Preprints
https://doi.org/10.5194/nhess-2021-101
https://doi.org/10.5194/nhess-2021-101

  13 Apr 2021

13 Apr 2021

Review status: this preprint is currently under review for the journal NHESS.

Monitoring and analysis of Woda landslide stability (China) combined with InSAR, GNSS and meteorological data

Bingquan Li1, Wenliang Jiang1, Yongsheng Li1, Yi Luo1, Haitao Qian1, Yanchao Wang1, Qisong Jiao1, Qingyun Zhang2, Zihan Zhou1, and Jingfa Zhang1 Bingquan Li et al.
  • 1National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing, China
  • 2The First Monitoring and Application Centre, China Earthquake Administration, Tianjin, China

Abstract. Detecting the slow motions of high and distant landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to rainfall. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. The method used in this paper can be used for early recognition and early warning of high and remote landslides.

Bingquan Li et al.

Status: open (until 25 May 2021)

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Bingquan Li et al.

Bingquan Li et al.

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Short summary
To identify the boundaries and deformation distributions of the unstable areas, the results of space-borne SAR and field surveys were combined, and the spatial deformation characteristics and time evolution of the landslide were analysed. The factor inducing landslide deformation is concentrated heavy rainfall. The research results show that SAR/InSAR technology can reveal the surface deformation of a landslide body and characterize the active stage and development trend.
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