4.7 Article

Detecting Chamoli landslide precursors in the southern Himalayas using remote sensing data

Journal

LANDSLIDES
Volume 18, Issue 10, Pages 3449-3456

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10346-021-01753-y

Keywords

Landslide precursor detection; Hazard chain; Remote sensing; Himalayan Mountains

Funding

  1. National Natural Science Foundation of China [41941016]
  2. National Institute of Natural Hazards, Ministry of Emergency Management of China [ZDJ2020-01]

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A study using Sentinel-2 images to diagnose the landslide trigger of a catastrophic flood in the Himalayan region of India revealed a high-position landslide causing massive destruction to local infrastructure. By monitoring slope stabilities in the Himalayan Mountains and beyond, it is urgent for regional sustainability in the face of similar hazard chains expected due to climate warming.
On 7 February 2021, a catastrophic flood destroyed two hydropower plants, killing at least 150 people in the Himalayan Uttarakhand state of India. This flood was reportedly initiated by a high-position landslide. This work explored the capability of using Sentinel-2 images to diagnose the landslide trigger of this event. There were 264 Sentinel-2 images taken before the landslide, 111 of which are clear. In a pre-landslide Sentinel-2 image, tensile cracks are clearly visible on the landslide head. In the post-landslide image acquired on 10 February 2021, a fresh landslide scarp stripped of snow is visible, indicating that a high-position landslide occurred that may have led to the disaster in the downstream areas. The landslide was initiated at an elevation of similar to 5600 m, slid to the valley floor (similar to 3800 m elevation) and scooped up an unconsolidated mixture of moraine, ice and water that wreaked havoc on local infrastructure. To derive the slope deformation that occurred before the landslide, we selected 15 Sentinel-2 images to compose 10 image pairs. To filter out background noise, we developed a new method to derive reliable slope deformation results. We found that the slope was consistently moving since 2016, after which it moved at least 25 m. We speculated that the slope instability was caused by the seasonal freeze-thaw process. With the impacts of climate warming, more similar hazard chains are expected in the Himalayan region. The regular monitoring of slope stabilities in the Himalayan Mountains and beyond is urgently needed for regional sustainability.

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