A study of earthquake inter-occurrence times distribution models in Taiwan

Chen, Chi Hsuan; Wang, Jui Pin; Wu, Yih‐Min; Chan, Chung-Han; Chang, Chien Hsin

doi:10.1007/s11069-012-0496-7

Cited by 34 publications

(18 citation statements)

References 38 publications

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“…The Gamma distribution is an exponential family distribution with two parameters, namely shape parameter a > 0 and scale parameter s > 0. It has been found by Kagan and Knopoff (1984), Chen et al (2013), Wang et al (2012) to provide a good model for main shock inter-arrival times. The Gamma distribution probability density function is:…”

Section: Gamma Process Immigrationmentioning

confidence: 92%

Inference for ETAS models with non-Poissonian mainshock arrival times

Kolev

Ross

2018

Stat Comput

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The Hawkes process is a widely used statistical model for point processes which produce clustered event times. A specific version known as the ETAS model is used in seismology to forecast earthquake arrival times under the assumption that mainshocks follow a Poisson process, with aftershocks triggered via a parametric kernel function. However, this Poissonian assumption contradicts several aspects of seismological theory which suggest that the arrival time of mainshocks instead follows alternative renewal distributions such as the Gamma or Brownian Passage Time. We hence show how the standard ETAS/Hawkes process can be extended to allow for non-Poissonian distributions by introducing a dependence based on the underlying process' behaviour. Direct maximum likelihood estimation of the resulting models is not computationally feasible in the general case, so we also present a novel Bayesian MCMC algorithm for efficient estimation using a latent variable representation. Keywords ETAS • Stress release • Renewal process • Hawkes process • Brownian passage times • RHawkes

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Section: Gamma Process Immigrationmentioning

confidence: 92%

Inference for ETAS models with non-Poissonian mainshock arrival times

Kolev

Ross

2018

Stat Comput

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“…Although the first seismic station in Taiwan was initiated in the late 19 th century, before 1973 there were only 15 stations equipped with the Gray-Milne, Wiechert, and Omori seismographs. In this period, corresponding magnitude of completeness (M c ) was about 4.3 -4.8 (Chen et al 2013). Afterward, the Taiwan Telemetric Seismic Network (TTSN) was operated, and M c decreased dramatically to about 2.0 -3.0.…”

Section: Psha In Southern Taiwanmentioning

confidence: 99%

The 2016 Meinong earthquake to TEM PSHA2015

Lee¹,

Wang²,

Chan³

et al. 2017

Terr. Atmos. Ocean. Sci.

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On 6 February 2016 (UTC 19:57), the Meinong earthquake with Richter magnitude (M L ) 6.6 struck southern Taiwan and caused hundreds of damaged buildings, resulting in 117 casualties. We investigated the relationship between the damaged buildings and the ground motion in the forms of peak ground acceleration (PGA), peak ground velocity (PGV), pseudo-spectral acceleration (SA) at 0.3 s (SA0.3), 1.0 s (SA1.0), and shaking duration to identify which ground motion parameter most represents building damage. PGV and SA1.0 present better correlation with consequent damage. The Intensity converted from PGV presents better correlation to the damage than PGA. We disaggregated the TEM PSHA2015 hazard contribution to the Meinong earthquake damage region (Southern Taiwan) from different seismic source typologies to clarify the seismic source contributing to the hazard. The hazards contributed by the Meinong earthquake were 16, 26, and 23% for PGA, SA0.3, and SA1.0, respectively. The predicted seismic hazard source areas were 38, 61, and 75% for PGA, SA0.3, and SA1.0, respectively, for the PSHA with a return period of 475 years. This result indicates that the 2016 Meinong earthquake did partially diminish the seismic hazard potential in southern Taiwan. However, more than about 80% of the seismic hazard potential, especially the fault sources were not yet released. These values suggest that the seismic hazard potential in southern Taiwan remains high regardless of the 2016 Meinong earthquake.

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“…Extreme rainfall commonly occurs in Taiwan along both sides of the Central Range, which acts as an orographic barrier to both easterly typhoons in July–October and westerly East Asian Monsoon in May–June. Catastrophic earthquakes also may occur on both sides of tectonically active Taiwan, with higher frequency along the western proside (66 events of magnitude ≥6 in the last century, more than one every other year [ Chen et al , ]) than along the eastern retroside (13 events with magnitude 6.0–6.7 in the last century). During major events, such as the Chi‐chi earthquake in 1999 ( M w 7.6 [ Shyu et al , ]), vertical displacements up to 11 m resulted in the formation of knickpoints along rivers [ Huang and Montgomery , ].…”

Section: Exhumation and Erosion In Space And Timementioning

confidence: 99%

Partitioning sediment flux by provenance and tracing erosion patterns in Taiwan

et al. 2017

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We critically evaluate the potential and limitations of an alternative way to calculate erosion rates based on petrographic and mineralogical fingerprints of fluvial sediments coupled with gauged sediment fluxes. Our approach allows us to apportion sediment loads to different lithological units, and consequently to discriminate erosion rates in different tectonic domains within each catchment. Our provenance data on modern Taiwanese sands indicate focused erosion in the Backbone Range and Tananao Complex of the retrowedge. Lower rates are inferred for the northern part of the island characterized by tectonic extension and for the western foothills in the prowedge. The principal factor of uncertainty affecting our estimates is the inevitably inaccurate evaluation of total sediment load, because only the suspended flux was measured. Another is the assumption that suspended load and bed load are derived from the same sources in fixed proportions. Additional errors are caused by the insufficiently precise definition of lithologically similar compositional end‐members and by the temporal variability of sediment composition at the outlet of each catchment related to the spatial variability of erosional processes and triggering agents such as earthquakes, typhoons, and landslides. To evaluate the robustness of our findings, we applied a morphometric technique based on the stream‐power model. The results obtained are broadly consistent, with local discrepancies ascribed to poorly constrained assumptions and choices of scaling parameters. Our local erosion estimates are consistent with GPS uplift rates measured on a decadal timescale and generally higher than basin‐wide results inferred from cosmogenic‐nuclide and thermochronology data.

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A study of earthquake inter-occurrence times distribution models in Taiwan

Cited by 34 publications

References 38 publications

Inference for ETAS models with non-Poissonian mainshock arrival times

Inference for ETAS models with non-Poissonian mainshock arrival times

The 2016 Meinong earthquake to TEM PSHA2015

Partitioning sediment flux by provenance and tracing erosion patterns in Taiwan

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