Modelling through-soil transport of phosphorus to surface waters from livestock agriculture at the field and catchment scale.

A model of phosphorus (P) losses in a small dairy farm catchment has been set up based on a linkage of weather-driven field-scale simulations using an adaptation of the MACRO model. Phosphorus deposition, both in faeces from grazing livestock in summer and in slurry spread in winter, has been represented. MACRO simulations with both forms of P deposition had been calibrated and tested at the individual field scale in previous studies. The main contaminant transport mechanism considered at both field and catchment scales is P sorbed onto mobile colloidal faeces particles, which move through the soil by macropore flow. Phosphorus moves readily through soil to field drains under wet conditions when macropores are water-filled, but in dry soil the P carrying colloids become trapped so losses remain at a low level. In the catchment study, a dairy farm is assumed to be composed of fields linked by a linear system of ditches which discharge into a single river channel. Results from linked simulations showed reasonable fits to values of catchment outflow P concentrations measured at infrequent intervals. High simulated outflow P concentrations occurred at similar times of year to high measured values, with some high loss periods during the summer grazing season and some during the winter when slurry would have been spread. However, there was a lack of information about a number parameters that would be required to carry out a more exact calibration and provide a rigorous test of the modelling procedure. It was nevertheless concluded that through soil flow of colloid sorbed P by macropore flow represents a highly plausible mechanism by which P is transported to river systems in livestock farming catchments. This represents an alternative to surface runoff transport, a mechanism to which high P losses from livestock farming areas have often been attributed. The occurrence of high simulated levels of loss under wet conditions indicates environmental benefits from avoiding slurry spreading on wet soil or during rain, and from some forms of grazing management.

Modelling nitrate losses from agricultural activities on a national scale.

The Nitrogen Risk Assessment Model for Scotland (NIRAMS) has been developed as a screening tool for prediction of streamwater N concentrations draining from agricultural land in Scotland. The objective of the model is to be able to predict N concentrations for ungauged catchments, to fill gaps in monitoring data and provide guidance in relation to policy development. The model uses national land use, soils and meteorology data sets and has been developed within an ArcView GIS user interface. The model includes modules to calculate N inputs to the land, residual N remaining at the end of the growing season, weekly time-series of leached N and transport of N at the catchment scale. The N leaching and transport are. controlled by hydrological modules, including a national water balance model and a catchment scale transport model. Preliminary testing of NIRAMS has been carried out on eight Scottish catchments, diverse in terms of geographic location as well as land use. The model is capable of predicting the correct mean level of stream N concentrations, as well as the basic characteristics of seasonal variation. As such the model can be of value for providing estimates of N concentrations in ungauged areas.

Predicting the effect of livestock inputs of E. coli on microbiological compliance of bathing waters.

Three alternative approaches to predicting delivery of faecal indicators from livestock sources to surface water in the catchment of the River Irvine, Ayrshire, Scotland, are described. These are a soil transport model which assumes all E. coli are transported through the soil, a regression model using observed E. coli concentrations in surface waters, and a distributed catchment model (PAMIMO). Each of these is linked to a simple group of equations describing inputs of E. coli from livestock to land, transport and inactivation in the river Irvine and mixing and inactivation in the sea. The models predict E. coli content of bathing water for Irvine beach. The regression model gives the best predictions of bathing water quality. The low values predicted by the soil transport model suggests that preventing surface runoff of faecal indicators from livestock would provide an adequate solution to the problem of bathing water contamination.