Located in the Minjiang River Valley,a major area affected by the 8.0 magnitude Wenchuan"5.12"earthquake,a particular debris flow gully in Northwestern Sichuan has complex geological structures and intense new tectonic movement.The prevalence of strong earthquakes,coupled with the deep incision of the Minjiang River,has created steep terrains.The main exposed stratum is soft rock,and the gully and its surroundings are abundant in material sources,making the area prone to debris flow disaster under heavy rainfall.By collecting the geological data of this region,conducting remote sensing interpretation,on-site geological investigation,and mechanical calculation,the paper studied the development characteristics of this debris flow gully and evaluated its susceptibility from aspects of terrain,material sources,and hydraulic conditions,and proposed corresponding preventive and control measures.The results show:(1)The debris flow gully in Northwestern Sichuan is caused by a rainstorm-induced collapse valley-type debris flow,with a catchment area of 20.8 km2,total solid material storage of approximately 258.9×104 m3,and a probable moving storage volume of about 64.5×104 m3.(2)The debris flow density is 1.74 t/m3 for a 100-year event,with an average flow rate of 5.12 m/s,a maximum peak flow rate of 535.4 m3/s,and a maximum flow uprush height of 1.34 m.The predicted deposition thickness for a 100-year event is 4.8 m,bringing a medium susceptibility risk.(3)Based on the debris flow development characteristics and susceptibility level in the engineering area,it is suggested to use bridge leaving enough clearance to pass the debris flow gully,and corresponding debris flow prevention measures and recommendations were proposed.The conclusions of this study can provide a useful reference for railway and highway investigation,design,and construction in the mountainous area of Northwestern Sichuan.
Northwest Sichuandebris flow gullydevelopment characteristicssusceptibility evaluationbridge engineeringpreventive and control measures
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NSTL
维普
万方数据
