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浙江大学学报(工学版)
浙江大学学报(工学版)  2017, Vol. 51 Issue (11): 2136-2143    DOI: 10.3785/j.issn.1008-973X.2017.11.006
土木与交通工程     
隐伏断层地震诱发滑坡易发性评价
黄赠, 王锐, 赵宇, 魏振磊
浙江大学 建筑工程学院, 浙江 杭州 310058
Susceptibility assessment of landslides triggered by buried fault earthquake
HUANG Zeng, WANG Rui, ZHAO Yu, WEI Zhen-lei
College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
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摘要：

针对隐伏断层地震诱发滑坡无明显空间分布规律导致滑坡易发性分区难度较大的问题，提出考虑同震地表变形因子的人工神经网络地震滑坡易发性评价方法.以2004年日本新泻中越地震为例，除选取地层岩性、高程、坡度、坡向、地表曲率、地震加速度峰值、距道路的距离等常规地震滑坡影响因子外，新增同震地表变形作为影响因子，利用地理信息系统（GIS）平台通过神经网络法进行地震滑坡易发性评价.结果表明，基于GIS的人工神经网络法对地震诱发滑坡易发性评价有较高的精度.同震地表变形对预测准确度有一定贡献，优于坡向、高程以及距道路的距离等常规影响因子.
Abstract:

The artificial neural network (ANN) method containing horizontal ground deformation factor, was proposed to solve the difficulty in susceptibility assessment of landslides triggered by buried fault, due to the unapparent relationship between buried fault earthquake and landslide occurrence. The landslide susceptibility assessment was performed in geographic information system (GIS) by taking the case of 2004 Mid-Niigata earthquake in Japan. Lithology, elevation, slope, aspect, curvature, earthquake peak acceleration, distance from roads and horizontal ground deformation were selected as influential factors. Results show that ANN method has a good accuracy in earthquake-induced landslide susceptibility assessment. Ground deformation was proved to have greater contribution to the assessment model accuracy than some ordinary factors such as aspect, elevation and the distance from roads.
收稿日期: 2016-07-19 出版日期: 2017-11-13
CLC:  P642.22  
基金资助:

国家自然科学基金资助项目（51208461）；浙江省自然科学基金资助项目（LY16D020002）.
通讯作者: 赵宇,男,副教授.ORCID:0000-0003-0453-1960.     E-mail: zhao_yu@zju.edu.cn
作者简介: 黄赠(1991-),男,硕士,从事防灾减灾工程等研究.ORCID:0000-0001-9541-035x.E-mail:huangzeng@zju.edu.cn
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引用本文:

黄赠, 王锐, 赵宇, 魏振磊. 隐伏断层地震诱发滑坡易发性评价[J]. 浙江大学学报(工学版), 2017, 51(11): 2136-2143.

HUANG Zeng, WANG Rui, ZHAO Yu, WEI Zhen-lei. Susceptibility assessment of landslides triggered by buried fault earthquake. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 2017, 51(11): 2136-2143.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2017.11.006    或    http://www.zjujournals.com/eng/CN/Y2017/V51/I11/2136

[1] KEEFER D K. Landslides caused by earthquakes[J]. Geological Society of America Bulletin, 1984, 95(4):406-421.
[2] XU C. Assessment of earthquake-triggered landslide susceptibility based on expert knowledge and information value methods:a case study of the 20 April 2013 Lushan, China Mw6. 6 earthquake[J]. Disaster Advances, 2013, 6(13):119-130.
[3] 许冲,徐锡伟,吴熙彦,等.2008年汶川地震滑坡详细编目及其空间分布规律分析[J].工程地质学报, 2013(1):25-44. XU Chong, XU Xi-wei, WU Xi-yan, et al. Response rate of seismic slope mass movements related to 2008 WenChuan earthquake and its spatial distribution analysis[J]. Chinese Journal of Rock Mechanics and Engineering, 2013(1):25-44.
[4] POURGHASEMI H R, JIRANDEH A G, PRADHAN B等. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran[J]. Journal of Earth System Science, 2013, 122(2):349-369.
[5] NANDI A, SHAKOOR A. A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses[J]. Engineering Geology, 2010, 110(1/2):11-20.
[6] YILMAZ I. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison:A case study from Kat landslides (Tokat-Turkey)[J]. Computers & Geosciences, 2009, 35(6):1125-1138.
[7] YESILNACAR E, TOPAL T. Landslide susceptibility mapping:A comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey)[J]. Engineering Geology, 2005, 79(3/4):251-266.
[8] SATO H P, SEKIGUCHI T, KOJIROI R, et al. Overlaying landslides distribution on the earthquake source, geological and topographical data:the Mid Niigata prefecture earthquake in 2004, Japan[J]. Landslides, 2005, 2(2):143-152.
[9] XU C, DAI F, XU X等. GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang River watershed, China[J]. Geomorphology, 2012, 145-146:70-80.
[10] 许冲,戴福初,姚鑫等.基于GIS的汶川地震滑坡灾害影响因子确定性系数分析[J].岩石力学与工程学报, 2010(S1):2972-2981. XU Chong, DAI Fu-chu, YAO Xiao-li, et al. GIS based certainty factor analysis of landslide triggering factors in WenChuan earthquake[J]. Chinese Journal of Rock Mechanics and Engineering, 2010, 29(S1):2972-2981.
[11] 许冲.利用同震滑坡分析2014年鲁甸地震震源性质与破裂过程[J].工程地质学报,2015, 23(4):755-759. XU Chong. Utilizing coseismic landslides to analyze the source and rupturing process of the 2014 LuDian earthquake[J]. Journal of Engineering Geology, 2015,23(4):755-759.
[12] YU Z, KAZUO K, TOMOHIRO F. Multi-scale decomposition of co-seismic deformation from high resolution dems:a case study of the 2004 mid-niigata earthquake[J]. Acta Geologica Sinica-English Edition, 2012, 86(4):1013-1021.
[13] MORI J, SOMERVILLE P. Seismology and strong ground motions in the 2004 niigata ken chuetsu, japan, earthquake[J]. Earthquake Spectra, 2006, 22(S1):9-21.
[14] GUZZETTI F, CARRARA A, CARDINALI M等. Landslide hazard evaluation:a review of current techniques and their application in a multi-scale study, Central Italy[J]. Geomorphology, 1999, 31(1/4):181-216.
[15] HASEGAWA S, DAHAL R K, NISHIMURA T et al. DEM-Based analysis of earthquake-induced shallow landslide susceptibility[J]. Geotechnical and Geological Engineering, 2009, 27(3):419-430.
[16] 许冲, 徐锡伟, 于贵华,等. 玉树地震滑坡影响因子敏感性分析[J]. 科技导报, 2012(1):18-24. XU Chong, XU Xi-wei, YU Gui-hua, et al. Susceptibility analysis of impact factors of landslides triggered by Yushu earthquake[J]. Science and Technology Review, 2012, 30(01):18-24.
[17] 土木学会, 東京大学, 京都大学等. 活褶曲地帯における地震被害データアーカイブスの構築と社会基盤施設の防災対策への活用法の提案[R].日本:文部科学省, 2008. Japan Society of Civil Engineers, Tokyo University, Kyoto University, et al. The flexible method of seismic damage data archive building and social infrastructure disaster prevention in active fault region[R]. Japan:Ministry of Education, Culture, Sports, Science and Technology, 2008.
[18] 陈晓利,赵健,叶洪.应用径向基概率神经网络研究地震滑坡[J].地震地质, 2006, 28(3):430-440. CHEN Xiao-li, ZHAO Jian, YE Hong.application of RBPNN in the research of earthquake-induced landslide[J]. Seismology and Geology, 2006, 28(3):430-440.
[19] 谭龙,陈冠,曾润强,等.人工神经网络在滑坡敏感性评价中的应用[J]. 兰州大学学报:自然科学版, 2014, 50(1):15-20. TAN Long, CHEN Guan, ZENG Run-qiang, et al. Application of artificial neural network in landslide susceptibility assessment[J]. Journal of Lanzhou University:Natural Sciences, 2014, 50(01):15-20.
[20] 刘艺梁,殷坤龙,刘斌.逻辑回归和人工神经网络模型在滑坡灾害空间预测中的应用[J]. 水文地质工程地质, 2010, 37(5):92-96. LIU Yi-liang, YIN Kun-long, LIU Bin. Application of logistic regression and artificial neural networks in spatial assessment of landslide hazard[J]. Hydrogeology and Engineering Geology, 2010, 37(05):92-96.
[21] 柯福阳,李亚云.基于BP神经网络的滑坡地质灾害预测方法[J].工程勘察, 2014, 42(8):55-60. KE Fu-yang, LI Ya-yun. The forecasting method of landslides based on improved BP neural network[J]. Geotechnical Investigation and Surveying, 2014, 42(8):55-60.
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