IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i11p8646-d1156517.html
   My bibliography  Save this article

Spatiotemporal Analysis of Earthquake Distribution and Associated Losses in Chinese Mainland from 1949 to 2021

Author

Listed:
  • Tongyan Zheng

    (China Earthquake Networks Center, Beijing 100045, China)

  • Lei Li

    (National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
    Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China
    School of Engineering and Technology, China University of Geosciences (Beijing), Beijing 100083, China)

  • Chong Xu

    (National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
    Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China)

  • Yuandong Huang

    (National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
    Key Laboratory of Compound and Chained Natural Hazards Dynamics, Ministry of Emergency Management of China, Beijing 100085, China
    School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing 100083, China)

Abstract

A comprehensive earthquake hazard database is crucial for comprehending the characteristics of earthquake-related losses and establishing accurate loss prediction models. In this study, we compiled the earthquake events that have caused losses since 1949, and established and shared a database of earthquake hazard information for the Chinese mainland from 1949 to 2021. On this basis, we preliminarily analyzed the spatiotemporal distribution characteristics of 608 earthquake events and the associated losses. The results show the following: (1) The number of earthquakes is generally increasing, with an average of annual occurrence rising from three to twelve, and the rise in the economic losses is not significant. The number of earthquakes occurring in the summer is slightly higher than that in the other three seasons. (2) The average depths of earthquakes within the six blocks display a decreasing trend from west to east, with a majority (63.8%) of earthquakes occurring at depths ranging from 5 to 16 km. (3) Although the number of earthquakes in the east is lower than that in the west, earthquakes in the east are more likely to cause casualties when they have the same epicenter intensity. Southwest China is located in the Circum-Pacific seismic zone where earthquake hazards are highly frequent. The results can provide fundamental data for developing earthquake-related loss prediction models.

Suggested Citation

  • Tongyan Zheng & Lei Li & Chong Xu & Yuandong Huang, 2023. "Spatiotemporal Analysis of Earthquake Distribution and Associated Losses in Chinese Mainland from 1949 to 2021," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8646-:d:1156517
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/11/8646/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/11/8646/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chaoxu Xia & Gaozhong Nie & Huayue Li & Xiwei Fan & Wenhua Qi, 2023. "A composite database of casualty-inducing earthquakes in mainland 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. 116(3), pages 3321-3351, April.
    2. Stav Shapira & Limor Aharonson-Daniel & Igal Shohet & Corinne Peek-Asa & Yaron Bar-Dayan, 2015. "Integrating epidemiological and engineering approaches in the assessment of human casualties in earthquakes," 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(2), pages 1447-1462, September.
    3. S. Turkan & G. Özel, 2014. "Modeling destructive earthquake casualties based on a comparative study for Turkey," 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 1093-1110, June.
    4. Shunichi Koshimura & Toshitaka Katada & Harold Mofjeld & Yoshiaki Kawata, 2006. "A method for estimating casualties due to the tsunami inundation flow," 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. 39(2), pages 265-274, October.
    5. José Badal & Miguel Vázquez-prada & Álvaro González, 2005. "Preliminary Quantitative Assessment of Earthquake Casualties and Damages," 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. 34(3), pages 353-374, March.
    6. Xing Huang & Huidong Jin, 2018. "An earthquake casualty prediction model based on modified partial Gaussian curve," 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. 94(3), pages 999-1021, December.
    Full references (including those not matched with items on IDEAS)

    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. Chaoxu Xia & Gaozhong Nie & Huayue Li & Xiwei Fan & Wenhua Qi, 2023. "A composite database of casualty-inducing earthquakes in mainland 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. 116(3), pages 3321-3351, April.
    2. Xia Chaoxu & Nie Gaozhong & Fan Xiwei & Li Huayue & Zhou Junxue & Zeng Xun, 2022. "A new model for the quantitative assessment of earthquake casualties based on the correction of anti-lethal level," 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(2), pages 1199-1226, January.
    3. Muhammet Gul & Ali Fuat Guneri, 2016. "An artificial neural network-based earthquake casualty estimation model for Istanbul city," 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. 84(3), pages 2163-2178, December.
    4. Stav Shapira & Tsafrir Levi & Yaron Bar-Dayan & Limor Aharonson-Daniel, 2018. "The impact of behavior on the risk of injury and death during an earthquake: a simulation-based study," 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. 91(3), pages 1059-1074, April.
    5. Li, Shuang & Yu, Xiaohui & Zhang, Yanjuan & Zhai, Changhai, 2018. "A numerical simulation strategy on occupant evacuation behaviors and casualty prediction in a building during earthquakes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1238-1250.
    6. Yingchun Li & Zhongliang Wu & Yizhe Zhao, 2011. "Estimating the number of casualties in earthquakes from early field reports and improving the estimate with time," 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. 56(3), pages 699-708, March.
    7. Manhao Luo & Shuangyun Peng & Yanbo Cao & Jing Liu & Bangmei Huang, 2023. "Earthquake fatality prediction based on hybrid feature importance assessment: a case study in Yunnan 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. 116(3), pages 3353-3376, April.
    8. S. Turkan & G. Özel, 2014. "Modeling destructive earthquake casualties based on a comparative study for Turkey," 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 1093-1110, June.
    9. Chen, Weiyi & Zhang, Limao, 2022. "An automated machine learning approach for earthquake casualty rate and economic loss prediction," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    10. Stav Shapira & Lena Novack & Yaron Bar-Dayan & Limor Aharonson-Daniel, 2016. "An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-11, March.
    11. Jin‐Feng Wang & Lian‐Fa Li, 2008. "Improving Tsunami Warning Systems with Remote Sensing and Geographical Information System Input," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1653-1668, December.
    12. Jiajun Wang & Zhichao He & Wenguo Weng, 2020. "A review of the research into the relations between hazards in multi-hazard risk analysis," 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. 104(3), pages 2003-2026, December.
    13. Goran Grozdanić & Vladimir M. Cvetković & Tin Lukić & Aleksandar Ivanov, 2024. "Sustainable Earthquake Preparedness: A Cross-Cultural Comparative Analysis in Montenegro, North Macedonia, and Serbia," Sustainability, MDPI, vol. 16(8), pages 1-35, April.
    14. S. Jonkman & J. Vrijling & A. Vrouwenvelder, 2008. "Methods for the estimation of loss of life due to floods: a literature review and a proposal for a new method," 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. 46(3), pages 353-389, September.
    15. Alireza Mostafizi & Haizhong Wang & Dan Cox & Lori A. Cramer & Shangjia Dong, 2017. "Agent-based tsunami evacuation modeling of unplanned network disruptions for evidence-driven resource allocation and retrofitting strategies," 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(3), pages 1347-1372, September.
    16. Huang Xing & Song Junyi & Huidong Jin, 2020. "The casualty prediction of earthquake disaster based on Extreme Learning Machine method," 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. 102(3), pages 873-886, July.
    17. Wanpeng Ding & Zhijian Wu & Beilei Zhan & Jian Liu & Jun Bi, 2023. "Analysis of seismic damage of a highway bridge during the 2021 Ms 7.4 earthquake in Maduo County, 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. 117(3), pages 2419-2434, July.
    18. Xuejun Jiang & Yunxian Li & Aijun Yang & Ruowei Zhou, 2020. "Bayesian semiparametric quantile regression modeling for estimating earthquake fatality risk," Empirical Economics, Springer, vol. 58(5), pages 2085-2103, May.
    19. Lizhe Jia & Hui Li & Zhongdong Duan, 2012. "Convex model for gross domestic product-based dynamic earthquake loss assessment method," 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. 60(2), pages 589-604, January.
    20. Tingting Ji & Hsi-Hsien Wei & Igal M. Shohet & Feng Xiong, 2021. "Risk-based resilience concentration assessment of community to seismic hazards," 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. 108(2), pages 1731-1751, September.

    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:gam:jsusta:v:15:y:2023:i:11:p:8646-:d:1156517. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.