Rapid Assessment of Landslides Induced by Jishishan Ms6.2 Earthquake in Gansu Province

ZENG Ying; ZHANG Yingbin; CHU Feng; LIU Jing; FENG Zhenhai; SU Jinrong

doi:10.3969/j.issn.0258-2724.20240041

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Journal of Southwest Jiaotong University > 2025 > Accepted Manuscript

ZENG Ying, ZHANG Yingbin, CHU Feng, LIU Jing, FENG Zhenhai, SU Jinrong. Rapid Assessment of Landslides Induced by Jishishan Ms6.2 Earthquake in Gansu Province[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240041

Citation:

ZENG Ying, ZHANG Yingbin, CHU Feng, LIU Jing, FENG Zhenhai, SU Jinrong. Rapid Assessment of Landslides Induced by Jishishan Ms6.2 Earthquake in Gansu Province[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240041

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Rapid Assessment of Landslides Induced by Jishishan Ms6.2 Earthquake in Gansu Province

doi: 10.3969/j.issn.0258-2724.20240041

1.
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
2.
China Road & Bridge Corporation, Beijing 100011, China
3.
Sichuan Earthquake Administration, Chengdu 610041, China

Received Date: 19 Jan 2024
Rev Recd Date: 10 Apr 2024

Available Online: 21 Jan 2025

Abstract

Abstract

Rapidly obtaining co-seismic landslide distribution and conducting disaster assessments after earthquakes are vital for effective emergency relief and reconstruction. Therefore, in this study, the InSAR data-Newmark physical fusion driver model (IDNPM) was used to rapidly assess the landslides triggered by the earthquake in Jishishan, Gansu Province on December 18, 2023, with a view to quickly and accurately grasping the macroscopic distribution of landslide hazards. Firstly, through the time series SBAS-InSAR, it was revealed that there was serious gully development and retrogressive erosion in this area. These geological characteristics provided a favorable breeding environment for landslides. Secondly, the IDNPM was used to quickly evaluate the landslide of Jishishan earthquake, and it was predicted that the steep slopes and gully sides of Zhaomuchuan Village, Tashapo Village, and Dahejia Town were the high-risk areas for earthquake-induced landslide. Finally, based on the field investigation, numerical simulation, and satellite identification technology, the reliability of the model in practical application was proven. The results indicate that a total of 2.657% of the region is at high risk. There is a need to focus on such zones by urgently clearing and stabilizing slopes where landslides have occurred. For areas where no landslides have occurred, monitoring and assessment measures should be taken to guard against possible post-earthquake secondary landslide events. The research results can provide strong data support for emergency relief and reconstruction work after earthquakes in the affected areas.
- earthquake,
- landslide,
- emergency assessment,
- prediction model,
- InSAR technology

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References

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