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Assessing the vulnerability and risk of maize to drought in China based on the AquaCrop model

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  • Zhu, Xiufang
  • Xu, Kun
  • Liu, Ying
  • Guo, Rui
  • Chen, Lingyi

Abstract

In the context of global climate change, droughts pose a serious threat to agricultural development and food security. Assessing the vulnerability and risk of regions to drought is important for its prevention. In this paper, to understand the vulnerability of maize to drought in different regions of China and quantify its risk, 241 prefecture-level administrative regions (including prefecture-level cities, autonomous prefectures, prefectures, and leagues) in the five main maize-growing regions of China are used as study area. By using a method of global sensitivity analysis, the extended Fourier amplitude sensitivity test (EFAST), we chose two parameters that are most sensitive to maize yield to calibrate the AquaCrop model. We then used it to simulate the water stress of maize in the study area under different irrigation scenarios as well as the corresponding production. We defined the drought hazard index (DHI) as the daily average of the crop water stress indicator during the growing season, and used it to describe the intensity of droughts. Vulnerability curves (the function of the DHI and rate of yield loss) of the entire growth season and various stages of growth were also formulated. These were used to determine the loss of maize yield under four levels of risk (return periods of 5, 10, 20, and 50 years). The results showed the following: 1) the vulnerability curve of maize for the entire growing season was consistent with logistic function, and the coefficient of determination of the equation of regression was R2 = 0.93. The rate of yield loss began increasing rapidly once the DHI had reached 0.2 and approached its maximum value when the DHI was 0.6. 2) The coefficients of determination of the results of regression in 14 scenarios, in which drought had occurred in different stages of growth, were between 0.28 and 0.92. Drought from the tasseling stage to the milk stage had the most significant negative effect on the maize yield, followed by the seventh leaf stage to the tasseling stage and the sowing stage to the seventh leaf stage. Drought from the milk stage to physiological maturity had the least negative effect on the maize yield. 3) Under all four risk levels, the DHI and the yield loss rate of maize in China decreased from the northwest to the southeast. The Northwest Irrigated Maize Region had the highest drought risk among the five maize-growing regions, followed by the North Spring Maize Region, the Huang-Huai-Hai Summer Maize Region, the South Hilly Maize Region, and the Southwest Mountain Maize Region. 4) The DHI calculated by the average method was more representative than that calculated using the accumulative method.

Suggested Citation

  • Zhu, Xiufang & Xu, Kun & Liu, Ying & Guo, Rui & Chen, Lingyi, 2021. "Assessing the vulnerability and risk of maize to drought in China based on the AquaCrop model," Agricultural Systems, Elsevier, vol. 189(C).
  • Handle: RePEc:eee:agisys:v:189:y:2021:i:c:s0308521x2030901x
    DOI: 10.1016/j.agsy.2020.103040
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    1. DeJonge, Kendall C. & Ascough, James C. & Ahmadi, Mehdi & Andales, Allan A. & Arabi, Mazdak, 2012. "Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments," Ecological Modelling, Elsevier, vol. 231(C), pages 113-125.
    2. Aiguo Dai, 2013. "Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(1), pages 52-58, January.
    3. Ran, Hui & Kang, Shaozhong & Li, Fusheng & Du, Taisheng & Tong, Ling & Li, Sien & Ding, Risheng & Zhang, Xiaotao, 2018. "Parameterization of the AquaCrop model for full and deficit irrigated maize for seed production in arid Northwest China," Agricultural Water Management, Elsevier, vol. 203(C), pages 438-450.
    4. Yaojie Yue & Jian Li & Xinyue Ye & Zhiqiang Wang & A-Xing Zhu & Jing-ai Wang, 2015. "An EPIC model-based vulnerability assessment of wheat subject to drought," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(3), pages 1629-1652, September.
    5. Zhiqiang Wang & Fei He & Weihua Fang & Yongfeng Liao, 2013. "Assessment of physical vulnerability to agricultural drought in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 67(2), pages 645-657, June.
    6. Aiguo Dai, 2013. "Erratum: Increasing drought under global warming in observations and models," Nature Climate Change, Nature, vol. 3(2), pages 171-171, February.
    7. Maxx Dilley & Robert S. Chen & Uwe Deichmann & Arthur L. Lerner-Lam & Margaret Arnold, 2005. "Natural Disaster Hotspots: A Global Risk Analysis," World Bank Publications - Books, The World Bank Group, number 7376.
    8. Corey Lesk & Pedram Rowhani & Navin Ramankutty, 2016. "Influence of extreme weather disasters on global crop production," Nature, Nature, vol. 529(7584), pages 84-87, January.
    9. Yang, Yunfeng & Chen, Guohua & Reniers, Genserik, 2020. "Vulnerability assessment of atmospheric storage tanks to floods based on logistic regression," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    10. Jieming Chou & Tian Xian & Runze Zhao & Yuan Xu & Fan Yang & Mingyang Sun, 2019. "Drought Risk Assessment and Estimation in Vulnerable Eco-Regions of China: Under the Background of Climate Change," Sustainability, MDPI, vol. 11(16), pages 1-14, August.
    11. Confalonieri, Roberto & Acutis, Marco & Bellocchi, Gianni & Donatelli, Marcello, 2009. "Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice," Ecological Modelling, Elsevier, vol. 220(11), pages 1395-1410.
    12. Abedinpour, M. & Sarangi, A. & Rajput, T.B.S. & Singh, Man & Pathak, H. & Ahmad, T., 2012. "Performance evaluation of AquaCrop model for maize crop in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 110(C), pages 55-66.
    13. Wei Wang & Fengying Wu & Ziyi Wang, 2020. "Revising Seismic Vulnerability of Bridges Based on Bayesian Updating Method to Evaluate Traffic Capacity of Bridges," Sustainability, MDPI, vol. 12(5), pages 1-16, March.
    14. Yaojie Yue & Lin Wang & Jian Li & A-xing Zhu, 2018. "An EPIC model-based wheat drought risk assessment using new climate scenarios in China," Climatic Change, Springer, vol. 147(3), pages 539-553, April.
    15. Wei Pei & Qiang Fu & Dong Liu & Tianxiao Li & Kun Cheng & Song Cui, 2019. "A Novel Method for Agricultural Drought Risk Assessment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 2033-2047, April.
    16. Hong Wu & Donald Wilhite, 2004. "An Operational Agricultural Drought Risk Assessment Model for Nebraska, USA," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 33(1), pages 1-21, September.
    17. Cui, Yi & Jiang, Shangming & Jin, Juliang & Ning, Shaowei & Feng, Ping, 2019. "Quantitative assessment of soybean drought loss sensitivity at different growth stages based on S-shaped damage curve," Agricultural Water Management, Elsevier, vol. 213(C), pages 821-832.
    18. Hao Guo & Xingming Zhang & Fang Lian & Yuan Gao & Degen Lin & Jing’ai Wang, 2016. "Drought Risk Assessment Based on Vulnerability Surfaces: A Case Study of Maize," Sustainability, MDPI, vol. 8(8), pages 1-22, August.
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