Site classification and probabilistic estimation of Vs30 for the Iranian strong-motion network

Abstract

Through a probabilistic approach, this study provides estimates of the time-averaged shear-wave velocity in the top 30 m of soil column (Vs30) for the stations of Iranian strong-motion network. For this purpose, we consider the strong-motion dataset of the Road, Housing and Urban Development Research Center for the period 1975–2018 from which 3828 three-component records from 1636 events with moment magnitude of >3, recorded at 892 stations (hypocentral distances of <300 km), are used in this study. The stations with known Vs30 (388 stations) are grouped into the NEHRP site classes; 3 stations in class A, 115 in class B, 213 in class C, 52 in class D, and 5 in class E. We obtain the probability density function and cumulative distribution function of the natural logarithm of horizontal-to-vertical response spectral ratio of ground-motion amplitudes, ln(H/V), at different periods as the basis for site classification and Vs30 estimation. We show that there is a strong dependency between site class and ln(H/V) at periods between 0.5 and 1.4 s. Using two classification criteria, we estimate the site class and Vs30 for 504 stations without this information. Our results show that there are 6 stations in site class A, 191 in class B, 76 in class C, 222 in class D, and 9 in class E. The residuals between observed and estimated Vs30 values (observed − estimated in logarithmic scale) do not show any trends and are consistent across all stations with a mean, standard deviation, and percentage error of 0.09, 0.19, and 15%, respectively. We also test our approach against the values obtained from the topography slope method proposed by Wald and Allen (2007), which results in a larger error with a mean, standard deviation, and percentage error of −0.41, 0.39, and 77%, respectively.