Climatic Change

, Volume 147, Issue 3–4, pp 555–569 | Cite as

Impacts of rainfall extremes on wheat yield in semi-arid cropping systems in eastern Australia

  • Puyu Feng
  • Bin Wang
  • De Li Liu
  • Hongtao Xing
  • Fei Ji
  • Ian Macadam
  • Hongyan Ruan
  • Qiang Yu


Investigating the relationships between climate extremes and crop yield can help us understand how unfavourable climatic conditions affect crop production. In this study, two statistical models, multiple linear regression and random forest, were used to identify rainfall extremes indices affecting wheat yield in three different regions of the New South Wales wheat belt. The results show that the random forest model explained 41–67% of the year-to-year yield variation, whereas the multiple linear regression model explained 34–58%. In the two models, 3-month timescale standardized precipitation index of Jun.–Aug. (SPIJJA), Sep.–Nov. (SPISON), and consecutive dry days (CDDs) were identified as the three most important indices which can explain yield variability for most of the wheat belt. Our results indicated that the inter-annual variability of rainfall in winter and spring was largely responsible for wheat yield variation, and pre-growing season rainfall played a secondary role. Frequent shortages of rainfall posed a greater threat to crop growth than excessive rainfall in eastern Australia. We concluded that the comparison between multiple linear regression and machine learning algorithm proposed in the present study would be useful to provide robust prediction of yields and new insights of the effects of various rainfall extremes, when suitable climate and yield datasets are available.



The first author acknowledges the China Scholarship Council (CSC) for the financial support for his PhD study. Facilities for conducting this study were provided by the New South Wales Department of Primary Industries and University of Technology, Sydney.

Supplementary material

10584_2018_2170_MOESM1_ESM.pdf (1.2 mb)
ESM 1 (PDF 1187 kb)


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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Puyu Feng
    • 1
    • 2
  • Bin Wang
    • 2
  • De Li Liu
    • 2
    • 3
  • Hongtao Xing
    • 1
    • 2
  • Fei Ji
    • 4
  • Ian Macadam
    • 3
  • Hongyan Ruan
    • 5
  • Qiang Yu
    • 1
    • 6
    • 7
  1. 1.School of Life Sciences, Faculty of ScienceUniversity of Technology SydneySydneyAustralia
  2. 2.NSW Department of Primary IndustriesWagga Wagga Agricultural InstituteWagga WaggaAustralia
  3. 3.Climate Change Research Centre and ARC Centre of Excellence for Climate System ScienceUniversity of New South WalesSydneyAustralia
  4. 4.NSW Office of Environment and HeritageQueanbeyanAustralia
  5. 5.Agricultural CollegeGuangxi UniversityNanningChina
  6. 6.State Key Laboratory of Soil Erosion and Dryland Farming on the Loess PlateauNorthwest A&F UniversityYanglingChina
  7. 7.College of Resources and EnvironmentUniversity of Chinese Academy of ScienceBeijingChina

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