Climatic Change

, Volume 156, Issue 4, pp 589–607 | Cite as

Modeling the sensitivity of wheat yield and yield gap to temperature change with two contrasting methods in the North China Plain

  • Huiqing Bai
  • Jing WangEmail author
  • Quanxiao Fang
  • Hong Yin


Wheat productivity in the North China Plain (NCP) is highly sensitive to climate change and varies greatly in spatial-temporal scale. Contrasting responses of wheat productivity to climate change were reported with different assessment methods. In this study, the impacts of climate warming (+ 2 °C) on wheat yields and yield gaps in the NCP were compared under rainfed, irrigated, and potential conditions using climatic resource utilization model (CRUM) and APSIM. Average potential yield increased 289 kg ha−1 per decade (P < 0.01) simulated by CRUM but decreased 219 kg ha−1 per decade (P < 0.01) simulated by APSIM across the NCP during 1961–2010. Under the + 2 °C scenario compared with current climate (1961–2010), wheat yields under potential, two irrigations, one irrigation, and rainfed conditions increased 27%, 23%, 28%, and 13% simulated by CRUM but decreased 7%, 8%, 10%, and 17% simulated by APSIM. Simulated yield gaps between potential yield and yields under rainfed and one and two irrigations by CRUM increased 33%, 27%, and 32%, respectively. Simulated yield gap between potential and rainfed yields by APSIM increased 9% while the gaps between potential yield and yields under one and two irrigations by APSIM decreased 12% and 10%. Without cultivar change, simulated shortened growth period by APSIM due to increased temperature would decrease wheat yields. By contrast, increased temperature under a constant growth period assumed by CRUM would increase yields especially potential yield. This suggested that wheat yields could be maintained by effective utilization of crop growth duration, such as breeding new cultivars under warming climate in the NCP.



This work is supported by the National Key Research and Development Program of China (2016YFD0300105) and the National Science Foundation of China (31671627).


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Huiqing Bai
    • 1
  • Jing Wang
    • 1
    Email author
  • Quanxiao Fang
    • 2
    • 3
  • Hong Yin
    • 4
  1. 1.College of Resources and Environmental SciencesChina Agricultural UniversityBeijingChina
  2. 2.Agronomy CollegeQingdao Agricultural UniversityQingdaoChina
  3. 3.Institute of Soil and Water ConservationChinese Academy of Sciences, Ministry of Water ResourcesYanglingChina
  4. 4.National Climate Center, China Meteorological AdministrationBeijingChina

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