Abstract
Water impoundment of large reservoirs exerts a significant triggering effect on reservoir bank landslides. Research on early identification and deformation evolution of reservoir bank landslides can provide important support for geological disaster prevention and control in reservoir areas. The Lianghekou Hydropower Station reservoir area features complex geological conditions, deeply incised valleys, steep slopes, and intense weathering and unloading effects, which induced numerous landslide hazards during the initial impoundment stage, posing a serious threat to the operation of the hydropower station and the life and property safety of residents in the reservoir area. This study first employs integrated methods including Stacking-InSAR technology, high-resolution optical satellite imagery, airborne LiDAR technology, and field investigations to identify active landslides in the reservoir area and establish a dynamic inventory; second, based on deformation information obtained from SBAS-InSAR technology, constructs an activity assessment index system for reservoir landslides and classifies the activity levels of landslide hazards; third, analyzes the spatial distribution patterns of active landslides in the study area based on its geological environment characteristics; finally, taking typical landslides as case studies, reveals the deformation and failure characteristics and evolution mechanisms of typical landslides through integrated multi-source remote sensing detection and field investigations, coupled with rainfall-reservoir water level-time series deformation data.
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Preamble
Comprehensive Identification and Deformation Evolution Characteristics of Landslides in the Reservoir Area during the Initial Impoundment of the Lianghekou Hydropower Station
Xueqing Li¹,², Weile Li¹
¹ State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059
² Sichuan Institute of Comprehensive Geological Survey, Chengdu 610081
Abstract
Large reservoir impoundment exerts a significant triggering effect on reservoir bank landslides. Research on early identification and deformation evolution characteristics of these landslides provides crucial support for geological disaster prevention and control in reservoir areas. The Lianghekou Hydropower Station reservoir area features complex geological conditions, deeply incised valleys, steep slopes, and intense weathering and unloading effects, which have induced numerous potential landslides during the initial impoundment phase, posing severe threats to hydropower station operations and the lives and property of local residents. This study first employs an integrated approach combining Stacking-InSAR technology, high-resolution optical satellite imagery, airborne LiDAR, and field investigations to identify active landslides and establish a dynamic inventory database. Second, based on deformation information obtained from SBAS-InSAR technology, we construct an activity assessment index system for reservoir landslides and classify potential landslide hazards according to their activity levels. Third, we analyze the spatial distribution patterns of active landslides in conjunction with the geological and environmental characteristics of the study area. Finally, focusing on typical landslides as case studies, we integrate multi-source remote sensing detection and field survey data, coupling rainfall, reservoir water level, and time-series deformation data to reveal the deformation characteristics and evolution mechanisms of these representative landslides.
Keywords: Lianghekou reservoir area; active landslides; comprehensive identification; deformation evolution characteristics; reservoir water level