Abstract
Investigating the development and evolution characteristics and disaster-forming dynamic processes of typical geological hazards along arterial highways in seismically active mountainous regions holds significant theoretical and practical importance for early hazard identification, risk assessment, and disaster prevention and mitigation in transportation corridors. This study focuses on the southern segment of the Longmenshan fault zone as the research area, integrating field investigation, remote sensing interpretation, and GIS spatial analysis techniques to reveal the superimposed influence patterns of multi-stage seismic events (the 2013 and 2022 Lushan earthquakes) on coseismic geological hazards along the Baoxing section of National Highway 351. Furthermore, employing the three-dimensional two-phase Material Point Method (MPM), we quantitatively simulated the complete initiation-motion-river blocking process of the high-elevation accumulation landslide at Xinhua Village and explored key technologies for scenario modeling of high-elevation collapse-slide disasters in seismically active areas. The results indicate: (1) A total of 215 coseismic geological hazards developed in 2022 within the study area, primarily distributed on slopes within the 1500 m elevation range on both banks of the Donghe River valley, on slopes of 30°–50°, sharing the common distribution characteristic with the 2013 coseismic geological hazards that high-steep slopes of hard rock are high-incidence areas for disasters. (2) The development and distribution of the 2022 coseismic geological hazards were mainly controlled by geomorphology, river, and fault factors, showing weak spatial coupling with epicenter locations; hazard points with significant highway impacts mainly developed at protruding mountain masses with multi-sided free faces and near fault zones, significantly influenced by superimposed multi-stage earthquakes and historical rainfall. (3) The high-elevation landslide at Xinhua Village, under the superimposed effects of multi-stage earthquakes, rainfall, and freeze-thaw cycles, exhibited progressive retrogressive deformation with continuous upward expansion over the past decade, finally experiencing large-scale instability and river blockage under the 2022 strong earthquake; the three-dimensional two-phase MPM simulation reproduced the complete process of landslide movement → water entry surge → accumulation dam formation, with results showing the landslide volume was approximately 760,000 m³, the maximum travel distance was approximately 609 m, and the surge height reached up to 8 m; the simulated post-movement accumulation morphology basically matched the actual field conditions. The research findings provide theoretical and technical support for pre-disaster risk assessment and post-disaster reconstruction of arterial highways in seismically active mountainous regions.
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Preamble
Development and Evolution Characteristics and Disaster Motion Processes of Geological Hazards on Mountainous Arterial Highways Under Lushan Earthquake Action
Wu Kai¹, Yi Xuebin¹, Fu Xiaodong²,³*, Du Wenjie²,³, Ding Haifeng²,³, Zhao Haisong¹, Xi Tian²,³
¹ Sichuan Highway Planning, Survey, Design and Research Institute Co., Ltd., Chengdu, Sichuan 610041, China
Abstract
Investigating the development-evolution characteristics and disaster dynamic processes of typical geological hazards along arterial highways in seismically active mountainous regions is of significant theoretical and practical importance for hazard early identification, risk assessment, and disaster mitigation of transportation corridors. This study focuses on the southern segment of the Longmenshan fault zone, integrating field surveys, remote sensing interpretation, and GIS spatial analysis to reveal the superimposed effects of multi-phase Lushan earthquakes (2013 and 2022) on co-seismic geological hazards along the Baoxing section of National Highway 351. Furthermore, the three-dimensional two-phase Material Point Method (MPM) was employed to quantitatively simulate the complete process of initiation, motion, and river blockage of the Xinhua Village high-level accumulation landslide, and to discuss key technologies for scenario forecasting of high-level collapse-slide hazards in frequent earthquake zones. The results indicate: (1) A total of 215 co-seismic geological hazards developed in 2022, primarily distributed on slopes within 1500 m elevation on both banks of the Dong River valley, particularly on slopes of 30°–50°, sharing the common distribution characteristic with 2013 co-seismic hazards that high and steep slopes of hard rock represent high-incidence areas. (2) The development and distribution of 2022 co-seismic hazards were mainly controlled by topographic, fluvial, and fault factors, showing weak spatial coupling with epicenter locations; hazards with significant highway impacts primarily developed at prominent mountain locations with multiple free faces and near fault zones, being significantly influenced by superimposed multi-phase earthquakes and historical rainfall. (3) The Xinhua Village high-level landslide, affected by superimposed effects of multi-phase earthquakes, rainfall, and freeze-thaw cycles, exhibited progressive retrogressive deformation continuously expanding upward over the past decade, culminating in large-scale instability and river blockage under the 2022 strong earthquake; the three-dimensional two-phase MPM simulation reproduced the complete process of landslide motion → water surge → dam formation, revealing a landslide volume of approximately 760,000 m³, maximum movement distance of approximately 609 m, and maximum surge height of 8 m, with the simulated post-motion deposit morphology being generally consistent with actual field conditions. The research findings provide theoretical and technical support for pre-disaster risk assessment and post-disaster reconstruction of arterial highways in strong earthquake mountainous regions.
Keywords: Lushan earthquake; geological hazard; development and evolution characteristics; three-dimensional two-phase MPM; motion process analysis