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Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling

Author

Listed:
  • Huili Chen

    (Peking University)

  • Zhongyao Liang

    (Peking University)

  • Yong Liu

    (Peking University)

  • Qingsong Jiang

    (Peking University)

  • Shuguang Xie

    (Peking University)

Abstract

China is an agricultural country with the largest population in the world. However, intensification of droughts and floods has substantial impacts on agricultural production. For effective agricultural disaster management, it is significant to understand and quantify the influence of droughts and floods on crop production. Compared with droughts, the influence of floods on crop production and a comprehensive evaluation of effects of droughts and floods are given relatively less attention. The impact of droughts and floods on crop production is therefore investigated in this study, considering spatial heterogeneity with disaster and yield datasets for 1949–2015 in China mainland. The empirical relationships between drought and flood intensity and yield fluctuation for grain, rice, wheat, maize and soybean are identified using a Bayesian hierarchical model. They are then used to explore what social-economic factors influenced the grain sensitivity to droughts and floods by the Pearson’s coefficient and locally weighted regression (LOSEE) plots. The modeling results indicate that: (a) droughts significantly reduce grain yields in 28 of 31 provinces and obvious spatial variability in drought sensitivity exists, with Loess Plateau having highest probability of crop failure caused by droughts; (b) floods significantly reduce grain yield in 20 provinces, while show positive effect in the northwestern and southwestern China; (c) the spatial patterns of influence direction of droughts and floods on rice, maize and soybean are consistent with the grain’s results; and (d) promoting capital investments and improving access to technical inputs (fertilizer, pesticide, and irrigation) can help effectively buffer grain yield lose from droughts.

Suggested Citation

  • Huili Chen & Zhongyao Liang & Yong Liu & Qingsong Jiang & Shuguang Xie, 2018. "Effects of drought and flood on crop production in China across 1949–2015: spatial heterogeneity analysis with Bayesian hierarchical modeling," 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. 92(1), pages 525-541, May.
    • Handle: RePEc:spr:nathaz:v:92:y:2018:i:1:d:10.1007_s11069-018-3216-0
    DOI: 10.1007/s11069-018-3216-0
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    Cited by:

    1. Wei Pei & Cuizhu Tian & Qiang Fu & Yongtai Ren & Tianxiao Li, 2022. "Risk analysis and influencing factors of drought and flood disasters 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. 110(3), pages 1599-1620, February.
    2. Rong Tang & Xiugui Wang & Xudong Han & Yihui Yan & Shuang Huang & Jiesheng Huang & Tao Shen & Youzhen Wang & Jia Liu, 2022. "Effects of Combined Main Ditch and Field Ditch Control Measures on Crop Yield and Drainage Discharge in the Northern Huaihe River Plain, Anhui Province, China," Agriculture, MDPI, vol. 12(8), pages 1-25, August.
    3. Nikunj K. Mangukiya & Ashutosh Sharma, 2022. "Flood risk mapping for the lower Narmada basin in India: a machine learning and IoT-based framework," 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. 113(2), pages 1285-1304, September.
    4. Qingqing Li & Yanping Cao & Shuling Miao & Xinhe Huang, 2022. "Spatiotemporal Characteristics of Drought and Wet Events and Their Impacts on Agriculture in the Yellow River Basin," Land, MDPI, vol. 11(4), pages 1-20, April.

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