The 2016 Mw 7.8 Kaikoura, New Zealand, earthquake
The 2016 Kaikoura, New Zealand, earthquake was one of the most complex ruptures ever recorded. The epicentre was located well inland, but the rupture area extended offshore and generated a modest tsunami which was recorded by tide gauges. Here, we present a detailed estimate of seafloor vertical displace- ment during the earthquake sequence by a joint inversion of tsunami waveforms and vertical displacement data observed at GPS stations and obtained by field surveys. The combined dataset provides a solution with good resolution, capable of resolving test sources of 20 km of characteristic diameter throughout the study area. We found two seafloor uplift regions which are located very close to the coast, one is located offshore of the Kaikoura peninsula and the other larger uplift region is located near the Kekerengu and Needles faults. To estimate crustal deformation with a complete spatial coverage of the event, the estimated seafloor vertical dis- placement was combined with the inland vertical displacement from InSAR and GPS datasets. This vertical displacement is then inverted for the fault slip distributions of the Needles, Jordan– Kekerengu, Papatea, Hundalee, Hump faults, and a newly identified fault beneath Kaikoura. We also found that the Needles fault is probably an offshore extension of the Kekerengu fault. The seismic moment calculated from the fault slip distributions by assuming a rigidity of 2.7 9 1010 N/m2, is 5.19 x 1020 Nm or equivalent to Mw 7.8. This total seismic moment estimate is consistent with that of the Global Centroid Moment Tensor solution. The tsunami potential energy calculated from the seafloor vertical displacement is 9.40 9 1012 J, of which about 70% is attributed to movement on the faults known to have ruptured, suggesting a secondary source for tsunami generation.
The 2014 Mw 7.1 Molucca Sea, Indonesia, earthquake
The coseismic slip of the 2014 Molucca Sea, Indonesia, earthquake (MOSEQ) is investigated using GPS data from continuously monitoring stations. Coseismic fault models are compared between the main fault, with a 25 west-dipping plane, and the 65 west-dipping splay-fault plane. In analyzing this earth- quake with fine faults sized resolution and homogenous fault models, we find that a splay fault ruptured during the mainshock. Our finding suggests that the 2014 MOSEQ occurred on an unmapped fault. Although we have limited GPS data available in the region, our results for coseismic slip are sufficient to explain the available GPS data. Our estimation suggesting that a maximum coseismic slip of around 36 cm occurred near the hypocenter, with cumulative seismic moment of 4.70 x 1019 N m (Mw 7.1).
The 2014 Mw 8.0 Iquique, Chile, earthquake
We applied a new method to compute tsunami Green’s functions for slip inversion of the 1 April 2014 Iquique earthquake using both near-field and far-field tsunami waveforms. Inclusion of the effects of the elastic loading of seafloor, compressibility of seawater, and the geopotential variation in the computed Green’s functions reproduced the tsunami traveltime delay relative to long-wave simulation and allowed us to use far-field records in tsunami waveform inversion. Multiple time window inversion was applied to tsunami waveforms iteratively until the result resembles the stable moment rate function from teleseismic inversion. We also used GPS data for a joint inversion of tsunami waveforms and coseismic crustal deformation. The major slip region with a size of 100 km × 40 km is located downdip the epicenter at depth ~28 km, regardless of assumed rupture velocities. The total seismic moment estimated from the slip distribution is 1.24 × 1021 N m (Mw 8.0).
The 2013 Mw 6.1 Aceh, Indonesia, earthquake
This study investigates the coseismic slip distribution of the 2 July 2013 Mw 6.1 Aceh earthquake using Global Positioning System (GPS) data, measured geo- logical surface offsets, and an aftershock distribution for a period of four days after the mainshock. We use the aftershock distribution to constrain the fault-plane strike of a right-lateral fault identified as the Pantan Terong segment. We estimate the coseismic slip distribution with dip angle information from the Global Centroid Moment Tensor (CMT) (model 1) and U.S. Geological Survey (USGS) (model 2) catalogs. We also estimate the coseismic slip distribution using another two fault models. Model 3 is constructed on a left-lateral fault, the Celala segment, which is perpendicular to the Aceh segment of the Sumatran fault, and model 4 is constructed using the multiple faults in models 2 and 3. We further estimate the coseismic slip distribution of this earthquake by employing an elastic dislocation model, inverting only the GPS dis- placements for model 3 and jointly inverting GPS displacements and geological surface offsets for models 1, 2, and 4. Minimum misfit between data and model is obtained with model 3, suggesting that the earthquake slip occurred along a left-lateral fault. Analysis of stress transfer caused by the 2013 earthquake indicates that the stress level along the Pantan Terong segment is > 0:4 bar and the southeast part of Aceh segment was brought ∼0:3 bar closer to failure, suggesting a possible earthquake oc- currence in the future. This work demonstrates that the seismicity-derived fault plane fails to predict the surface displacement, and that the inferred Celala segment produces positive stress on Pantan Terong segment and potentially triggered all the aftershocks.
The 2012 Mw 8.6 Indian Ocean earthquake
Based on continuous GPS data, we analyze coseismic deformation due to the 2012 Indian Ocean earthquake. We use the available coseismic slip models of the 2012 earthquake, derived from geodetic and/or seismic waveform inversion, to calculate the coseismic displacements in the Andaman-Nicobar, Sumatra and Java. In our analysis, we employ a spherical, layered model of the Earth and we find that Java Island experienced coseismic displacements up to 8 mm, as also observed by our GPS net- work. Compared to coseismic offsets measured from GPS data, a coseismic slip model derived from multiple observations produced better results than a model based on a single type of observation.
The 2 September 2009 Mw 6.8 Tasikmalaya intraslab earthquake
We estimate the fault model of the 2 September 2009 Tasikmalaya intraslab earthquake based on the GPS data available in western Java, Indonesia. The focal mechanism of the earthquake was used to help construct two possible fault models: a west-dipping fault with a strike of 160.8º and an east-dipping fault with a strike of 34.0°. In this study, vertical information from GPS data is crucial for constructing the top depth of the fault. The subsidence information from GPS data located near the epicenter suggests that the earthquake involved a deeper fault model. While the amount of the moment release of the east-dipping fault (Model dipE) is equivalent to Mw 6.9, the moment release of the west-dipping fault (Model dipW) is equivalent to Mw 6.8. The GPS data inversion indicates that Model dipW produces a better fit than Model dipE. The tsunami simulation indicates that the tsunami height generated by the east-dipping fault is smaller than that generated by the west-dipping fault, implying that the maximum tsunami height of the latter is closer to agreement with the reported one. Unlike Model dipE, the stress transfer analysis of Model dipW indicates that most of the aftershocks were located in the region where ΔCFF is positive, suggesting positive stress from the ruptured triggered aftershocks. The combined analysis of GPS data, tsunami simulation, and stress transfer suggests that the fault ruptured during the 2009 earthquake was dipping westward with a steep dip angle.
