1.西南交通大学 四川 成都;2.成都经开区国投集团有限公司四川 成都;3.成都天府新区规划设计研究院有限公司四川 成都;4.四川省公路规划勘察设计研究院有限公司 四川 成都
1.Southwest Jiaotong University,Chengdu,Sichuan;2.CHENGDU TIANFU NEW AREA INSTITUTE OF PLANNING DESIGH CO,LTD,Chengdu,Sichuan;3.Sichuan Highway Planning,Survey,Design and Research Institute Ltd,Chengdu,Sichuan
滑坡在地震、降雨和坡脚开挖时会发生慢速滑动，部分滑坡直接失稳破坏，但是部分慢速滑坡会慢慢变得稳定，呈休眠状态。目前，滑坡恢复稳定的自愈合过程外在表现和内在机制还研究较少，尤其是坡脚侵蚀型慢速滑坡的自愈合特征研究。2020年6月17日，四川省丹巴县梅龙沟爆发的泥石流堵塞小金川，形成泥石流-堰塞湖-溃决洪水灾害链，且溃决洪水掏蚀坡脚，导致阿娘寨古滑坡复活。通过对阿娘寨滑坡应急监测数据发现，阿娘寨古滑坡初期存在大变形，但后期变形逐渐稳定，存在强度恢复的自愈合现象。另外，数据表明滑坡的两次突然启动和小金川流量增大侵蚀坡脚相关，和地震和降雨关系不大。通过现场监测数据分析，滑坡刚发生时变形速率高达118 mm/h，本文建立的预测模型表明，在没有外在触发因素条件下，滑体会在8月21日左右变形速率低至1 mm/h。本文以阿娘寨滑坡为例，分析滑坡的变形过程和自愈合特征，并基于野外监测数据建立自愈合过程预测模型，该方法对于科学评估滑坡稳定性，减小滑坡防治设计成本具有重要意义。
Landslides would move slowly during earthquakes, rainfall and excavation at the foot of the slope, and some landslides will be directly destabilized and damaged, but some slow-moving landslides will gradually become stable and in a dormant state. At present, the external manifestations and internal mechanisms of self-healing process are still less studied, especially the self-healing characteristics of erosive slow-speed landslides at the foot of the slope. On June 17, 2020, a debris flow broke out in Meilonggou, Danba County, Sichuan Province, blocking Xiaojinchuan, forming a chain of debris flow - dammed lake - burst flood disaster. The outburst flood eroded the foot of the slope, leading to the resurrection of the ancient landslide in Anianzhai. Through the emergency monitoring data of the Anianangzhai landslide, it found that although the ancient landslide of Anianzhai had large deformation in the initial stage, the deformation gradually stabilized in the later stage, and there was a self-healing phenomenon of strength recovery. Monitoring data show that the two sudden starts of the landslide are closely related to the increasing discharge and toe erosion, and have little to do with earthquakes and rainfall. By the calculation of monitoring data, the deformation rate of the landslide is as high as 118 mm/h when it just occurs.In the absence of external triggers, our prediction model indicated that the deformation rate of the sliding body was as low as 1 mm/h around August 21. This study analyzed the deformation process and self-healing characteristics of the Anyangzhai landslide, and established a self-healing prediction model based on field monitoring data. This method is of great significance for scientific evaluation of landslide stability and reduction of landslide control design cost.
李磊,阮冰清,杨振,等. 基于野外监测的阿娘寨滑坡自愈合特征研究[J]. 科学技术与工程, , ():复制