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Spatiotemporal characteristics of earthquake disaster losses in China from 1993 to 2016

  • Xiaoli Li
  • Zhiqiang Li
  • Jiansi Yang
  • Yaohui Liu
  • Bo Fu
  • Wenhua Qi
  • Xiwei Fan
Original Paper

Abstract

On the basis of data obtained from China Earthquake Administration and China National Statistics Bureau, this paper focuses on the earthquake disaster loss characteristics in 31 provinces or municipalities of China from 1993 to 2016. The trends of direct economic losses, casualties and affected population are also analyzed by constructing two relative earthquake loss indexes (losses/GDP and losses/E) and employing gray correlation theory. Results show that during the 24 years, without taking Wenchuan Ms8.0 earthquake into account, the direct economic losses exhibit a significant increasing trend while losses/GDP also increases but is not significant. Meanwhile, the injuries and affected population both witness a decline trend but the fatalities show the opposite. According to the correlational degree of each year, 8 years (1995, 1996, 1998, 2003, 2008, 2010, 2013 and 2014) suffered losses of equal or above moderate grade. Regionally, the western China suffered the most accumulative direct economic losses and losses/GDP. However, the ranking results of losses/E demonstrate that the central China is the most vulnerable when confronting with the same earthquake. Specifically, Sichuan and Yunnan suffered losses of extra-large grade, Qinghai of large grade and Tibet, Xinjiang and Guangdong of moderate grade. These discoveries are helpful for earthquake mitigation and preparedness as well as earthquake loss evaluation in China.

Keywords

Spatiotemporal characteristics Earthquake disaster losses Losses/GDP Losses/E Gray correlation theory Correlational degree Loss grade 

Notes

Acknowledgements

This work was supported by Central Public-Interest Scientific Institution Basal Research Fund (Grant No. IGCEA1610), the National Natural Science Foundation of China (Grant No. 41,601,390) and Special Project Funding for Seismic Research (Grant No. 20130801805). The authors are grateful to Li Yang from Department of Earthquake Emergency Rescue, China Earthquake Administration and Zheng Tongyan from China Earthquake Networks Center, China Earthquake Administration for the help in data collection.

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Institute of GeophysicsChina Earthquake AdministrationBeijingChina
  2. 2.Institute of GeologyChina Earthquake AdministrationBeijingChina

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