Characteristics, mechanisms, and post-disaster lessons of the delayed semi-diagenetic landslide in Hanyuan, Sichuan, China

Landslides following rainfall occurrence are a widespread phenomenon. The neglect of this phenomenon leads to serious loss of life when disasters occur. At 03:45 (GMT + 8) on August 21, 2020, a semi-diagenetic landslide occurred in Zhonghai Village, Hanyuan County, China, which occurred 42 h after earlier rainfall. Nine people privately returned to their homes after evacuation of the dangerous area. In this disaster, eight people were lost and one injured. This study explores the failure characteristics, inducement, and mechanisms of the landslide via field investigations, resident interviews, multi-temporal images, field drilling, and geotechnical tests. Hydrological numerical calculations were also performed to uncover the seepage and transfer processes of the groundwater in the slope. Finally, problems in the current community early warning system were analyzed and corresponding suggestions put forward. The results show that the maximum sliding depth of the landslide was 27.5 m, the total area was 80,000 m(2), and the sliding volume was about 58,0000 m(3), making it a medium-sized deep landslide. In addition to the vertical seepage of rainfall in the landslide area, the downward movement of rainfall in the back and upper catchment areas along the silt sand strata also affected the stability of the landslide. More needs to be done to make the population aware of this lag phenomenon to achieve scientific disaster reduction. This study not only provides a case study of a lagging semi-diagenetic landslide, but also provides insight into hydrological boundary determination and landslide early warning system construction.

Automated summary

This study examines a semi-diagenetic landslide disaster that occurred in China, analyzing its failure characteristics, inducement, and mechanisms through field investigations and numerical calculations. The study also identifies issues with the current community early warning system and suggests improvements to enhance scientific disaster reduction efforts.