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Representing weather-year variation in whole-farm optimisation models: Four-stage single-sequence vs eight-stage multi-sequence

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  • Young, Michael
  • Young, John
  • Kingwell, Ross S.
  • Vercoe, Philip E.

Abstract

The trade-off between accuracy and complexity is a common issue faced in farm systems analysis. To provide insights into the importance of representing weather-year sequence in farm modelling, two whole-farm optimisation models are constructed and applied to a mixed enterprise farming system in a subregion of Western Australia. The frameworks are (i) four-stage single-sequence stochastic programming with recourse (4-SPR) to capture weather-year variation and management tactics tailored to each weather-year and (ii) eight-stage multi-sequence stochastic programming with recourse (8-SPR) to outline weather-year sequences and management tactics tailored to particular weather-year sequences. Results show that single-year stochastic programming generates similar expected profit and strategic management as multi-year stochastic programming. However, optimal tactical farm management is affected by the outcome of the previous year. Tactical decision-making in response to the outcome of the preceding weather-year increases profitability by 14%. Technology changes over the last decade, particularly the increase in computer speed and computational power, increase the ease of construction and application of the 4-SPR and 8-SPR frameworks. Nonetheless, choosing which framework is best to apply to a particular issue or opportunity remains a challenge.

Suggested Citation

  • Young, Michael & Young, John & Kingwell, Ross S. & Vercoe, Philip E., 2023. "Representing weather-year variation in whole-farm optimisation models: Four-stage single-sequence vs eight-stage multi-sequence," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(01), September.
    • Handle: RePEc:ags:aareaj:343074
    DOI: 10.22004/ag.econ.343074
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    References listed on IDEAS

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