A study of aftershocks of 20 October 1991 Uttarkashi earthquake

The Uttarkashi earthquake of 20 October 1991, which caused widespread damage in the Galhwal Himalayan region, was followed by a prominent aftershock. activity extending over a period of about two months. The aftershock activity was monitored using temporary networks established after the mainshock and the permanent stations in operation in the region. About 142 aftershocks could be located accurately using the data of these stations. The b-value of the Gutenberg-Richter's relationship for the aftershock sequence works out to be 0.6. The temporal distribution of the aftershocks suggests a hyperbolic decay with a decay constant (p) of 1.17. Macroseismic observations derived from field surveys show good agreement with the instrumentally determined source parameters.

Combining a Locally Restricted Anisotropic Spatial Kernel with an ETAS Incomplete Model for Better Forecasts of the 2019 Ridgecrest Sequence

Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model seismic clustering is the Epidemic Type Aftershock Sequence (ETAS) model, that shows three major biases: First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three effects can substantially bias the parameter estimation and particularly lead to underestimated cluster sizes. In this article, we combine the approach of Grimm (2021), which introduced a generalized anisotropic and locally restricted spatial kernel, with the ETAS-Incomplete (ETASI) time model of Hainzl (2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g.~allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and desaster response.

Machine-Learning-Based High-Resolution Earthquake Catalog Reveals How Complex Fault Structures Were Activated during the 2016–2017 Central Italy Sequence

The 2016–2017 central Italy seismic sequence occurred on an 80 km long normal-fault system. The sequence initiated with the Mw 6.0 Amatrice event on 24 August 2016, followed by the Mw 5.9 Visso event on 26 October and the Mw 6.5 Norcia event on 30 October. We analyze continuous data from a dense network of 139 seismic stations to build a high-precision catalog of ∼900,000 earthquakes spanning a 1 yr period, based on arrival times derived using a deep-neural-network-based picker. Our catalog contains an order of magnitude more events than the catalog routinely produced by the local earthquake monitoring agency. Aftershock activity reveals the geometry of complex fault structures activated during the earthquake sequence and provides additional insights into the potential factors controlling the development of the largest events. Activated fault structures in the northern and southern regions appear complementary to faults activated during the 1997 Colfiorito and 2009 L’Aquila sequences, suggesting that earthquake triggering primarily occurs on critically stressed faults. Delineated major fault zones are relatively thick compared to estimated earthquake location uncertainties, and a large number of kilometer-long faults and diffuse seismicity were activated during the sequence. These properties might be related to fault age, roughness, and the complexity of inherited structures. The rich details resolvable in this catalog will facilitate continued investigation of this energetic and well-recorded earthquake sequence.

Classification of earthquake repeaters in the central Ionian Islands area

<p>The central Ionian Islands area accommodates remarkable seismic activity with frequent strong (M>6.0) earthquake occurrence and continuous microseismicity. The dominant seismotectonic characteristic is the Kefalonia Transform Fault Zone (<em>KTFZ</em>), a dextral transform active boundary between oceanic subduction and continental collision, running along the western coastlines of Kefalonia and Lefkada Islands. KTFZ comprises two main fault branches (Kefalonia and Lefkada) connected with a step over zone in between. In the past 20 years, four strong earthquakes ruptured the Lefkada (06/08/2003–M6.5 and 17/11/2015–M6.5) and the Kefalonia (20/01/2014–M6.0 and 03/02/2014–M6.1) branches. Their aftershock activity along with the continuous microseismicity and some bursts of seismicity comprising moderate earthquakes, provided the data set proper for detailing seismicity characteristics in the area.</p><p>We investigate the identification of repeating earthquakes (repeaters), which are earthquakes with highly similar waveforms caused by rupture of the same fault area, through different clustering approaches, aiming to explore strategies for the discrimination of repeaters in an accurately located dataset. We compiled a catalog of ~15600 manually picked earthquakes in the period 09/2016 – 01/2020. Relocation with the Double Difference method, using cross–correlation differential times, resulted in highly accurate locations with spatial errors ranging from a few tens to a few hundreds of meters.</p><p>The establishment of groups of repeaters (multiplets) is discussed based on several approaches. We identify multiplets by grouping event pairs that contain a common event, which is a widely used method, against the application of a density-based clustering algorithm, known as DBSCAN. In DBSCAN events are grouped into multiplets based on their similarity (cross-correlation coefficient), information which is provided through a distance matrix of all event pairs whose elements correspond to zero when their cross-correlation coefficient is equal to one and so forth. A multiplet is created when an event is directly connected with at least  events, i.e. their distance is within the similarity upper cutoff, ε. We discuss differences between the two approaches and proper parameter setting for the DBSCAN algorithm for multiplet grouping and we explore geodynamic implications of the classified clusters.</p><p><strong>Acknowledgments</strong></p><p>This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Kinematic properties, active deformation and stochastic modelling of seismogenesis at the Kefalonia - Lefkada transform zone” (MIS-5047845).</p>

Extreme value statistics of interval maximum amplitudes due to aftershocks and its application for early forecast

<p>Waveforms from many aftershocks occurring immediately after a large earthquake tend to overlap in a seismogram, which makes it difficult to pick their P- and S-wave phases. Accordingly, to determine hypocenter and magnitude of the aftershocks becomes difficult and thereby causes deterioration of earthquake catalog. Using such deteriorated catalog may cause misevaluation of ongoing aftershock activity. Since aftershock activity is usually most intense in the early period after a large earthquake, requirement of early aftershock forecast and deterioration of the aftershock catalog are impatient.</p><p>Several methods for aftershock forecast, using deteriorated automatic earthquake catalog (Omi et al., 2016, 2019) or continuous seismic envelopes (Lippiello et al., 2016), have been proposed to overcome such a situation. In this study, I propose another method that evaluates excess probability of maximum amplitude (EPMA) due to aftershocks using a continuous seismogram. The proposed method is based on the extreme value statistics, which provides probability distribution of maximum amplitudes within constant time intervals. From the Gutenberg-Richter and the Omori-Utsu laws and a conventional ground motion prediction equation (GMPE), I derived this interval maximum amplitude (IMA) follows the Frechet distribution (or type Ⅱ extreme-value distribution). Using the Monte-Carlo based approach, I certified that this distribution is well applicable to IMAs and available for forecasting maximum amplitudes even if many seismograms are overlapped.</p><p>Applying the Frechet distribution to the first 3 hour-long seismograms of the 2008 Iwate-Miyagi Nairiku earthquake (M<sub>W</sub> 6.9), Japan, I computed the EPMAs for 4 days at 4 stations. The maximum amplitudes due to experienced aftershocks proceeded following mostly within the 10 % to 90 % EPMA curves. This performance may be acceptable for a practical use.</p><p>Differently from the catalog-based method, the proposed method is almost unaffected by overlap of seismograms even in early lapse times. Since it is based on a single station processing, even seismic “network” is not required, and can be easily deployed at locations of poor seismic network coverage. So far, this method is correctly applicable for typical mainshock-aftershock (Omori-Utsu-like) sequence only. However, potentially, it could be extended to multiple sequences including secondary aftershocks and remotely triggered earthquakes.</p>

Crustal Fault Connectivity of the Mw 7.8 2016 Kaikōura Earthquake Constrained by Aftershock Relocations

©2019. American Geophysical Union. All Rights Reserved. The 14 November 2016 Mw7.8 Kaikōura earthquake in the northern South Island, New Zealand, involved highly complex, multifault rupture. We combine data from a temporary network and the permanent national seismograph network to repick and relocate ~2,700 aftershocks of M≥3 that occurred between 14 November 2016 and 13 May 2017. Automatic phase-picking is carried out using REST, a newly developed hybrid method whose pick quality is assessed by comparing automatic picks for a subset of 138 events with analysts' picks. Aftershock hypocenters computed from high-quality REST picks and a 3-D velocity model cluster almost exclusively in the shallow crust of the upper plate and reveal linkages at depth between surface-rupturing fault segments. Only eight aftershocks are relocated on a deeper structure positioned between patches of geodetically detected afterslip. This indicates that afterslip has not triggered significant earthquake activity on the subduction interface during the period of aftershock activity analyzed.

Crustal Fault Connectivity of the Mw 7.8 2016 Kaikōura Earthquake Constrained by Aftershock Relocations

©2019. American Geophysical Union. All Rights Reserved. The 14 November 2016 Mw7.8 Kaikōura earthquake in the northern South Island, New Zealand, involved highly complex, multifault rupture. We combine data from a temporary network and the permanent national seismograph network to repick and relocate ~2,700 aftershocks of M≥3 that occurred between 14 November 2016 and 13 May 2017. Automatic phase-picking is carried out using REST, a newly developed hybrid method whose pick quality is assessed by comparing automatic picks for a subset of 138 events with analysts' picks. Aftershock hypocenters computed from high-quality REST picks and a 3-D velocity model cluster almost exclusively in the shallow crust of the upper plate and reveal linkages at depth between surface-rupturing fault segments. Only eight aftershocks are relocated on a deeper structure positioned between patches of geodetically detected afterslip. This indicates that afterslip has not triggered significant earthquake activity on the subduction interface during the period of aftershock activity analyzed.

Seismic rate variations prior to the 2010 Maule, Chile MW 8.8 giant megathrust earthquake

The MW 8.8 Maule earthquake is the largest well-recorded megathrust earthquake reported in South America. It is known to have had very few foreshocks due to its locking degree, and a strong aftershock activity. We analyze seismic activity in the area of the 27 February 2010, MW 8.8 Maule earthquake at different time scales from 2000 to 2019. We differentiate the seismicity located inside the coseismic rupture zone of the main shock from that located in the areas surrounding the rupture zone. Using an original spatial and temporal method of seismic comparison, we find that after a period of seismic activity, the rupture zone at the plate interface experienced a long-term seismic quiescence before the main shock. Furthermore, a few days before the main shock, a set of seismic bursts of foreshocks located within the highest coseismic displacement area is observed. We show that after the main shock, the seismic rate decelerates during a period of 3 years, until reaching its initial interseismic value. We conclude that this megathrust earthquake is the consequence of various preparation stages increasing the locking degree at the plate interface and following an irregular pattern of seismic activity at large and short time scales.