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

Author:

Young Michael12ORCID,Young John3,Kingwell Ross S.145ORCID,Vercoe Philip E.12

Affiliation:

1. School of Agriculture and Environment The University of Western Australia Perth Western Australia Australia

2. Institute of Agriculture The University of Western Australia Perth Western Australia Australia

3. Farming Systems Analysis Service Kentdale Western Australia Australia

4. Australian Export Grains Innovation Centre Kensington Western Australia Australia

5. Department of Primary Industries and Regional Development South Perth Western Australia Australia

Abstract

AbstractThe 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.

Funder

Department of Primary Industries and Regional Development, Government of Western Australia

Publisher

Wiley

Subject

Economics and Econometrics,Agricultural and Biological Sciences (miscellaneous)

Reference54 articles.

1. ABARES. (2010)Australian agricultural commodity statistics: sheep[Online]. Available from:https://www.agriculture.gov.au/abares/research‐topics/agricultural‐outlook/data#_2010

2. ABARES. (2016)Australian agricultural census 2015–16 visualisations[Online]. Available from:http://www.agriculture.gov.au/abares/data/agricultural‐census‐visualisations#production‐area‐number‐and‐yield

3. ABARES. (2022)Australian agricultural commodity statistics: sheep[Online]. Available from:https://www.agriculture.gov.au/abares/research‐topics/agricultural‐outlook/data#_2022

4. Water use and salinity in the Murray?Darling Basin: A state-contingent model

5. Impacts of climatic variability in Australian agriculture: a review;Anderson J.R.;Review of Marketing and Agricultural Economics,1979

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3