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<p>Large-scale red-bed landslides are mainly induced by prolonged rainfall, resulting in significant risks that may be exacerbated by climate change. In June 2022, a deep-seated red-bed landslide with a gentle dip destroyed a village in Tianziling Town in Guangdong, China, after the end of a prolonged heavy rainfall. Such large landslides were not previously reported in Guangdong. This raises two scientific questions: The mechanisms of the landslide remain to be clarified; more importantly, is there any sign for the early identification of similar concealed potential sites? To provide answers, we conducted a comprehensive field investigation, drone mapping, geological borehole drilling, lab tests, and in situ monitoring. It was found that the landslide was a reactivation from an old landslide, with a short moving distance of 37 to 71&#xa0;m and a velocity of 0.61 to 1.18&#xa0;m/min. Both landslides exhibited highly consistent post-landslide anomaly landform. Long-lasting rainfall was the direct trigger of the landslide, with 40.0%–71.1% strength reduction of immersed mudstone, hydraulic pressure at rear cracks, and uplift pressure along the failure plane. For the first time, we propose to identify potential similar landslides by searching in the LiDAR map for residual rock pillars, providing a new approach for the early identification and prevention of such types of landslides. Post-event monitoring suggests possible future failure.</p>

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Investigation of a large-scale red-bed landslide in Guangdong, China, and implication for landslide early identification

  • 期刊论文

  • 发表日期：

    2025年9月26日

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  • Shou-Yong Yi,
  • Feng Peng,
  • Jie Zou,
  • Tian-He Wang,
  • Cai-Zheng Tian,
  • Shan-Cai Yang,
  • Ping Shen

摘要

Large-scale red-bed landslides are mainly induced by prolonged rainfall, resulting in significant risks that may be exacerbated by climate change. In June 2022, a deep-seated red-bed landslide with a gentle dip destroyed a village in Tianziling Town in Guangdong, China, after the end of a prolonged heavy rainfall. Such large landslides were not previously reported in Guangdong. This raises two scientific questions: The mechanisms of the landslide remain to be clarified; more importantly, is there any sign for the early identification of similar concealed potential sites? To provide answers, we conducted a comprehensive field investigation, drone mapping, geological borehole drilling, lab tests, and in situ monitoring. It was found that the landslide was a reactivation from an old landslide, with a short moving distance of 37 to 71 m and a velocity of 0.61 to 1.18 m/min. Both landslides exhibited highly consistent post-landslide anomaly landform. Long-lasting rainfall was the direct trigger of the landslide, with 40.0%–71.1% strength reduction of immersed mudstone, hydraulic pressure at rear cracks, and uplift pressure along the failure plane. For the first time, we propose to identify potential similar landslides by searching in the LiDAR map for residual rock pillars, providing a new approach for the early identification and prevention of such types of landslides. Post-event monitoring suggests possible future failure.