The 2016 M7.8 Kaikōura earthquake is one of the most complex earthquakes in recorded history, with significant rupture of at least 21 crustal faults. Using a matched-filter detection routine, precise cross-correlation pick corrections, and accurate location and relocation techniques, we construct a catalog of 33,328 earthquakes between 2009 and 2020 on and adjacent to the faults that ruptured in the Kaikōura earthquake. We also compute focal mechanisms for 1,755 of the earthquakes used as templates. Using this catalog we reassess the rupture pathway of the Kaikōura earthquake. In particular we show that: (1) the earthquake nucleated on the Humps Fault; (2) there is a likely linking offshore reverse fault between the southern fault system and the Papatea Fault, which could explain the anomalously high slip on the Papatea Fault; (3) the faults that ruptured in the 2013 Cook Strait sequence were reactivated by the Kaikōura earthquake and may have played a role in the termination of the earthquake; and (4) no seismicity on an underlying subduction interface is observed beneath almost all of the ruptured region suggesting that if deformation did occur on the plate interface then it occurred aseismically and did not play a significant role in generating co-seismic ground motion.

Slow slip events have previously been observed along the Hikurangi subduction zone beneath the North Island of New Zealand. These slow slip episodes occur both on the shallow plate interface (< 15km depth) and at the deeper end of the seismogenic zone (> 30km depth). We present the first catalog of low-frequency earthquakes (LFEs) in the Hikurangi subduction zone, located beneath the Kaimanawa Range on the central Hikurangi margin, downdip of a region that regularly (every 4-5 years) hosts M7 slow slip events. To systematically detect LFEs using continuous seismic data recorded by GeoNet, we developed a matched-filter technique with template waveforms derived from previous observations of tectonic tremor. The workflow presented in this work is composed of two iterations of a matched-filter search. In each iteration, the detections were gathered into families and their common waveforms postprocessed with machine-learning methods to extract high-quality waveforms, allowing us to pick seismic phase arrivals with which to locate the LFEs. We found that LFEs occur in episodes of intense activity during the neighboring updip M7 slow slip events. We also observe a recurrence time of 2 years between other large bursts of LFEs, suggestive of a shorter cycle of slow slip. We hypothesize that these and other frequent LFE episodes highlight smaller slow transients that have not yet been geodetically observed.

Slow-Slip Events (SSEs) haven been observed along the Hikurangi subduction zone of the North Island of New-Zealand. They occur both in the shallow plate interface (<15km depth) and at the deeper end of the seismogenic-zone (>30km depth). Some slow slip events in New-Zealand are also accompanied by tectonic tremors, although tremor is not as common at the Hikurangi subduction zone compared to other subduction zones. We present a systematically generated catalog of low-frequency earthquakes (LFEs) for the central Hikurangi margin. To detect preliminary LFEs from the continuous seismic data we used a Matched-Filter technique with template waveforms from the tectonic tremor catalog of Romanet & Ide [2019]. The resulting detections were gathered as families and an innovative stacking technique was used to extract high-quality waveforms in order to build a set of LFE templates for a second Matched-Filter search. From these second generation detections, we developed a methodology to continuously scan the entire dataset for coherent impulsive waveforms similar to LFE that occuring on the subducting plate interface. The LFEs are organized into episodes of intense activity during deep M7 SSEs that occur absit every 5 years beneath the Manawatu region. One of our LFE bursts occurs during a small, deep SSE recognized at the central Hikurangi margin in 2008 (Wallace and Eberhart-Phillips, 2013). We expect that the other LFE episodes highlight small slow transients that have not yet been geodetically observed. In this presentation, we discuss the spatiotemporal evolution of LFEs in regard to potential aseismic transients that can be observed in the GPS data-set acquired by GeoNet.

Repeating earthquakes provide a novel way of monitoring how stresses load faults between large earthquakes. To date, however, and despite the availability of long-duration, high-quality seismological datasets, little attention has been paid to tectonic repeating earthquakes in New Zealand. We develop a workflow and composite criterion for identifying repeating earthquakes in New Zealand, using data from the GeoNet permanent seismic network, and present New Zealand’s first decadal-scale repeating earthquake catalog. For events to be identified as repeating in this study, two or more events must have a normalized cross-correlation of at least 0.95 at two or more seismic stations, when calculated for 75% of the earthquake coda. By applying our composite criterion to seismicity around the Raukumara Peninsula, northern Hikurangi subduction margin, we have identified 62 repeating earthquake families occurring between 2003 and 2018, consisting of 160 individual earthquakes. These families have a magnitude range of MW 1.5-4.5 and recurrence intervals of < 1-12 years. The repeating earthquake families identified in this study coincide with the location and timing of previously identified slow-slip events and tremor. However, the responses shown to slow-slip are not consistent within families or within regional groups.

Conventional earthquake detection methods suffer significant degradations in completeness during high-rate sequences such as aftershock sequences or volcanic swarms. Missed earthquakes during the early periods of aftershock sequences can affect aftershock forecasts and hazard estimates. Missed events during volcanic unrest sequences can impact rate estimations, leading to the sequence being mis-characterized. Much recent work has addressed how matched-filters can be used to overcome some aspects of catalog incompleteness during high-rate sequences, by detecting similar events using cross-correlation. Here we describe the application of open-source (GPL v3.0) software to the near-real-time implementation of matched-filter earthquake detection. Our software (RT-EQcorrscan) is written in Python, and leverages the extensive Obspy package, as well as EQcorrscan and Obsplus to provide matched-filter methods and database handling respectively. RT-EQcorrscan is designed to be modular, so that users can readily utilize only the components they require, or make use of pre-built command-line utilities controlled by simple that can handle thousands of templates over tens of channels of seismic data within the processing capacity (memory and CPU usage) of a standard desktop personal computer. Detections are made within a few seconds of data arriving, with latency due to data delivery and a requirement for full network move-out. At the same time, RT-EQcorrscan has an overarching “Reactor” module to listen to a web-service and respond to new events. If an event occurs that meets user-defined criteria, the Reactor will initiate a near-real-time matched-filter process encompassing the region surrounding the trigger event. Subsequent trigger events in different regions can also be handled with threaded operations. This system is backed-up by a constantly updating template database built on Obsplus, allowing groups of templates to be rapidly deployed. In this presentation we will discuss the key implementation details, as well as showcasing some examples of the system in operation.