The 12 September 2016 Gyeongju earthquakes: 2. Temporary seismic network for monitoring aftershocks

Kim, Kwanghee; Kang, Taeuk; Rhie, Junkee; Kim, Young‐Hee; Park, Yongcheol; Kang, Su Young; Han, Min; Kim, Jeongmu; Park, Jechan; Kim, Minook; Kong, ChangHwan; Heo, Dabeen; Lee, Heekyoung; Park, Euna; Park, Hyejin; Lee, Sang-Jun; Cho, Sungwon; Woo, Jeong-Ung; Lee, Sang‐Hyun; Kim, Juhwan

doi:10.1007/s12303-016-0034-9

Cited by 49 publications

(14 citation statements)

References 3 publications

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“…However, the strike angles inferred from the aftershock seismicity and the focal mechanism solution of the main shock are not consistent with that of the surface trace (Hong et al, ; K.‐H. Kim et al, ; Y. Kim et al, ; Y. Kim et al, ) (Figure b). Kim et al () suggested that the centroid location relative to the hypocenter location implies the rupture propagating SSW‐ward for the main shock event.…”

Section: Introductionmentioning

confidence: 86%

Fault Rupture Model of the 2016 Gyeongju, South Korea, Earthquake and Its Implication for the Underground Fault System

Uchide

Song

2018

Geophysical Research Letters

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The 2016 Gyeongju earthquake (ML 5.8) was the largest instrumentally recorded inland event in South Korea. It occurred in the southeast of the Korean Peninsula and was preceded by a large ML 5.1 foreshock. The aftershock seismicity data indicate that these earthquakes occurred on two closely collocated parallel faults that are oblique to the surface trace of the Yangsan fault. We investigate the rupture properties of these earthquakes using finite‐fault slip inversion analyses. The obtained models indicate that the ruptures propagated NNE‐ward and SSW‐ward for the main shock and the large foreshock, respectively. This indicates that these earthquakes occurred on right‐step faults and were initiated around a fault jog. The stress drops were up to 62 and 43 MPa for the main shock and the largest foreshock, respectively. These high stress drops imply high strength excess, which may be overcome by the stress concentration around the fault jog.

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Section: Introductionmentioning

confidence: 86%

Fault Rupture Model of the 2016 Gyeongju, South Korea, Earthquake and Its Implication for the Underground Fault System

Uchide

Song

2018

Geophysical Research Letters

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“…Peak ground acceleration (PGA) is the degree to which the ground shakes at the Earth's surface [10]; it is generally the most important indicator for evaluating seismic vulnerability because it is related to the amount of fault activity [35]. In this study, raw data measured at each National Weather Services observatory in South Korea were converted to acceleration data and interpolated throughout Gyeongju [8,9]. We also used distance data from each fault to evaluate how the degree of damage changes with the structure of the fault plane.…”

Section: Physical Indicatorsmentioning

confidence: 99%

“…A magnitude 5.8 earthquake occurred in Gyeongju, South Korea, at 20:32:54 on September 12, 2016; this earthquake was preceded by a 5.1 foreshock, followed by many aftershocks, the largest of which (4.5) occurred at 11:33:58 on September 19, 2016 [8,9]. The M L 5.8 Gyeongju Earthquake was recorded as the largest earthquake since South Korea began measuring earthquakes in 1978 [8,9]. Tremors from this earthquake were detected in most parts of the country; although no surface ruptures occurred, 23 people were injured and 5368 properties were destroyed [9,10].…”

Section: Introductionmentioning

confidence: 99%

Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

et al. 2019

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In this study, we performed seismic vulnerability assessment and mapping of the ML5.8 Gyeongju Earthquake in Gyeongju, South Korea, as a case study. We applied logistic regression (LR) and four kernel models based on the support vector machine (SVM) learning method to derive suitable models for assessing seismic vulnerabilities; the results of each model were then mapped and evaluated. Dependent variables were quantified using buildings damaged in the 9.12 Gyeongju Earthquake, and independent variables were constructed and used as spatial databases by selecting 15 sub-indicators related to earthquakes. Success and prediction rates were calculated using receiver operating characteristic (ROC) curves. The success rates of the models (LR, SVM models based on linear, polynomial, radial basis function, and sigmoid kernels) were 0.652, 0.649, 0.842, 0.998, and 0.630, respectively, and the prediction rates were 0.714, 0.651, 0.804, 0.919, and 0.629, respectively. Among the five models, RBF-SVM showed the highest performance. Seismic vulnerability maps were created for each of the five models and were graded as safe, low, moderate, high, or very high. Finally, we examined the distribution of building classes among the 23 administrative districts of Gyeongju. The common vulnerable regions among all five maps were Jungbu-dong and Hwangnam-dong, and the common safe region among all five maps was Gangdong-myeon.

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“…Hereafter, for convenience, we refer to the three events of M L 5.1, M L 5.8 and M L 4.5 as E1, E2 (the main shock) and E3, respectively. From the distribution of the hypocentres and inverted moment tensors of the three events, it has been demonstrated that these earthquakes occurred on a deep-seated fault system at a depth range of 10-18 km (Kim et al 2016a;Hong et al 2017;Son et al 2017;Kim et al 2017a,b;Lee et al 2018). In particular, Son et al (2017) delineated two distinct parallel dextral faults striking to the NNE-SSW direction from relocated aftershocks, and Uchide & Song (2018) observed that the inverted finite fault slips of E1 and E2 propagated towards SSW and NNE directions, respectively.…”

Section: Introductionmentioning

confidence: 99%

The 2016 Gyeongju earthquake sequence revisited: aftershock interactions within a complex fault system

Woo

Rhie

Kim

et al. 2019

Geophysical Journal International

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, a moderate earthquake (M L 5.8) occurred in Gyeongju, South Korea, located hundreds of kilometres away from the nearest plate boundaries. The earthquake, the largest instrumentally recorded event in South Korea, occurred in a sequence of thousands of earthquakes, including a M L 5.1 event 50 min before the main quake and a M L 4.5 event a week later. As a case study, we analyse the source parameters of the 2016 Gyeongju earthquake sequence: precise relocations, fault structures, focal mechanisms, stress tensor analysis and Coulomb stress changes. To determine high-resolution hypocentres and focal mechanisms, we employ our temporary seismic network for aftershock monitoring as well as regional permanent seismic networks. The spatio-temporal distribution of events and inverted moment tensors indicate that the M L 5.1 event and the M L 5.8 event occurred on two parallel dextral faults striking NNE-SSW at a depth of 11-16 km, and the M L 4.5 event occurred on their conjugate fault with sinistral displacements. Seismicity on the fault for the M L 5.1 event abruptly decreased as soon as the M L 5.8 event occurred. This is not solely explained by the Coulomb stress change and requires more complex processes to explain it. The tectonic stress field obtained from inverted focal mechanisms suggests that the heterogeneity between the intermediate and minimum principal stresses exists along the NNE-SSW and vertical directions. The Coulomb stress changes imparted from the M L 5.1 event and the M L 5.8 event are matched with the off-fault seismicity, including that from the M L 4.5 event. Multifaceted observations, such as Coulomb stress interactions between parallel or conjugate faults and the heterogeneity of the tectonic stress field in the aftershock area, may reflect the reactivation processes of a complex fault system. This study offers a distinctive case study to understand the general characteristics of intraplate earthquakes in multifault systems.

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The 12 September 2016 Gyeongju earthquakes: 2. Temporary seismic network for monitoring aftershocks

Cited by 49 publications

References 3 publications

Fault Rupture Model of the 2016 Gyeongju, South Korea, Earthquake and Its Implication for the Underground Fault System

Fault Rupture Model of the 2016 Gyeongju, South Korea, Earthquake and Its Implication for the Underground Fault System

Performance of Logistic Regression and Support Vector Machines for Seismic Vulnerability Assessment and Mapping: A Case Study of the 12 September 2016 ML5.8 Gyeongju Earthquake, South Korea

The 2016 Gyeongju earthquake sequence revisited: aftershock interactions within a complex fault system

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