New Ground Motion to Intensity Conversion Equations (GMICEs) for New Zealand

Abstract

Macroseismic intensities play a key role in the engineering, seismological, and loss modeling communities. However, at present, there is an increasing demand for instrumental data-based loss estimations that require statistical relationships between intensities and strong-motion data. In New Zealand, there was an urgent need to update the ground motion to intensity conversion equation (GMICE) from 2007, developed prior to a large number of recent earthquakes including the 2010–2011 Canterbury and 2016 Kaikōura earthquake sequences. Two main factors now provide us with the opportunity to update New Zealand’s GMICE: (1) recent publication of New Zealand’s Strong-Motion Database, corresponding to 276 New Zealand earthquakes with magnitudes 3.5–7.8 and 4–185 km depths; and (2) recent generation of a community intensity database from GeoNet’s “Felt Classic” (2004–2016) and “Felt Detailed” (2016–2019) questionnaires, corresponding to around 930,000 individual reports. Ground-motion data types analyzed are peak ground velocity (PGV) and peak ground acceleration (PGA). The intensity database contains 67,572 felt reports from 917 earthquakes, with magnitudes 3.5–8.1, and 1797 recordings from 247 strong-motion stations (SMSs), with hypocentral distances of 5–345 km. Different regression analyses were tested, and the bilinear regression of binned mean strong-motion recordings for 0.5 modified Mercalli intensity bins was selected as the most appropriate. Total least squares regression was chosen for reversibility in the conversions. PGV provided the best-fitting results, with lower standard deviations. The influence of hypocentral distance, earthquake magnitude, and the site effects of local geology, represented by the mean shear-wave velocity in the first 30 m depth, on the residuals was also explored. A regional correction factor for New Zealand, suitable for adjustment of global relationships, has also been estimated.

New Ground Motion to Intensity Conversion Equations for China

“…Mortalla et al [11] underestimate the intensity values for all intensity levels. Additionally, Ma et al [27] and Caprio et al [10] overestimate the intensity values at low levels but underestimate at higher levels, whereas Trifunac and Brady's study [20] has the opposite trend, leading to underestimating the values at low levels and overestimating at higher levels.…”

“…Liu et al [21], Trifunac and Brady [20], and Faenza and Michelini [2] overestimate intensity values at all intensity levels, whereas Wald et al [3] and Worden et al [6] underestimate the intensity values approximately for all intensity levels. Additionally, Atkinson and Kaka [5], Ma et al [27], Caprio et al [10], Du et al [22], Ahmadzadeh et al [12], and Mortalla et al [11] present different slopes leading to underestimating the values at low levels and overestimating at higher levels.…”

“…In some countries or regions with abundant seismic records (e.g., the United States, Japan, Italy, Turkey, New Zealand, and Taiwan), researchers have explored the correlation between seismic intensity and ground motion parameters and established the corresponding ground motion to intensity conversion equations (GMICEs) [3][4][5][6][7][8][9][10][11][12]. At present, there are numerous seismic intensity scales, such as modified Mercalli intensity (MMI), Mercalli-Cancani-Sieberg (MCS) intensity, JMA intensity in Japan, and so on in which MMI is the most widely used.…”

“…e authors obtained the PGA and PGV to intensity conversion equations and provided regional correction factors to the global relationships for Italy, Greece, and California, as well as a regional similarity study for other regions of the world [10]. Moratalla et al considered a large amount of data derived from New Zealand earthquakes and developed the updated GMICEs between MMI and PGA/PGV [11]. e work also proposed a regional correction factor for New Zealand, suitable for the global relationships of Caprio et al [10].…”

Field Insights and Analysis of the 2018 Mw 7.5 Palu, Indonesia Earthquake, Tsunami and Landslides

“…We estimate predicted PGA values based on inverse ground motion to intensity conversion equations (GMICEs). Inverse GMICEs describe the relationships between the MMI determined at a site and the estimated PGA and PGV values at the same site (Moratalla et al, 2020;Worden et al, 2012). For comparison, we select regions with a similar tectonic setting to that of northwestern Sulawesi.…”