Impact of precipitation on Beishan landslide deformation from 1986 to 2023 - Liu, Meng; Yang, Wentao; Xu, Chong; Yang, Yuting; Taylor, Liam; Shi, Peijun (Frontiers in Earth Science, 2024)
Investigating the response of landslide activity to climate change is crucial for understanding disastrous effects of climate change on high mountains. However, there is a lack of long-term, spatial-temporal consistent measurement of landslide activity prohibiting the study of this relationship. In this work, we used two methods to derive time-series of a landslide's deformation and study its relationship with precipitation in northeast Tibetan Plateau. The Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) method with Sentinel-1A images is firstly applied to derive timeseries of the landslide's deformation from 2020 to 2021. A recently developed method to derive cumulative deformations of optical images was used with Landsat 5 and Sentinel-2 images to derive the long-term deformation time-series from 1986 to 2023. Centimetre scale deformations detected by the Interferometric Synthetic Aperture Radar (InSAR) method are mainly located in the upper and eastern parts of the landslide, whereas metre scale deformations detected by optical method are in the middle of the landslide. Time-series results from both methods show that intra-annual initiations of the landslide's deformation occurred in rainy months (from July to October). Although there seems to be no direct relations between interannual deformations and precipitation, significant displacements since 2020 occurred after exceptionally wet years from 2018 (with a record-breaking precipitation year in 2020). With optical images, we found the maximum cumulative deformation of the landslide is >35 m since 1986 with major deformations (>20 m) found after 2020, which may indicate an imminent risk to the Lijie town near the landslide's toe. With climate change, increased precipitation is expected in future, which may trigger more similar landslides in this region its vicinity. This work demonstrates an executable framework to assess landslide hazard risk under climate change.