Earthquake swarms in Taiwan: A composite declustering method for detection and their spatial characteristics

Peng, Wei; Marsan, David; Chen, Kate Huihsuan; Pathier, Erwan

doi:10.1016/j.epsl.2021.117160

Cited by 14 publications

(35 citation statements)

References 49 publications

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“…A detailed comparison shows that 94 repeating earthquakes are included in swarm sequences, and 324 repeating earthquakes are located within 5 km from their closest swarm events. Such a strong spatial correlation between earthquake swarms and repeating earthquakes was also presented by Peng et al (2021), which detected earthquake swarms in Taiwan and found that 86% of repeating earthquakes were located within 5 km from the closest swarm events in southeast Taiwan. The analysis of spatiotemporal distributions of SSEs, repeating earthquakes, tremors, and earthquake swarms in western Nankai (Figures 10 and 11) shows that the deep slow and shallow fast migration modes proposed by Uchida et al (2020) are accompanied by seismic activities including not only repeating earthquakes but also earthquake swarms in some localized areas.…”

Section: Correlation Between Earthquake Swarms and Repeating Earthquakessupporting

confidence: 56%

“…Peng et al. (2021) proposed a method to detect earthquake swarms from non‐stationary background seismicity rates in Taiwan. Here we use the same method for the Nankai region.…”

Section: Methodology For Swarm Detectionmentioning

confidence: 99%

“…Peng et al. (2021) detected earthquake swarms as events with background rates higher than the 2‐year averages in Taiwan and compared the swarm distributions with repeating earthquakes.…”

Section: Introductionmentioning

confidence: 99%

“…This study aims at detecting earthquake swarms which may be related to aseismic transients in the Nankai region by following the methods in Nishikawa and Ide (2017) and Peng et al. (2021). Hence, we take the results obtained by both methods as earthquake swarms, and further merge them together to make detailed analyses.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Detection and Characterization of Earthquake Swarms in Nankai and Its Association With Slow Slip Events

2023

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Various types of slow earthquakes occur in the Nankai subduction zone, among which the slow slip events (SSEs) seem to connect the shallow and deep part of the subduction plate and further trigger seismic or aseismic transients in surrounding areas. This study uses a version of space‐time epidemic‐type aftershock sequence (ETAS) model with non‐stationary background rate to detect earthquake swarms that may be related to SSEs in the Nankai region. We detect 999 swarm sequences including 13,387 earthquakes, accounting for about 18 percent of all M ≥ 1.0 earthquakes in the selected region along the Nankai trough. The detected swarms are mostly distributed in the Hyuga‐nada, Bungo Channel, Kii Channel, and Tokai regions, forming a complementary pattern to SSEs. Nearly 70 percent of swarm events are located in western Nankai, with the southern part characterized by a higher occurrence rate, which is consistent with the smaller recurrence interval of SSEs in this region. By comparing occurrence times of swarm events to those of SSEs, we find that some SSEs are accompanied by enhanced swarm activities during their occurrence periods. In addition, the swarm rates increase to higher levels in the southern part of western Nankai during the 2003 and 2010 Bungo SSEs, indicating the high sensitivity of earthquake swarms to the migrations of slow earthquakes in this region.

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Section: Correlation Between Earthquake Swarms and Repeating Earthquakessupporting

confidence: 56%

“…Peng et al. (2021) proposed a method to detect earthquake swarms from non‐stationary background seismicity rates in Taiwan. Here we use the same method for the Nankai region.…”

Section: Methodology For Swarm Detectionmentioning

confidence: 99%

“…Peng et al. (2021) detected earthquake swarms as events with background rates higher than the 2‐year averages in Taiwan and compared the swarm distributions with repeating earthquakes.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Detection and Characterization of Earthquake Swarms in Nankai and Its Association With Slow Slip Events

2023

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“…Marsan et al [19] introduced an ETAS model with a time-dependent background component for the detection of aseismic transients. The modified ETAS model is used efficiently to reveal both main shock-aftershocks and earthquake swarms [20,21]. Finally, the Nearest-Neighbor metric proposed by Baiesi and Paczuski [22] adopts a nonparametric definition of a cluster considering the space-time-magnitude proximity among earthquakes.…”

Section: Introductionmentioning

confidence: 99%

Identification and Temporal Characteristics of Earthquake Clusters in Selected Areas in Greece

2022

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The efficiency of earthquake clustering investigation is improved as we gain access to larger datasets due to the increase of earthquake detectability. We aim to demonstrate the robustness of a new clustering method, MAP-DBSCAN, and to present a comprehensive analysis of the clustering properties in three major seismic zones of Greece during 2012–2019. A time-dependent stochastic point model, the Markovian Arrival Process (MAP), is implemented for the detection of change-points in the seismicity rate and subsequently, a density-based clustering algorithm, DBSCAN, is used for grouping the events into spatiotemporal clusters. The two-step clustering procedure, MAP-DBSCAN, is compared with other existing methods (Gardner-Knopoff, Reasenberg, Nearest-Neighbor) on a simulated earthquake catalog and is proven highly competitive as in most cases outperforms the tested algorithms. Next, the earthquake clusters in the three areas are detected and the regional variability of their productivity rates is investigated based on the generic estimates of the Epidemic Type Aftershock Sequence (ETAS) model. The seismicity in the seismic zone of Corinth Gulf is characterized by low aftershock productivity and high background rates, indicating the dominance of swarm activity, whereas in Central Ionian Islands seismic zone where main shock-aftershock sequences dominate, the aftershock productivity rates are higher. The productivity in the seismic zone of North Aegean Sea vary significantly among clusters probably due to the co-existence of swarm activity and aftershock sequences. We believe that incorporating regional variations of the productivity into forecasting models, such as the ETAS model, it might improve operational earthquake forecasting.

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Deep long-period earthquakes at Akutan Volcano are more directly related to magmatic processes than volcano-tectonic earthquakes

Song

Tan

Roman

2022

Preprint

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Both volcano-tectonic (VTs) and deep long-period earthquakes (DLPs) have been documented at Akutan Volcano, Alaska and may reflect different active processes. In this study, we perform high-resolution earthquake detection, classification, and relocation using seismic data from 2005-2017 to investigate their relationship with underlying magmatic processes. We find that the 2,787 VTs and 787 DLPs are concentrated above and below the shallow magma reservoir respectively. The DLPs' low-frequency content is likely a source instead of path effect considering its uniformity across stations. Both VT and DLP swarms occur preferentially during inflation episodes with no clear migration. However, the largest VT swarms occur during non-inflating periods, and only VT swarms contain repeating events. Therefore, we conclude that the VTs represent fault rupture triggered by magma/fluid movement or larger earthquakes, while the DLPs are directly related to unsteady magma movement through a complex pathway or represent slow fault ruptures triggered by magma movement.

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Earthquake swarms in Taiwan: A composite declustering method for detection and their spatial characteristics

Cited by 14 publications

References 49 publications

Detection and Characterization of Earthquake Swarms in Nankai and Its Association With Slow Slip Events

Detection and Characterization of Earthquake Swarms in Nankai and Its Association With Slow Slip Events

Identification and Temporal Characteristics of Earthquake Clusters in Selected Areas in Greece

Deep long-period earthquakes at Akutan Volcano are more directly related to magmatic processes than volcano-tectonic earthquakes

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