Abstract

Under the influence of climate change, permafrost landforms are sensitive to seasonal heave and contraction, thus exacerbating surface instability and fostering landslides as a consequence. In the pastureland of Zhimei on the Qinghai-Tibet Plateau (QTP), a typical earthflow has drawn significant attention through social media. However, detailed knowledge of the deformation characteristics, internal hydrothermal regime, and structure is still scarce. In this study, we aim to enhance traditional satellite synthetic aperture radar interferometry to divide ground deformation into the seasonal oscillation and slope deformation components and identify the magnitude and spatial distribution of unstable slopes in frozen regions. Then, the use of unmanned aerial vehicles (UAVs) was combined with geophysical monitoring techniques to recognise the deformation dynamics from the pre- to post-failure stages. Sentinel-1 images, covering almost five years, highlighted that obvious creep behaviour dominated at the pre-failure stage, while a seasonal deformation pattern characterised by a piecewise distribution associated with the hydrothermal regime was observed at the post-failure stage. Fast retrogressive erosion on the head scarps at the post-failure stage was clearly identified by multidifferential digital surface models from the UAV observations. To better understand the internal structure, both electrical resistivity tomography and ground-penetrating radar were combined to determine the seasonal frozen thickness, underlying thawing materials, and vertical cracks, which controlled the kinematic evolution from the initial creep to the narrow and long oversaturated flow that represented the terminal portion of the landslide. Finally, by comparing in situ monitoring data with field investigations, the main driving factors controlling the movement mechanism are discussed. Our results highlight the specific kinematic behaviour of an earthflow and can provide a reference for slope destabilisation on the QTP under the influence of climate change.

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