• ISSN 1673-5722
  • CN 11-5429/P

基于HVSR的DONET1海底地震动场地效应研究

周旭彤 胡进军 谭景阳 崔鑫

周旭彤,胡进军,谭景阳,崔鑫,2021. 基于HVSR的DONET1海底地震动场地效应研究. 震灾防御技术,16(1):105−115. doi: 10.11899/zzfy20210111
引用本文: 周旭彤,胡进军,谭景阳,崔鑫,2021. 基于HVSR的DONET1海底地震动场地效应研究. 震灾防御技术,16(1):105−115. doi: 10.11899/zzfy20210111
doi:10.11899/zzfy20210111. doi: 10.11899/zzfy20210111
Citation: doi:10.11899/zzfy20210111. doi: 10.11899/zzfy20210111

基于HVSR的DONET1海底地震动场地效应研究

doi: 10.11899/zzfy20210111
基金项目: 国家重点研发计划(2017YFC1500403;2018YFC1504401);国家自然科学基金(52078470;51578516)
详细信息
    作者简介:

    周旭彤,男,生于1996年。硕士研究生。主要从事海域地震动方面的研究。E-mail:iemzxt@163.com

    通讯作者:

    胡进军,男,生于1978年。博士,研究员,博士生导师。主要从事地震动模型和设计地震动方面的研究。E-mail:hu-jinjun@163.com

The Study of Site Effect of DONET1 Offshore Ground Motions Based on HVSR

  • 摘要: 为基于谱比方法研究海底地震动场地效应,选取日本DONET1台网的20个海底台站2014—2021年记录的1634组地震数据,对其进行筛选和处理后,利用水平与竖向谱比(HVSR)方法考虑不同布设对海底5组节点台站(KMA、KMB、KMC、KMD、KME)谱比特征的影响。研究结果表明:KMA与KME节点台站具有相似的场地特征,KMB与KMD节点台站分散布置在2种场地,KMC节点台站场地与其他节点均不相似,这与长期地质调查结果相似;海底台站谱比曲线呈多峰值现象,其中KMB、KMC、KMD分组台站利用HVSR方法识别的主频变异性较高,KMA、KME分组台站主频较稳定;相同地形条件下,布设方式相同的海底台站谱比曲线随频率分布相似,海底复杂场地条件下,采用装沙沉底方式布置的台站识别场地条件时出现偏差;海底复杂因素对掩埋沉箱方式布设的台站谱比曲线的影响主要集中在频率<5 Hz的低频处;海底复杂因素对未埋入海底台站谱比曲线的影响主要集中在频率为5—10 Hz的高频处。研究结果可为海底地震动场地效应研究提供参考。
  • 图  1  共振频率识别方法的对比

    Figure  1.  Comparison of resonance frequency identification methods

    图  2  海底台站布设

    Figure  2.  Embedment condition of offshore stations

    图  3  海底台站及地震事件分布

    Figure  3.  Distribution of offshore stations and earthquake events

    图  4  海底地震动数据处理

    Figure  4.  Processing of records of offshore ground motion

    图  5  海底地震动S波数据处理

    Figure  5.  Processing S wave for offshore ground motion

    图  6  平滑效果对比

    Figure  6.  Smoothing effect comparison of different smooth windows for KMC11 stations

    图  7  HVSR谱比结果

    Figure  7.  The results of HVSR at offshore stations in DONET1

    图  8  海底台站主频和变异系数分布

    Figure  8.  Distribution of dominant frequency and variable coefficient for offshore stations

    图  9  海底台站HVSR幅值

    Figure  9.  HVSR amplitude for offshore stations

    图  10  DONET1海底台站按地形分组分布

    Figure  10.  The DONET1offshore stations grouped by topography

    图  11  不同区域谱比曲线对比

    Figure  11.  Comparison of H/V curves in different regions

    图  12  布设方式对HVSR幅值的影响

    Figure  12.  The effect of embedment condition on the amplitude of HVSR

    表  1  DONET1台网海底台站信息(Kaneda等,2015

    Table  1.   The information of DONET1 offshore sites(Kaneda et al,2015

    布设方式台站命名纬度/°经度/°海水深度/m记录数量
    掩埋沉箱KMA01N33.805E136.5572 03996
    装沙沉底KMA02N33.752E136.6492 011107
    装沙沉底KMA03N33.648E136.6042 06378
    装沙沉底KMA04N33.678E136.4672 05482
    掩埋沉箱KMB05N33.477E136.9261 99883
    装沙沉底KMB06N33.358E136.9222 49995
    掩埋沉箱KMB07N33.361E136.8071 980101
    掩埋沉箱KMB08N33.466E136.8041 924101
    掩埋沉箱KMC09N33.058E136.8313 511100
    未埋KMC10N33.053E136.9334 247123
    未埋KMC11N33.003E136.7794 378122
    掩埋沉箱KMC12N33.128E136.8193 784114
    掩埋沉箱KMD13N33.220E136.6902 44188
    掩埋沉箱KMD14N33.173E136.5772 35089
    掩埋沉箱KMD15N33.233E136.5631 90976
    掩埋沉箱KMD16N33.305E136.5961 97095
    装沙沉底KME17N33.485E136.4452 05420
    装沙沉底KME18N33.386E136.3832 05223
    掩埋沉箱KME19N33.446E136.2561 90920
    掩埋沉箱KME20N33.544E136.3321 97721
    下载: 导出CSV
  • [1] 陈苏, 周越, 李小军等, 2018. 近海域地震动的时频特征与工程特性. 振动与冲击, 37(16): 227-233.

    Chen S., Zhou Y., Li X. J., et al., 2018. Time-frequency and engineering characteristics on offshore ground motion. Journal of Vibration and Shock, 37(16): 227-233. (in Chinese)
    [2] 胡进军, 刁红旗, 谢礼立, 2013. 海底强地震动观测及其特征的研究进展. 地震工程与工程振动, 33(6): 1-8.

    Hu J. J., Diao H. Q., Xie L. L., 2013. Review of observation and characteristics of seafloor strong motion. Earthquake Engineering and Engineering Vibration, 33(6): 1-8. (in Chinese)
    [3] 李小军, 陈苏, 任治坤等, 2020. 海域地震区划关键技术研究项目及研究进展. 地震科学进展, 50(1): 2-19. doi: 10.3969/j.issn.2096-7780.2020.01.001

    Li X. J., Chen S., Ren Z. K., et al., 2020. Project plan and research progress on key technologies of seismic zoning in sea areas. Progress in Earthquake Sciences, 50(1): 2-19. (in Chinese) doi: 10.3969/j.issn.2096-7780.2020.01.001
    [4] 任叶飞, 温瑞智, 山中浩明等, 2013. 运用广义反演法研究汶川地震场地效应. 土木工程学报, 46(S2): 146-151.

    Ren Y. F., Wen R. Z., Yamanaka H., et al., 2013. Research on site effect of Wenchuan earthquake by using generalized inversion technique. China Civil Engineering Journal, 46(S2): 146-151. (in Chinese)
    [5] 荣棉水, 李小军, 王振明等, 2016. HVSR方法用于地震作用下场地效应分析的适用性研究. 地球物理学报, 59(8): 2878-2891. doi: 10.6038/cjg20160814

    Rong M. S., Li X. J., Wang Z. M., et al., 2016. Applicability of HVSR in analysis of site-effects caused by earthquakes. Chinese Journal of Geophysics, 59(8): 2878-2891. (in Chinese) doi: 10.6038/cjg20160814
    [6] 谭景阳, 胡进军, 周旭彤等, 2020. 考虑不同分类的海底地震动特性及其不确定性分析. 天津大学学报(自然科学与工程技术版), 53(12): 1264-1271.

    Tan J. Y., Hu J. J., Zhou X. T., et al., 2020. Characteristics and uncertainty of classified seafloor ground motion. Journal of Tianjin University (Science and Technology), 53(12): 1264-1271. (in Chinese)
    [7] 谭景阳, 胡进军, 周旭彤等, 2021. 海底与陆地地震动反应谱比定量分析. 振动与冲击, 40(2): 213-219, 227.

    Tan J. Y., Hu J. J., Zhou X. T., et al., 2021. Quantitative analysis on the difference of spectral ratios between offshore and onshore ground motions. Journal of Vibration and Shock, 40(2): 213-219, 227. (in Chinese)
    [8] 温瑞智, 任叶飞, 王宏伟等, 2017. 强震动记录分析与应用-芦山MS7.0地震为例. 北京: 地震出版社
    [9] 姚鑫鑫, 任叶飞, 温瑞智等, 2019. 强震动记录H/V谱比法计算处理的若干关键环节. 震灾防御技术, 14(4): 719-730. doi: 10.11899/zzfy20190403

    Yao X. X., Ren Y. F., Wen R. Z., et al., 2019. Some technical notes on the data processing of the spectral ratio based on the strong-motion records. Technology for Earthquake Disaster Prevention, 14(4): 719-730. (in Chinese) doi: 10.11899/zzfy20190403
    [10] Araki, E., Yokobiki T., Kawaguchi K., et al., 2013. Background seismic noise level in DONET seafloor cabled observation network. In: IEEE International Underwater Technology Symposium (UT). Tokyo, Japan: IEEE, 1—4.
    [11] Boore D. M., Smith C. E., 1999. Analysis of earthquake recordings obtained from the seafloor earthquake measurement system (SEMS) Instruments deployed off the coast of southern California. Bulletin of the Seismological Society of America, 89(1): 260-274. doi: 10.1785/BSSA0890010260
    [12] Boore D. M., Stephens C. D., Joyner W. B., 2002. Comments on baseline correction of digital strong-motion data: examples from the 1999 Hector Mine, California, earthquake. Bulletin of the Seismological Society of America, 92(4): 1543-1560. doi: 10.1785/0120000926
    [13] Boore D. M., Bommer J. J., 2005. Processing of strong-motion accelerograms: needs, options and consequences. Soil Dynamics and Earthquake Engineering, 25(2): 93-115. doi: 10.1016/j.soildyn.2004.10.007
    [14] Dhakal Y. P., Aoi S., Kunugi T., et al., 2017. Assessment of nonlinear site response at ocean bottom seismograph sites based on S-wave horizontal-to-vertical spectral ratios: a study at the Sagami Bay area K-NET sites in Japan. Earth, Planets and Space, 69(1): 29. doi: 10.1186/s40623-017-0615-5
    [15] Diao H. Q., Hu J. J., Xie L. L., 2014. Effect of seawater on incident plane P and SV waves at ocean bottom and engineering characteristics of offshore ground motion records off the coast of southern California, USA. Earthquake Engineering and Engineering Vibration, 13(2): 181-194. doi: 10.1007/s11803-014-0222-4
    [16] Field E. H., Jacob K. H., 1993. The theoretical response of sedimentary layers to ambient seismic noise. Geophysical Research Letters, 20(24): 2925-2928. doi: 10.1029/93GL03054
    [17] Field E. H., Jacob K. H., 1995. A comparison and test of various site-response estimation techniques, including three that are not reference-site dependent. Bulletin of the Seismological Society of America, 85(4): 1127-1143.
    [18] Field E. H., Johnson P. A., Beresnev I. A., et al., 1997. Nonlinear ground-motion amplification by sediments during the 1994 Northridge earthquake. Nature, 390(6660): 599-602. doi: 10.1038/37586
    [19] Ghofrani H., Atkinson G. M., 2014. Site condition evaluation using horizontal-to-vertical response spectral ratios of earthquakes in the NGA-West 2 and Japanese databases. Soil Dynamics and Earthquake Engineering, 67: 30-43. doi: 10.1016/j.soildyn.2014.08.015
    [20] Hu J. J., Tan J. Y., Zhao J. X., 2020. New GMPEs for the Sagami bay region in japan for moderate magnitude events with emphasis on differences on site amplifications at the seafloor and land seismic stations of K‐NET. Bulletin of the Seismological Society of America, 110(5): 2577-2597. doi: 10.1785/0120190305
    [21] Kaneda, Y., Kawaguchi K., Araki E., et al., 2015. Development and application of an advanced ocean floor network system for megathrust earthquakes and tsunamis. In: Favali, P., Beranzoli L., De Santis A., eds., Seafloor Observatories: A New Vision of the Earth from the Abyss. Berlin, Heidelberg: Springer, 643—662.
    [22] Kawaguchi K., Kaneko S., Nishida T., et al., 2015. Construction of the DONET real-time seafloor observatory for earthquakes and tsunami monitoring. In: Favali, P., Beranzoli L., De Santis A., eds., Seafloor Observatories: A New Vision of the Earth from the Abyss. Berlin, Heidelberg: Springer, 211—228.
    [23] Konno K., Ohmachi T., 1998. Ground-motion characteristics estimated from spectral ratio between horizontal and vertical components of microtremor. Bulletin of the Seismological Society of America, 88(1): 228-241.
    [24] Kubo H., Nakamura T., Suzuki W., et al., 2018. Site amplification characteristics at Nankai seafloor observation network, DONET1, Japan, evaluated using spectral inversion. Bulletin of the Seismological Society of America, 108(3A): 1210-1218. doi: 10.1785/0120170254
    [25] Kubo H., Nakamura T., Suzuki W., 2019. Ground-motion characteristics and nonlinear soil response observed by DONET1 seafloor observation network during the 2016 Southeast Off-Mie, Japan, earthquake. Bulletin of the Seismological Society of America, 109(3): 976-986. doi: 10.1785/0120170296
    [26] Nakamura Y., 1989. A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface. Quarterly Report of RTRI, 30(1): 25-33.
    [27] Nakamura Y., 2019. What is the Nakamura method?. Seismological Research Letters, 90(4): 1437-1443.
    [28] Nakano M., Tonegawa T., Kaneda1 Y., 2012. Orientations of DONET seismometers estimated from seismic waveforms. JAMSTEC Report of Research and Development, 15: 77-89. doi: 10.5918/jamstecr.15.77
    [29] Régnier J., Cadet H., Bonilla L F., et al., 2013. Assessing nonlinear behavior of soils in seismic site response: statistical analysis on KiK-net strong-motion data. Bulletin of the Seismological Society of America, 103(3): 1750-1770. doi: 10.1785/0120120240
    [30] Ren Y. F., Wen R. Z., Yao X. X., et al., 2017. Five parameters for the evaluation of the soil nonlinearity during the MS8.0 Wenchuan Earthquake using the HVSR method. Earth, Planets and Space, 69(1): 116. doi: 10.1186/s40623-017-0702-7
    [31] Tan J. Y., Hu J. J., 2021. A prediction model for vertical-to-horizontal spectral ratios of ground motions on the seafloor for moderate magnitude events for the Sagami Bay region in Japan. Journal of Seismology, 25(1): 181-199. doi: 10.1007/s10950-020-09932-5
    [32] Wen K. L., Chang T. M., Lin C. M., et al., 2006a. Identification of nonlinear site response using the H/V spectral ratio method. Terrestrial Atmospheric and Oceanic Sciences, 17(3): 533-546. doi: 10.3319/TAO.2006.17.3.533(T)
  • 加载中
图(12) / 表(1)
计量
  • 文章访问数:  262
  • HTML全文浏览量:  21
  • PDF下载量:  24
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-11-30
  • 网络出版日期:  2021-07-12
  • 刊出日期:  2021-03-01

目录

    /

    返回文章
    返回