Ground Motion to Intensity Conversion Equations (GMICEs): A Global Relationship and Evaluation of Regional Dependency

Abstract

We analyzed the regional dependence of ground motion to intensity conversion equations and derived a new global relationship to improve ground motion and intensity estimates for earthquake hazard applications, including those related to the ShakeMap system. For this purpose, we merged several databases collected by other authors in different geographical regions to highlight any systematic regional effects in the relationship between macroseismic intensities and both peak ground velocity and peak ground acceleration. Our database contains macroseismic intensities derived from expert assignments or from the "Did You Feel It?" database, paired with peak ground motions (PGM) from seismic stations. We constrain our intensity-ground-motion pairs to those with a maximum 2 km separation. For each region, we derived invertible relationships between intensities and ground motion using an orthogonal regression. We also derived a global relationship to quantify the regional differences. We investigated the dependence of intensity on predictor variables such as PGM, magnitude, and hypocentral distance. Our analyses indicate that PGM is the most robust predictor variable of intensity. Within one standard deviation, our regional and global results are in agreement with the relations of Worden et al. (2012) for California, Faenza and Michelini (2010) for Italy, Tselentis and Danciu (2008) for Greece, and Atkinson and Kaka (2007) for central-eastern United States. The earthquakes in the study ranged in magnitude from 2.5 to 7.3, and the distances ranged from less than a kilometer to about 200 km from the epicenter.

A comparison of observed and predicted ground motions from the 2015 MW7.8 Gorkha, Nepal, earthquake

“…Given the close correspondence between EMS-98 and MMI intensities (Musson et al 2010), one expects the published relationships to hold for EMS-98 intensities as well. It is possible that the relationship between instrumental PGA and intensity will be regionally variable, as inferred by Caprio et al (2015); it is also possible that an incomplete consideration of differences in vulnerability will give rise to an apparent regional variation in the relationship.…”

Earthquake-triggered landslides along the Hyblean-Malta Escarpment (off Augusta, eastern Sicily, Italy) – assessment of the related tsunamigenic potential

“…However, if one considers the macroseismic field of E1693 and makes use of a proper PGA-I regression relationship, one can estimate the PGA values of E1693 in the area off Augusta where the slides are supposedly located. In literature there are several regression laws computed for the Italian territory (see Chiaruttini and Siro, 1981;Margottini et al, 1992;Decanini et al, 1995;Faccioli and Cauzzi, 2006;Faenza and Michelini, 2010;Caprio et al, 2015). If we use the relation computed recently by Paparo and Tinti (2017), one sees that in correspondence of an MCS intensity XI, the PGA is 0.51 g, much larger than the value associated with the third seismic zone.…”

Earthquakes on the surface: earthquake location and area based on more than 14 500 ShakeMaps

“…Douglas (2003) classifies them into three categories: those related to the earthquake source (e.g., magnitude, depth, or faulting mechanism), travel path (e.g., geology can have a significant impact on attenuation), and local site conditions. The prediction, estimation, and recording of strong ground motion parameters are active fields of ongoing research and technological improvements (Douglas, 2003;Denolle et al, 2014;Wald et al, 2011;Caprio et al, 2015;Kong et al, 2016). SCEC, for example, has a Ground Motion Prediction Working Group.…”