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Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

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  • Chao Chen
  • Walter Baethgen
  • Andrew Robertson

Abstract

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Chao Chen & Walter Baethgen & Andrew Robertson, 2013. "Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003," Climatic Change, Springer, vol. 116(3), pages 767-788, February.
  • Handle: RePEc:spr:climat:v:116:y:2013:i:3:p:767-788
    DOI: 10.1007/s10584-012-0509-2
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    1. Ludwig, Fulco & Asseng, Senthold, 2006. "Climate change impacts on wheat production in a Mediterranean environment in Western Australia," Agricultural Systems, Elsevier, vol. 90(1-3), pages 159-179, October.
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    Cited by:

    1. Junjun Cao & Guoyong Leng & Peng Yang & Qingbo Zhou & Wenbin Wu, 2022. "Variability in Crop Response to Spatiotemporal Variation in Climate in China, 1980–2014," Land, MDPI, vol. 11(8), pages 1-13, July.
    2. Quan, Hao & Ding, Dianyuan & Wu, Lihong & Qiao, Ruonan & Dong, Qin'ge & Zhang, Tibin & Feng, Hao & Wu, Lianhai & Siddique, Kadambot H.M., 2022. "Future climate change impacts on mulched maize production in an arid irrigation area," Agricultural Water Management, Elsevier, vol. 266(C).
    3. Zhu, Ping & Jia, Xiaoxu & Zhao, Chunlei & Shao, Mingan, 2022. "Long-term soil moisture evolution and its driving factors across China’s agroecosystems," Agricultural Water Management, Elsevier, vol. 269(C).
    4. Nazan An & Mustafa Tufan Turp & Murat Türkeş & Mehmet Levent Kurnaz, 2020. "Mid-Term Impact of Climate Change on Hazelnut Yield," Agriculture, MDPI, vol. 10(5), pages 1-20, May.
    5. Gao, Yukun & Zhao, Hongfang & Zhao, Chuang & Hu, Guohua & Zhang, Han & Liu, Xue & Li, Nan & Hou, Haiyan & Li, Xia, 2022. "Spatial and temporal variations of maize and wheat yield gaps and their relationships with climate in China," Agricultural Water Management, Elsevier, vol. 270(C).
    6. Xiao, Dengpan & Liu, De Li & Wang, Bin & Feng, Puyu & Waters, Cathy, 2020. "Designing high-yielding maize ideotypes to adapt changing climate in the North China Plain," Agricultural Systems, Elsevier, vol. 181(C).
    7. Yujie Liu & Qiaomin Chen & Qinghua Tan, 2019. "Responses of wheat yields and water use efficiency to climate change and nitrogen fertilization in the North China plain," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(6), pages 1231-1242, December.
    8. Jinglun Peng & Moonju Kim & Kyungil Sung, 2020. "Yield Prediction Modeling for Sorghum–Sudangrass Hybrid Based on Climatic, Soil, and Cultivar Data in the Republic of Korea," Agriculture, MDPI, vol. 10(4), pages 1-11, April.
    9. Zhang, Chao & Xie, Ziang & Wang, Qiaojuan & Tang, Min & Feng, Shaoyuan & Cai, Huanjie, 2022. "AquaCrop modeling to explore optimal irrigation of winter wheat for improving grain yield and water productivity," Agricultural Water Management, Elsevier, vol. 266(C).
    10. Shirazi, Sana Zeeshan & Mei, Xurong & Liu, Buchun & Liu, Yuan, 2022. "Estimating potential yield and change in water budget for wheat and maize across Huang-Huai-Hai Plain in the future," Agricultural Water Management, Elsevier, vol. 260(C).
    11. Chen, Qiaomin & Liu, Yujie & Ge, Quansheng & Pan, Tao, 2018. "Impacts of historic climate variability and land use change on winter wheat climatic productivity in the North China Plain during 1980–2010," Land Use Policy, Elsevier, vol. 76(C), pages 1-9.
    12. Bassino, Jean-Pascal & Lagoarde-Segot, Thomas & Woitek, Ulrich, 2022. "Prenatal climate shocks and adult height in developing countries. Evidence from Japan (1872–1917)," Economics & Human Biology, Elsevier, vol. 45(C).
    13. Sun, Shuang & Yang, Xiaoguang & Lin, Xiaomao & Sassenrath, Gretchen F. & Li, Kenan, 2018. "Climate-smart management can further improve winter wheat yield in China," Agricultural Systems, Elsevier, vol. 162(C), pages 10-18.

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