Coulomb stress changes due to main earthquakes in Southeast Iran during 1981 to 2011

Asayesh, Behnam Maleki; Hamzeloo, H; Zafarani, Hamid

doi:10.1007/s10950-018-9797-y

Cited by 5 publications

(4 citation statements)

References 43 publications

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“…However, it is not the only forcing factor, because otherwise earthquakes will happen in a well-known periodically way. Multiple studies have demonstrated that the rupture of moderate earthquakes can modify the stress state on the nearby fault system, which may promote or inhibit the occurrence of an earthquake (Asayesh et al, 2019;Ishibe et al, 2015;King et al, 1994;Ma et al, 2005;Wang et al, 2017). Our study has confirmed that nonnegligible stress triggering effects with absolute values of calculated ΔCFSs are larger than 0.1 bar on the large earthquakes or nearby active faults from preceding earthquake ruptures in central Taiwan.…”

Section: Other Earthquake Triggering Mechanismssupporting

confidence: 77%

“…In our study, we found significant Coulomb stress increase on the rupture planes of the 1941 Chungpu, 1998 Rueyli, and 1999 Chi-Chi earthquakes, which may also indicate strong influence on rupture propagation of large mainshocks due to preceding earthquakes. In another case, Asayesh et al (2019) proved that preceding earthquakes for 30 years significantly affected the rupture of the subsequent large mainshocks in the 10.1029/2019JB019010…”

Section: Comparison To Other Regionsmentioning

confidence: 96%

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Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017

Wdowinski

Hsu

et al. 2020

JGR Solid Earth

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Though large efforts have been made in studying earthquake generation processes, earthquake triggering in central Taiwan is still not well understood. The occurrence of 14 mainshocks with ML≥ 6.0 from 1900 to 2017 and the presence of eight active fault systems provide excellent data sets for studying earthquake interaction in central Taiwan. We examined the coseismic Coulomb stress changes (ΔCFSs) due to mainshocks in the sequence and other surrounding earthquakes comprising 3 smaller magnitude mainshocks with 5.5 ≤ML≤ 6.0 and 25 aftershocks with ML≥ 5.5. When considering only triggering effects from mainshocks in the sequence, the compounded ΔCFSs are significant for all 13 mainshocks with 8 being promoted (ΔCFS > 0.1 bar) and 5 being inhibited (ΔCFS < −0.1 bar). After adding effects from other surrounding earthquakes, we found that five mainshocks were promoted and seven were inhibited. Yet it is questionable whether the 2016 mainshock was promoted, because the calculated uncertainties at the hypocenter might reduce ΔCFS below the 0.1 bar triggering threshold. In addition, significant positive ΔCFSs (>2 bars) on the Chukou, Chaochou, and Chishan faults and flat decollement of central Taiwan suggest failure promotion on those active faults. Contrarily, significant negative ΔCFSs (<−0.2 bar) on the Changhua, Shungtung, Chelungpu, and Hsinhua faults suggest that ruptures on those faults might be inhibited. We also conducted sensitivity studies indicating uncertainty level of 33–38% of the calculated ΔCFSs. Our findings indicate that preceding earthquakes have affected nucleation and rupture propagation of large earthquakes in central Taiwan during the past 120 years.

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Section: Other Earthquake Triggering Mechanismssupporting

confidence: 77%

Section: Comparison To Other Regionsmentioning

confidence: 96%

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017

Wdowinski

Hsu

et al. 2020

JGR Solid Earth

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“…Contemporary research about forecasting earthquakes follows numerous approaches, including those based purely on a statistical analysis of the earthquake catalogs and physics-based methods (e.g. Helmstetter et al 2007;Morales-Esteban et al 2010;Martínez-Álvarez et al 2013;Asim et al 2018;Maleki Asayesh et al 2019;Mancini et al 2019;Ahmad et al 2019;Tareen et al 2019;Tariq et al 2019;Asayesh et al 2020;Mignan & Broccardo 2020;Rhoades et al 2020;Sharma et al 2020;Asayesh et al 2022;Ebrahimian et al 2022, etc. ).…”

Section: Introductionmentioning

confidence: 99%

Statistical power of spatial earthquake forecast tests

Asim

Hainzl

Schorlemmer

et al. 2023

Geophysical Journal International

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Summary The Collaboratory for the Study of Earthquake Predictability (CSEP) is an international effort to evaluate earthquake forecast models prospectively. In CSEP, one way to express earthquake forecasts is through a grid-based format: the expected number of earthquake occurrences within 0.1○ × 0.1○ spatial cells. The spatial distribution of seismicity is thereby evaluated using the Spatial test (S-test). The high-resolution grid combined with sparse and inhomogeneous earthquake distributions leads to a huge number of cells causing disparity in the number of cells and the number of earthquakes to evaluate the forecasts, thereby affecting the statistical power of the S-test. In order to explore this issue, we conducted a global earthquake forecast experiment, in which we computed the power of the S-test to reject a spatially non-informative uniform forecast model. The S-test loses its power to reject the non-informative model when the spatial resolution is so high that every earthquake of the observed catalog tends to get a separate cell. Upon analyzing the statistical power of the S-test, we found, as expected, that the statistical power of the S-test depends upon the number of earthquakes available for testing, e. g. with the conventional high-resolution grid for the global region, we would need more than 32000 earthquakes in the observed catalog for powerful testing, which would require approximately 300 years to record M ≥ 5.95. The other factor affecting the power is more interesting and new; it is related to the spatial grid representation of the forecast model. Aggregating forecasts on multi-resolution grids can significantly increase the statistical power of the S-test. Using the recently introduced Quadtree to generate data-based multi-resolution grids, we show that the S-test reaches its maximum power in this case already for as few as 8 earthquakes in the test period. Thus we recommend for future CSEP experiments the use of Quadtree-based multi-resolution grids, where available data determine the resolution.

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“…The distribution of aftershocks is not uniform but associated with the inhomogeneous stress changes induced by the mainshock (Reasenberg and Simpson, 1992;Deng and Sykes, 1996;Meade et al, 2017). In particular, the spatial distribution of aftershocks generally correlates with positive Coulomb stress changes (King et al, 1994;Asayesh et al, 2019Asayesh et al, , 2020b. Numerous models for aftershock forecasting have already been proposed spanning the range of physicsbased models (Freed, 2005;Steacy et al, 2005;Asayesh et al, 2020a), statistical models (Ogata and Zhuang, 2006;Hainzl, 2022;Ebrahimian et al, 2022), hybrid physics-based and statistical models (Bach and Hainzl, 2012), and machine learning models (DeVries et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Towards improving the spatial testability of aftershock forecast models

Asim¹,

Asayesh²,

Hainzl³

et al. 2023

Nat. Hazards Earth Syst. Sci.

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Abstract. Aftershock forecast models are usually provided on a uniform spatial grid, and the receiver operating characteristic (ROC) curve is often employed for evaluation, drawing a binary comparison of earthquake occurrences or non-occurrence for each grid cell. However, synthetic tests show flaws in using the ROC for aftershock forecast ranking. We suggest a twofold improvement in the testing strategy. First, we propose to replace ROC with the Matthews correlation coefficient (MCC) and the F1 curve. We also suggest using a multi-resolution test grid adapted to the earthquake density. We conduct a synthetic experiment where we analyse aftershock distributions stemming from a Coulomb failure (ΔCFS) model, including stress activation and shadow regions. Using these aftershock distributions, we test the true ΔCFS model as well as a simple distance-based forecast (R), only predicting activation. The standard test cannot clearly distinguish between both forecasts, particularly in the case of some outliers. However, using both MCC-F1 instead of ROC curves and a simple radial multi-resolution grid improves the test capabilities significantly. The novel findings of this study suggest that we should have at least 8 % and 5 % cells with observed earthquakes to differentiate between a near-perfect forecast model and an informationless forecast using ROC and MCC-F1, respectively. While we cannot change the observed data, we can adjust the spatial grid using a data-driven approach to reduce the disparity between the number of earthquakes and the total number of cells. Using the recently introduced Quadtree approach to generate multi-resolution grids, we test real aftershock forecast models for Chi-Chi and Landers aftershocks following the suggested guideline. Despite the improved tests, we find that the simple R model still outperforms the ΔCFS model in both cases, indicating that the latter should not be applied without further model adjustments.

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Coulomb stress changes due to main earthquakes in Southeast Iran during 1981 to 2011

Cited by 5 publications

References 43 publications

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017

Statistical power of spatial earthquake forecast tests

Towards improving the spatial testability of aftershock forecast models

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Coulomb stress changes due to main earthquakes in Southeast Iran during 1981 to 2011

Cited by 5 publications

References 43 publications

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to ML≥ 5.5 Earthquakes From 1900 to 2017

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to ML≥ 5.5 Earthquakes From 1900 to 2017

Statistical power of spatial earthquake forecast tests

Towards improving the spatial testability of aftershock forecast models

Contact Info

Product

Resources

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Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017

Earthquake Interactions in Central Taiwan: Probing Coulomb Stress Effects Due to M_L≥ 5.5 Earthquakes From 1900 to 2017