Using the water quality models, SAGIS-SIMCAT and SWAT, a reduction in the risk of exceeding drinking water quality standards at a water treatment works intake was shown for nutrients and metaldehyde as a result of introducing farm measures. The costs of these measures were then compared to the economic benefits of reduced risk.

Impact of agricultural measures on metaldehyde (number of days exceeding drinking water standard) and nitrate (99 percentile) at river intake. Scenarios – S1 = 6m buffer strips, S2 = Max application rate 0.16 kg ha^-1, S3 = No application slope > 2%, S4 = No application on clay soils, BM = best measures, MM = maximum measures.

The water quality models SWAT (metaldehyde) and SAGIS-SIMCAT (phosphorus and nitrate) were set up and calibrated on the River Wensum (Norfolk). For SWAT, a daily timestep was used whereas SAGIS-SIMCAT was set up with statistical data (mean and standard deviations) for the period 2010 to 2012. Sequential Uncertainty Fitting was applied to calibrate SWAT whilst SAGIS-SIMCAT was calibrated by a calibration technique developed for UKWIR.

Model scenarios were then run to test the impact of catchment measures (e.g. substitution of metaldehyde by the alternative ferric phosphate and farm management to reduce nutrients defined using the agricultural management model, Farmscoper) on operational and compliance risk at Anglian Water’s Costessey Pits intake. Compliance risk for metaldehyde was assessed as the number of days exceeding the drinking water standard, whilst for nitrate and phosphorus mean, 95 and 99 percentile values were compared to the standard at the intake and associated reservoir.

The water quality models SWAT (metaldehyde) and SAGIS-SIMCAT (phosphorus and nitrate) were set up and calibrated on the River Wensum (Norfolk). SWAT includes parameters which define the physical and chemical properties of pesticides and control their transport and fate within the model (Arnold et al., 2012). Metaldehyde is not included in the SWAT pesticide database and so the values of these properties for metaldehyde were determined from the literature and manually added to the model database. Inputs to SAGIS are based on a combination of observed data (e.g. for point sources and output from other models; notably PSYCHIC and NEAP N for phosphorus and nitrogen respectively; Comber et al. 2013). For SWAT, a daily time-step was used whereas SAGIS-SIMCAT was set up with statistical data for the period 2010 to 2012. Sequential Uncertainty Fitting was applied to calibrate SWAT whilst SAGIS-SIMCAT was calibrated by a calibration technique developed for UKWIR.

For SWAT, the following scenarios were run (the percentage reduction in pesticide use is also shown). 

For SAGIS, agricultural measures were applied to reduce the catchment inputs of both nitrogen and phosphorus from the catchment based on output from the model, Farmscoper, calculated at the waterbody scale. The following measures were applied:

• Best practice voluntary measures
•  Maximum measures

Compliance risk for metaldehyde was assessed as the number of days exceeding the drinking water standard at the Costessey Pits intake and further downstream at the Heigham intake. For nitrate the mean, 95 percentile and 99 percentile values were generated with a view to assessing the risk of exceedance of the drinking water standard. For phosphorus, the key issue is the impact on nutrient loading and consequent enrichment of the bank side storage reservoir, Costessey Pits, that provides short-term storage of river water before treatment. Average phosphorus loads (kg/day) were compared as well as predicted mean and percentile values in the reservoir.  In addition, SAGIS provides information on source apportionment which was reviewed to identify the key pollution sources.

In addition, Farmscoper provides indicative implementation costs for the measures whilst substitution costs for metaldehyde with ferric phosphate were calculated based in the Anglian Water’s incentive scheme ‘Slug It Out’.  These costs were compared to the operational and compliance risk benefits.

S.D.W.Comber, R.Smith, P.W.G.Daldorph, M.J. Gardner, C.Constantino, and B.Ellor (2013) Development of a Chemical Source Apportionment Decision Support Framework for Catchment Management. Environ. Sci. Technol., 2013, 47 (17), pp 9824–9832

Arnold, J. G., Kiniry, J. R., Srinivasan, R., Williams, J. R., Haney, E. B. and Neitsch, S. L. (2012). Soil and Water Assessment Tool Input/Output File Documentation, Version 2012. Temple: Texas Water Resources Institute.

For metaldehyde measures considered included: no applications to high risk areas (high slope and clay soils), reduced maximum application rates, cultural measures to reduce need for application and buffer strips. Although no mitigation option resulted in nil-exceedance of the drinking water standard for metaldehyde at the intake, some measures resulted in a marked reduction in the risk of water quality non-compliance (percentage of time exceeding standard reduced from 15% to 6%). The findings suggest that the most effective approach to reduce metaldehyde concentrations at the raw water inlet sites involves targeting areas that are at a relatively high-risk of metaldehyde loss. For phosphorus, only a marginal reduction in reservoir nutrient loading was achieved as a result of best practice voluntary measures and maximum measures but for nitrate the 99 percentile was reduced further below the standard increasing headroom and therefore reducing risk. 

River Wensum catchment showing location of Costessey Pits intake

Modelled metaldehyde concentrations at Costessey Pits intake (using SWAT)

Source apportionment of nitrate along the length of the River Wensum (arrow shows location of intake)

Drinking water standard for metaldehyde and percent exceedance curves for the Costessey Pits inlet