The impact of on-site wastewater from high density cluster developments on groundwater quality

    The impact of on-site wastewater from high density cluster developments on groundwater quality P.J. Morrissey, P.M. Johnston, L.W. Gill PII: DOI: Reference:

S0169-7722(15)30012-7 doi: 10.1016/j.jconhyd.2015.07.008 CONHYD 3148

To appear in:

Journal of Contaminant Hydrology

Received date: Revised date: Accepted date:

16 April 2015 23 July 2015 31 July 2015

Please cite this article as: Morrissey, P.J., Johnston, P.M., Gill, L.W., The impact of onsite wastewater from high density cluster developments on groundwater quality, Journal of Contaminant Hydrology (2015), doi: 10.1016/j.jconhyd.2015.07.008

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ACCEPTED MANUSCRIPT The impact of on-site wastewater from high density cluster developments on

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groundwater quality

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Morrissey P.J, Johnston P.M., Gill L.W.

College Dublin, College Green, Dublin 2, Ireland

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Department of Civil, Structural and Environmental Engineering, Museum Building, Trinity

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(email: [email protected], [email protected], [email protected])

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ACCEPTED MANUSCRIPT Abstract The net impact on groundwater quality from high density clusters of unsewered housing across a

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range of hydro(geo)logical settings has been assessed. Four separate cluster development sites

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were selected, each representative of different aquifer vulnerability categories. Groundwater samples were collected on a monthly basis over a two year period for chemical and

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microbiological analysis from nested multi-horizon sampling boreholes upstream and

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downstream of the study sites. The field results showed no statistically significant difference between upstream and downstream water quality at any of the study areas, although there were

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higher breakthroughs in contaminants in the High and Extreme vulnerability sites linked to high intensity rainfall events; these however, could not be directly attributed to on-site effluent.

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Linked numerical models were then built for each site using HYDRUS 2D to simulate the

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attenuation of contaminants through the unsaturated zone from which the resulting hydraulic and contaminant fluxes at the water table were used as inputs into MODFLOW MT3D models to

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simulate the groundwater flows. The results of the simulations confirmed the field observations

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at each site, indicating that the existing clustered on-site wastewater discharges would only cause limited and very localised impacts on groundwater quality, with contaminant loads being quickly dispersed and diluted downstream due to the relatively high groundwater flow rates. Further simulations were then carried out using the calibrated models to assess the impact of increasing cluster densities revealing little impact at any of the study locations up to a density of 6 units/hectare with the exception of the Extreme vulnerability site.

Keywords: on-site wastewater, septic tank, cluster developments, vadose zone, modelling

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ACCEPTED MANUSCRIPT 1. Introduction Limited research appears to have been carried out to investigate the impacts of the density of

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domestic wastewater treatment systems (DWTSs) on groundwater quality. Field research across the world has often focussed on how treated effluent from different on-site treatment systems

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disperses into the subsoil through the percolation area and how pollutants are attenuated (e.g. Beal, et al., 2008; Gill et al., 2007, 2009; Jenssen and Siegrist, 1990, Van Cuyk et al., 2001).

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However, it is uncertain what the effects of higher hydraulic and contaminant loads generated by

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a cluster development or grouped development would be when discharged into a concentrated area. This situation occurs in many rural areas whereby single dwellings incorporating on-site

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waste water treatment systems tend to be constructed in a clustered arrangement, typically following a “ribbon” of dwellings along local roadways. Many field studies have associated high

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densities of DWTS with increasing groundwater nitrate concentrations down-gradient, for

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example Close et al. (1989) and Pang et al. (2006) in New Zealand, Andersen et al. (2006) in Florida (USA) and Meile et al. (2010) in Georgia (USA), but there have been few attempts to

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determine critical densities which could be incorporated into local or national policies. The issue of septic tank density and groundwater contamination was studied by Yates (1985) in the United States who reported that the United States Environmental Protection Agency (USEPA) has designated areas with septic tank densities of 1 or more systems per 16 acres (6.48 hectares / 6.48 x104 m2) as regions of potential groundwater contamination; however, the minimum lot size required for the inclusion of a septic tank was only 0.47acres (0.19 hectares). In Australia, Gardner et al. (1997) determined that a minimum plot size of 0.25 hectares should be the limit on the basis of nutrient and hydraulic loading rates (as well as statutory set-back distances). For low permeability soils their study also recommended an additional 0.15 hectares giving a minimum 3

ACCEPTED MANUSCRIPT plot size of 0.4 hectares in such scenarios. Finally, there have been attempts to model the water table mounding beneath high densities of percolation areas (Poeter and McCray, 2008) but this

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has not been developed further to determine contaminant pollution of the underlying aquifer.

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Groundwater is an important resource in the Republic of Ireland both from a water supply perspective as well as an environmental perspective as the baseflows in Irish rivers during dry

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weather periods are generally supported from groundwater sources. Approximately one third of

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the Irish population is served by decentralised DWTSs (CSO, 2011) many of which have been built to older standards and it is not known what the combined effects of groups of treatment

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systems in a relatively dense arrangement may have on groundwater quality, particularly in areas of varying hydro(geo)logical settings. Indeed, there have been a number of recent legislative

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documents in Ireland that have defined national policy with respect to the siting and installation

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of a single DWTS, but no guidance on whether there should be a limit on the density of DWTSs imposed under different hydrogeological conditions. Gill et al. (2009) estimated empirically that

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an upper limit of one house every third of a hectare might be appropriate with respect to the

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density of DWTSs in an area to meet the requirements of the EU Nitrates legislation. However, this estimate was based on an extrapolation of previous field research on contaminant transport down through the vadose zone, rather than actual field monitoring of groundwater quality downstream of such DWTSs. Hence, given that much rural development in Ireland is in the form of cluster or ribbon type along roads, the aim of this research was to quantify the impact of nutrient and microbial pollution on groundwater downstream of several cluster developments in different aquifer hydro(geo)logical settings. These studies were carried out in a temperate climate in areas with heterogeneous glacially deposited subsoils overlaying mainly fractured bedrock systems - a typical scenario for many northern European and northern American areas

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ACCEPTED MANUSCRIPT impacted by glaciation during the last the ice age. This was achieved by specific field monitoring of groundwater quality upstream and downstream of cluster developments in addition to linked

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numerical modelling of the pollutant transport and attenuation in the vadose zone and

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groundwater which was used both to corroborate the field investigations and then provide further

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insights into the impact of increasing house density on groundwater quality.

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2. Materials and methods

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2.1 Site selection

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Groundwater quality was monitored upstream and downstream of relatively high density clusters of DWTSs over an extended period of time in four study areas, each classified as having

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a different groundwater vulnerability. Vulnerability is determined and mapped by the Geological

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Survey of Ireland by a combination of factors such as the leaching characteristics of the topsoil, the permeability and thickness of the subsoil, the thickness and properties of the unsaturated

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zone, the type of aquifer (defined as poor, locally important or regionally important – see Supplemental information) and the amount and nature of groundwater recharge (Misstear et al., 2008). Four suitable sites were chosen in The Naul, Co. Dublin (Low vulnerability), Rhode, Co. Offaly (Moderate vulnerability), Carrigeen, Co. Kilkenny (High vulnerability) and Faha, Co. Limerick (Extreme vulnerability) (Fig. S.1) with catchment characteristics given in Table 1.

2.2 Instrumentation Boreholes were drilled specifically for this study using an Air Rotary Casing Hammer drilling rig, one upstream and two downstream of each cluster system in order to provide sampling 5

ACCEPTED MANUSCRIPT locations for groundwater monitoring. The first downstream boreholes were located approximately 50 – 100 m from the centre of the cluster, with the second downstream boreholes

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approximately 100 – 300 m further away. A nested array of 52 mm diameter piezometers was

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then installed in each of the boreholes typically containing three horizons; one in the saturated zone above the bedrock (if present), one in the bedrock subsoil interface (transition zone) and

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one approximately 5 m into the bedrock. This arrangement enabled monitoring of contaminants

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moving downwards into the aquifer as well as spatially as they travelled with the groundwater local gradient. Pumping tests were undertaken at each of the nested piezometers to ensure the

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independence of each sampling horizon. Borehole logs were kept from each hole as shown on the schematic cross-section on Fig. 1 for the Low vulnerability site in Co. Dublin (see Figs S.2 to

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S.4 in Supplementary Information).

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A topographical survey was carried out at all of the study locations using a Trimble 4700 GPS System to determine accurate co-ordinates and elevations of the tops of monitoring boreholes

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(and therefore accurate depths of piezometers), riverbeds/streambeds and locations of treatment

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systems/percolation area.

Falling head soil percolation tests were carried out in accordance with EPA (2009) at all of the study sites to define a T-value from which an estimate of the field saturated hydraulic conductivity of the subsoil could be derived at a depth representative of where the infiltrating effluent would enter the subsoil.

2.3 Field monitoring and water quality analysis Samples were collected from each of the monitoring boreholes on a monthly basis over a 2 year period from November 2010 to November 2012. At each site visit, each piezometer was purged

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ACCEPTED MANUSCRIPT of three times the borehole volume to remove stagnant water and draw in water representative of the quality of groundwater in the surrounding aquifer (ASTM, 2005). The water samples were

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transferred into 500 mL sterile autoclaved plastic sample bottles, labelled and transferred to a

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cooler box for transportation back to the Trinity College laboratory. Additional samples were taken for the determination of Total phosphorus which required 25 mL of water to be transferred

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to sterile 50 mL borosilicate glass bottles using a sterilised 25 mL graduated cylinder. All sample

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bottles were cleaned thoroughly between uses and then sterilised at 121C for 20 minutes using a Hirayama HV-25 Autoclave. A number of water sample parameters were measured on-site

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including: temperature, Electrical Conductivity (EC), pH and water level in each piezometer. In the laboratory, samples were analysed for the presence of Enterococcus faecalis using the

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membrane filtration method according to the Certified Laboratory Standard Methods (APHA,

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2005). The determination of E. coli was carried out using membrane filtration incubated on Lauryl Sulphate Broth for 18 hours at 44°C. Water samples were also analysed for ammonium

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(NH4-N), nitrate (NO3-N), nitrite (NO2-N), total nitrogen (N) and chloride (Cl) using a Merck

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Spectroquant Nova 60 spectrophotometer and the associated USEPA approved reagent test kits. The ascorbic acid test method (involving addition of ascorbic acid and ammonium molybdate reagents to the sample followed by spectrophotometric measurement) was selected for the determination of total dissolved phosphorus (ortho-P) due to the typically low concentrations. Bromide was analysed on samples for two monthly sampling cycles (to investigate the Cl/Br ratios) using a Bromide Ion-Selective Electrode (ELIT 8271). Slug tests were carried out in accordance with British Standard ISO 14686:2003 on all piezometers located in the bedrock horizon to estimate a value for transmissivity as well as hydraulic conductivity (K) of the aquifer. Soil samples were taken from the excavated holes used

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ACCEPTED MANUSCRIPT for the falling head percolation tests at each of the study areas and a particle size distribution analysis was undertaken to determine soil texture. The particle size properties were determined

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by wet sieve analysis according to British Standard 1377 1990. X-ray Diffraction Analysis

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Dublin to determine the mineralogy (see Figs. S.5 to S.8).

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(XRD) was also carried out on the soil samples by the Geology Department in Trinity College

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2.4 Modelling the unsaturated zone

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Numerical modelling of pollutant attenuation in the vadose zone and groundwater dilution and dispersion in the saturated zone were carried out to provide insight into the collected field data as

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well as to confirm that the upstream and downstream boreholes were indeed upstream and downstream of the cluster developments.

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HYDRUS 2D/3D (vers 2.02) was used to model the unsaturated zone from which the results

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were then fed into a regional groundwater model using Groundwater Vistas to determine the direction of groundwater movement and potential dilution and dispersion of DWTS effluent

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plumes. HYDRUS simulates variably saturated transient water content and volumetric flux using a numerical solution to the Richards’ equation (Šimůnek, 2007). The Fickian-based convectiondispersion equation was used to model nitrogen and phosphorus transport. An additional attachment-detachment module contained within HYDRUS was also used for modelling the transport of bacteria. The mixed form of the Richards’ equation (Richards, 1931) describes water flow in the variably-saturated vadose zone with the HYDRUS software using finite elements to determine a numerical solution to the analytic equation. In addition to calculating pressure heads throughout the model space, the convection-dispersion solute transport equations can also be implemented. 8

ACCEPTED MANUSCRIPT The solute transport equations allowed for the effects of both first-order degradation (independent of other solutes), and first-order decay (and also production) reactions, which,

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therefore, allowed sequential first-order chain reactions to be reflected accurately (Šimůnek &

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van Genuchten, 2006). The approach was used to model nitrogen species taking into account both the nitrification and denitrification reactions that occur in the soil. The results of the falling

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head percolation tests carried out at each of the study sites were used to calibrate 2D inverse

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models from which the appropriate soil hydraulic parameters were determined. The 2D model domain was setup using the dimensions of a typical DWTS percolation area

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with parallel infiltration trenches receiving distributed effluent as per the national legislation (EPA, 2009). To simplify the model, the trench and surrounding subsoil were assumed to be

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symmetrical about the centre line of the trench and thus only half of the domain geometry needed

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to be simulated. A second modelling scenario (Scenario 2) took account of the fact that poor building practices often result in all the effluent heading down a single percolation trench instead

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of being evenly distributed between several parallel trenches. The boundary conditions used for

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these model setups were atmospheric boundary condition with surface runoff at the surface, variable flux at the base of the trenches and constant head at the base which was set to the average measured groundwater depth at each site. These 2D direct models with water and solute transport were used to determine the contaminant loading and concentrations at the water.

2.5 Modelling groundwater flow Three-dimensional distributed finite difference models were developed for each study catchments using the MODFLOW package of Groundwater Vistas (Advanced vers. 6). Each catchment was divided up in layers or blocks, and then finite difference numerical techniques 9

ACCEPTED MANUSCRIPT were used to solve a series of differential equations to describe the different types of flow in the catchment (McDonald and Harbaugh, 1988). Topographic information from a Digital Elevation

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Model (DEM) was merged with any other available topographic surveys of the study areas

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including river beds using ArcGIS (vers. 10.0) to populate the model space. The resultant shapefiles were then exported to Surfer 10, which was used to fill a grid using Kriging

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interpolation at 20 m intervals. Depth-to-bedrock information was created with the data extracted

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from drilled borehole and rockhead data acquired during the course of this study in addition to information gathered from existing wells and boreholes. Catchment groundwater divides were

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calculated using ArcHydro tools and were set as no flow boundaries. Rivers/streams were set as river boundaries. Ditches and drains were set as drain boundaries. The base of the catchment

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was set as the catchment outlet and set as a constant head boundary. The boreholes that were

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monitored along with any other groundwater heads that were available (river levels etc.) were set as target heads to calibrate the model. Values for hydraulic conductivity and specific storage

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were estimated based on all available information including pumping tests carried out on the

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boreholes during this study. Models were then executed using the MODFLOW package of Groundwater Vistas adjusting parameters to calibrate the models against available target head values across each catchment. Following calibration in steady state for water flow only, the MT3D contaminant package was run for the various contaminant packages, again for steady state water flow conditions for a period of one year. The MT3D package for MODFLOW is a modular three-dimensional transport model for simulation of advection, dispersion/diffusion, and chemical reactions of contaminants in groundwater flow systems (Zheng and Wang, 1999). All of the contaminants were added to the input using an area of recharge analogous with the area of the plume at the water table as determined from the HYDRUS modelling. The recharge flux was

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ACCEPTED MANUSCRIPT set to that predicted by HYDRUS (m/day) and the contaminants were added as respective concentrations in that incoming recharge water. Following the initialisation period, the models

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which time a ‘quasi steady state’ developed within the model.

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were then ran under transient flow and effluent loading conditions for a period of three years by

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3. Field results

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The results from the field studies are presented for each of the four study sites in the following

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areas: rainfall, subsoil conditions, field measurements, nitrogen, phosphorus and bacteria.

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3.1 Rainfall and subsoil

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A summary of the annual average rainfall across the four study sites with annual average potential evapotranspiration (ET0) is given in Table 1. Results of the falling head percolation

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tests and the equivalent Ks values together with the soil textural classifications are given in Table 2. Ks values ranged from 0.06 – 0.21 m/d with subsoil at each of the sites containing varying proportions of clay. The XRD analysis of the soil samples (see Supplemental Information) found that all samples contained lithian muscovite and ordered albite; both of these minerals contain aluminium oxide hydroxide, which has been found to adsorb phosphorus. In addition, the subsoils at the Moderate and High vulnerability sites also contained calcite and quartz. The subsoil from the Extreme vulnerability site additionally contained dolomite indicating the likely dolomitisation of the underlying limestone bedrock.

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ACCEPTED MANUSCRIPT 3.2 Water levels and EC Water levels (mOD) were monitored at the boreholes at each of the study sites between

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November 2010 and October 2012, as shown in Fig. 2. Due to initial clogging of fines at the Low vulnerability site this monitoring period was curtailed whilst remediation steps were undertaken.

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Water levels at the Low vulnerability site were not responsive to rainfall with relatively static water levels observed during the period monitored, as would be expected. A trend in monitored

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EC values was observed (see Fig. S.9) with lower values observed during winter months and

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higher values during the summer (total range 200 – 600 µscm-1). Given the seasonal nature of this trend, it is likely that the increased summer levels were due to local agricultural practices

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and not nearby DWTSs. The water levels at both the Moderate and High vulnerability sites were very responsive to rainfall with levels observed fluctuating either in sync or with a time lag

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depending on months with higher rainfall amounts. Again, the EC values measured during this period revealed a similar seasonal pattern to that observed at the Low vulnerability site, ranging

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between 220 – 850 µscm-1 (Moderate vulnerability) and more muted variations between 300 –

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400 µscm-1 (High vulnerability). The water levels over time at the Extreme vulnerability site indicate the existence of a more complicated groundwater flow regime. Water levels were responsive to rainfall, however the nature of the response was complicated by the influence of the nearby tidal river Maigue. The study site was located less than 500 m from the river bank and less than 2000 m from the Maigue estuary. A comparison of 24 hour tidal levels (data from the Irish Marine Institute) and water levels in the boreholes showed that each of the boreholes could be shown to respond to the river’s tidal influence at different time shifts depending on borehole location and depth. EC

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ACCEPTED MANUSCRIPT values over the monitored period indicate the seasonal fluctuations (as seen at the other sites) but

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with higher baseline values with no value falling below 550 – 600 µscm-1.

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3.3 Nitrogen

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3.3.1 Low vulnerability site

Single factor analysis of variance (ANOVA) statistical analysis between upstream and

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downstream monitoring boreholes revealed no significant difference in nitrate concentrations at

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either of the sampling horizons (p-values of 0.566 for horizon 2 (n = 45) and 0.878 for horizon 3 (n = 45)) with very low mean concentrations both upstream (0.165 mg-N/L) and downstream

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(0.168 mg-N/L) of the cluster of DWTSs – see Table 3 and Fig. S.10 for details. Other forms of nitrogen such as nitrite and ammonium were below the levels of detection across the study

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period. No relationship to rainfall events was found (Pearson’s correlation coefficient, r = 0.164).

3.3.2 Moderate Vulnerability Site Nitrate values ranged from 0.5 to 13.2 mg-N/L across the sampling period (see Table 4) and revealed a clear trend in all boreholes of higher concentrations during the winter months with lowest values recorded in the autumn months (Fig. 3); this is generally consistent with previous studies in Ireland on nitrate leaching to groundwater (Fenton et al., 2009). Again, nitrite and ammonium levels were below the levels of detection (0.002 and 0.016 mg-N/L respectively) across the study period. 13

ACCEPTED MANUSCRIPT Single factor ANOVA tests between the two sampling horizons both upstream and downstream did show a significant difference between mean nitrate concentrations at the

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shallower horizon (horizon 1). This was due to the upstream borehole having higher mean nitrate

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concentrations (6.82 mg-N/L) than the downstream borehole results (3.43 mg-N/L), indicating that nitrate concentrations were actually reducing downstream of the cluster development. There

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was no clear trend between rainfall and the recorded levels of nitrates; however rainfall levels

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were influencing water levels in the boreholes as discussed in Section 3.2.

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3.3.3 High vulnerability site

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Statistical tests comparing upstream and downstream mean nitrate concentrations yielded an ANOVA p-value of 0.065 (n = 69), close to the 0.05 level of significance. However, mean nitrate

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concentrations decreased downstream of the DWTS cluster falling from a mean value of 6.3 mg-

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N/L upstream to 5.1 mg-N/L downstream (see Table 4); again other forms of nitrogen were below the levels of detection across the study period. A weak correlation (but statistically

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insignificant, r = 0.24) between rainfall and nitrate values was found indicating higher nitrate levels during months with higher rainfall as can be observed on Fig. 4. This is similar to what was found previously by other research in Ireland (Hynds et al., 2012) and has been attributed to nutrients being washed into the groundwater during heavy rainfall events.

3.3.4 Extreme vulnerability site All forms of nitrogen were recorded at some or all of the boreholes across the study period with nitrate found consistently and other forms found on a more sporadic basis. Nitrate values across the sampling period (ranging from 0.2 – 9.8 mg-N/L) again revealed a trend of higher values 14

ACCEPTED MANUSCRIPT occurring during the winter months – see Fig.5. Statistical tests comparing upstream and downstream mean nitrate concentrations did show significantly higher concentrations

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downstream of the study site, possibly indicating impacts on groundwater quality from the

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DWTS cluster at this site. However, the downstream values were always within 0.2 mg-N/L of those found upstream.

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Elevated levels of nitrite in a groundwater sample in this area with a shallow groundwater

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table (typically only 1-5 to 2 m depth) indicates incomplete nitrification (in the subsoil), either as a result of the particular geological conditions in the area (such as the subsoil properties) and/or

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relatively close pollution. This indicates that the pollutants are being transported into the groundwater aquifer quickly, which might be expected at this Extreme vulnerability site.

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Pearson’s correlation analysis carried out between nitrate, nitrite and ammonium concentrations

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showed a weak to moderate correlation between NO2 and NH4 with over 50% of the comparisons made having a correlation coefficient of 0.4 or higher (and 20% with correlation

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coefficients greater than 0.5). These weak to moderate correlations indicate that at times of the

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year when values of NH4 and NO2 were recorded there was either a large pollutant load added at the surface (such as slurry spreading or cattle grazing) or the pathway to groundwater was shortened in duration due to high rainfall. Although a very weak correlation was found between these values and monthly rainfall, it is hypothesized that these higher values were caused by much shorter intense rainfall events (which would effectively be damped out in the cumulative monthly data) and therefore illustrate the vulnerability of the groundwater to pollution in these areas.

3.4 Phosphorus, chloride and bromide

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3.4.1 Low vulnerability site

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No trend in ortho-P values was observed during the study and single factor ANOVA analysis between borehole locations at the two sample horizons did not show a significant difference

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between upstream and downstream ortho-P levels (p-values of 0.174 and 0.303 respectively – Table S.1). Chloride values ranged from 3.8 to 45.7 mg/L and no significant difference in mean

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chloride concentrations with depth or between upstream and downstream values was found

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(Table S.2). Chloride and bromide ions have been used to differentiate between various sources of anthropogenic and naturally occurring contaminants in groundwater due to their conservative

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nature. Previous studies have suggested that the ratio of chloride to bromide (Cl/Br) ions by mass can point to the source of the ions in a water sample. Katz et al. (2010) suggested that ratios

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between 400 to 1100 can be attributed to chemical constituents associated with human activities -

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in this case pollution owing to DWTSs. Cl/Br mass ratios recorded at this location during the

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study ranged between 202 and 339.

3.4.2 Moderate vulnerability site Ortho-P concentrations appeared to follow a trend with higher values recorded during the period March – June (mean 61 μg-P/l) and lower values during the rest of the year (mean 41 μg-P/l – see Supplementary Information Table S.1 for full details). Statistical tests indicated no significant difference between mean ortho-P concentrations with depth (p-value = 0.874, 0.828) into the aquifer or any significant difference between upstream and downstream P concentrations (p-values = 0.533, 0.074, 0.971); in addition no clear relationship with rainfall was observed. 16

ACCEPTED MANUSCRIPT Chloride values ranged from 9.4 to 136 mg/L with a trend of higher values in December and February/March. No statistical difference was found with depth or between upstream and

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downstream values. In addition none of the sampling horizons had Cl/Br mass ratios in the range

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that might indicate nearby anthropogenic pollutants (range = 55 to 417).

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3.4.3 High vulnerability site

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Ortho-P values were higher in winter/spring period compared to the summer/autumn period,

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consistent with recorded nitrate trends. No significant difference was found between the different depth horizons or between the upstream and downstream ortho-P concentrations (p-value of

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0.801).

Chloride values ranged from 7.9 to 86 mg/L during the study period with a seasonal trend of

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higher concentrations during spring and early summer periods. Statistical tests between means at

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the different horizon depths did not yield a significant result and neither did the comparison between upstream and downstream chloride concentrations (p-value of 0.763). Cl/Br mass ratios

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of 532 and 591 were recorded during one sampling period in October 2012 at the downstream borehole lower depth horizons. This corresponded to a period of heavy rainfall following a few weeks of extremely dry weather in September. However, given that DWTSs tend to produce a constant loading output throughout the year and given that at most other times of the year, the water quality was generally better downstream of the cluster. It is possible that this may have been an isolated instance.

3.4.4 Extreme vulnerability site

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ACCEPTED MANUSCRIPT Ortho-P concentrations were in the range 25 to 100 μg-P/L. Comparisons between mean concentrations with depth at each of the boreholes resulted in statistically insignificant outcomes

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indicating that phosphorus concentrations did not vary significantly with depth. Equally,

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differences compared between upstream and downstream mean phosphorus concentrations across the 3 sampling horizons returned insignificant outcomes. Chloride concentrations ranged

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between 15 and 75 mg/L with no significant difference found neither between mean values at the

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different horizon depths nor between upstream and downstream sampling horizons.

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Chloride/bromide mass ratios were in the range 83 – 237.

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3.5.1 Low vulnerability site

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3.5 Indicator bacteria

E. coli and Enterococci were generally absent from samples taken during the study and no clear

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trend of occurrence with either time or rainfall emerged. ANOVA analysis between upstream

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and downstream E. coli and Enterococci numbers did not yield any significant differences between each borehole location (p-values of 0.853 and 0.376 for horizons 2 and 3).

3.5.2 Moderate vulnerability site E. coli occurrences were either very low or absent altogether during the course of the study with the exception of a number of peaks (up to a max of 25 CFU/100 mL) at the shallowest sampling level (just 2.5 m depth into the subsoil) in the second borehole furthest downstream (see Supplementary Information Table S.2 for summary statistics). Due to the isolated nature of these peaks and distance from the cluster development (~250 m), this was most likely to be a result of

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ACCEPTED MANUSCRIPT localised agricultural practices in the vicinity of the borehole. Neither E-coli nor Enterococci results showed any significant difference between upstream and downstream values when the

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isolated peaks recorded for the shallow sampling depth at the furthest downstream borehole were

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removed.

A more detailed analysis of these indicator organisms was undertaken in relation to the

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antecedent quantities of rainfall, using a similar technique as carried out previously by Hynds et

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al. (2012). Rainfall was summed for the preceding 24, 48, 120 hours and 21, 30, 45 and day periods. A relationship (if one exists) was then established between rainfall and the presence or

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absence of the indicator bacteria groups. The results revealed a highly significant (p-values 0.002), relationship between Enterococci and E. coli numbers with the 30 day cumulative

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antecedent rainfall at this location.

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3.5.3 High vulnerability site

E. coli occurrences were more frequent and reached higher peaks than at either of the two

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previous study locations with peaks picked up between December to March and also between July to October up to maximum concentrations of around 50 cfu/100ml as shown in Fig. 6 below. Differences between upstream and downstream E. coli numbers were statistically insignificant even though mean upstream E. coli numbers were higher (2.3 cfu/ 100mL) than downstream (1.04 cfu/100 mL) with Enterococci analysis providing similar results (see Table S.3). Regression analysis using the rainfall intervals outlined previously gave a significant result for the 24 hour rainfall interval for E. coli with a highly significant p-value of 0.007.

3.5.4 Extreme vulnerability site 19

ACCEPTED MANUSCRIPT Occurrences of E. coli and Enterococci bacteria indicated clear peaks during two distinct periods of the year - March to April and August to October - ranging from 10 to 60 cfu/100 mL as shown

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in Fig. 7 below (and Table S.3). Enterococci concentrations increased with depth into the aquifer

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with a p-value of 0.01 for the upstream borehole and 0.05 for the second downstream borehole; however, the statistical tests for E-coli concentrations with depth yielded insignificant p-values

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of 0.07 and 0.12 for the same boreholes. Both indicator bacteria species had a similar outcome in

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the statistical analysis between upstream and downstream concentrations which did not yield significant results. The regression analysis using summed daily rainfall intervals gave highly

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4.1 Vadose zone

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4. Modelling results

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and E. coli (p-values 0.0001 and 0.006).

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significant results for both 24 and 48 hour cumulative antecedent rainfall for both Enterococci

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HYDRUS 2D was used in order to calibrate the soil hydraulic properties based on field work carried out during this study and then used to model contaminant fluxes through the unsaturated zone to provide inputs to the groundwater flow modelling. Particle size distribution analysis from the soil samples taken at the sites, in conjunction with the results from the falling head percolation tests were used to calibrate the models for soil hydraulic parameters using the inverse solution code contained within HYDRUS 2D. This resulted in the soils at the four sites being modelled with the following saturated hydraulic conductivity values (Ks): 0.84 cm/h for the Low vulnerability site; 0.5 cm/h for the Moderate vulnerability site; 0.875 cm/h for the High vulnerability site; and 0.25 cm/h for the Extreme vulnerability site. Note, the lower value of Ks at the Extreme vulnerability site can be explained by the fact that vulnerability is determined by a 20

ACCEPTED MANUSCRIPT combination of several factors (as described in Section 2.1) two of which are the depth of the unsaturated zone (which is very shallow) and the type of aquifer (which is Regionally Important

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in this area).

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Models were run for two different qualities of DWTS effluent, Septic Tank Effluent (STE) and Secondary treated Effluent (SE) using concentrations, loading rates and derived attenuation

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rates for the different contaminants as gained previous studies in Ireland on 6 different subsoil

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types by Gill et al. (2007; 2009). As the DWTSs on the field sites have been in operation for extended periods of time, the 2D models were setup for a simulation period of 11 years (4017

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days) to simulate the long term contaminant loads to the water table, with the first year used provide appropriate initial conditions for a continuous 10 year set of results. Recharge from

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rainfall was input at the ground surface which was calculated using the appropriate recharge

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coefficient for the soil type (Misstear et al., 2008), daily effective rainfall and the corresponding values for potential evapotranspiration.

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Nitrogen was modelled as a solute chain reaction with kinetic coefficients determined from

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the detailed Irish field studies across a range of subsoil types. As per previous field studies the HYDRUS simulations (for all four soil types and model setups) showed that NH4 concentrations did not migrate further than 1.15 m below the base of the percolation trenches being nitrified in the unsaturated conditions. Nitrate concentrations however, did migrate downwards and formed plumes beneath the percolation trenches after 2 years of simulations with differing maximum concentrations for STE and SE loading, as shown on Fig. 8. The predicted NO3 concentrations at the water table interface for a DWWT on each site is given in Table 4 and also Fig. 9, showing highest fluxes to the water table at the Moderate and Extreme vulnerability sites (mainly due to the water table being present at a shallower depths on these sites). At the Low vulnerability site

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ACCEPTED MANUSCRIPT the model showed that the nitrate plume would not yet have reached the groundwater through the low permeability clay subsoil. Ortho-P was found to be largely attenuated within the first metre

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of subsoil beneath the percolation trenches in the previous Irish field studies which was again

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was well simulated in the model – see Fig. 10. Equally, field studies have shown very high removal rates up to 5 log (99.999%) of bacteria have been found within the first metre of subsoil

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beneath the percolation trenches in previous Irish studies which were again well simulated.

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4.2 Groundwater modelling

The groundwater model for all four study areas simulated the direction of groundwater flow (see

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equipotential results in Figs. S.11 to S.14) which confirmed that the “downstream” boreholes were indeed downstream of the cluster systems. Input values for contaminant fluxes of nitrate

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and ortho-P were taken from the HYDRUS 2D simulation outputs at the groundwater table and

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were simulated as conservative tracers in the groundwater modelling (i.e. only attenuated by groundwater dilution). An example of the nitrate plume at the Moderate vulnerability site is

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shown on Fig. 11 whereby the contaminant plume from the DWTS cluster does not reach the first downstream monitoring borehole, BH-O2. At the High vulnerability site the simulation showed some combination between individual systems plumes forming, but the concentrations of nitrate in this plume were low and again the plume did not extend more than 180 m downstream of the cluster development. The transport of bacteria in the aquifer was not treated as a non-reactive tracer due to the natural die-off that occurs over time. For the steady state model a removal rate at the lower end of the reported values of 0.7 d-1 was used (Jiang et al., 2010) as this was deemed to be a conservative approach. It was also assumed that 50% of the systems in each cluster would have 22

ACCEPTED MANUSCRIPT been poorly constructed whereby a single percolation trench received the entire effluent load (i.e. Scenario 2). MT3D did not predict any significant plume of bacteria downstream of the cluster

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developments at the Low, Moderate or High vulnerability sites. All of the bacteria were removed

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within 60 m of the cluster with most being removed within 30 m. For the Extreme vulnerability site however, the simulation did show a plume of concentration 1 cfu/L migrating almost 300 m

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downstream of the cluster development (Fig. 12) with a localised plume of 2 cfu/L developed in

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the vicinity of the DWTSs which had been modelled through the unsaturated zone by an overloaded trench (i.e. Scenario 2). Also shown in Fig. 12 are the average bacteria concentrations

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at each of the boreholes during the study. It can be seen that at horizon c of the closest downstream borehole (BH-L2), the results for E-coli and Enterococci are similar to those

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estimated by the model. However, the average concentrations measured in both the upstream

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borehole (BH-L1) and the more distant downstream borehole (BH-L3) are higher than those predicted by the modelling. This can mainly be attributed to a number of very high spikes in

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concentrations that were recorded during the study which, as discussed in Section 3, coincided

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with spikes in all forms of nitrogen indicating a localised source of pollution entering the groundwater very quickly before nitrification could take place. The fact that both upstream and downstream concentrations of E. coli and Enterococci respectively were similar would also suggest that these levels are not associated with the DWTS cluster, but with other sources which are not being explicitly modelled.

5. Discussion The field monitoring results indicated that the clusters of DWTSs did not appear to be having a significant negative impact on groundwater quality in any of the different sites monitored. 23

ACCEPTED MANUSCRIPT Statistical analysis of the results showed that in nearly all scenarios, mean concentrations of all parameters monitored were similar upstream and downstream of the clustered developments

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regardless of the groundwater vulnerability. Bacterial spikes in groundwater were recorded

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following intense rainfall events and shown by regression analysis to be correlated particularly in higher vulnerability locations, but the source of such contamination could not be explicitly linked

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to the clusters of DWTSs.

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The vadose zone models (validated against previous field trials in percolation areas carried out across a range of Irish subsoils) confirmed that the thickness of unsaturated subsoil beneath

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the percolation area is a critical factor with respect to the magnitude of the concentrations of contaminants entering groundwater. When linked with the groundwater flow models for each

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cluster in an innovative approach for modeling the net impact of groups of on-site systems from

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their individual specific locations, the simulations showed that the expected plumes of contaminants from clusters of DWTSs tend to be very localised, with most not spreading

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significantly further than 250 m downstream, whilst the more mobile contaminants (particularly

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NO3) were seen to migrate up to 500 m downstream of the clusters. Further simulations were then carried out using the linked models to assess the impact of increasing cluster densities up to a density of 6 units/ hectare – the increase in densities was undertaken assuming that any new systems added would have secondary treatment systems installed. In general these simulations at each of the study areas all indicated the same findings; whilst increasing the density of DWTSs does increase the concentrations of pollutants within the localised plumes, the effects further downstream are significantly muted and have dissipated within 250 – 500 m downstream. The Extreme vulnerability site did show the highest impact on groundwater quality as shown in Fig. 13 below. It can be seen that whilst the plume did

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ACCEPTED MANUSCRIPT propagate a short distance (~150 m) further downstream in the 4 units/ hectare scenario, the relative concentrations within the plume were low (only 0.1 mg-N/L). Similar results were found

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for the scenarios involving bacteria with a density of 6 units/ha leading to the propagation of the

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1 cfu/100 mL plume concentration contour approximately 160 m further downstream. The results of this study can be shown to be in broad agreement with the findings of Yates

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(1985) and Gardner et al. (1997) who suggested that 5 and 4 units/ hectare respectively would

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appear to be limits on acceptable density. These field results (and associated modelling) have been carried out in a temperate northern climate with effluent discharging into heterogeneous

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glacially derived subsoils overlying aquifers (certainly for the Moderate, High and Extreme vulnerability sites) which are representative of those characterised by secondary permeability

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(i.e. fractures / fissures) which may be enhanced by karstification (as is the case at the Extreme

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vulnerability site). The active zone of groundwater flow in such aquifers is generally tens of metres in thickness and transmissivity values usually exceed 100 m2/d. The Low vulnerability

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site is more representative of an aquifer where flow occurs in thin fracture zones (only a few

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metres in thickness) in the shallow bedrock, with transmissivities being less than 50 m2/day. It is clear that the typical ‘ribbon’ style of developments in Ireland would suggest that the development of a minimum plot size would be a more useful criterion as opposed to a specifying a specific density by groundwater vulnerability. A minimum plot size of 0.17 hectares would appear to be satisfactory to protect groundwater (a density of 6/ hectare) for all groundwater vulnerabilities with the exception of Extreme which would require a larger plot size of up to 0.28 hectares (or a density of 3.5/ hectare). The minimum plot size that is currently being used as a ‘rule of thumb’ by some Irish local authorities is 0.2 hectares and this would appear adequate for most cases particularly when the considerations regarding minimum distances from boundaries

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ACCEPTED MANUSCRIPT are taken into consideration; although no official national guidance exists. It is also clear that the recommendations of the EPA (2009) must be enforced particularly in higher vulnerability areas,

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as the thickness of subsoil beneath of DWTSs soil disposal area was found to be far more

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important compared to density for reducing the load to groundwater.

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6. Conclusions

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This study indicates that clusters of DWTSs under such hydrogeological conditions,

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representative of a temperate climate in areas with heterogeneous glacially deposited subsoils overlaying mainly fractured bedrock systems, did not appear to be having a significant negative

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impact on groundwater quality in any of the different sites monitored. Almost all scenarios found mean concentrations of all parameters were similar upstream and downstream of the clustered

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developments regardless of the groundwater vulnerability. Although some bacterial spikes were

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recorded following intense rainfall events, particularly in higher vulnerability locations, this could not be definitively attributed to DWTSs. It was noted that unless an adequate percolation

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area is incorporated in the DWTS construction, the soil will become overloaded and much higher contaminant loading will occur to groundwater. The field data corroborated by modelling results that were obtained by linking two models, one to simulate pollutant attenuation in the vadose zone for each DWTS which then fed into a more regional groundwater model which simulated dilution and dispersion of the DWTS point sources in the saturated zone. This approach indicated that the relative high groundwater flow rates and recharge in such fractured aquifers leads to significant dilution / dispersion downstream of any potential contamination from clusters of DWTSs up to a density of 6 units/ hectare with the exception of High and Extreme Vulnerability

26

ACCEPTED MANUSCRIPT sites where densities above 2.5 units/ hectare were modelled to show some minor impacts

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downstream.

Acknowledgements

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The authors gratefully acknowledge the support of the Environmental Protection Agency (EPA,

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Ireland) for funding this research under the Science, Technology, Research and Innovation for

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the Environment (STRIVE) 2007–2013 program..

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References

American Public Health Association, 2005. Standard Methods for the Examination of Water and

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Wastewater, 21st ed. Washington, DC: American Public Health Assoc., American Water

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Works Assoc., Water Environment Fed. American Society for Testing and Materials (ASTM), 2005. Standard Guide for Purging

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Methods for Wells Used for Ground-Water Quality Investigations. ASTM D6452-99. Andersen, Hazen, Sawyer, P.C., 2006. A review of nitrogen loading and treatment performance recommendations for onsite wastewater treatment systems (OWTS) in the Wekiva study area. Published Report. Available at: www.doh.state.fl.us/environment/ostds/wekiva. Accessed January 2013. Beal, C.D., Rassam, D.W., Gardner, E.A., Kirchhof, G., Menzies, N.W., 2008. Influence of hydraulic loading and effluent flux on surface surcharging in soil absorption systems. J. Hydrol. Eng. 13(8), 681-692.

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ACCEPTED MANUSCRIPT Close, M.E., Hodgson, L.R., Tod, G., 1989. Field evaluation of fluorescent whitening agents and sodium tripolyphosphate as indicators of septic tank contamination in domestic wells. NZ J.

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Marine Freshwater Resources 23, 563–568. CSO, 2011. Census 2011. Profile 4 The Roof over our Heads - Housing in Ireland, Central

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Statistics Office, Cork, Ireland.

Protection Agency, Wexford, Ireland.

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EPA, 2009. Code of Practice: Wastewater Treatment Systems for Single Houses. Environmental

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Fenton, O., Coxon, C.E., Haria, A.H., Horan, B., Humphreys, J., Johnston, P., 2009 Variations in travel time and remediation potential for N loading to groundwaters in four case studies in

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Ireland: Implications for policy makers and regulators. Tearmann: Irish J. Agri-Environ. Res.

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7, 129-142.

Gardner, T., Geary, P., Gordon, I., 1997. Ecological sustainability and on-site effluent treatment

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systems. Australian J. Env. Manag. 4, 144-156.

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Gill, L.W., O’Súilleabháin, C., Misstear, B.D.R., Johnston, P.M., 2007. The treatment performance of different subsoils in Ireland receiving on-site wastewater effluent. J. Env. Qual. 36(6), 1843-1855. Gill, L.W., O’Luanaigh, N., Johnston, P.M., Misstear, B.D.R., O`Suilleabhain, C., 2009. Nutrient loading on subsoils from on-site wastewater effluent, comparing septic tank and secondary treatment systems. Water Res. 43, 2739-2749. Hynds, P.D., Misstear, B.D., Gill, L.W., 2012. Development of a microbial contamination susceptibility model for private domestic groundwater sources. Water Resources Res. 48(12), W12504. 28

ACCEPTED MANUSCRIPT Jenssen, P.D., Siegrist, R.L., 1990. Technology assessment of wastewater treatment by soil infiltration systems. Water Sci. Technol. 2(3/4), 83-92.

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Jiang, S., Pang, L., Buchan, G.D., Šimůnek, J., Noonan, M.J., Close, M.E., 2010. Modeling water flow and bacterial transport in undisturbed lysimeters under irrigations of dairy shed

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effluent and water using HYDRUS-1D. Water Res. 44(4), 1050-1061. Katz, B.G., Eberts, S.M., Kauffman, L.J., 2011. Using Cl/Br ratios and other indicators to assess

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potential impacts on groundwater quality from septic systems: A review and examples from

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principal aquifers in the United States. J. Hydrol. 397, 151-166. McDonald, M.G., Harbaugh, A.W., 1988. A Modular Three-Dimensional Finite-Difference

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Ground-Water Flow Model, USGS TWRI Chapter 6-A1.

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Meile C., Porubsky, W.P., Walker, R.L., Payne K., 2010. Natural attenuation of nitrogen loading

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from septic effluents: Spatial and environmental controls. Water Res. 44(5), 1399–1408. Misstear B.D.R., Brown L., Daly D., 2008. A methodology for making initial estimates of

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groundwater recharge from groundwater vulnerability mapping. Hydrogeol. J. 17(2), 275-285. Pang, L., Nokes, C., Simunek, J., Kikkert, H, Hector, R., 2006. Modeling the impact of Clustered Septic Tank Systems on Groundwater Quality. Vadose Zone J. 5, 599–609. Poeter, E.P., McCray, J.E., 2008. Modeling water-table mounding to design cluster and highdensity wastewater soil absorption systems, ASCE J. Hydrologic Eng., 13(8), 710-719. Richards, L.A., 1931. Capillary conduction of fluid through porous mediums. Physics 1(5), 318– 333.

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ACCEPTED MANUSCRIPT Šimůnek, J., van Genuchten., M.Th., 2006. Contaminant Transport in the Unsaturated Zone: Theory and Modeling, Chapter 22 in The Handbook of Groundwater Engineering, Ed.

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Jacques Delleur, Second Edition, CRC Press, pp. 1-22. Šimůnek, J., van Genuchten, M.Th., Šejna, M., 2007. The HYDRUS Software Package for

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Simulating the Two- and Three-Dimensional Movement of Water, Heat, and Multiple Solutes in Variably-Saturated Media User Manual. PC Progress, Prague, Czech Republic.

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Van Cuyk, S., Siegrist, R., Logan, A., Masson, S., Fischer, E., Figueroa, L., 2001. Hydraulic and

systems. Water Res. 35(4), 953-964.

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purification behaviours and their interactions during wastewater treatment in soil infiltration

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Yates M.V., 1985. Septic tank density and ground-water contamination. Ground Water 23(5)

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586–591.

Zheng, C., Wang, P., 1999. MT3DMS, A modular three-dimensional multi-species transport

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model for simulation of advection, dispersion and chemical reactions of contaminants in

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groundwater systems. Documentation and user’s guide, U.S. Army Engineer Research and Development Centre, Vicksburg, MS, USA.

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Fig. 1 - Summary borehole logs with schematic cross section at Naul, Co. Dublin.

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Fig. 2 - Water level and rainfall variation over time at the study sites.

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Fig. 3 - Nitrate concentrations during the study period at the Moderate vulnerability site with monthly rainfall.

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Fig. 4 - Nitrate concentrations during the study period at the High vulnerability site with monthly rainfall.

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Fig. 5 - Nitrate concentrations during the study period at the Extreme vulnerability site with monthly rainfall.

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Figure 6 – Indicator bacteria concentrations during the study period with monthly rainfall at the High vulnerability site.

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Fig. 7 – Indicator bacteria concentrations during the study period with monthly rainfall at the Extreme vulnerability site.

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Fig. 8 - Nitrate concentration results (in mg-N/L) from HYDRUS 2D simulation the High vulnerability site for (a) STE, (b) SE, (c) overloaded single trench for STE and (d) SE.

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Fig. 9. Nitrate concentration results (in mg-N/L) from HYDRUS 2D simulations at (a) Low (b) Moderate (c) High and (d) Extreme vulnerability sites.

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Fig. 10 – Pollutant plume from HYDRUS 2D simulations for (a) ortho-P (STE; mg-P/L) and (b) Ammonia (STE; mg-NH4-N/L) at the Moderate vulnerability site.

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Fig. 11 - Steady state nitrate plume from the cluster development at the Moderate vulnerability site.

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Fig. 12 - Plume of bacteria concentrated predicted by MT3D from the DWTSs and average concentrations recorded at each borehole (red dot) during the field monitoring at the Extreme vulnerability site.

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Fig. 13 - Nitrate concentration plumes (mg-N/L) predicted by MT3D from increasing densities of DWTSs at the Extreme vulnerability site.

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ACCEPTED MANUSCRIPT Table 1. Catchment and cluster characteristics. Naul, Co. Dublin Low

Location Vulnerability†

Rhode, Co. Offaly Moderate

Carrigeen, Co. Kilkenny High

Faha, Co. Limerick Extreme Dinantian pure unbedded limestones

Namurian Mudstones & Sandstones

Dinantian pure bedded limestones

Devonian & Dinantian limestones

Subsoil†

Low permeability tills or clays (up to 40 m deep)

Low to moderate permeability tills (5 –15m deep)

Higher permeability tills (6m (or less) deep)

Soil type†

Drumkeeran: fine clayey drift with siliceous stones

Elton: fine loamy drift with limestones

Mean annual rainfall (mm)*

840

944

1015

870

Mean annual PE (mm)*

445

440

530

490

No. of DDWTS

21

11

17

20

0.30

0.18

0.20

1.04

2.44

2.04

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0.35

Density (Units/ha)

1.82

†

* data from Met Eireann

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Ave. plot size (ha)

from Geological Survey of Ireland

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Bedrock†

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Clonroche: fine loamy drift with siliceous stones

Shallow limestone till & alluvium (0 – 2m) Elton: fine loamy drift with limestones

ACCEPTED MANUSCRIPT Table 2 - Results of subsoil analysis at each of the study sites. T-value (mins/25mm)

Equivalent Ks (m/d)

Soil Textual Classification (BS5930)

Naul, Co, Dublin

22

0.20

SILT/CLAY

Rhode, Co. Offaly

30

0.12

Carrigeen, Co. Kilkenny

18.3

0.21

Faha, Co. Limerick

39

0.06

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Site Location

PSA Soil Classification (USDA)* LOAM CLAY

SILT/CLAY

sandy clay LOAM

CLAY

silt LOAM

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SILT/CLAY

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*Soil classification based on the soil particle soil analysis results and using the United States Department of Agriculture (USDA) method

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ACCEPTED MANUSCRIPT Table 3. Summary statistics for nitrate concentrations at each of the borehole horizons across the four sites (all values in mg/L)

Avg.

Downstream Borehole 1

Std. Dev

Avg.

Std. Dev

Low Vulnerability Site*

Downstream Borehole 2 Avg.

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Upstream Borehole

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Horizon

Std. Dev

Horizon 2

0.24 (n=15)

0.341

0.33 (n=15)

0.667

0.147 (n=15)

0.342

Horizon 3

0.087(n=15)

0.336

0.067 (n=15)

0.18

0.12 (n=15)

0.326

1.445

**

**

1.351

**

**

1.507

3.34 (n=23)

1.671

**

**

6.82 (n=23)

3.045

3.43 (n=23)

Horizon 2

4.08 (n=23)

1.572

3.24 (n=23)

Horizon 3

3.79 (n=23)

1.725

2.89 (n=23)

Horizon 1

**

**

Horizon 2

**

**

Horizon 3

6.30 (n=23)

2.764

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Horizon 1

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Moderate Vulnerability Site*

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High Vulnerability Site* 4.42 (n=23) 2.104 4.90 (n=23)

1.929

**

**

5.10 (n=23)

2.184

**

**

1.47 (n=23)

Horizon 2

0.93 (n=23)

Horizon 3

1.48 (n=23)

2.001

**

**

1.82 (n=23)

2.881

1.184

**

**

1.18 (n=23)

1.864

2.307

1.66 (n=23)

2.407

1.01 (n=23)

1.369

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Horizon 1

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Extreme Vulnerability Site*

*Due to local ground conditions and site access issues it was not always possible to monitor 3 boreholes with 3 horizons at all sites

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**This sampling horizon was either not installed or was dry for the entire period of monitoring and therefore sampling was not possible

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ACCEPTED MANUSCRIPT Table 4 - Simulated average nitrate concentrations (mg/L) at the water table interface after 3650 days (10 years) for STE and SE sources. 4 Trenches

Single Trench

STE

SE

STE

SE

Naul – Low Vulnerability

0

0

0

0

Rhode – Moderate Vulnerability

32

24

42.1

28.7

Carrigeen – High Vulnerability

16

9.2

38.1

22.4

Faha – Extreme Vulnerability

34.6*

26.3*

44.3*

31.2*

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*Assumed 1.2m of unsaturated subsoil beneath base of trench

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Location

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Highlights

Impact on groundwater quality from high density cluster developments monitored



No significant impact from cluster systems on monitored downstream groundwater



Linked models of pollutant transport through unsaturated zone and groundwater



Models corroborate field study results



Little potential contamination from clusters up to a density of 6 units/ha

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

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