地震地质 ›› 2019, Vol. 41 ›› Issue (3): 774-788.DOI: 10.3969/j.issn.0253-4967.2019.03.015

• 研究论文 • 上一篇    下一篇

应用2类Newmark简易模型进行2008年汶川地震滑坡评估

马思远1, 许冲1, 王涛2, 刘甲美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. 中国地质科学院地质力学研究所, 国土资源部新构造运动与地质灾害重点实验室, 北京 100081
  • 收稿日期:2018-02-11 修回日期:2018-10-29 出版日期:2019-06-20 发布日期:2019-07-28
  • 通讯作者: 许冲,男,研究员,主要从事滑坡地震地质学研究,E-mail:xc11111111@126.com。
  • 作者简介:马思远,男,1992年生,2015年于河南理工大学获地质工程专业学士学位,在读硕士研究生,主要从地震滑坡危险性研究,E-mail:87856449@qq.com。
  • 基金资助:
    "十三五"国家重点研发计划(2017YFC1501001)资助。

APPLICATION OF TWO SIMPLIFIED NEWMARK MODELS TO THE ASSESSMENT OF LANDSLIDES TRIGGERED BY THE 2008 WENCHUAN EARTHQUAKE

MA Si-yuan1, XU Chong1, WANG Tao2, LIU Jia-mei2   

  1. 1. Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, Beijing 100029, China;
    2. Institute of Geomechanics, Chinese Academy of Geological Sciences, Key Laboratory of Neotectonics Movement & Geohazards, Ministry of Land and Mineral Resources of China, Beijing 100081, China
  • Received:2018-02-11 Revised:2018-10-29 Online:2019-06-20 Published:2019-07-28

摘要: 本研究的目的是利用真实的汶川同震滑坡数据分别对利用IaPGA参数的2种简易New ̄mark滑坡预测模型进行定量评估分析。根据研究区的地形数据和区域地质资料,获得了研究区的临界加速度(ac)分布,利用基于全球地震动记录拟合得到的Newmark经验公式,结合汶川地震的IaPGA参数分布,获得了基于2个地震动参数的滑坡位移分布图。大体上,基于Ia参数的滑坡危险性评估结果略好于基于PGA参数简易模型的评估结果。基于Ia的评估结果能够更好地反映同震滑坡的宏观分布特征。然而,2种Newmark模型反演得到的滑坡面积要明显大于实际滑坡物源区的面积。这提醒我们基于当前岩性和地震动数据只能获得宏观区域的滑坡相对危险性。而通过更为准确的地形数据和输入参数,才能进一步提高预测位移结果的精确度。

关键词: 汶川地震, 地震滑坡, Newmark累积位移模型, Arias烈度(Ia), 地震动峰值加速度(PGA)

Abstract: At present, with the wide application of the Newmark method, various Newmark empirical formulas with different ground motion parameters have been fitted by many researchers based on global strong-motion records. However, the existing study about the Wenchuan earthquake does not quantitatively evaluate the applicability of different Newmark models based on the actual landslides distribution. The aim of this paper is to present a comparison between observed landslides from the 2008 Wenchuan earthquake and predicted landslides using Newmark displacement method based on different ground motion parameters. The factor-of-safety map and critical acceleration(ac)map in the study area are obtained by using the terrain data and geological data. The distribution of Arias intensity(Ia)and PGA in the study area is obtained by using the attenuation formulas of Arias intensity(Ia)and PGA, which is regressed by Wenchuan ground motion records. Based on the distribution of Arias intensity(Ia)and PGA parameters, we obtained the predicted locations of landslide using Newmark regression equations which are generated using global strong-motion records. The results shows that the assessment results can better reflect the macroscopic distribution characteristics of co-seismic landslides, most predicted landslide cells are distributed on the two sides of the Beichuan-Yingxiu Fault, especially the Pengguan complex rock mass in the hanging wall. The abilities to predict landslide occurrence of the two Newmark simplified models are different. On the whole, the evaluated result of simplified model based on parameter Ia is better than that based on PGA parameter. The GFC values obtained by the Newmark model of Ia and PGA parameters are 65.7% and 34.9%respectively. The evaluated result based on Ia can better reflect the macro distribution of coseismic landslides. The Ls_Pred value based on the Newmark model of parameter Ia is 26.5%, and the Ls_Pred value based on the Newmark model of PGA parameter is 10.3%. However the total area of predicted landslides accounts for 2.4% of the study area, which indicates that the predicted landslide cells are greater than the observed landslide cells. This reminds us that depending on the current input of shear strength and ground-motion parameters, we can only conduct landslide hazard assessment in macro areas, the ability to predict landslide can be improved using more accurate topographic data and input parameters.

Key words: Wenchuan earthquake, earthquake-triggered landslides, Newmark cumulative displacement models, Arias intensity(Ia), PGA

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