Simulating field-scale nitrogen management scenarios involving fertiliser and slurry applications

The long-term effects of nitrogen (N) fertiliser and slurry management practices in agricultural systems has been simulated using event driven physically based models. The Swedish soil water model SOIL and its associated nitrogen cycle model SOILN has been used to simulate the long-term impacts (over 12 years) of 360 management scenarios; three slurry applications with 10 spreading dates (involving single and split applications) for surface spreading and injection of slurry, and three fertiliser applications with two spreading dates. The effects of the N management scenarios on NO₃–N drainage flows, total gaseous N losses and crop yields for grass, winter and spring cereals is investigated. Furthermore, seven soils with varying degrees of drainage efficiency and three climatic conditions (East and West coast Scotland and Southern Ireland) are studied.The aim of this work is to produce N-budget tables for an expert agricultural decision system (ADS) which deals specifically with N best management practises for fertiliser and slurry applications. Simulations conducted in this study were based on input parameters calibrated for specific sites in previous studies on hydrology and NO₃–N transport to subsurface drains with associated crop growth.The results of this study show that increasing rates of N applications (in the form of slurry and fertiliser) resulted in a non-linear increase in both the N leached through subsurface drains and the N harvest yield. Surface spreading and injection of slurry gave similar trends. The most important decision about slurry spreading concerns the selection of spreading date and the selection of fields which are likely to produce only moderate leaching effects. Application of slurry in autumn (as a single or split loading), invariably leads to large losses through N leaching, with a single application always resulting in the highest loss. Significant differences are evident for N leaching from the seven soil types. Climatic variation as exemplified in the three meteorological data sets, produces noticeable and significant differences in both N leached and harvest crop totals. This study also aims to identify that a field environmental risk assessment (ERA) using a physically based model such as SOILN can be determined such that strategic agronomic decisions involving N management can be made. In practice this is so provided that a farm manager can recognise and match the actual soil type and drainage condition of the fields on which spreading is to occur with the simulated field types within a similar climate region.