Nitrogen Risk Assessment Model for Scotland: I. Nitrogen leaching

International audienceThe Nitrogen Risk Assessment Model for Scotland (NIRAMS) has been developed for prediction of streamwater N concentrations draining from agricultural land in Scotland. The objective of the model is to predict N concentrations for ungauged catchments, to fill gaps in monitoring data and to provide guidance in relation to policy development. The model uses nationally available data sets of land use, soils, topography and meteorology and has been developed within a Geographic Information System (GIS). 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. This paper presents the methodology for calculating N balances for different land uses and for predicting the time sequence of N leaching after the end of the growing season. Maps are presented of calculated residual N and N leaching for the whole of Scotland and the spatial variability in N leaching is discussed. The results demonstrate the high variability in N leaching across Scotland. The simulations suggest that, in the areas with greatest residual N, the losses of N are not directly proportional to the amount of residual N, because of their coincidence with lower rainfall. In the companion paper, the hydrological controls on N transport within NIRAMS are described, and results of the full model testing are presented. Keywords: nitrogen, diffuse pollution, agriculture, leaching, land use, model, national, catchmen

Re-shaping models of E.coli population dynamics in livestock faeces: Increased bacterial risk to humans?

Dung-pats excreted directly on pasture from grazing animals can contribute a significant burden of faecal microbes to agricultural land. The aim of this study was to use a combined field and modelling approach to determine the importance of Escherichia coli growth in dung-pats when predicting faecal bacteria accumulation on grazed grassland. To do this an empirical model was developed to predict the dynamics of an E. coli reservoir within 1 ha plots each grazed by four beef steers for six months. Published first-order die-off coefficients were used within the model to describe the expected decline of E. coli in dung-pats. Modelled estimates using first-order kinetics led to an underestimation of the observed E. coli land reservoir, when using site-specific die-off coefficients. A simultaneous experiment determined the die-off profiles of E. coli within fresh faeces of beef cattle under field relevant conditions and suggested that faecal bacteria may experience growth and re-growth in the period post defecation when exposed to a complex interaction of environmental drivers such as variable temperature, UV radiation and moisture levels. This growth phase in dung-pats is not accounted for in models based on first-order die-off coefficients. When the model was amended to incorporate the growth of E. coli, equivalent to that observed in the field study, the prediction of the E. coli reservoir was improved with respect to the observed data and produced a previously unquantified step-change improvement in model predictions of the accumulation of these faecal bacteria on grasslands. Results from this study suggest that the use of first-order kinetic equations for determining land-based reservoirs of faecal bacteria should be approached with caution and greater emphasis placed on accounting for actual survival patterns observed under field relevant conditions