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UAV survey and numerical modeling of loess landslides: an example from Zaoling, southern Shanxi Province, China

Author

Listed:
  • Siyuan Ma

    (Institute of Geology, China Earthquake Administration)

  • Jiangbo Wei

    (Xi’an University of Science and Technology
    Xi’an University of Science and Technology)

  • Chong Xu

    (National Institute of Natural Hazards, Ministry of Emergency Management of China (former Institute of Crustal Dynamics, China Earthquake Administration))

  • Xiaoyi Shao

    (Institute of Geology, China Earthquake Administration)

  • Shiyang Xu

    (Lanzhou Institute of Seismology, China Earthquake Administration
    China Earthquake Administration and Gansu Province)

  • Shaofeng Chai

    (Lanzhou Institute of Seismology, China Earthquake Administration
    China Earthquake Administration and Gansu Province)

  • Yulong Cui

    (Anhui University of Science and Technology)

Abstract

This work attempted to reveal the geometric and kinematic characteristics of a loess landslide that occurred at Zaoling, southern Shanxi Province, China, on March 15, 2019. Based on the high-resolution unmanned aerial vehicle survey and DEM data acquired after this event, the topography of the study area was reconstructed to estimate the volumes of the source area and the deposit area of the landslide. Coupled with the high-resolution three-dimensional topographic data, three-dimensional particle flow code was used to simulate the motion process and depositing characteristics of the landslide. Results show that the Zaoling landslide is a deep-seated loess landslide with a projection area of 9844 m2 and the attitude of the sliding surface 355°∠37° (trending and dip). The total volumes of the source zone and accumulation zone are 77,000 and 82,000 m3, respectively. The simulation results show that the whole sliding process lasts about 17 s. The maximum average velocity of the sliding body is 5.12 m/s and the average sliding displacement is 33.3 m. Comparing the depositing thickness obtained from the simulation with the reality shows that the accumulation thickness of the deposit area decreases gradually from the center to both sides. The accumulation characteristics from the simulation are roughly consistent with those of the actual landslide. According to the latest landslide classification system for loess slopes, the Zaoling landslide is a typical rotational slide. It is a typical case for loess landslide studies, in particular, its special failure mechanism and kinematic features.

Suggested Citation

  • Siyuan Ma & Jiangbo Wei & Chong Xu & Xiaoyi Shao & Shiyang Xu & Shaofeng Chai & Yulong Cui, 2020. "UAV survey and numerical modeling of loess landslides: an example from Zaoling, southern Shanxi 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. 104(1), pages 1125-1140, October.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:1:d:10.1007_s11069-020-04207-1
    DOI: 10.1007/s11069-020-04207-1
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    References listed on IDEAS

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    1. Ling Xu & Xiaojuan Qiao & Caixia Wu & Javed Iqbal & Fuchu Dai, 2012. "Causes of landslide recurrence in a loess platform with respect to hydrological processes," 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. 64(2), pages 1657-1670, November.
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    Cited by:

    1. Masanori Kohno & Yuki Higuchi & Yusuke Ono, 2023. "Evaluating earthquake-induced widespread slope failure hazards using an AHP-GIS combination," 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(2), pages 1485-1512, March.
    2. Qin Yigen & Yang Genlan & Liu Bangyu & Xu Jinxing, 2024. "Study on deformation and failure mechanism of low-dip red bed slope with soft-hard interbedded structure: a case study of Chishui, 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. 120(12), pages 10539-10557, September.
    3. Chenchen Xie & Yuandong Huang & Lei Li & Tao Li & Chong Xu, 2023. "Detailed Inventory and Spatial Distribution Analysis of Rainfall-Induced Landslides in Jiexi County, Guangdong Province, China in August 2018," Sustainability, MDPI, vol. 15(18), pages 1-17, September.
    4. Yulong Cui & Pengpeng Bao & Chong Xu & Gui Fu & Qisong Jiao & Yi Luo & Lingling Shen & Xiwei Xu & Fenglin Liu & Yuejun Lyu & Xiuhong Hu & Tao Li & Yongsheng Li & Yimin Liu & Yunfeng Tian, 2020. "A big landslide on the Jinsha River, Tibet, China: geometric characteristics, causes, and future stability," 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 2051-2070, December.
    5. Xuan-hao Wang & Wei Cui & Gui-ke Zhang & Hong Yang, 2023. "Identification of rocky ledge on steep, high slopes based on UAV photogrammetry," 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 3201-3224, April.

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