Rapid disaster assessment of a M 6.8 earthquake in Dingri, Xizang, China

Abstract

We conducted a rapid seismic intensity assessment of a M 6.8 earthquake in Dingri, Xizang, using a ground motion parameter attenuation model based on the shortest fault distance combined with either an empirical equation for the surface rupture length or data on the aftershocks that occurred within 1.5 ​hr after the earthquake. The assessment showed that the empirical equation for the relationship between the surface rupture length and magnitude established by Wells et al. yielded a surface rupture length that was closer to the actual value, while the seismic intensity determined using a combination of the ground motion parameter attenuation model and the empirical equation for the surface rupture length was relatively in line with the intensity from the actual investigation. This study also demonstrated that manual intervention and screening are needed for aftershocks within 1.5 ​hr after the earthquake if this information is to be employed in the intensity assessment. In addition, if the death assessment model does not consider the seismic vulnerability of local buildings, significant errors can occur in practice. Nevertheless, the disaster assessment results were obtained within 5 ​min after the earthquake, thus providing important data support for the government emergency command and decision-making associated with the emergency rescue response.

Keywords

Dingri earthquake / Seismic intensity / Death assessment / Earthquake emergency

CRediT authorship contribution statement

Can Zhang: Formal analysis. Hongme Guo: Project administration. Dongming Wang: Investigation. Yuping Yang: Data curation. Zhen Zhao: Data curation. Ying Zhang: Investigation. Zonghang He: Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author agreement and Acknowledgement

All authors agree for this publication. We would like to thank the China Earthquake Disaster Prevention Center, Seismic Active Fault Survey Data Center (https://www.activefault-datacenter.cn), Dingri Earthquake Scientific Expedition Team of China University of Geosciences, China Earthquake Networks Center and USGS (https://www.usgs.gov)for providing data support.

This study was supported by the National Key R&D Program of China (2020YFA07106003), the National Natural Science Foundation of China (42061073), and the Innovation Team of Sichuan Earthquake Agency (202401).

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