Agriculture and Forestry Systems Modelling

Our core capabilities

We apply operational research methods to the study of systems in agriculture, forestry, and the environment.  Operational research is the discipline of applying advanced analytical methods to help make better decisions (See the Operational Research Society web site).  

For the agricultural sector, the main areas of application are prediction of future agricultural land use, policy support for public bodies (primarily Defra) and analysis of the environmental impacts of agricultural production, particularly through Life Cycle Assessment (LCA) (see our LCA page).  

Silsoe Whole Farm Model: our whole farm model provides information on the potential profitability and environmental impact of the crops, operations and machinery systems on farms with differing locations, soil types and climates under future scenarios. It analyses the effects of decisions made on arable and livestock farms and the impact of policy changes. This extremely powerful tool answers fundamental management questions; for instance, "given a milk quota and a farm area, what system maximises profit at least cost to the environment?" or "what would be the effect of introducing a tax on chemical inputs?" We also provide information about what will happen in the face of global trends and changes. For example, we try to predict the future of farming in different regions in the face of climate change and answer questions like, "What crops will farmers choose to grow?" and, "will farmers be forced to abandon dairy farming?".

For the forestry sector, our work has focused on predicting the effect of forestry, agroforestry and arable systems on food and timber production, farm profitability, and carbon sequestration (see our Farm Woodlands and Agroforestry pages).



Staff expertise 

  • Eric Audsley: Operational research, agricultural systems modelling, linear programming (LP), life cycle assessment (LCA), land use prediction
  • Adrian Williams: LCA, greenhouse gases, GHG, agriculture, food, environment, systems, analysis, carbon footprint
  • Daniel Sandars: agriculture, operational research, environment, modelling, policy & decision analysis, linear programming, life cycle assessment
  • David Parsons: mathematics, operational research, systems modelling, optimisation, agriculture, risk, decision support
  • Paul Burgess: arable, agroforestry and forestry bio-economic modelling
  • Anil Graves: economics of ecosystem services and land use policy, stakeholder analysis
  • Joe Morris: Professor emeritus; environmental and natural resource economics, stakeholder analysis
  • Julia Chatterton: mathematical modelling, agriculture, environment, uncertainty, land use/change, food, systems analysis, life cycle assessment (LCA
  • Kerry Pearn: mathematical modelling, systems analysis

 

Defining projects:

Silsoe whole farm model

Eric Audsley, Daniel Sandars, Kerry Pearn

The Silsoe Whole Farm Model is a PC-based linear programming model of a farm designed to determine the cropping, labour and machinery plus environmental burdens, which optimise long term profit or a multiple objective of profit, risk and environmental criteria. It is ideal for examining the impact of changes on a farms such as economic changes, new crops, or changes to inputs, yields or climate. The model has been developed over many years and applied to a wide range of projects including all those listed on this page.

 

Climsave: 2010 - 2013 (ongoing)

Eric Audsley, Daniel Sandars, Ian Holman, Kerry Pearn
Intensive model of land use and climate change in Europe.

CLIMSAVE is a pan-European project that is developing a user-friendly, interactive web-based tool that will allow stakeholders to assess climate change impacts and vulnerabilities for a range of sectors, including agriculture, forests, biodiversity, coasts, water resources and urban development. The linking of models for the different sectors will enable stakeholders to see how their interactions could affect European landscape change. The tool will also enable stakeholders to explore adaptation strategies for reducing climate change vulnerability, discovering where, when and under what circumstances such actions may help and better inform the development of robust policy responses. Cranfield’s main input is to the agricultural systems modelling of land use under climate change and future socio-economic scenarios.

 

ChReam (RELU): 2008-2010

Eric Audsley, Kerry Pearn

This project investigated future agricultural land use, crop selection and the amount of N leached from the agricultural land in the Humber catchment, given scenarios defining changes in policy, climate, and socio-economics.  The leaching output is linked with a model of water quality for the Humber Catchment at the Hydrological Response Unit scale, which predicts the nitrate concentration in rivers. The model of agricultural land use considers a choice of two agricultural systems (‘intensive’ and ‘extensive’), broadly arable/dairy and beef/sheep farms.  Each “farm”, modelled as a soil-climate cluster, is optimised to determine the most profitable option for each cluster.  The “farms” are then aggregated to obtain values (including amount of N leached) for larger spatial scales.  Once the models have been calibrated to the baseline census data, then, given the scenario input values, the model estimates the future cropping at each location; identifies land use (arable cropping or dairy or extensive sheep/beef), and thus the change in amount of N leached due to the adaptation of the systems as a consequence of the scenario.  Whilst suggested measures to reduce leaching do do so, scenarios such as increased temperature or prices for crops, all substantially increase nitrate leaching.

 

Agricultural Futures and implications for the environment (Defra ISO209): 2003 - 2005 

Eric Audsley, Joe Morris, Kerry Pearn, Andy Angus, Sue Rickard

This study explored a number of future scenarios for agriculture in England and Wales. The overall purpose of the study was to help inform Government policy on agriculture and the rural environment. The specific objectives were to: (a) identify and explain the identities, characteristics and outcomes of possible long term futures for agriculture in England and Wales, (b) determine the implications of these outcomes for environmental objectives, and (c) identify possible policy interventions and research priorities to help promote sustainable agriculture. Access the Final Report Summary here. 

 

Silvoarable Agroforestry for Europe (SAFE): 2001- 2005

Paul Burgess, Anil Graves
Pan- European Research project to improve the prediction of the financial and environmental impacts of including silvoarable systems on European farms.

 

Assessing Climate Change Effects on Land use and Ecosystems: from Regional Analysis to The European Scale (ACCELERATES): 2001-2004

Eric Audsley, Kerry Pearn

This project aimed to assess the vulnerability of European agroecosystems to environmental change. The project examined how climate, policy and socio-economic pressures drive changes in agricultural land use and hence the wider ecosystem. The integrated project was a precursor to the current CLIMSAVE project.  Cranfields main in put was again the agricultural land use modelling.

 

Regional Climate Change Impact and Response Studies in East Anglia and North West England (REGIS) and Development of a metamodel tool for regional integrated climate change management. (REGIS2) (Defra CC0362)

Eric Audsley, Ian Holman, Kerry Pearn

REGIS developed and applied a methodology for stakeholder-led, regional Integrated Assessment (IA) of the impact of climate change.  Cranfield modelled agriculture and water.  However,  most existing models for the sectors represented have unacceptably long runtimes for allowing rapid simulation and interactive engagement with the IA.  Hence the two-year ‘Development of a metamodel tool for regional integrated climate change management’ (RegIS2) project was born.  It investigated and developed the use of computationally simpler modelling techniques, so called ‘metamodels’ or ‘reduced form models’, within a user friendly interface (the ‘Regional Impact Simulator’) to make the RegIS methodology available to the wider stakeholder community.
The tool can be downloaded using this link.