Abstrak Studi seismisitas dan analisis potensi bahaya bencana seismik di wilayah Maluku Utara dapat dilakukan dengan menentukan parameter a-value dan b-value di wilayah tersebut. Kedua parameter mendiskripsikan level seismisitas dan akumulasi stres mekanik yang disimpan oleh batuan geologi bawah permukaan di wilayah tersebut. Secara prinsip, parameter a-value dan b-value ditentukan dari distribusi frekuensi-magnitudo gempa melalui hukum Gutenberg-Richter. Dalam penelitian ini, hukum Gutenberg-Richter diterapkan pada sumber gempa tektonik dari katalog gempa USGS (http://earthquake.usgs.gov/earthquakes/) selama 2009-2019 dengan kedalaman mencapai 551 km dan variasi magnitudo . Kedua parameter dihitung dengan metode least-squares dan maximum likelihood, di mana perbedaan signifikan a-value dan b-value menurut kedua metode tersebut merefleksikan level akurasi kedua metode tersebut. Metode maximum likelihood memberikan a-value dan b-value yang lebih akurat karena melibatkan penapisan data sebelum proses pengolahan data. Persamaan empiris Gutenberg-Richter yang diperoleh dari metode maximum likelihood adalah , di mana a = 9,73 dan b = 1,39 dengan adalah jumlah kejadian gempa dan adalah gempa dengan magnitudo lebih besar dari (batas bawah magnitudo di mana hukum Gutenberg-Richter berlaku valid). Analisis variasi spasial dan temporal b-value serta variasi spasial a-value berhasil merekonstruksi 3 kejadian gempa relatif besar antara 2009-2019. Kombinasi temuan b-value ≈ 1,4, a-value ≈ 9,7 dan a-value (annual) ≈ 8,7 dengan bantuan ZMAP6,0 menunjukkan bahwa seluruh wilayah Maluku Utara merupakan wilayah yang rentan terhadap bencana gempa dengan frekuensi gempa tinggi yang dipicu seismisitas relatif tinggi di wilayah tersebut. Temuan ini memicu peningkatan kesadaran dan kesiagaan terhadap potensi bahaya bencana gempa tektonik di Maluku Utara. Kata Kunci: seismisitas, bencana seismik, a-value, b-value, hukum Gutenberg-Richter Abstract Seismic studies and corresponding seismic hazard analysis in North Maluku can be performed using determination of a-value and b-value parameters. These parameters describe seismicity level and mechanical stress accumulated in subsurface structure in the region of interest. In principle, a-value and b-value were obtained from frequency-magnitude distribution provided by Gutenberg-Richter law. In this study, this law was generated using earthquake datasets from USGS at http://earthquake.usgs.gov/earthquakes/, where events occurred between 2009-2019 with varying magnitudes and depths to 551 km. The methods included the least-squares and maximum likelihood, where significant differences in the parameters acquired reflect levels of accuracy. The maximum likelihood method yielded accurate results for a-value and b-value due to data declustering prior to data processing. The Gutenberg-Richter law in a log-linear expression was obtained, where a = 9.73 and b = 1.39 with is the cumulative number of occurence and denotes events with magnitudes greater than (defined as the magnitude at which the lower end of the distribution starts to deviate from the Gutenberg-Richter law). Analysis of spatial and temporal variations of b-value and spatial variation of a-value successfully reconstructed 3 occurrences of large magnitudes during 2009-2019. A combined finding of b-value ≈ 1,4, a-value ≈ 9,7 dan a-value (annual) ≈ 8,7 by ZMAP6.0 found for North Maluku reveals that the whole parts of the region are vulnerable to tectonic earthquakes with high frequency owing to relatively high seismicity. This calls for increased awareness of and preparedness for possible seismic threats in North Maluku. Keywords: seismicity, seismic hazard, a-value, b-value, Gutenberg-Richter law
A back-projection technique allows seismologists to analyse rupture properties once seismic signals from a dense array of seismic networks are available. The observed waveforms are then traced back in space and time to the source region of an earthquake under investigation. In this study, the method utilised the back-projection image of the recorded high-frequency P-seismic waveforms filtered at 0.25-1.0 Hz by Multiple Signal Classification (MUSIC) processing to estimate the extent and the spread of earthquake rupture propagation of the M w 7.5 Palu event on 28 September 2018, generating a severe tsunami. This study aims to estimate rupture duration, its extent (the distance over which rupture propagates) and the corresponding speed, and rupture directivity (where most of the seismic energy propagates). The results revealed that the front of rupture propagates slightly offset southward at about 2.9 km/s over a distance of ~140 km away from the epicentre for about 49 s before slowing down at much smaller amplitudes after reaching the south end of Palu Bay. This finding is consistent with an NNW-SSE orientation of the active Palu-Koro Fault lying along the bay, suggesting that the strong ground motion is associated with the fault activities. This study has therefore substantial implications for enhanced earthquake and tsunami early warnings, helping the government and local authority build community resilience by warning people at risk from future possible earthquake and tsunami hazards.
Data declustering separates mainshocks from both foreshocks and aftershocks while a reliable estimate of completeness magnitude is a key point in seismic parameter determination. These play a role in seismicity-related work. In this preliminary study, we reported seismicity in two Indonesian provinces, namely NTB and NTT, as part of eastern Sunda Arc using the USGS catalogue during 1970-2021 based on performance of three declustering methods (Gardner and Knopoff, Reasenberg, Uhrhammer). These methods were tested along with three techniques of M c determination (MAXC, EMR, BC) provided by ZMAP to estimate minimum magnitude cut-offs, leading to an accurate completeness magnitude. After careful examination, the Reasenberg and BC techniques were proved to be suitable for characterising seismicity in the regions of interest, where M c was calculated under a linear assumption of the cumulative frequency-magnitude distribution (FMD), widely known as the Gutenberg-Richter law. The results revealed that b and a parameters are influenced by the choice of a specific declustering algorithm and calculation of M c. NTT was found to have a higher level of seismicity than NTB and seismicity rates in the southern part of both provinces were higher than those in the northern part. However, the number of strong ground motion with M w ≥ 6.5 in the northern area was larger than that in the southern, indicating the potency of Flores Back-arc Thrust for generating large earthquakes hence possible tsunamis.
This study examines a relationship between earthquake size and maximum tsunami amplitude using large earthquakes of M_w> 7.5 that led to trans-Pacific and Indonesian tsunamis. The data were sampled from tide gauges or DART surface buoys for seven Pacific tsunamis (the 2006 Kuril, Russia, 2009 New Zealand, 2011 Tohoku-oki, Japan, 2013 Solomon Island, 2010 Maule, 2014 Iquique, and 2015 Illapel) and six Indonesian tsunamis (the 2004 Indian Ocean, 2006 Pangandaran, 2007 Bengkulu, 2010 Mentawai, 2010 Simeulue, and 2012 Northern Sumatera). We found that the size better scales with M_w instead of other measures when relating to the mean maximum amplitude η. The main finding for the trans-Pacific cases was that the M_w scale is a logarithmic function of the mean amplitude, M_w = 0.77 log η + 8.84, consistent with previous work. For the Indonesian events, it was found that M_w = 1.92 log η + 10.36, reflecting different tsunami dynamics in the Pacific and Indian Oceans. The apparent difference is thus attributable to differences in both the topographical complexity and tsunami directivity in the two oceans. This is vital as the results provide insight into the nature of tsunami propagation approaching shorelines hence useful for improved tsunami early warning.
Earthquake size can be estimated using magnitude-rupture area scaling developed from modelled fault dimensions and measured moment magnitudes. In this study, a measure of a fault plane geometry was provided by rupture area A and the size scaled with moment magnitude Mw. Using global earthquakes datasets containing 90 events with varying magnitudes 4.45 ≤ Mw ≤ 9.20 during years of 1960-2015, we classified the data into separate strike-slip, dip-slip (normal and reverse) and subduction-zone earthquakes. The study aims to search for reliable scaling used for magnitude prediction of earthquakes around the globe for each type of source mechanism. We found from the Mw−A scaling proposed in this study that the magnitude for subduction events was likely to saturate to a maximum value possible Mw ≈ 9.3 at rupture areas much larger than those for strike-slips and dip-slips. This suggests that rocks in the subduction-zone are able to accumulate high stress, implying large seismic energy release via strong ground motion when an earthquake occurs at the plate boundary. Taking into account cases under consideration that included intraplate-fault and subduction processes covering a wide range of magnitudes from moderate to large sizes, the results are relevant to Indonesian tectonic settings, where active crustal faults have been recently found throughout the country and in particular a future megathrust subduction-zone earthquake of Mw ~ 9.0 is possible to occur off the south coasts of Java Island, the most densely populated island in Indonesia. These potential seismic threats call for increasing awareness of disaster preparedness, particularly for local community in regions with a high level of vulnerability to tsunami and earthquake disasters. Therefore, a reliable earthquake early warning is of primary importance, which is best integrated into an existing tsunami early warning for maximum security from future seismic hazards.
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