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Anna E. Kaiser

Publications and source records attributed to Anna E. Kaiser.

4 recordsLinked to original sources

Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

The 14 November 2016 M w "> M w Mw 7.8 Kaikōura earthquake generated more than 10,000 landslides over a total area of about 10 , 000    km 2 "> 10 , 000 km 2 10,000 km2 , with the majority concentrated in a smaller area of about 3600    km 2 "> 3600 km 2 3600 km2 . The largest landslide triggered by the earthquake had an approximate volume of 20 ( ± 2 )    M   m 3 "> 20 ( ± 2 ) M m 3 20(±2) M m3 , with a runout distance of about 2.7 km, forming a dam on the Hapuku River. In this article, we present version 1.0 of the landslide inventory we have created for this event. We use the inventory presented in this article to identify and discuss some of the controls on the spatial distribution of landslides triggered by the Kaikōura earthquake. Our main findings are (1) the number of medium to large landslides (source area ≥ 10 , 000    m 2 "> ≥ 10 , 000 m 2 ≥10,000 m2 ) triggered by the Kaikōura earthquake is smaller than for similar‐sized landslides triggered by similar magnitude earthquakes in New Zealand; (2) seven of the largest eight landslides (from 5 to 20    M   m 3 "> 20 M m 3 20 M m3 ) occurred on faults that ruptured to the surface during the earthquake; (3) the average landslide density within 200 m of a mapped surface fault rupture is three times that at a distance of 2500 m or more from a mapped surface fault rupture; (4) the “distance to fault” predictor variable, when used as a proxy for ground‐motion intensity, and when combined with slope angle, geology, and elevation variables, has more power in predicting landslide probability than the modeled peak ground acceleration or peak ground velocity; and (5) for the same slope angles, the coastal slopes have landslide point densities that are an order of magnitude greater than those in similar materials on the inland slopes, but their source areas are significantly smaller.

Bulletin of the Seismological Society of America

Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence

The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment ( M 0 ), corner frequency ( f c ), and high-frequency site attenuation ( κ ). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the M 0 , f c , and κ for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single M 0 and f c , while any remaining residual kappa, κ r "> κ r κr , is allowed to differ per station record to reflect varying high-frequency falloff due to path and site attenuation. We use a parametric forward modeling method, calculating initial M 0 and f c values from the local GNS New Zealand catalog M w, GNS magnitudes and measuring an initial κ r "> κ r κr using an automated high-frequency linear regression method. Final solutions for M 0 , f c , and κ r "> κ r κr are iteratively computed through minimization of the residual function, and the Brune model stress drop is then calculated from the final, best-fit f c . We perform the spectral fitting routine on nested array seismic data that include the permanent GeoNet accelerometer network as well as a dense network of nearly 200 Quake Catcher Network (QCN) MEMs accelerometers, analyzing over 180 aftershocks M w,GNS ≥ 3.5 that occurred from 9 September 2010 to 31 July 2011. QCN stations were hosted by public volunteers and served to fill spatial gaps between existing GeoNet stations. Moment magnitudes determined using the spectral fitting procedure ( M w,SF ) range from 3.5 to 5.7 and agree well with M w,GNS , with a median difference of 0.09 and 0.17 for GeoNet and QCN records, respectively, and 0.11 when data from both networks are combined. The majority of events are calculated to have stress drops between 1.7 and 13 MPa (20th and 80th percentile, correspondingly) for the combined networks. The overall median stress drop for the combined networks is 3.2 MPa, which is similar to median stress drops previously reported for the Canterbury sequence. We do not observe a correlation between stress drop and depth for this region, nor a relationship between stress drop and magnitude over the catalog considered. Lateral spatial patterns in stress drop, such as a cluster of aftershocks near the eastern extent of the Greendale fault with higher stress drops and lower stress drops for aftershocks of the 2011 M w,GNS 6.2 Christchurch mainshock, are found to be in agreement with previous reports. As stress drop is arguably a method-dependent calculation and subject to high spatial variability, our results using the parametric Gauss–Newton algorithm strengthen conclusions that the Canterbury sequence has stress drops that are more similar to those found in intraplate regions, with overall higher stress drops that are typically observed in tectonically active areas.

Christchurch

Improved rapid magnitude estimation for a community-based, low-cost MEMS accelerometer network

Immediately following the M w 7.2 Darfield, New Zealand, earthquake, over 180 Quake‐Catcher Network (QCN) low‐cost micro‐electro‐mechanical systems accelerometers were deployed in the Canterbury region. Using data recorded by this dense network from 2010 to 2013, we significantly improved the QCN rapid magnitude estimation relationship. The previous scaling relationship ( Lawrence et al. , 2014 ) did not accurately estimate the magnitudes of nearby (<35 km) events. The new scaling relationship estimates earthquake magnitudes within 1 magnitude unit of the GNS Science GeoNet earthquake catalog magnitudes for 99% of the events tested, within 0.5 magnitude units for 90% of the events, and within 0.25 magnitude units for 57% of the events. These magnitudes are reliably estimated within 3 s of the initial trigger recorded on at least seven stations. In this report, we present the methods used to calculate a new scaling relationship and demonstrate the accuracy of the revised magnitude estimates using a program that is able to retrospectively estimate event magnitudes using archived data.

Bulletin of the Seismological Society of America

Estimating seismic site response in Christchurch City (New Zealand) from dense low-cost aftershock arrays

The Mw 7.1 September 2010 Darfield earthquake, New Zealand, produced widespread damage and liquefaction ~40 km from the epicentre in Christchurch city. It was followed by the even more destructive Mw 6.2 February 2011 Christchurch aftershock directly beneath the city&rsquo;s southern suburbs. Seismic data recorded during the two large events suggest that site effects contributed to the variations in ground motion observed throughout Christchurch city. We use densely-spaced aftershock recordings of the Darfield earthquake to investigate variations in local seismic site response within the Christchurch urban area. Following the Darfield main shock we deployed a temporary array of ~180 low-cost 14-bit MEMS accelerometers linked to the global Quake-Catcher Network (QCN). These instruments provided dense station coverage (spacing ~2 km) to complement existing New Zealand national network strong motion stations (GeoNet) within Christchurch city. Well-constrained standard spectral ratios were derived for GeoNet stations using a reference station on Miocene basalt rock in the south of the city. For noisier QCN stations, the method was adapted to find a maximum likelihood estimate of spectral ratio amplitude taking into account the variance of noise at the respective stations. Spectral ratios for QCN stations are similar to nearby GeoNet stations when the maximum likelihood method is used. Our study suggests dense low-cost accelerometer aftershock arrays can provide useful information on local-scale ground motion properties for use in microzonation. Preliminary results indicate higher amplifications north of the city centre and strong high-frequency amplification in the small, shallower basin of Heathcote Valley.

Christchurch