Modelling and monitoring nutrient pollution at the large catchment scale: the implications of sampling regimes on model performance

Abstract. Daily and sub daily nutrient data are now becoming available to support nutrient research and which will help underpin policy making. It is vital that water quality models that utilize these high-frequency data sets are both appropriate and suitably accurate. Here we address the capability of process based models applied at larger catchment scales (size 100–500 km²) and show what phenomena can be simulated by exploiting high frequency data for larger catchments. Hence we can suggest the dominant processes that underpin the fluxes observed in larger catchment and thus what can be simulated, and to what accuracy. Thus the implications of new sampling frequency and model structure can be addressed and the implication to catchment management is discussed. Here we show a case study using the Frome catchment (414 km²), Dorset UK, which demonstrates:

1. The use of process based model of nutrient flow and nutrient flux (TOPCAT) for use in larger catchments.
2. Simulations of high frequency data at weekly and sub daily time steps, thus reflecting the simulations' strengths and weaknesses.
3. Cumulative distributions of observed and simulated fluxes – as an effective means of communicating the catchment dynamics in larger catchments.