地震地质 ›› 2015, Vol. 37 ›› Issue (1): 291-306.DOI: 10.3969/j.issn.0253-4967.2015.23

• 鲁甸地震专题研究论文 • 上一篇    下一篇

2014年鲁甸MS6.5地震震前与同震滑坡空间分布规律对比分析

田颖颖1,2, 许冲1, 徐锡伟1, 吴赛儿2, 陈剑2   

  1. 1 中国地震局地质研究所, 活动构造与火山重点实验室, 北京 100029;
    2 中国地质大学(北京), 工程技术学院, 北京 100083
  • 收稿日期:2014-10-28 修回日期:2015-01-23 发布日期:2015-05-15
  • 通讯作者: 许冲,副研究员,E-mail:xuchong@ies.ac.cn,xc11111111@126.com
  • 作者简介:田颖颖,女,1989年生,中国地质大学(北京)地质工程专业在读硕士研究生,研究方向为滑坡危险性评价,E-mail:t190403098@163.com。
  • 基金资助:

    国家自然科学基金(41472202,41202235)和中国地震局"云南鲁甸6.5级地震专题研究"共同资助

SPATIAL DISTRIBUTION ANALYSIS OF COSEISMIC AND PRE-EARTHQUAKE LANDSLIDES TRIGGERED BY THE 2014 LUDIAN MS6.5 EARTHQUAKE

TIAN Ying-ying1,2, XU Chong1, XU Xi-wei1, WU Sai-er2, CHEN Jian2   

  1. 1 Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China;
    2 School of Engineering and Technology, China University of Geosciences, Beijing 100083, China
  • Received:2014-10-28 Revised:2015-01-23 Published:2015-05-15

摘要:

2014年8月3日, 云南省昭通市鲁甸县发生了MS6.5地震, 地震诱发了大量滑坡。文中以牛栏江沿线鲁甸县、巧家县和会泽县交界处面积为44.13km2的区域为研究区, 开展地震震前与同震滑坡的空间分布规律对比分析。根据震前Google Earth高分辨率影像与震后0.2m分辨率的超高分辨率航片数据, 分别建立了震前滑坡与同震滑坡数据库。结果表明, 研究区内震前有284处滑坡, 本次地震触发1 053处滑坡。借助10m×10m分辨率的数字高程模型(DEM)数据, 基于GIS平台提取研究区的高程、坡度、坡向、曲率、岩性、烈度、河流共7个主要因子, 并利用滑坡的面积百分比(Landslide Areas Percentage, LAP)和点密度(Landslide Number Density, LND)对比分析震前与同震滑坡的空间分布规律。结果表明, 震前与同震滑坡的易发高程区间分别为<1 200m与1 200~1 300m。坡度越大越容易发生滑坡, 其中坡度<10°的区域由于距离河流很近, 也为滑坡易发区。震前与同震滑坡发育的优势坡向都是近S向。当斜坡为凹坡时(曲率值为负值), 滑坡易发性较高。地震烈度越大, 越易发生同震滑坡。灰岩夹白云质灰岩分布区很容易发生滑坡, 玄武岩和火山角砾岩分布区在地震力的作用下边坡的稳定性也大大降低。震前、同震滑坡的发生与到河流的距离大致呈现正相关性。震前滑坡LAP的峰值大多数都与震前已经存在的大型滑坡有密切的对应关系。

关键词: 鲁甸地震, 震前滑坡, 同震滑坡, 空间分布, 滑坡密度

Abstract:

On August 3, 2014, an MS6.5 earthquake happened in the Ludian County, Zhaotong City of Yunnan Province. This earthquake caused a large number of landslides. In order to study the spatial distribution of the coseismic and pre-earthquake landslides, a 44.13km2 area at the junction of Ludian County, Qiaojia County and Huize County along the Niulanjiang River is selected in this study. By visual interpretation of the Google Earth pre-earthquake high resolution images and the coseismic aerial data of 0.2m resolution of this area, the landslide databases of pre-earthquake and coseismic are established. The result shows that there are 284 pre-earthquake landslides, and 1053 earthquake-induced landslides. Then with the help of 10m×10m resolution DEM data and the GIS, the extracted factors of elevation, slope angle, slope aspect, curvature, lithology, earthquake intensity and drainages are used to analyze the spatial distribution of the coseismic and pre-earthquake landslides by adopting LAP(Landslide Areas Percentage)and LND(Landslide Number Density). The results show that areas with elevation <1 200m and 1 200~1 300m are prone to landslides whatever pre-earthquake or coseismic. With the slope gradient increasing, it is much more prone to landslide, and the area of <10°, close to the rivers, is also much susceptible. The advantage slope aspect is almost near S direction. Concave slope(when the curvature is negative)is much susceptible to landslides, and with the curvature decreasing, the landslide susceptibility gets higher. The region of limestone with dolomitic limestone is sensitive to landslide; in the areas consisting of basalt and volcanic breccia, the slope stability is greatly reduced under the effect of seismic force. The larger the intensity is, the more landslides happened. For either pre-earthquake or coseismic landslides, there is a positive correlation between landslide spatial distribution and the distance to rivers. The large pre-earthquake landslides have effective influence on LAP.

Key words: Ludian earthquake, pre-earthquake landslides, coseismic landslides, spatial distribution, landslide density

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