Remote Sensing (Aug 2024)

Identification and Deformation Characteristics of Active Landslides at Large Hydropower Stations at the Early Impoundment Stage: A Case Study of the Lianghekou Reservoir Area in Sichuan Province, Southwest China

  • Xueqing Li,
  • Weile Li,
  • Zhanglei Wu,
  • Qiang Xu,
  • Da Zheng,
  • Xiujun Dong,
  • Huiyan Lu,
  • Yunfeng Shan,
  • Shengsen Zhou,
  • Wenlong Yu,
  • Xincheng Wang

DOI
https://doi.org/10.3390/rs16173175
Journal volume & issue
Vol. 16, no. 17
p. 3175

Abstract

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Reservoir impoundment imposes a significant triggering effect on bank landslides. Studying the early identification of landslides and their stability concerning reservoir water levels and rainfall is vital for guaranteeing the safety of residents and infrastructure in reservoir regions. This study proposed a method for establishing a dynamic inventory of active landslides at large hydropower stations using integrated remote sensing techniques, demonstrated at Lianghekou Reservoir. We employed interferometric stacking synthetic aperture radar (stacking-InSAR) technology, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology, and optical satellite images to identify and catalogue active landslides. Moreover, we conducted field investigations to examine the deformation characteristics of landslides. Finally, Pearson’s correlation analysis was employed to evaluate the response between deformation values, reservoir water levels, and rainfall. The results revealed 75 active landslides, including 12 long-term active landslides before impoundment and 63 new landslides after impoundment, which were primarily concentrated in the Waduo and Yazho–Zatou regions. The correlation coefficient between landslide deformation values and the reservoir level was high (0.93), while the correlation coefficient with rainfall was low (0.57). The results of this research offer a crucial foundation for preventing and mitigating landslides in reservoir areas.

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