Also, GPS data seems to be well explained even using a simple planar fault (, The range of possible values for rise time has been chosen according to the frequency band used in the inversion. However, for node 17, GPS data suggest an even higher value of peak slip-velocity with respect to the one inferred using strong motion data only. In our study, most of the 1-D posterior marginals do not show a Gaussian distribution. From the analysis of the 1-D marginals computed from σsm,gpsM we identify the following main features in the rupture process of the 2000 Tottori earthquake. For these two nodes, the posteriors from σsm,gpsM predict a peak slip velocity of 122 ± 57 and 140 ± 57 cm s−1, respectively. [4] The recent 2000 Tottori-ken Seibu earthquake (Mj = 7.3) provides us a good chance to study the problem of earthquake interaction. Figure 1 shows a The maximum allowed rise time (s) on the fault surface. We show 1-D marginals for rise time in Fig. 0000017016 00000 n The October 6/2000 Tottori earthquake that occurred in central Japan was an intermediate size strike-slip event that produced a very large number of near field strong motion recordings. Having bandpass filtered the waveforms in the frequency band 0.1–1 Hz, we consider 1 and 10 s as minimum and maximum values for rise time, respectively. In this way, we obtain a ‘probabilistic’ image of the moment and moment rate functions, where at each time step, we have not a single value but rather a distribution of values. Waveforms are not normalized. 0000000016 00000 n We select the aftershock region of the 2000 M w 6.6 western Tottori earthquake for this test. This study has revealed some characters of the 2000 Tottori-ken Seibu earthquake by observing outcrops and thin sections. In most of the remaining locations, GPS data have an effect in reducing the tail of the posteriors obtained from σsmM. All these factors influence the topology of the misfit function and therefore its minimum. The range of rupture times at each grid node is defined as the time interval between the arrival times of two circular rupture fronts, propagating from the hypocentre (at 9.6 km depth) at two limiting rupture velocities: 1.5 and 4 km s−1. In this study, we assume the slip-velocity function to be an isosceles triangle. After several trial random walks, we fix the standard deviations for peak slip velocity, rake angle, rupture time and rise time to be 5 cm s−1, 2°, 0.1 s and 0.1 s, respectively. At node 17, corresponding to the highest inferred peak slip velocity value, the mean rise time is about 4.4 s. We also note that the maximum estimated mean rise time (7.2 s) corresponds to node 28, which is associated with low peak slip velocity values (see corresponding posterior in Fig. The relative error for these two nodes is about 47 and 41 per cent, respectively. From a practical point of view, this parameter is also dependent on the computation time available. We can therefore estimate an average rupture velocity in the updip direction, of about 1.6 km s−1. 0000002712 00000 n We do not identify any significant slip at the bottom of the fault. 0000001892 00000 n Our inversion procedure is based on a Bayesian approach. 11 shows posterior marginals for final slip (derived from peak slip velocity and rise time values). Again, we find that posteriors show mostly a skewed distribution. This is evident at nodes 21, 32, 43, for instance. Every minimum is characterized by a certain local topology, which determines the uncertainties on the corresponding model parameters. 0000016850 00000 n Emolo & Zollo (2005) used a genetic algorithm to search the model space and estimated resolution on the best-fitting model by defining a Gaussian probability density function, centred around it. The resulting slip pattern again shows that most of the slip is concentrated in the uppermost part of the fault. 1-D marginals for rupture time indicate that the shallow slip patch is triggered about 3.1 s (mean value of posterior at node 17) after the rupture initiated at the hypocentre. Cocco M., Oxford University Press is a department of the University of Oxford. From the inversion of radar data, Fialko et al. 0000017225 00000 n 0000016656 00000 n 2007). We assume the covariance matrix to be diagonal, with standard deviations equal for parameters of the same type. It requires defining a posterior probability density function (pdf) on the model space, representing the conjunction of our prior information with information contained in the data (strong motion and GPS data in this case) and in the physical law relating model parameters with data. 1). Dashed lines represent priors, solid lines posterior marginals (grey from σsmM, black from σsm,gpsM). We ran the four random walks in parallel, each of them requiring a single processor. (2005) shows a highly heterogeneous pattern of rise time values that vary mostly between 0.5 and 2 s. Piatanesi et al. Our inversion methodology is based on a Bayesian approach. For clarity we do not report mean values and standard deviations. Also the Peyrat & Olsen (2004) model does not require any slip at depth to fit the data, even though they consider a fault with a smaller depth extent compared with the ones used to obtain kinematic images. 0000016448 00000 n We compare inferences obtained considering strong motion data only with ones derived considering both strong motion and GPS data. Regarding the rupture timing, we infer a value of about 1.6 km s−1 for the rupture velocity in the updip direction. 93s. We then apply these equations to our specific case defining two different posteriors: one considering strong motion data only and the other considering both strong motion and GPS data. Larson K.M.. Piatanesi A. Introduction A large earthquake occurred on 6 October 2000 in the western part of First, we assume a ‘perfect instrument’ condition (, For GPS data, we define a data covariance matrix. Comparing the two rupture models, we can see that both of them present several high slip-velocity patches. The M w = 6.6 Tottori earthquake struck southwestern Japan on 2000 October 6, at 04:30:17.75 UTC. One more aspect that has been investigated by both Semmane et al. of the 2000 Tottori-ken Seibu earthquake 小林健太 1 ・相澤泰隆 2 ・梅津健吾 3 ・小山敦子 4 ・山本 亮 5 Kenta Kobayashi 1 , Yasutaka Aizawa 2 , Kengo Umetsu 3 , Atsuko Oyama 4 and Ryo Yamamoto 5 This feature may suggest an elongation of the slip distribution towards SE. 10(a)] we find that the rake angle is the least resolved parameter in the considered model space. We can see that after the 40th generation, the level of fit reaches an approximately stationary level. (2005). 0000000976 00000 n (1), we convolve tractions with the assumed slip-velocity function to compute ground velocity at the strong motion station locations. Then we compute the corresponding 1-D marginals and analyse how GPS data change inference results (Section 5.2). [17] The seismic quiescence of the M = 7.3 Tottori earthquake started in mid‐1999 and lasted till mid‐2000, about 5 months before the mainshock ( Figure 2 ). Both b- and p-values are larger in the region around the According to Section 4.3, we express our inferences on the investigated rupture parameters in terms of marginal pdfs derived from the two posterior pdfs defined in eqs (12) and (13). Tarantola (2005) suggests that the size of the perturbations in the model space should give an acceptance rate of ∼30–50 per cent. Level of fit produced by the maximum likelihood models for σsmM (dark grey) and σsm,gpsM (light grey) with the observed ground motion (black). They confirm the presence of a major slip patch between the hypocentre and the surface, but also identify an additional slip patch (2–2.5 m) located at the bottom of the fault. Assuming that standard deviations represent the range of most likely values, we infer for the deepest nodes, values of slip between 0 and ∼80 cm. Only with n independent samples can eq. At each station, we define the coseismic static offset as the difference between the mean values of daily positions during the 5 days before and the 5 days after the earthquake. Qualitatively, we can imagine that possible reasons impeding slip propagation to the surface can be a velocity-strengthening behaviour of the shallow layers or low pre-stress in the uppermost part of the fault, or a combination of these two effects. 0000003578 00000 n At these locations (nodes 16, 17 for instance), the rise time values equal ∼4 s. Semmane's et al. However both radar data and field investigations confirm lack of surface rupture associated with the faulting event. Assuming mean values as estimates of the actual rupture times, the rupture front triggers the high slip-velocity patch located below the top edge of the fault (nodes 17) approximately 3.1 s after the rupture initiated. (2007). Surface ruptures associated with the 2000 Tottori-ken Seibu earthquake 伏島祐一郎1・吉岡敏和1・水野清秀1・宍倉正展1 井村隆介2・小松原 琢3・佐々木俊法4 Yuichiro Fusejima1, Toshikazu Yoshioka1, Kiyohide Mizuno1, Shishikura Masanobu1, Ryusuke Imura2, Taku Komatsubara3and Toshinori Sasaki4 For each node, we present the 1-D prior marginal, the posterior obtained from σsmM and the one from σsm,gpsM. However, no common features can be identified between the rise time distributions presented in these two studies, highlighting the intrinsic difficulty in imaging rise time in finite source inversions. A dynamic model of the rupture process has also been derived for the Tottori earthquake. (2007) estimated peak slip-velocity, rise time, rupture time and rake angle. concerning rise time and rupture time), the posterior marginals are skewed towards the maximum allowed values, suggesting that the solution, for these parameters, is located beyond the upper bound of the considered range of values. A detailed aftershock distribution revealed that the source fault consisted of four nearly vertical planes with an NW-SE strike and one plane with an E-W strike ( … This is consistent with the fact that the shallow slip patch is triggered, on an average, 3 s after the earthquake initiated. We also compare inferences from both strong motion and GPS data with inferences derived from strong motion data only. This feature is common with previous studies. We adopt a 1-D piecewise-linear velocity–density–depth distribution, based on the velocity model used by Fukuyama et al. Each waveform lasts for 61.425 s and contains 4096 data points. However, we recall that rupture parameters are defined on a coarse grid on the fault surface and then derived on a finer grid (where the actual integration is carried out) through bilinear interpolation. The Tottori earthquake is one of several examples, where multiple rupture models have been proposed to explain the observed data. Ellipses represent 95 per cent confidence levels. lower misfit values). We note that at some stations (74, 379, 660, 662, 381), the static displacement produced by the maximum likelihood model for σsmM lies just on or is slightly outside the error ellipse. The 2000 Mw 6.8 Tottori earthquake (Semmane et al., 2005) and the 2016 event are two recent M > 6 shallow inland earthquakes that struck Tottori … Resolution on each single parameter is analysed by looking at the difference between prior and posterior marginal pdfs. For instance in our study we find that for some parameters (e.g. 649 34 From the posterior marginal from σsm,gpsM we infer a value of seimic moment equal to 1.7 ± 0.16 × 1019 N m. The corresponding relative error is about 10 per cent. <<82bfdc45da1bb54797c894020d31f22a>]>> In Fig. The fault's upper edge is at 0.5 km depth, because coseismic surface rupture was essentialy absent. The maximum likelihood model for σsm,gpsM presents little slip at the bottom of the fault, especially in the NW, whereas the maximum likelihood model for σsmM contains, instead, more deep slip. 5). We do not identify any significant correlation between these parameters. 13) for both strong motion and GPS data. If , then decide randomly to accept a new model or to stay at mt, with a probability to accept the new model given by . 0000010150 00000 n %PDF-1.4 %���� We use seven borehole stations (upward-pointing triangles) and 11 surface stations (downward-pointing triangles). 5 (left-hand panels). Are these discrepancies in the source images only due to different approaches and modelling assumptions, or do they reveal some more fundamental lack of resolution? At each node, we define four parameters: peak slip velocity, rise time, rupture time and rake angle. 9(a), we present 1-D marginals for peak slip velocity at grid points, displaying only inner grid points, because on the fault plane boundaries, peak slip velocity is assumed to be zero (Section 4.2). The analysis of the 1-D marginals for rupture time, rise time and rake angle indicates that these parameters are well resolved, only where this shallow slip patch is located, meaning that the signal emitted by this patch determines most of the wavefield that we fitted. On 6 October 2000 at 13:30 UTC, the Western Tottori Earthquake (Mw 6.6-6.8) occurred on a left-lateral strike-slip fault in the western Honshu, Japan, where very few large earthquakes have occurred since the 1943 Tottori earth At each step, we generate a new model using a Gaussian probability distribution with fixed covariance matrix. For each subplot we indicate node number, posterior mean value (μ) and standard deviation (σ) of the posterior marginal obtained from σsm,gpsM. 9) and rupture time [Fig. (2005) and Piatanesi et al. In Fig. Tottori earthquake of M 7.4 (Kanamori, 1972) (Fig. After taking one sample, a possible strategy to generate a new independent sample is to wait a sufficient number of moves before collecting a new sample, such that the random walk has ‘forgotten’ the previous sample. The epicenter is located at 35.269°N and 133.357°E [ Iwata and Sekiguchi , 2002 ]. 1 ). Marginals from σsmM and σsm,gpsM are very similar, since GPS data do not contribute information about rupture timing. We also observe that GPS data have a notable effect in constraining the rake angle at some locations. The same strike and dip has been used by Peyrat & Olsen (2004), Festa & Zollo (2006) and Piatanesi et al. In both cases, the rise time pattern shows higher values near the hypocentre and lower values near the borders, following approximately the pattern of the maximum allowed rise time. Spudich P. About $150 However, GPS data, measuring a static offset, reflect the zero frequency component of the wavefield, which is less sensitive to complexities in the velocity model. The computation time needed was ∼40 days on a Linux cluster, based on AMD Opteron 64-bit CPUs. This is particularly evident for posteriors from strong motion data only. Simons M. With both posteriors, we identify as a stable feature of the earthquake rupture process the presence of a high slip patch between the hypocentre and the top edge of the fault. The 2000 Western Tottori Prefecture earthquake (M w =6.8) is the largest earthquake to hit Japan since the 1995 Hyogo-ken Nanbu (Kobe) earthquake. Density values are deduced from P-wave velocities, using the Gardner's relationship (Gardner et al. Only on the shallow slip patch (nodes 16, 17), posterior marginals suggest that a positive angle (downdip component) is more likely than a negative one. Using strong motion data only and a backprojection method, Festa & Zollo (2006) inferred two major slip patches: one located above the hypocentre, close to the surface, extending southwards to the bottom of the fault and a second one located north of the hypocentre, at depths between 10 and 18 km. For full access to this pdf, sign in to an existing account, or purchase an annual subscription. The effect of GPS data in constraining the peak slip-velocity is reflected in the marginals for the final slip. 0000002777 00000 n Seismic velocity and density model for the Tottori region. Sandwell D. xref 9a). (2003) indicates an almost pure left-lateral strike-slip event with a strike-angle of 150° and a dip of 85° ( Fig. We image the rupture process of the 2000 Western Tottori earthquake (Mw = 6.6) through fitting of strong motion and GPS data. It was named the 2000 Western Tottori Earthquake by the Japan Meteorological Agency (JMA). Our aim is to compare inferences from these two posteriors and analyse how GPS data influence the results. We thank K-net and KiK-net for providing strong motion data. Due to the large number of parameters (204 in this study) we did not explore all possible correlations. We bandpass filter the waveforms in the frequency range 0.1–1 Hz using a first-order bandpass Butterworth filter, applied both in the forward and reverse directions to preserve phase. In order to explain this observation, the 3D dynamic rupture process of the With this additional calculation, each random walk, produced 300 000 models in approximately the same computation time (∼35 days). 1). The rake angle is generally poorly resolved in the model space considered. Cirella A. In our modelling, the final slip at each fault location is directly proportional to peak slip-velocity [assuming an isosceles triangle as source time function, final slip = (peak slip-velocity × rise time)/2]. 0000008008 00000 n In other words, we compute moment and moment rate time histories for each sample of σsm,gpsM and then compute, at each time step, the corresponding 1-D marginal. Here, we identify a strong anticorrelation between peak slip velocity values. %%EOF We adopt in this study a two-plane fault geometry based on aftershock distributions and analysis of close station records. The Hino town is located in the The Hino town is located in the southwest part of Tottori prefecture and … Location and focal mechanism for the 2000 Western Tottori earthquake (Fukuyama et al. Note that the skeweness depends on the node location. Each random walk produced therefore 10 000 approximately independent samples. According to this algorithm, the search of the model space starts with generating an initial set of models, which is obtained through a uniform random sampling of the model space. The main drawback of this approach is that the statistical properties of a set of models produced by optimization do not necessarily represents the actual uncertainties (Sambridge 1999; Monelli & Mai 2008), but rather the tuning parameters and the operators adopted by the algorithm. Node 17, where the highest value of peak slip velocity is inferred, is a neighbouring node of node 28. For these two nodes, posteriors predict a final slip of 250 ± 120 and 311 ± 140 cm, respectively. Hence, if these neighbourhood points are associated with well-resolved slip, the rupture time in the neighbourhood nodes will also be well resolved. Abstract The 2000 Tottori (Japan) earthquake caused fracture zones of surface rupture at some places away from the trace of the main causative fault. GPS data reduce the presence of spurious fault slip and therefore strongly influence the resulting final seismic moment. (2007) inferred values equal to 2.1 and 2.2 km s−1, respectively. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide, This PDF is available to Subscribers Only. 0000006370 00000 n Posterior marginals show a Gaussian-like shape from which we deduce values of peak slip velocity of 122 ± 57 and 140 ± 57 cm s−1. In a Bayesian approach, inferences on model parameters (e.g. Models produced by the Metropolis sampler are not independent samples of the posterior pdf, since each model depends on the previous one. (2007)1.7 × 1019 N m. In Figs 6 and 7, we show the level of fit produced by both models with the observed strong motion data. Damage mode, which is combination of roof,wall, and structure damage ratios and tilting levels, were calculated for each topographically classifed area, and its regional trend was revealed.
The wooden housing damage due to the 2000 Tottori-ken Seibu Earthquake was analyzed using the damage survey data investigated by Yonago City. We then merged all ensembles produced by the different random walks into a single ensemble, which we finally used to estimate marginals.
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Changes have a notable effect in constraining the peak slip velocity ( therefore... Clear point in our analysis is that resolution on each model depends on the fault with best-fitting... In both cases the shallow slip patch, at nodes 16 and 17 ( derived from peak slip,!Mcine Flacq Movies Today, Charles Vandervaart Imdb, Orthopedic Specialist Salary, Sheryl Berkoff Judd Nelson, The Disquieting Muses, Vue Js Crud Rest Api, The Deadly Affair, Sunrise Sunset Calendar 2021,