Site database for national strong motion stations in mainland China

被引:2
|
作者
Ji, Kun [1 ,2 ]
Ren, Yefei [2 ]
Zhu, Chuanbin [3 ]
Zhang, Yuting [2 ]
Yao, Xinxin [4 ]
Wang, Daren [2 ]
Zhang, Peng [2 ]
Si, Hongjun [5 ]
Kishida, Tadahiro [6 ,7 ]
Liu, Ye [2 ]
Yaghmaei-Sabegh, Saman [8 ]
Wen, Ruizhi [2 ]
机构
[1] Hohai Univ, Coll Civil & Transportat Engn, Nanjing, Peoples R China
[2] China Earthquake Adm, Inst Engn Mech, Harbin, Peoples R China
[3] Northumbria Univ, Fac Engn & Environm, Newcastle Upon Tyne, England
[4] Jilin Jianzhu Univ, Sch Emergency Sci & Engn, Jilin, Peoples R China
[5] Seismol Res Inst Inc, Tokyo, Japan
[6] Khalifa Univ Sci & Technol, Abu Dhabi, U Arab Emirates
[7] Univ Calif Los Angeles, Los Angeles, CA USA
[8] Univ Tabriz, Dept Civil Engn, Tabriz, Iran
关键词
Site effect; Geological condition; Site parameters; Site classification; Horizontal-to-vertical spectral ratio (HVSR); SPECTRAL RATIO; CLASSIFICATION METHOD; OBSERVATION NETWORK; CONDITIONS MAP; VS30; PREDICTION; V-S30; CALIFORNIA; PROXY; H/V;
D O I
10.1016/j.enggeo.2024.107651
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Ground motion amplification and spectral content are significantly influenced by local soil and geological conditions. This article summarizes the development of the China Site Database (CNSDB) in the China Ground Motion Flatfile project. CNSDB contains site information for 1450 strong-motion recording stations within the National Strong Motion Observation Network System (NSMONS) in China. The primary site information in CNSDB includes the time-averaged shear-wave velocity in the upper 30 m (VS30), and site class according to the seismic design code in China. These site data are derived using different methods from various data sources. Priority is given to approaches that minimize bias and dispersion relative to measurement-based results. Recommended VS30 values and site class are derived from reliable velocity profiles or field survey results whenever available. A China-specific VS30 extrapolation model is developed using 6179 engineering boreholes and is then utilized to estimate VS30 for profiles <30 m. VS30 values and site class are estimated from horizontal-to-vertical spectral ratio (HVSR) curves of earthquake recordings using machine-learning techniques. For the remaining sites without velocity profiles or sufficient ground-motion recordings for HVSR computation, VS30 values are determined as the weighted average of proxy-based estimates using geological attributes, topographic slope, and terrain categories. We also discuss the potential application of CNSDB in the development of China seismic hazard map considering site amplification factors.
引用
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页数:16
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