Abstract
In this study, we use the strong motion records and seismic intensity data from 11 moderate-to-strong earthquakes in the mainland of China since 2008 to develop new conversion equations between seismic intensity and peak ground motion parameters. Based on the analysis of the distribution of the dataset, the reversible conversion relationships between modified Mercalli intensity (MMI) and peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo-spectral acceleration (PSA) at natural vibration periods of 0.3 s, 1.0 s, 2.0 s, and 3.0 s are obtained by using the orthogonal regression. The influence of moment magnitude, hypocentral distance, and hypocentral depth on the residuals of conversion equations is also explored. To account for and eliminate the trends in the residuals, we introduce a magnitude-distance-depth correction term and obtain the improved relationships. Furthermore, we compare the results of this study with previously published works and analyze the regional dependence of conversion equations. To quantify the regional variations, a regional correction factor for China, suitable for adjustment of global relationships, has also been estimated.
Highlights
As a qualitative index to describe the ground vibration and degree of damage caused by an earthquake, the seismic intensity provides a simple macroscopic scale to characterize the magnitude of an earthquake’s impact on human communities, so it is widely used in earthquake disaster assessment, loss estimation, structural response analyses, historical earthquake disaster recurrence, and other fields all over the world [1]
Seismic intensity is typically obtained by experts who investigate the building damage and human response to an earthquake in an area where that earthquake strikes. Ground motion parameters, such as peak ground acceleration (PGA), peak ground velocity (PGV), and pseudo-spectral acceleration (PSA), which are used as quantitative indexes to describe the degree of ground vibration, are usually obtained from the records of seismic observation instruments deployed in earthquake areas
The orthogonal regression, which is known as total least square regression or Deming regression [25], has been used to fit our modified Mercalli intensity (MMI)-logPGM data pairs and develop the ground motion to intensity conversion equations (GMICEs) for China. e orthogonal regression calculates the residuals as the minimum perpendicular distance from a point to the regression line
Summary
As a qualitative index to describe the ground vibration and degree of damage caused by an earthquake, the seismic intensity provides a simple macroscopic scale to characterize the magnitude of an earthquake’s impact on human communities, so it is widely used in earthquake disaster assessment, loss estimation, structural response analyses, historical earthquake disaster recurrence, and other fields all over the world [1]. Seismic intensity is typically obtained by experts who investigate the building damage and human response to an earthquake in an area where that earthquake strikes Ground motion parameters, such as PGA, PGV, and PSA, which are used as quantitative indexes to describe the degree of ground vibration, are usually obtained from the records of seismic observation instruments deployed in earthquake areas. It is worth noting that the conversion equations from PGA/PGV to MMI are not scrutinized and revised by using recent local seismic data; in addition, as of the robust correlation relationships between MMI and PSA, which are very useful because the spectral quantities are strong indicators of the structural response which directly influence the observed intensity values, have not been studied in detail for Chinese earthquake dataset. Two realistic factors inspire us to develop the new GMICEs. (1) Since 2008, the operation of China Digital Strong Motion Network has greatly increased the quantity and quality of the strong motion observation stations, and in recent years, the mainland of China has experienced a number of moderate-tostrong destructive earthquakes, resulting in large volumes of strong motion records and post-earthquake seismic intensity data. (2) With the rapid development of national economy, the structure of buildings, seismic resistance, and the types of earthquake damage have changed significantly, and the distribution of the peak ground motion corresponding to the seismic intensity may change . us, in this study, we intend to use the recent seismic dataset of China and develop the new conversion equations between seismic intensity and PGA, PGV, and PSA
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