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Dynamic risk assessment of waterlogging disaster for maize based on CERES-Maize model in Midwest of Jilin Province, China

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  • Enliang Guo

    (Northeast Normal University)

  • Jiquan Zhang

    (Northeast Normal University)

  • Yongfang Wang

    (Northeast Normal University)

  • Ha Si

    (Northeast Normal University)

  • Feng Zhang

    (Northeast Normal University)

Abstract

Waterlogging disasters are one of the most destructive meteorological disasters, which lead to crop yield reduction and cause a great threat to humanity and economic structure. This study presents the methodology and procedure for dynamic risk assessment of waterlogging disasters for maize in Midwest of Jilin Province, China. We took the representative waterlogging disaster years of 1994, 2005, and 2010 as examples, the growth-stage waterlogging index was established to assess the waterlogging disaster hazard by using standard antecedent precipitation index and the relative humidity index. Maize growing data and maize planting area data were combined to assess the waterlogging disaster vulnerability of maize, in which the CERES-Maize model was used to simulate the growth of maize at a daily time step for each grid. Based on the theory of natural disaster risk, the dynamic risk assessment model of waterlogging disaster for maize was built. In this study, the risk indexes were divided into five classes by using an optimal partition method. The grid GIS technology was used to map the spatial distribution of data and the grade of waterlogging disaster risk at a resolution of 5000 × 5000 m. The results show that areas with very low waterlogging disaster risk are mainly located in western and northeastern regions; in contrast, very high and high waterlogging disaster risk levels are mainly located in southern and central regions. Meanwhile, high risk areas at different growth stages gradually spread from the southwestern to the Midwestern and southeastern regions. This study could help the government when they make strategic decisions regarding food security in China, and the method of dynamic waterlogging risk disaster assessment could also be applied for other crops to control and prevent the occurrence and development of waterlogging disasters and reduce their adverse influence.

Suggested Citation

  • Enliang Guo & Jiquan Zhang & Yongfang Wang & Ha Si & Feng Zhang, 2016. "Dynamic risk assessment of waterlogging disaster for maize based on CERES-Maize model in Midwest of Jilin Province, 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. 83(3), pages 1747-1761, September.
    • Handle: RePEc:spr:nathaz:v:83:y:2016:i:3:d:10.1007_s11069-016-2391-0
    DOI: 10.1007/s11069-016-2391-0
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    References listed on IDEAS

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    Cited by:

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    2. Riao, Dao & Guga, Suri & Bao, Yongbin & Liu, Xingping & Tong, Zhijun & Zhang, Jiquan, 2023. "Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 275(C).
    3. Yuhe Ji & Guangsheng Zhou & Lixia Wang & Shudong Wang & Zongshan Li, 2019. "Identifying climate risk causing maize (Zea mays L.) yield fluctuation by time-series data," 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. 96(3), pages 1213-1222, April.
    4. Dang Luo & Wenxin Mao & Huifang Sun, 2017. "Risk assessment and analysis of ice disaster in Ning–Meng reach of Yellow River based on a two-phased intelligent model under grey information environment," 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. 88(1), pages 591-610, August.
    5. He, Guohua & Geng, Chenfan & Zhao, Yong & Wang, Jianhua & Jiang, Shan & Zhu, Yongnan & Wang, Qingming & Wang, Lizhen & Mu, Xing, 2021. "Food habit and climate change impacts on agricultural water security during the peak population period in China," Agricultural Water Management, Elsevier, vol. 258(C).
    6. Ying Guo & Rui Wang & Zhijun Tong & Xingpeng Liu & Jiquan Zhang, 2019. "Dynamic Evaluation and Regionalization of Maize Drought Vulnerability in the Midwest of Jilin Province," Sustainability, MDPI, vol. 11(15), pages 1-21, August.

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