甘肃积石山县M_(S)6.2地震同震地质灾害发育特征与易发性评价  

Development characteristics and susceptibility assessment of coseismic geological hazards of Jishishan M_(S)6.2 earthquake,Gansu Province,China

作　　者：刘帅 何斌 王涛[1,2,3] 刘甲美 曹佳文 王浩杰 张帅 李坤[1,2,3] 李冉 张永军 窦晓东[4,5] 吴中海 陈鹏 丰成君 LIU Shuai;HE Bin;WANG Tao;LIU Jiamei;CAO Jiawen;WANG Haojie;ZHANG Shuai;LI Kun;LI Ran;ZHANG Yongjun;DOU Xiaodong;WU Zhonghai;CHEN Peng;FENG Chengjun(Institute of Geomechanics,Chinese Academy of Geological Sciences,Beijing 100081,China;Key Laboratory of Active Tectonics and Geological Safety,Ministry of Natural Resources,Beijing 100081,China;Observation and Research Station of Geological Disaster in Baoji,Shaanxi Province,Ministry of Natural Resources,Baoji 721001,Shaanxi,China;Geological Environment Monitoring Institute of Gansu Province,Lanzhou 730050,Gansu,China;Lanzhou Urban Geological Disaster Field Scientific Observation and Research Station,Lanzhou 730050,Gansu,China;China Geological Survey,Beijing 100037,China)

机构地区：[1]中国地质科学院地质力学研究所,北京100081 [2]自然资源部活动构造与地质安全重点实验室,北京100081 [3]自然资源部陕西宝鸡地质灾害野外科学观测研究站,陕西宝鸡721001 [4]甘肃省地质环境监测院,甘肃兰州730050 [5]兰州城市地质灾害野外科学观测研究站,甘肃兰州730050 [6]中国地质调查局,北京100037

出　　处：《地质力学学报》2024年第2期314-331,共18页Journal of Geomechanics

基　　金：国家“十四五”重点研发计划项目(2022YFC3003505,2022YFC3004302);中国地质调查局地质调查项目(DD20221738);国家自然科学基金项目(41572313);自然资源部科技人才工程资助项目(121106000000180039-2207)。

摘　　要：2023年12月18日,甘肃积石山县发生M_(S)6.2地震,诱发的同震地质灾害严重威胁到人民生命和财产安全,因此及时总结分析同震地质灾害发育规律并进行县域易发性评价,对支撑震后恢复重建至关重要。通过应急排查、野外调查与结果分析,对同震地质灾害发育特征进行分析总结;以震后排查的同震新增和加剧隐患点为分析样本,采用Pearson相关性系数与随机森林Gini系数分析方法,筛选了15个影响因子,并运用机器学习-随机森林模型对积石山县进行同震地质灾害易发性评价。结果表明,震区同震地质灾害总体发育程度不强,规模以小型为主,崩滑流地质灾害隐患可分为3大类、8个亚类,绝大部分分布在黄土丘陵区;积石山县同震地质灾害随机森林模型易发性评价(AUC=0.961)结果显示,极高易发区面积占比约8.67%,主要分布在胡林家乡、徐扈家乡、柳沟乡等乡镇,且县域及各乡镇易发性分级结构与隐患点密度分布吻合程度高。评价结果对已有排查隐患点以外的震裂山体或潜在崩滑流灾害具有重要指示作用,可为积石山县灾后恢复重建规划提供决策支撑,同时将Pearson相关性系数与随机森林Gini系数的影响因子筛选方法及机器学习模型——随机森林应用于易发性评价中,可为其他山地丘陵区地质灾害易发性评价提供参考。[Objective]On December 18,2023,an MS 6.2 earthquake occurred in Jishishan County,Gansu Province,China.Coseismic geological hazards induced by the earthquake crucially threatened the safety of personnel and property.Existing research is mainly concentrated in the vicinity of active faults and the concentrated distribution area of hidden danger points.Moreover,no special susceptibility assessment studies have been carried out on coseismic geological hazards in the administrative area of Jishishan County,making it challenging to meet the needs of the county’s post-disaster recovery and reconstruction planning.Hence,the development laws of coseismic geological hazards must be summarized and analyzed crucially,and county susceptibility must be analyzed in time to support post-earthquake recovery and reconstruction.[Methods]The development characteristics of coseismic geological hazards are analyzed and summarized through emergency investigations,field surveys,and result analysis.Using the newly added and exacerbated coseismic hazard points identified during post-earthquake investigations as analysis samples,influencing factors were selected using the Pearson correlation coefficient and random forest Gini coefficient analysis methods.Then,a machine learning-random forest model was applied to assess the susceptibility of coseismic geological hazards in Jishishan County.[Results]In analyzing the development characteristics of coseismic geological hazards,we identified 134 instances of increased and exacerbated hazards in Jishishan County.Overall,the degree of development of these hazards was relatively low,with primarily small-scale occurrences.These hazards were categorized into three main types and eight sub-categories:①Collapse(including cut slope loess collapse,high loess collapse,and high rock collapse);②Landslide(encompassing loess landslide,secondary sand/mudstone landslide,and potential landslide);and③Debris flow(comprising gully debris flow and slope debris flow).In terms of factor selection,15 influenci

关 键 词：积石山地震 同震 地质灾害 易发性 随机森林 影响因子 

分 类 号：P694[天文地球—地质学] X43[环境科学与工程—灾害防治]