NGAUGE: A decision support system to optimise N fertilisation of British grassland for economic and environmental goals

Institute of Grassland and Environmental Research, Soil Science and Environmental Quality, North Wyke, Okehampton, Devon EX20 2SB, UK
Agriculture Ecosystems & Environment (Impact Factor: 3.4). 08/2005; 109(1):20-39. DOI: 10.1016/j.agee.2005.02.021


The poor efficiency with which nitrogen (N) is often used on grassland farms is well documented, as are the potential consequences of undesirable emissions of nitrogen. As fertiliser represents a major input of nitrogen to such systems, its improved management has good potential for increasing the efficiency of nitrogen use and enhancing environmental and economic performance. This paper describes the development, structure and potential application of a new decision support system for fertiliser management for British grassland. The underlying empirically-based model simulates monthly nitrogen flows within and between the main components of the livestock production system according to user inputs describing site conditions and farm management characteristics. The user-friendly decision support system (‘NGAUGE’) has a user interface that was produced in collaboration with livestock farmers to ensure availability of all required inputs. NGAUGE is an improvement on existing nitrogen fertiliser recommendation systems in that it relates production to environmental impact and is therefore potentially valuable to policy makers and researchers for identifying pollution mitigation strategies and blueprints for novel, more sustainable systems of livestock production. One possible application is the simulation of the phenomenon of pollution swapping, whereby, for example, the adoption of strategies for the reduction of nitrate leaching may exacerbate emissions of ammonia and nitrous oxide. Outputs of the decision support system include a field- and target-specific N fertiliser recommendation together with farm- and field-based N budgets, comprising amounts of N in both production and loss components of the system. Recommendations may be updated on a monthly basis to take account of deviations of weather conditions from the 30-year mean. The optimisation procedure within NGAUGE enables user-specified targets of herbage production, N loss or fertiliser use to be achieved while maximising efficiency of N use. Examples of model output for a typical grassland management scenario demonstrate the effect on model predictions of site and management properties such as soil texture, weather zone, grazing and manure applications. Depending on existing management and site characteristics, simulations with NGAUGE suggest that it is possible to reduce nitrate leaching by up to 46% (compared with a fertiliser distribution from existing fertiliser recommendations), and fertiliser by 33%, without sacrificing herbage yield. The greatest improvements in efficiency are possible on sandy-textured soils, with moderate N inputs.

Download full-text


Available from: Agustin Del Prado, Jan 30, 2015
  • Source
    • "feeding nitrification inhibitors: Ledgard et al., 2008 or salt supplementation) during the grazing period has also been proposed as a means to reduce N 2 O emissions. Improving fertiliser efficiency, optimising methods, timing and rates of applications (Brown et al., 2005), using NH 4 + -based fertilisers rather than nitrate-based ones (e.g. Dobbie and Smith, 2003) and employing nitrification chemical inhibitors (e.g. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Climate change mitigation and adaptation have generally been considered in separate settings for both scientific and policy viewpoints. Recently, it has been stressed (e.g. by the latest IPCC reports) the importance to consider both mitigation and adaptation from land management together. To date, although there is already large amount of studies considering climate mitigation and adaptation in relation to grassland-based systems, there are no studies that analyse the potential synergies and tradeoffs for the main climate change mitigation and adaptation measures within the current European Policy context. This paper reviews which mitigation and adaptation measures interact with each other and how, and it explores the potential limitations and strengths of the different policy instruments that may have an effect in European grassland-based livestock systems.
    Grassland Science in Europe: EGF at 50: The future of European grasslands., Grassland Science in Europe: Volume 19 edited by Hopkins A., Collins R., Fraser M.D, King V.R, Lloyd D.C, Moorby J., Robson P.R.H, 09/2014: chapter Synergies between mitigation and adaptation to climate change in grassland-based farming systems.: pages 61-74; IBERS., ISBN: 978-0-9926930-1-2
  • Source
    • "Details of the modelling framework are reported elsewhere (Theobald et al., 2004). It consists of the following five models, simulating N flows in the atmosphere, grazed fields, arable fields, farmyards and river catchments: LADD Atmospheric dispersion and deposition (Dragosits et al., 2002) SUNDIAL N cycling in arable systems (Smith et al., 1996) FYNE NH 3 and N 2 O emissions from farmyards (Theobald et al., 2004) NGauge N flows of grazed systems (Brown et al., 2005) INCA Catchment flows of N (Whitehead et al., 1998) The models are linked as shown in Figure 1. The input data for the models are land cover maps (derived from aerial photographs), farm management data (collected through farm surveys) and meteorological data. "

  • Source
    • "To extrapolate the experimental data gained at a limited number of field sites to regional scales, process-based models have been developed and adopted to assist the policy making process in agricultural studies. Many process-based simulation models for estimating N 2 O emissions have been developed, such as DNDC (Li et al., 1992a, 1992b, 2006; Brown et al., 2002), NGAUGE (Brown et al., 2005), SIMSdairy (del Prado and Scholefield, 2008), MOTOR (Whitmore, 2007), CENTURY (Parton et al., 1988; Melillo et al., 1995) and Daycent (Parton et al., 1998). Agro-ecosystem models generally operate at a scale that simulates soil biogeochemical processes at a particular site, and this can then be upscaled through a regular or irregular grid. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Grazed grassland systems are an important component of the global carbon cycle and also influence global climate change through their emissions of nitrous oxide and methane. However, there are huge uncertainties and challenges in the development and parameterisation of process-based models for grazed grassland systems because of the wide diversity of vegetation and impacts of grazing animals. A process-based biogeochemistry model, DeNitrification-DeComposition (DNDC), has been modified to describe N(2)O emissions for the UK from regional conditions. This paper reports a new development of UK-DNDC in which the animal grazing practices were modified to track their contributions to the soil nitrogen (N) biogeochemistry. The new version of UK-DNDC was tested against datasets of N(2)O fluxes measured at three contrasting field sites. The results showed that the responses of the model to changes in grazing parameters were generally in agreement with observations, showing that N(2)O emissions increased as the grazing intensity increased.
    Environmental Pollution 03/2012; 162:223-33. DOI:10.1016/j.envpol.2011.11.027 · 4.14 Impact Factor
Show more