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Which is a better proxy, site period or depth to bedrock, in modelling linear site response in addition to the average shear-wave velocity?

Authors
/persons/resource/chuanbin

Zhu,  Chuanbin
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/pilz

Pilz,  M.
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/fcotton

Cotton,  Fabrice
2.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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4709914.pdf
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Citation

Zhu, C., Pilz, M., Cotton, F. (2020): Which is a better proxy, site period or depth to bedrock, in modelling linear site response in addition to the average shear-wave velocity? - Bulletin of Earthquake Engineering, 18, 3, 797-820.
https://doi.org/10.1007/s10518-019-00738-6


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_4709914
Abstract
This study aims to identify the best-performing site characterization proxy alternative and complementary to the conventional 30 m average shear-wave velocity VS30, as well as the optimal combination of proxies in characterizing linear site response. Investigated proxies include T0 (site fundamental period obtained from earthquake horizontal-to-vertical spectral ratios), VSz (measured average shear-wave velocities to depth z, z = 5, 10, 20 and 30 m), Z0.8 and Z1.0 (measured site depths to layers having shear-wave velocity 0.8 and 1.0 km/s, respectively), as well as Zx-infer (inferred site depths from a regional velocity model, x = 0.8 and 1.0, 1.5 and 2.5 km/s). To evaluate the performance of a site proxy or a combination, a total of 1840 surface-borehole recordings is selected from KiK-net database. Site amplifications are derived using surface-to-borehole response-, Fourier- and cross-spectral ratio techniques and then are compared across approaches. Next, the efficacies of 7 single-proxies and 11 proxy-pairs are quantified based on the site-to-site standard deviation of amplification residuals of observation about prediction using the proxy or the pair. Our results show that T0 is the best-performing single-proxy among T0, Z0.8, Z1.0 and VSz. Meanwhile, T0 is also the best-performing proxy among T0, Z0.8, Z1.0 and Zx-infer complementary to VS30 in accounting for the residual amplification after VS30-correction. Besides, T0 alone can capture most of the site effects and should be utilized as the primary site indicator. Though (T0, VS30) is the best-performing proxy pair among (VS30, T0), (VS30, Z0.8), (VS30, Z1.0), (VS30, Zx-infer) and (T0, VSz), it is only slightly better than (T0, VS20). Considering both efficacy and engineering utility, the combination of T0 (primary) and VS20 (secondary) is recommended. Further study is needed to test the performances of various proxies on sites in deep sedimentary basins.