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Rapid Estimation of Earthquake Fatalities in Mainland China Based on Physical Simulation and Empirical Statistics—A Case Study of the 2021 Yangbi Earthquake

Author

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  • Yilong Li

    (Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, China)

  • Zhenguo Zhang

    (Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, China
    Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China
    Guangdong Provincial Key Laboratory of Geophysical High-Resolution Imaging Technology, Southern University of Science and Technology, Shenzhen 518055, China)

  • Wenqiang Wang

    (Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, China)

  • Xuping Feng

    (Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, China)

Abstract

At present, earthquakes cannot be predicted. Scientific decision-making and rescue after an earthquake are the main means of mitigating the immediate consequences of earthquake disasters. If emergency response level and earthquake-related fatalities can be estimated rapidly and quantitatively, this estimation will provide timely, scientific guidance to government organizations and relevant institutions to make decisions on earthquake relief and resource allocation, thereby reducing potential losses. To achieve this goal, a rapid earthquake fatality estimation method for Mainland China is proposed herein, based on a combination of physical simulations and empirical statistics. The numerical approach was based on the three-dimensional (3-D) curved grid finite difference method (CG-FDM), implemented for graphics processing unit (GPU) architecture, to rapidly simulate the entire physical propagation of the seismic wavefield from the source to the surface for a large-scale natural earthquake over a 3-D undulating terrain. Simulated seismic intensity data were used as an input for the fatality estimation model to estimate the fatality and emergency response level. The estimation model was developed by regression analysis of the data on human loss, intensity distribution, and population exposure from the Mainland China Composite Damaging Earthquake Catalog (MCCDE-CAT). We used the 2021 Ms 6.4 Yangbi earthquake as a study case to provide estimated results within 1 h after the earthquake. The number of fatalities estimated by the model was in the range of 0–10 (five expected fatalities). Therefore, Level IV earthquake emergency response plan should have been activated (the government actually overestimated the damage and activated a Level II emergency response plan). The local government finally reported three deaths during this earthquake, which is consistent with the model predictions. We also conducted a case study on a 2013 Ms7.0 earthquake in the discussion, which further proved the effectiveness of the method. The proposed method will play an important role in post-earthquake emergency response and disaster assessment in Mainland China. It can assist decision-makers to undertake scientifically-based actions to mitigate the consequences of earthquakes and could be used as a reference approach for any country or region.

Suggested Citation

  • Yilong Li & Zhenguo Zhang & Wenqiang Wang & Xuping Feng, 2022. "Rapid Estimation of Earthquake Fatalities in Mainland China Based on Physical Simulation and Empirical Statistics—A Case Study of the 2021 Yangbi Earthquake," IJERPH, MDPI, vol. 19(11), pages 1-14, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6820-:d:830663
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    References listed on IDEAS

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    1. Andrew Tatem & Catherine Linard, 2011. "Population mapping of poor countries," Nature, Nature, vol. 474(7349), pages 36-36, June.
    2. Erfan Firuzi & Kambod Amini Hosseini & Anooshiravan Ansari & Yasamin O. Izadkhah & Mina Rashidabadi & Mohammad Hosseini, 2020. "An empirical model for fatality estimation of earthquakes in Iran," 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. 103(1), pages 231-250, August.
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