IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v83y2016i3d10.1007_s11069-016-2391-0.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-016-2391-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-016-2391-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Naderpour, Mohsen & Lu, Jie & Zhang, Guangquan, 2015. "An abnormal situation modeling method to assist operators in safety-critical systems," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 33-47.
    3. Enliang Guo & Jiquan Zhang & Xuehui Ren & Qi Zhang & Zhongyi Sun, 2014. "Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning 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. 74(2), pages 947-965, November.
    4. Majid Mirzaei & Yuk Huang & Ahmed El-Shafie & Tayebeh Chimeh & Juneseok Lee & Nariman Vaizadeh & Jan Adamowski, 2015. "Uncertainty analysis for extreme flood events in a semi-arid region," 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 1947-1960, September.
    5. Quirin Schiermeier, 2011. "Increased flood risk linked to global warming," Nature, Nature, vol. 470(7334), pages 316-316, February.
    6. Qi Zhang & Jiquan Zhang & Chunyi Wang & Liang Cui & Denghua Yan, 2014. "Risk early warning of maize drought disaster in Northwestern Liaoning 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. 72(2), pages 701-710, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jingpeng Guo & Kebiao Mao & Yinghui Zhao & Zhong Lu & Xiaoping Lu, 2019. "Impact of Climate on Food Security in Mainland China: A New Perspective Based on Characteristics of Major Agricultural Natural Disasters and Grain Loss," Sustainability, MDPI, vol. 11(3), pages 1-25, February.
    2. 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.
    3. 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).
    4. 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.
    5. 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).
    6. 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.
    7. Guo, Yajiaoxue & Sun, Zhanxiang & Bai, Wei & Zhang, Zhe & Zhang, Yue & Du, Hongjun & Sun, Tianran & Zhang, Jinyu & Peng, Pu & Ji, Yafei & Cai, Qian & Dong, Zhi & Zhang, Xu & Feng, Liangshan & Feng, Ch, 2024. "Drought risk assessment for maize/peanut intercropping based on crop model and SPEI," Agricultural Systems, Elsevier, vol. 221(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Islam, Moinul & Kotani, Koji & Managi, Shunsuke, 2016. "Climate perception and flood mitigation cooperation: A Bangladesh case study," Economic Analysis and Policy, Elsevier, vol. 49(C), pages 117-133.
    2. Mompremier, R. & Her, Y. & Hoogenboom, G. & Migliaccio, K. & Muñoz-Carpena, R. & Brym, Z. & Colbert, R.W. & Jeune, W., 2021. "Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology," Agricultural Water Management, Elsevier, vol. 243(C).
    3. Chen, Shang & He, Liang & Cao, Yinxuan & Wang, Runhong & Wu, Lianhai & Wang, Zhao & Zou, Yufeng & Siddique, Kadambot H.M. & Xiong, Wei & Liu, Manshuang & Feng, Hao & Yu, Qiang & Wang, Xiaoming & He, J, 2021. "Comparisons among four different upscaling strategies for cultivar genetic parameters in rainfed spring wheat phenology simulations with the DSSAT-CERES-Wheat model," Agricultural Water Management, Elsevier, vol. 258(C).
    4. You, Qidong & Guo, Jianbin & Zeng, Shengkui & Che, Haiyang, 2024. "A dynamic Bayesian network based reliability assessment method for short-term multi-round situation awareness considering round dependencies," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    5. Attia, Ahmed & El-Hendawy, Salah & Al-Suhaibani, Nasser & Alotaibi, Majed & Tahir, Muhammad Usman & Kamal, Khaled Y., 2021. "Evaluating deficit irrigation scheduling strategies to improve yield and water productivity of maize in arid environment using simulation," Agricultural Water Management, Elsevier, vol. 249(C).
    6. Bahram Choubin & Farzaneh Sajedi Hosseini & Omid Rahmati & Mansor Mehdizadeh Youshanloei, 2023. "A step toward considering the return period in flood spatial 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. 115(1), pages 431-460, January.
    7. Zhou, Jian-Lan & Lei, Yi, 2020. "A slim integrated with empirical study and network analysis for human error assessment in the railway driving process," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    8. N. Zafirah & N. A. Nurin & M. S. Samsurijan & M. H. Zuknik & M. Rafatullah & M. I. Syakir, 2017. "Sustainable Ecosystem Services Framework for Tropical Catchment Management: A Review," Sustainability, MDPI, vol. 9(4), pages 1-25, April.
    9. Junnan Xiong & Chongchong Ye & Weiming Cheng & Liang Guo & Chenghu Zhou & Xiaolei Zhang, 2019. "The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province," Sustainability, MDPI, vol. 11(10), pages 1-18, May.
    10. Nadir Elagib, 2015. "Drought risk during the early growing season in Sahelian Sudan," 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. 79(3), pages 1549-1566, December.
    11. Ruiling Sun & Zaiwu Gong & Weiwei Guo & Ashfaq Ahmad Shah & Jie Wu & Haiying Xu, 2022. "Flood disaster risk assessment of and countermeasures toward Yangtze River Delta by considering index interaction," 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. 112(1), pages 475-500, May.
    12. Xueyou Zhang & Junfei Chen & Chong Yu & Qian Wang & Tonghui Ding, 2024. "Emergency risk assessment of sudden water pollution in South-to-North Water Diversion Project in China based on driving force–pressure–state–impact–response (DPSIR) model and variable fuzzy set," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 20233-20253, August.
    13. Zhang, Ziya & Li, Yi & Chen, Xinguo & Wang, Yanzi & Niu, Ben & Liu, De Li & He, Jianqiang & Pulatov, Bakhtiyor & Hassan, Ishtiaq & Meng, Qingtao, 2023. "Impact of climate change and planting date shifts on growth and yields of double cropping rice in southeastern China in future," Agricultural Systems, Elsevier, vol. 205(C).
    14. Tian Qiao & Hussein Hoteit & Marwan Fahs, 2021. "Semi-Analytical Solution to Assess CO 2 Leakage in the Subsurface through Abandoned Wells," Energies, MDPI, vol. 14(9), pages 1-15, April.
    15. Cui, Yi & Zhou, Yuliang & Jin, Juliang & Jiang, Shangming & Wu, Chengguo & Ning, Shaowei, 2023. "Spatiotemporal characteristics and obstacle factors identification of agricultural drought disaster risk: A case study across Anhui Province, China," Agricultural Water Management, Elsevier, vol. 289(C).
    16. Junfei Chen & Menghua Deng & Lu Xia & Huimin Wang, 2017. "Risk Assessment of Drought, Based on IDM-VFS in the Nanpan River Basin, Yunnan Province, China," Sustainability, MDPI, vol. 9(7), pages 1-16, June.
    17. Shirin Karimi & Bahman Jabbarian Amiri & Arash Malekian, 2019. "Similarity Metrics-Based Uncertainty Analysis of River Water Quality Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 1927-1945, April.
    18. Yan, Ling & Jin, Jiming & Wu, Pute, 2020. "Impact of parameter uncertainty and water stress parameterization on wheat growth simulations using CERES-Wheat with GLUE," Agricultural Systems, Elsevier, vol. 181(C).
    19. Swenja Surminski & Delioma Oramas-Dorta, 2013. "Do flood insurance schemes in developing countries provide incentives to reduce physical risks?," GRI Working Papers 119, Grantham Research Institute on Climate Change and the Environment.
    20. Ahmadi, Mehdi & Ascough, James C. & DeJonge, Kendall C. & Arabi, Mazdak, 2014. "Multisite-multivariable sensitivity analysis of distributed watershed models: Enhancing the perceptions from computationally frugal methods," Ecological Modelling, Elsevier, vol. 279(C), pages 54-67.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:83:y:2016:i:3:d:10.1007_s11069-016-2391-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.