High-Intensity Assignments for the 22 February 2011 Mw 6.2 Christchurch, Canterbury, New Zealand, Earthquake: A Contribution toward Understanding the Severe Damage Caused by This Event

2019 ◽  
Vol 90 (4) ◽  
pp. 1468-1482 ◽  
Author(s):  
Tatiana Goded ◽  
Matt Gerstenberger ◽  
Mark Stirling ◽  
Jim Cousins ◽  
Silvia Canessa
Keyword(s):  
New Zealand ◽  
Ground Motion ◽  
Peak Ground Velocity ◽  
Correlation Equations ◽  
Intensity Data ◽  
Severe Damage ◽  
Damage Distribution ◽  
Intensity Correlation ◽  
Needed Information ◽  
Detailed Picture

ABSTRACT This article presents modified Mercalli intensity (MMI) data for the 22 February 2011 Mw 6.2 Christchurch, New Zealand, earthquake. These data include intensity levels above MMI 8 that have not been assigned previously. Two sources of data have been used in this research: GeoNet’s “Felt Classic” online questionnaires and felt reports gathered during a field study in Christchurch in February 2013. Taken together, these sets of data provided 331 valid (i.e., with all the needed information) felt reports in areas of MMI 8 or above, with 299 (90%) of the reports used to assign MMI levels above 8. This article presents a more detailed picture of the geographical damage distribution of this earthquake than has previously been available. The data differentiate damage in the center of Christchurch, with 8 communities assigned a community MMI (CMMI) of 9, 11 communities a CMMI of 10, and 8 communities a CMMI of 11, which is the maximum possible intensity in the New Zealand MMI scale, and a level of intensity not previously reported in New Zealand (Dowrick et al., 2008). The geographical damage distribution for Christchurch has been updated for intensities below MMI 8. This was done using a recently developed method that groups intensity data and allows intensities to be aggregated for a community and a single value assigned. Comparisons between MMI and peak ground velocity using the CMMI data and two ground-motion intensity correlation equations (GMICEs) indicate an underestimation of MMI when using the GMICEs and the need to review New Zealand’s GMICE.

Distribution of ground-motion intensity inferred from questionnaire survey, earthquake recordings, and microtremor measurements—A case study in Christchurch, New Zealand, during the 1994 arthurs pass earthquake

1997 ◽  
Vol 87 (2) ◽  
pp. 356-369
Author(s):  
Takumi Toshinawa ◽  
J. John Taber ◽  
John B. Berrill
Keyword(s):  
New Zealand ◽  
Ground Motion ◽  
Intensity Data ◽  
Amplification Factors ◽  
Areal Distribution ◽  
Local Site ◽  
Geological Conditions ◽  
The City ◽  
Microtremor Measurements

Abstract The areal distribution of seismic ground-motion intensity in the city of Christchurch, New Zealand, during the 1994 Arthurs Pass Earthquake (ML 6.6) was evaluated using an intensity questionnaire together with local site amplifications inferred from seismic recordings and microtremors. In order to estimate the intensity in parts of the city where no intensity data were available, intensity data were compared to relative levels of shaking determined from both weak-motion and microtremor recordings. Weak ground-motion amplification factors were determined using ratios of ground accelerations at five sediment sites with respect to a rock site. Microtremor amplification factors were determined from horizontal-to-vertical spectral ratios at a 1-km spacing throughout the city. A positive correlation between weak-motion and microtremor amplification factors allowed extrapolation of microtremor amplification to estimated MM intensity (EMMI). EMMI ranged from 3 to 6 and was consistent with the questionnaire intensity and geological conditions and showed detailed information on the areal distribution of ground-motion intensity in the city.

scholarly journals Empirical Correlations between Peak Ground Velocity and Spectrum-Based Intensity Measures

2012 ◽  
Vol 28 (1) ◽  
pp. 17-35 ◽  
Author(s):  
Brendon A. Bradley
Keyword(s):  
Ground Motion ◽  
Peak Ground Velocity ◽  
Strongly Correlated ◽  
Correlation Equations ◽  
Ground Acceleration ◽  
Intensity Measures ◽  
Ground Motion Selection ◽  
Crustal Earthquakes ◽  
Short Period ◽  
Spectrum Intensity

Empirical correlation equations between peak ground velocity ( PGV) and several spectrum-based ground motion intensity measures are developed. The intensity measures examined in particular were: peak ground acceleration ( PGA), 5% damped pseudo-spectral acceleration ( SA), acceleration spectrum intensity ( ASI), and spectrum intensity ( SI). The computed correlations were obtained using ground motions from active shallow crustal earthquakes and four ground motion prediction equations. Results indicate that PGV is strongly correlated (i.e., a correlation coefficient of [Formula: see text]) with SI, moderately correlated with medium to long-period SA (i.e., [Formula: see text] for vibration periods 0.5-3.0 seconds), and also moderately correlated with short period SA, PGA and ASI ([Formula: see text]). A simple example is used to illustrate one possible application of the developed correlation equations for ground motion selection.

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

2020 ◽  
Vol 92 (1) ◽  
pp. 448-459 ◽  
Author(s):  
Jose M. Moratalla ◽  
Tatiana Goded ◽  
David A. Rhoades ◽  
Silvia Canessa ◽  
Matthew C. Gerstenberger
Keyword(s):  
New Zealand ◽  
Ground Motion ◽  
Strong Motion ◽  
Peak Ground Velocity ◽  
Least Squares Regression ◽  
Data Types ◽  
Ground Acceleration ◽  
Hypocentral Distance ◽  
Motion Data ◽  
Recent Earthquakes

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.

scholarly journals Seismic Hazard Assessment for the Tianshui Urban Area, Gansu Province, China

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Zhenming Wang ◽  
David T. Butler ◽  
Edward W. Woolery ◽  
Lanmin Wang
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Design ◽  
Hazard Analysis ◽  
Seismic Hazard Assessment ◽  
Gansu Province ◽  
Mitigation Measures ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Acceleration Time Histories

A scenario seismic hazard analysis was performed for the city of Tianshui. The scenario hazard analysis utilized the best available geologic and seismological information as well as composite source model (i.e., ground motion simulation) to derive ground motion hazards in terms of acceleration time histories, peak values (e.g., peak ground acceleration and peak ground velocity), and response spectra. This study confirms that Tianshui is facing significant seismic hazard, and certain mitigation measures, such as better seismic design for buildings and other structures, should be developed and implemented. This study shows that PGA of 0.3 g (equivalent to Chinese intensity VIII) should be considered for seismic design of general building and PGA of 0.4 g (equivalent to Chinese intensity IX) for seismic design of critical facility in Tianshui.

A theoretical study of the radiation from small strikeslip earthquakes at close distances

1983 ◽  
Vol 73 (1) ◽  
pp. 83-96 ◽  
Author(s):  
Michel Campillo ◽  
Michel Bouchon
Keyword(s):  
Ground Motion ◽  
Epicentral Distance ◽  
Homogeneous Medium ◽  
Source Model ◽  
Strike Slip ◽  
Peak Ground Velocity ◽  
Corner Frequency ◽  
Crack Model ◽  
Sharp Change ◽  
S Wave

abstract We present a study of the seismic radiation of a physically realistic source model—the circular crack model of Madariaga—at close distance range and for vertically heterogeneous crustal structures. We use this model to represent the source of small strike-slip earthquakes. We show that the characteristics of the radiated seismic spectra, like the corner frequency, are strongly affected by the presence of the free surface and by crustal layering, and that they can be considerably different from the ones of the homogeneous-medium far-field solution. The vertical and radial displacement spectra are the most strongly affected. We use this source model to calculate the decay of peak ground velocity with epicentral distance and source depth for small strike-slip earthquakes in California. For distances between 10 and 80 km, the peak horizontal velocity decay is of the form r−1.25 for a 4-km hypocentral depth and r−1.65 for deeper sources. The predominance of supercritically reflected arrivals beyond epicentral distances of 70 to 80 km produces a sharp change in the rate of decay of the ground motion. For most of the cases considered, the peak ground velocity increases between 80 and 100 km. We also show that the S-wave velocity in the source layer is the lower limit of phase velocities associated with significant ground motion.

scholarly journals The 30 October 2020 Samos (Eastern Aegean Sea) Earthquake: effects of source rupture, path and local-site conditions on the observed and simulated ground motions

2021 ◽  
Author(s):  
Aybige Akinci ◽  
Daniele Cheloni ◽  
AHMET ANIL DINDAR
Keyword(s):  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Aegean Sea ◽  
Peak Ground Velocity ◽  
Ground Shaking ◽  
Local Site ◽  
Eastern Aegean ◽  
Motion Characteristics ◽  
Eastern Aegean Sea

Abstract On 30 October 2020 a MW 7.0 earthquake occurred in the eastern Aegean Sea, between the Greek island of Samos and Turkey’s Aegean coast, causing considerable seismic damage and deaths, especially in the Turkish city of Izmir, approximately 70 km from the epicenter. In this study, we provide a detailed description of the Samos earthquake, starting from the fault rupture to the ground motion characteristics. We first use Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) data to constrain the source mechanisms. Then, we utilize this information to analyze the ground motion characteristics of the mainshock in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and spectral pseudo-accelerations. Modelling of geodetic data shows that the Samos earthquake ruptured a NNE-dipping normal fault located offshore north of Samos, with up to 2.5-3 m of slip and an estimated geodetic moment of 3.3 ⨯ 1019 Nm (MW 7.0). Although low PGA were induced by the earthquake, the ground shaking was strongly amplified in Izmir throughout the alluvial sediments. Structural damage observed in Izmir reveals the potential of seismic risk due to the local site effects. To better understand the earthquake characteristics, we generated and compared stochastic strong ground motions with the observed ground motion parameters as well as the ground motion prediction equations (GMPEs), exploring also the efficacy of the region-specific parameters which may be improved to better predict the expected ground shaking from future large earthquakes in the region.

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