pathogen dynamics in the natural environment is necessary in order to model their fate, protect water sources and manage contamination (Meays et al., 2004). Sources of pathogens can be divided into two categories, point and diffuse sources, each of which varies spatially in relation to land use and human population. Point sources are STWs discharges of domestic and industrial wastewater, urban runoff and storm water drainage, and agricultural effluent drainage systems (
INCA modelling of pathogens in catchments
In this paper we utilise the INCA Model as the main platform for a new pathogens model. INCA is a catchment scale process based model to calculate pollutant transfer from diffuse sources and point sources to the catchment outlet, as shown in Fig. 1. To date, the INCA model family includes simulation of nitrogen, phosphorus, sediments, chloride, carbon and mercury (Whitehead et al., 1998, Whitehead et al., 2011, Whitehead et al., 2013, Wade et al., 2002a, Wade et al., 2002b, Lazar et al., 2010,
Application of INCA-Pathogens to the River Thames
The River Thames has been subject to several INCA studies for nutrients such as N and P, and details of the catchment characteristics are given by Jin et al. (2012); Crossman et al. (2013) and Whitehead et al. (2013). The geology of the River Thames catchment is mainly of highly permeable, dual-porosity chalk, although the upper part of the catchment is characterised by low permeability clays, and the lower part characterised as sands and sandstone (BGS, 2014). The catchment has an average base
Model calibration and dynamics
Simulated daily flow over the calibration period (2002–2008) provided an acceptable reproduction of the observed flow (R2 = 0.67) at Reach 22, as shown in Fig. 4 and similar results are given elsewhere for the INCA application to the Thames (Jin et al., 2012, Futter et al., 2014). The livestock input, light proportionality constant for water column TC die-off, and sediment settlement and entrainment coefficients, were calibrated to get the best model fit and Table 3 shows the decay rates and
Land use change scenario analysis
As part of the River Thames case study, an assessment was undertaken of the likely effects of land use change on TC in the catchment. The future land use scenario was developed by Castellazzi et al. (2010) and represents sub-versions of an IPCC storyline, considering food security as a main driving force for land use change. In this scenario, it is assumed that world food demand increases, raising grain prices and the UK farmers respond by switching to more intensive arable farming. The land
Discussion and conclusions
A new model to simulate pathogen transport, dynamics and distribution has been developed and applied to the Thames. As might be expected, there are uncertainties associated with the pathogen modelling structures, equations and parameters, There are also uncertainties associated with pathogen field observations, which have high natural variability and are difficult to measure. There is also limited understanding of the factors that influence pathogen survival and regrowth, particularly in
Acknowledgements
We are grateful to the DEFRA and NERC modelling programme that is part of the NERC Macronutrient Cycles Programme and to the Academy of Finland AKVA (Sustainable Governance of Aquatic Resources) Programme for funding this project (CONPAT Aquatic contaminants — pathways, health risks and management). We are very grateful to the reviewers who in their thoroughness have enabled a much improved paper to be produced.
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