Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red b...Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar(SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on In SAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone(US), a lower uplifted zone(LU), and a toe zone(Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index(GLSI) and deformation normalization index(DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage(ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall.展开更多
基金funded by the List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021(Grant No.2021-MS4-105)the Science and Technology Project of Yunnan Traffic Planning Design Institute Co.,Ltd.(Grant No.ZL-2021-03)+7 种基金the Postgraduate Scientific Research Innovation Project of Yunnan University(Grant No.2020192)the National Key Research and Development Program of China(Grant No.2018YFC1504906)the National Natural Science Foundation of China(Grant No.41872251)the Plateau Mountain Ecology and Earth’s Environment Discipline Construction Project(Grant No.C1762101030017)the Joint Foundation Project between Yunnan Science and Technology Department and Yunnan University(Grants No.C176240210019 and 2019FY003017)the Yunnan Postdoctoral Foundation(Grant No.C615300504031)the China Geological Survey Project(Grant No.DD20221824)the science and technology innovation program of the department of transportation,Yunnan province,China(No.2019301)。
文摘Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar(SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on In SAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone(US), a lower uplifted zone(LU), and a toe zone(Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index(GLSI) and deformation normalization index(DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage(ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall.
