Journal
REMOTE SENSING
Volume 14, Issue 11, Pages -Publisher
MDPI
DOI: 10.3390/rs14112683
Keywords
reservoir landslide; multi-source monitoring data; InSAR; displacement back analysis; numerical modeling
Categories
Funding
- National Natural Science Foundation of China [51825905, 52179141, U1865204]
- Huaneng Group Science and Technology Project [HNKJ18-H24]
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This article introduces the necessity and feasibility of using multi-source monitoring data in landslide displacement back analysis in reservoir areas. By utilizing surface InSAR and internal inclinometers, the article predicts landslide deformation through numerical modeling and evaluates the deformation state and stability of landslides, which is crucial for reservoir risk mitigation and the sustainable development of hydropower resources.
Landslides that occur in the littoral zone of a reservoir can directly damage the hydraulic structures and threaten the lives and property around the reservoir. Due to the spatial variability and heterogeneities of rock mass, a limited amount of data obtained from laboratory and in situ tests cannot comprehensively characterize the mechanical properties of rock and soil masses. Therefore, displacement back analysis is often performed to determine the mechanical parameters of rock and soil masses. The spaceborne Interferometric synthetic aperture radar (InSAR) has proved to be a powerful tool for geodesy in the measurement of landslide movement. However, InSAR can only measure the surface motion of the landslide without the subsurface information. This study uses multi-source monitoring data in the landslide displacement back analysis, including surface InSAR and an internal borehole inclinometer. The identified material parameters and finite element simulation are used to predict the landslide deformation. The case study of the Cheyiping landslide located in the Lancang River basin demonstrates the necessity and feasibility of using multi-source monitoring data in landslide displacement back analysis. The Cheyiping landslide is currently in the creep deformation stage. The decrease in shear strength of rock masses due to the rheological deformation and the change in reservoir water level are the internal and external factors leading to excessive landslide deformation. The numerical modeling can accurately simulate the landslide movement using the identified material parameters. By combing multi-source monitoring data and numerical modeling, the reservoir landslide deformation analysis can help evaluate the landslide deformation state and stability, which is vital for reservoir risk mitigation and the sustainable development of hydropower resources.
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