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Concurrent drought threatens wheat and maize production and will widen crop yield gaps in the future

Author

Listed:
  • Hou, Miaolei
  • Li, Yi
  • Biswas, Asim
  • Chen, Xinguo
  • Xie, Lulu
  • Liu, Deli
  • Li, Linchao
  • Feng, Hao
  • Wu, Shufang
  • Satoh, Yusuke
  • Pulatov, Alim
  • Siddique, Kadambot H.M.

Abstract

Drought poses a significant threat to global crop production. As the global community grapples with the escalating challenges of climate change, understanding the multifaceted impacts of concurrent drought on food security becomes imperative.

Suggested Citation

  • Hou, Miaolei & Li, Yi & Biswas, Asim & Chen, Xinguo & Xie, Lulu & Liu, Deli & Li, Linchao & Feng, Hao & Wu, Shufang & Satoh, Yusuke & Pulatov, Alim & Siddique, Kadambot H.M., 2024. "Concurrent drought threatens wheat and maize production and will widen crop yield gaps in the future," Agricultural Systems, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:agisys:v:220:y:2024:i:c:s0308521x24002063
    DOI: 10.1016/j.agsy.2024.104056
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    References listed on IDEAS

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    1. Chen, Xinguo & Li, Yi & Yao, Ning & Liu, De Li & Javed, Tehseen & Liu, Chuncheng & Liu, Fenggui, 2020. "Impacts of multi-timescale SPEI and SMDI variations on winter wheat yields," Agricultural Systems, Elsevier, vol. 185(C).
    2. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    3. He, Jianqiang & Jones, James W. & Graham, Wendy D. & Dukes, Michael D., 2010. "Influence of likelihood function choice for estimating crop model parameters using the generalized likelihood uncertainty estimation method," Agricultural Systems, Elsevier, vol. 103(5), pages 256-264, June.
    4. Wang, Fei & Lai, Hexin & Li, Yanbin & Feng, Kai & Zhang, Zezhong & Tian, Qingqing & Zhu, Xiaomeng & Yang, Haibo, 2022. "Dynamic variation of meteorological drought and its relationships with agricultural drought across China," Agricultural Water Management, Elsevier, vol. 261(C).
    5. Ma, Haijiao & Wang, Jianliang & Liu, Tao & Guo, Yahui & Zhou, Yang & Yang, Tianle & Zhang, Weijun & Sun, Chengming, 2023. "Time series global sensitivity analysis of genetic parameters of CERES-maize model under water stresses at different growth stages," Agricultural Water Management, Elsevier, vol. 275(C).
    6. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    7. 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).
    8. Xuhui Wang & Christoph Müller & Joshua Elliot & Nathaniel D. Mueller & Philippe Ciais & Jonas Jägermeyr & James Gerber & Patrice Dumas & Chenzhi Wang & Hui Yang & Laurent Li & Delphine Deryng & Christ, 2021. "Global irrigation contribution to wheat and maize yield," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    9. Sara Minoli & Jonas Jägermeyr & Senthold Asseng & Anton Urfels & Christoph Müller, 2022. "Global crop yields can be lifted by timely adaptation of growing periods to climate change," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    10. Yao, Ning & Li, Yi & Liu, Qingzhu & Zhang, Siyuan & Chen, Xinguo & Ji, Yadong & Liu, Fenggui & Pulatov, Alim & Feng, Puyu, 2022. "Response of wheat and maize growth-yields to meteorological and agricultural droughts based on standardized precipitation evapotranspiration indexes and soil moisture deficit indexes," Agricultural Water Management, Elsevier, vol. 266(C).
    11. De Liu & Heping Zuo, 2012. "Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia," Climatic Change, Springer, vol. 115(3), pages 629-666, December.
    12. Jingwen Zhang & Kaiyu Guan & Bin Peng & Ming Pan & Wang Zhou & Chongya Jiang & Hyungsuk Kimm & Trenton E. Franz & Robert F. Grant & Yi Yang & Daran R. Rudnick & Derek M. Heeren & Andrew E. Suyker & Wi, 2021. "Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    13. Berti, Antonio & Tardivo, Gianmarco & Chiaudani, Alessandro & Rech, Francesco & Borin, Maurizio, 2014. "Assessing reference evapotranspiration by the Hargreaves method in north-eastern Italy," Agricultural Water Management, Elsevier, vol. 140(C), pages 20-25.
    14. Araneda-Cabrera, Ronnie J. & Bermúdez, María & Puertas, Jerónimo, 2021. "Assessment of the performance of drought indices for explaining crop yield variability at the national scale: Methodological framework and application to Mozambique," Agricultural Water Management, Elsevier, vol. 246(C).
    15. Xiao, Xin & Ming, Wenting & Luo, Xuan & Yang, Luyi & Li, Meng & Yang, Pengwu & Ji, Xuan & Li, Yungang, 2024. "Leveraging multisource data for accurate agricultural drought monitoring: A hybrid deep learning model," Agricultural Water Management, Elsevier, vol. 293(C).
    16. Xu, Xuegong & Hou, Lisheng & Lin, Huiping & Liu, Wenzheng, 2006. "Zoning of sustainable agricultural development in China," Agricultural Systems, Elsevier, vol. 87(1), pages 38-62, January.
    17. Paolo D’Odorico & Davide Danilo Chiarelli & Lorenzo Rosa & Alfredo Bini & David Zilberman & Maria Cristina Rulli, 2020. "The global value of water in agriculture," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(36), pages 21985-21993, September.
    18. Felicia Chiang & Omid Mazdiyasni & Amir AghaKouchak, 2021. "Evidence of anthropogenic impacts on global drought frequency, duration, and intensity," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    19. Javad Bazrafshan & Majid Cheraghalizadeh & Kokab Shahgholian, 2022. "Development of a Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI) for Drought Monitoring in a Changing Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(10), pages 3523-3543, August.
    20. Cao, Meng & Chen, Min & Liu, Ji & Liu, Yanli, 2022. "Assessing the performance of satellite soil moisture on agricultural drought monitoring in the North China Plain," Agricultural Water Management, Elsevier, vol. 263(C).
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