A post on the NZ Raw blog written by Mark Lincoln on 4 September 2010. Mark says, "This is the first [blog post] I wrote on 4th Sept. I always remember an announcer on the radio having the first on-air interview with Geonet/EQC (obviously only 1 or 2 staff members at that stage!). The announcer asked if the aftershocks would carry on for much longer and the Geonet guy said they could carry on for a few weeks. Radio announcer seemed shocked".
In the early morning of 4th September 2010 the region of Canterbury, New Zealand, was subjected to a magnitude 7.1 earthquake. The epicentre was located near the town of Darfield, 40 km west of the city of Christchurch. This was the country’s most damaging earthquake since the 1931 Hawke’s Bay earthquake (GeoNet, 2010). Since 4th September 2010 the region has been subjected to thousands of aftershocks, including several more damaging events such as a magnitude 6.3 aftershock on 22nd February 2011. Although of a smaller magnitude, the earthquake on 22nd February produced peak ground accelerations in the Christchurch region three times greater than the 4th September earthquake and in some cases shaking intensities greater than twice the design level (GeoNet, 2011; IPENZ, 2011). While in September 2010 most earthquake shaking damage was limited to unreinforced masonry (URM) buildings, in February all types of buildings sustained damage. Temporary shoring and strengthening techniques applied to buildings following the Darfield earthquake were tested in February 2011. In addition, two large aftershocks occurred on 13th June 2011 (magnitudes 5.7 and 6.2), further damaging many already weakened structures. The damage to unreinforced and retrofitted clay brick masonry buildings in the 4th September 2010 Darfield earthquake has already been reported by Ingham and Griffith (2011) and Dizhur et al. (2010b). A brief review of damage from the 22nd February 2011 earthquake is presented here
1. Background and Objectives This poster presents results from ground motion simulations of small-to-moderate magnitude (3.5≤Mw≤5.0) earthquake events in the Canterbury, New Zealand region using the Graves and Pitarka (2010,2015) methodology. Subsequent investigation of systematic ground motion effects highlights the prediction bias in the simulations which are also benchmarked against empirical ground motion models (e.g. Bradley (2013)). In this study, 144 earthquake ruptures, modelled as point sources, are considered with 1924 quality-assured ground motions recorded across 45 strong motion stations throughout the Canterbury region, as shown in Figure 1. The majority of sources are Mw≥4.0 and have centroid depth (CD) 10km or shallower. Earthquake source descriptions were obtained from the GeoNet New Zealand earthquake catalogue. The ground motion simulations were performed within a computational domain of 140km x 120km x 46km with a finite difference grid spacing of 0.1km. The low-frequency (LF) simulations utilize the 3D Canterbury Velocity Model while the high-frequency (HF) simulations utilize a generic regional 1D velocity model. In the LF simulations, a minimum shear wave velocity of 500m/s is enforced, yielding a maximum frequency of 1.0Hz.
Having a quick but reliable insight into the likelihood of damage to bridges immediately after an earthquake is an important concern especially in the earthquake prone countries such as New Zealand for ensuring emergency transportation network operations. A set of primary indicators necessary to perform damage likelihood assessment are ground motion parameters such as peak ground acceleration (PGA) at each bridge site. Organizations, such as GNS in New Zealand, record these parameters using distributed arrays of sensors. The challenge is that those sensors are not installed at, or close to, bridge sites and so bridge site specific data are not readily available. This study proposes a method to predict ground motion parameters for each bridge site based on remote seismic array recordings. Because of the existing abundant source of data related to two recent strong earthquakes that occurred in 2010 and 2011 and their aftershocks, the city of Christchurch is considered to develop and examine the method. Artificial neural networks have been considered for this research. Accelerations recorded by the GeoNet seismic array were considered to develop a functional relationship enabling the prediction of PGAs. http://www.nzsee.org.nz/db/2013/Posters.htm
This poster presents work to date on ground motion simulation validation and inversion for the Canterbury, New Zealand region. Recent developments have focused on the collection of different earthquake sources and the verification of the SPECFEM3D software package in forward and inverse simulations. SPECFEM3D is an open source software package which simulates seismic wave propagation and performs adjoint tomography based upon the spectral-element method. Figure 2: Fence diagrams of shear wave velocities highlighting the salient features of the (a) 1D Canterbury velocity model, and (b) 3D Canterbury velocity model. Figure 5: Seismic sources and strong motion stations in the South Island of New Zealand, and corresponding ray paths of observed ground motions. Figure 3: Domain used for the 19th October 2010 Mw 4.8 case study event including the location of the seismic source and strong motion stations. By understanding the predictive and inversion capabilities of SPECFEM3D, the current 3D Canterbury Velocity Model can be iteratively improved to better predict the observed ground motions. This is achieved by minimizing the misfit between observed and simulated ground motions using the built-in optimization algorithm. Figure 1 shows the Canterbury Velocity Model domain considered including the locations of small-to-moderate Mw events [3-4.5], strong motion stations, and ray paths of observed ground motions. The area covered by the ray paths essentially indicates the area of the model which will be most affected by the waveform inversion. The seismic sources used in the ground motion simulations are centroid moment tensor solutions obtained from GeoNet. All earthquake ruptures are modelled as point sources with a Gaussian source time function. The minimum Mw limit is enforced to ensure good signal-to-noise ratio and well constrained source parameters. The maximum Mw limit is enforced to ensure the point source approximation is valid and to minimize off-fault nonlinear effects.
