Target Earthquakes Research Articles

Machine Learning-Based Precursor Detection Using Seismic Multi-Parameter Data

The application of certain mathematical–statistical methods can quantitatively identify and extract the abnormal characteristics from the observation data, and the comprehensive analysis of seismic multi-parameters can study and judge the risk of the tectonic regions better than a single parameter. In this study, the machine learning-based detection of seismic multi-parameters using the sliding extreme value relevancy method, based on the earthquake-corresponding relevancy spectrum, was calculated in the tectonic regions in the western Chinese mainland, and the R-value evaluation was completed. Multi-parameter data included the b value, M value (missing earthquakes), ƞ value (the relationship between seismic magnitude and frequency), D value (seismic hazard), Mf value (intensity factor), N value (earthquake frequency), and Rm value (modulation parameter). The temporal results showed that the high-value anomalies appeared before most target earthquakes during the training period. Moreover, some target earthquakes also occurred during the advantageous extrapolation period with high-value anomalies. The spatial results showed that some months before the target earthquakes, there was indeed a significant abnormal enhancement area that appeared near the epicenter, and the anomaly gradually disappeared after the earthquakes. This study demonstrated that machine learning techniques for detecting earthquake anomalies using seismic multi-parameter data were feasible.

Deterministic ground motion modeling with target earthquakes and site effects in eastern Azerbaijan

In the context of assessing seismic hazard, accurately predicting ground motion stands out as a crucial task. Achieving precision in ground motion modeling proves valuable in revealing the actual pattern, even when faced with insufficient data on soil structure, provided there is precise information about the seismic source. This study introduces a methodology for calculating local- and near-field ground motion, expressed in peak ground acceleration (PGA) and intensity values. The deterministic approach is employed, incorporating source characteristics and one-dimensional (1D) site effects. For the chosen test area, the Ismayilli-Shamakhi region on the southeastern slope of the Greater Caucasus in Azerbaijan, two seismic scenarios are investigated: the 1902 Shamakhi earthquake (magnitude M = 6.8) and the November 25, 2000 Baku-Caspian earthquake (two shocks with moment magnitude Mw = 6.08 and 6.18). Different soil types are considered to validate the proposed methodological procedures. The analysis involves the computation of peak ground acceleration motion for two scenario earthquakes: a local-field event with M = 6.8 and a near-field event with Mw = 6.5, representing the average magnitude of the 2000 Baku-Caspian earthquake. The computed peak ground acceleration values are then used to derive intensities. Notably, the 1902 Shamakhi earthquake and the 2000 Baku-Caspian earthquake exhibit similar trends on surface PGA values. The local-field scenario estimates PGA values ranging from 77 to 328 gal, corresponding to MSK-64 scale intensity levels of VII-IX. The near-field scenario, with PGA values ranging from 28 to 62 gal, aligns with MSK-64 intensity levels of VI–VII. In the final assessment, the amplification factor in the study area varies between 0.55 and 0.83. The seismic hazard level is identified as high in the southern and southeastern regions, particularly in areas with soft shallow and medium-depth soils, indicating a high potential for ground motion amplification.

Soil moisture-based global liquefaction model (SMGLM) using soil moisture active passive (SMAP) satellite data

The role of soil saturation condition on the liquefaction occurrence highlights the need for a tool to track the ground-truth soil moisture content involved in this seismic phenomenon. Soil Moisture Active Passive (SMAP) satellite estimates near-real time surface and root zone soil moisture measurements with global coverage. Typical proxies for soil saturation in liquefaction analysis include average water table depth patterns, mean annual precipitation measurements, and topographic conditions. As an alternative to these proxies, this paper incorporates satellite-based soil moisture data to enhance the understanding of the interrelation between saturation conditions and liquefaction events. Proposing a new approach for sampling non-liquefaction cases, a liquefaction/non-liquefaction database was developed in this paper based on reconnaissance reports of eleven target earthquakes. Well-known geospatial explanatory variables as well as new SMAP-based soil moisture parameters, affecting soil liquefaction, are used to develop a new soil moisture-based global liquefaction model (SMGLM), which is compared with an existing global liquefaction model. Considering the ongoing advancement of earth observing satellites, the results of this paper can build a basis for developing fully satellite-based models that could identify liquefied sites using high resolution near-real time soil moisture data.

Scaling of earthquake ground motions for tri-directional nonlinear response history analyses of reinforced concrete rectangular bridge piers

In performance-based earthquake design (PBED), both the capacity of the structure and the demand from earthquake ground shaking are required to establish the desired performance levels. A range of possible demands can be estimated through nonlinear response history analyses (NRHA), which requires a suite of earthquake ground motions appropriately scaled to the target earthquake intensity for which the structure's performance is to be evaluated. The scaling is usually done for a particular earthquake intensity measure (IM) to get the associated dispersion in the engineering demand parameter (EDP). Several scaling strategies are available for uni-directional (Uni-NRHA) and bi-directional nonlinear response history analyses (Bi-NRHA). However, for tri-directional nonlinear response history analysis (Tri-NRHA), one literature suggests using the same scale factor (SF) for the vertical component, which is estimated for the Bi-NRHA. Therefore, in this study, three well-known scaling strategies, which are usually used for Uni-NRHA, are employed with 16 different methods for application in Tri-NRHA of a reinforced concrete (RC) single-column bridge pier modelled as a single-mass three-degree-of-freedom (3DoF) system. The absolute maximum drift is taken as the EDP, and a total of 1920 Tri-NRHA of the pier are performed using two suites of 20 far-fault and 20 near-fault ground motions, which are scaled to three levels of target earthquake intensity. The sufficiency and efficiency of all the scaling methods are checked statistically under all three target intensities. The study reports the effects of (i) vertical components in calculating the SF, (ii) earthquake intensity and structural nonlinearity, and (iii) far-fault and near-fault ground motion characteristics on the dispersion of the EDP. Out of 16 scaling methods, one is found to be acceptably efficient than the others for application in Tri-NRHA under both far-fault and near-fault ground motions at all target intensities.

Observation of Ultra-Low-Frequency Wave Effects in Possible Association with the Fukushima Earthquake on 21 November 2016, and Lithosphere–Atmosphere–Ionosphere Coupling

The study presents seismogenic ULF (ultra-low-frequency) wave effects, as observed at our own new magnetic observatory at Asahi (geographic coordinates: 35.770° N, 140.695° E) in Chiba Prefecture. Our target earthquake (EQ) is a huge one offshore of Fukushima prefecture (37.353° N, 141.603° E) with a magnitude (M) of 7.4, which occurred at 20.59 h on November 21 UT, 2016. As a sampling frequency of 1 Hz was chosen for our induction magnetometer, we could detect both ULF wave effects: ULF radiation from the lithosphere, and the ULF depression effect, indicative of lower ionospheric perturbations. Observing the results of polarization analyses, we detected clear enhancements in ULF (frequency = 0.01–0.03 Hz) lithospheric radiation 14 days, 5 days, and 1 day before the EQ, and also observed a very obvious phenomenon of ULF (0.01–0.03 Hz) depression just 1 day prior to the EQ, which is regarded as the signature of lower ionospheric perturbations. These findings suggest that pre-EQ seismic activity must be present in the lithosphere, and also that the lower ionosphere was very much perturbed by the precursory effects of the Fukushima EQ. These new observational effects from our station have been compared with our previous investigations on different seismogenic topics for the same EQ, including the ULF observations at another magnetic observatory at Kakioka, belonging to the Japan Meteorological Agency (JMA), about 50 km north of our Asahi station, subionospheric VLF/LF propagation data (Japanese and Russian data), AGW (Atmospheric gravity wave) activity in the stratosphere, and satellite observation of particle precipitations. We have found that seismogenic anomalies of different parameters tend to happen just around the EQ day, but mainly before the EQ, and have found the chain-like tendency of the effects of the lithosphere, which seem to propagate upwards the lower ionosphere. Finally, we will try to gain a better understanding of the physical phenomena or mechanisms of the lithosphere–atmosphere–ionosphere coupling (LAIC) process during the EQ preparation phase.

Comparison between alarm-based and probability-based earthquake forecasting methods

SUMMARY In a recent work, we applied the every earthquake a precursor according to scale (EEPAS) probabilistic model to the pseudo-prospective forecasting of shallow earthquakes with magnitude $M\ 5.0$ in the Italian region. We compared the forecasting performance of EEPAS with that of the epidemic type aftershock sequences (ETAS) forecasting model, using the most recent consistency tests developed within the collaboratory for the study of earthquake predictability (CSEP). The application of such models for the forecasting of Italian target earthquakes seems to show peculiar characteristics for each of them. In particular, the ETAS model showed higher performance for short-term forecasting, in contrast, the EEPAS model showed higher forecasting performance for the medium/long-term. In this work, we compare the performance of EEPAS and ETAS models with that obtained by a deterministic model based on the occurrence of strong foreshocks (FORE model) using an alarm-based approach. We apply the two rate-based models (ETAS and EEPAS) estimating the best probability threshold above which we issue an alarm. The model parameters and probability thresholds for issuing the alarms are calibrated on a learning data set from 1990 to 2011 during which 27 target earthquakes have occurred within the analysis region. The pseudo-prospective forecasting performance is assessed on a validation data set from 2012 to 2021, which also comprises 27 target earthquakes. Tests to assess the forecasting capability demonstrate that, even if all models outperform a purely random method, which trivially forecast earthquake proportionally to the space–time occupied by alarms, the EEPAS model exhibits lower forecasting performance than ETAS and FORE models. In addition, the relative performance comparison of the three models demonstrates that the forecasting capability of the FORE model appears slightly better than ETAS, but the difference is not statistically significant as it remains within the uncertainty level. However, truly prospective tests are necessary to validate such results, ideally using new testing procedures allowing the analysis of alarm-based models, not yet available within the CSEP.

Strong ground motion simulations of the 2016 Kumamoto earthquakes using corrected empirical Green’s functions: methods and results for ESG6 blind prediction Steps 2 and 3 with improved parameters

This paper describes the methods and results of the strong ground motion simulations for three earthquakes from the 2016 Kumamoto earthquake sequence using corrected empirical Green’s functions. The target earthquakes were an aftershock (Mw 5.5), the largest foreshock of the sequence (Mw 6.1), and the mainshock (Mw 7.1). The corrected empirical Green’s function method was used in the simulations. This simulation method combines simple source and path factors with empirical site amplification and phase factors to generate realistic site-specific strong motions. Simulations were originally conducted to participate in blind prediction exercises in ESG6. Although the simulations performed in this study were based on the models submitted to the blind prediction committee, several modifications were made after the blind prediction exercise. First, the observed records at the target site of the blind prediction called KUMA were used to compare observed and synthetic strong ground motions. In addition, a regional spectral inversion was conducted to obtain a more appropriate Q-value and site amplification factor. Synthetic strong motions were found to explain the observed strong ground motions at KUMA and other stations. Comparisons with predictions by other methods and the sensitivity to the rupture scenario were also discussed. These results provide useful information for applying the corrected Green’s function method to strong ground motion simulations.Graphical

Centrality measure and visualization technique for multiple-parent nodes of earthquakes based on correlation-metric

In this paper, we address the problem of earthquake declustering, and propose a k-nearest neighbors approach based on the selection of multiple-parent nodes with respect to each of the given earthquakes, which can be regarded as a natural extension of the conventional correlation-metric method based on the selection of a single-parent node. Based on this approach, we develop a centrality measure that exploits link weight assigned by a logarithmic-distance scheme and a technique of individually visualizing each set of child nodes with respect to given target earthquakes. For experimental evaluation, we used an earthquake catalog covering Japan and selected 24 earthquakes that caused considerable damage or casualties. We first show that our proposed centrality measure using a logarithmic-distance scheme can rank these 24 major earthquakes higher than four link-weighting schemes (i.e., uniform, magnitude, inverse-distance, and normalized-inverse-distance weighting) and conventional single-parent selection. We then show that unlike the conventional approach to simultaneously visualizing all the events in the catalog, our proposed technique can produce a naturally interpretable classification result for these 24 major earthquakes, by individually visualizing each set of the first to k-th child nodes with different colored markers plotted in the directly interpretable spatio and temporal metrics. As a consequence, we confirm that our approach based on multiple-parent selection is vital and promising.

A 20-Year Journey of Forecasting with the “Every Earthquake a Precursor According to Scale” Model

Nearly 20 years ago, the observation that major earthquakes are generally preceded by an increase in the seismicity rate on a timescale from months to decades was embedded in the “Every Earthquake a Precursor According to Scale” (EEPAS) model. EEPAS has since been successfully applied to regional real-world and synthetic earthquake catalogues to forecast future earthquake occurrence rates with time horizons up to a few decades. When combined with aftershock models, its forecasting performance is improved for short time horizons. As a result, EEPAS has been included as the medium-term component in public earthquake forecasts in New Zealand. EEPAS has been modified to advance its forecasting performance despite data limitations. One modification is to compensate for missing precursory earthquakes. Precursory earthquakes can be missing because of the time-lag between the end of a catalogue and the time at which a forecast applies or the limited lead time from the start of the catalogue to a target earthquake. An observed space-time trade-off in precursory seismicity, which affects the EEPAS scaling parameters for area and time, also can be used to improve forecasting performance. Systematic analysis of EEPAS performance on synthetic catalogues suggests that regional variations in EEPAS parameters can be explained by regional variations in the long-term earthquake rate. Integration of all these developments is needed to meet the challenge of producing a global EEPAS model.

Blind broad-band (0–10 Hz) numerical prediction of the 3-D near field seismic response of anMW6.0 extended fault scenario: application to the nuclear site of Cadarache (France)

SUMMARYIn this paper, physics-based numerical simulation (PBS) is employed to render a broad-band (0–10 Hz) realization of the near-field seismic response of the experimental nuclear site of Cadarache, located nearby the active Middle Durance Fault (southeastern France). The sensitivity of the earthquake numerical model to geological features is investigated by comparison with geophysical measurements and past aftershock and by highlighting the amplification induced by the soft sediments below Cadarache. The blind prediction of an MW6 target earthquake is approached by synthesizing four different finite-fault scenarios. The outcome is compared to the standard ground motion prediction equations (GMPEs), unveiling a possible GMPE overestimation of the pseudospectral acceleration ordinates at short natural periods, supporting the actual need to integrate synthetic and empirical predictions when direct observations are not available.

Application of Soil Moisture Active Passive (SMAP) Satellite Data in Seismic Response Assessment

The proven relationship between soil moisture and seismic ground response highlights the need for a tool to track the Earth’s surface soil moisture before and after seismic events. This paper introduces the application of Soil Moisture Active Passive (SMAP) satellite data for global soil moisture measurement during earthquakes and consequent events. An approach is presented to study areas that experienced high level of increase in soil moisture during eleven earthquakes. Two ancillary datasets, Global Precipitation Measurement (GPM) and Global Land Data Assimilation (GLDAS), were used to isolate areas that had an earthquake-induced increase in soil moisture from those that were due to hydrological processes. SMAP-based soil moisture changes were synthesized with seismic records developed by the United States Geological Survey (USGS), mapped ground failures in reconnaissance reports, and surface changes marked by Synthetic Aperture Radar (SAR)-based damage proxy maps. In the majority of the target earthquakes, including Croatia 2020, Greece 2020, Indonesia 2018, Taiwan 2016, Ecuador 2016, and Nepal 2015, a relationship between the SMAP soil moisture estimates and seismic events was evident. For these events, the earthquake-induced soil moisture response occurred in liquefaction-prone seismic zones. The New Zealand 2016 event was the only study region for which there was a clear inconsistency between ΔSMSMAP and the seismic records. The promising relationship between soil moisture changes and ground deformations indicates that SMAP would be a useful data resource for geotechnical earthquake engineering applications and reconnaissance efforts.

How Useful Are Strain Rates for Estimating the Long-Term Spatial Distribution of Earthquakes?

Strain rates have been included in multiplicative hybrid modelling of the long-term spatial distribution of earthquakes in New Zealand (NZ) since 2017. Previous modelling has shown a strain rate model to be the most informative input to explain earthquake locations over a fitting period from 1987 to 2006 and a testing period from 2012 to 2015. In the present study, three different shear strain rate models have been included separately as covariates in NZ multiplicative hybrid models, along with other covariates based on known fault locations, their associated slip rates, and proximity to the plate interface. Although the strain rate models differ in their details, there are similarities in their contributions to the performance of hybrid models in terms of information gain per earthquake (IGPE). The inclusion of each strain rate model improves the performance of hybrid models during the previously adopted fitting and testing periods. However, the hybrid models, including strain rates, perform poorly in a reverse testing period from 1951 to 1986. Molchan error diagrams show that the correlations of the strain rate models with earthquake locations are lower over the reverse testing period than from 1987 onwards. Smoothed scatter plots of the strain rate covariates associated with target earthquakes versus time confirm the relatively low correlations before 1987. Moreover, these analyses show that other covariates of the multiplicative models, such as proximity to the plate interface and proximity to mapped faults, were better correlated with earthquake locations prior to 1987. These results suggest that strain rate models based on only a few decades of available geodetic data from a limited network of GNSS stations may not be good indicators of where earthquakes occur over a long time frame.

Application of Modified-Partial Capacity Design Method on 6- and 15-story Square Buildings with Variation in number of Elastic Columns

Modified-Partial Capacity Design (M-PCD) is proposed as one alternative of structural design methods. In M-PCD, the partial side sway mechanism where beams and some columns may develop plastic hinges. This method uses two structural models during the design process. The models are used to simulate undamaged and damaged structures when subjected to design earthquake (R=8.0) and larger target earthquake (R=1.6) respectively. In this study, 6- and 15-story square buildings with 30% and 50% elastic column are designed using M-PCD. Performances of the buildings are investigated by using non-linear time history analysis. Results show that the buildings’ performances are still unsatisfactory, especially for the 15-story buildings. However, it should be noted that the levels of earthquakes used for the analysis were larger than that used for the design. A more accurate prediction of the required strength should be developed further to improve M-PCD.

A Broadband Kinematic Source Inversion Method Considering Realistic Earth Models and Its Application to the 1992 Landers Earthquake

AbstractGenerating broadband ground motions requires fine enough scales in the source model, but small scales may lead to unacceptable computational efforts for source inversion. To resolve this challenge, a novel kinematic source inversion method is proposed in this study to map the detailed rupture process associated with broadband seismic radiation. This method addresses two key issues for imaging the rupture process of earthquakes: proper source models describing the rupture process and accurate Green’s functions. For the first issue, the rupture process of target earthquakes is modeled by a recently proposed multidimension source model, which is composed of several superimposed layers with degressive scales to generate broadband ground motions. Due to the self‐similarity of the parameters of subsource on different layers, the number of variables to be considered in the inversion procedure is comparable to that of the conventional finite‐fault source model. For the second issue, the spectral element method is used to compute the Green’s functions with high‐resolution topography and three‐dimensional (3D) velocity structures. The introduction of accurate 3D velocity structures enables to reproduce the ground motions of target earthquakes in a wide range of frequency. With the multidimension source model and accurate Green’s functions, an evolutionary many‐objective optimization algorithm is used to search for the best rupture‐process parameters. The rupture process of the 1992 Landers earthquake is mapped by the proposed inversion method, and the ground motions from the forward simulation with the inverted rupture process have an impressive agreement with the records in a wide range of frequency.

Quantifying the Sensitivity of Microearthquake Slip Inversions to Station Distribution Using a Dense Nodal Array

ABSTRACT To investigate the sensitivity of slip inversions to station distribution and choice of empirical Green’s function (EGF), we examine three microearthquakes that occurred within the high-density LArge-n Seismic Survey in Oklahoma (LASSO) nodal seismic array. The LASSO array’s dense distribution of 1825 geophones provides an exceptional level of spatial and azimuthal coverage, allowing for more accurate inversions of slip than are possible with typical station distributions. The highly accurate slip inversions, in turn, allow for the exploration of the sensitivity of slip inversions to station distribution and parameter choices. We examine the effects of these choices using three well-recorded strike-slip microearthquakes (ML 1.7, 2.3, and 2.7) using an EGF method. From this analysis and the systematic testing of varied network arrangements, we find that station distributions that have uniform coverage of azimuth and distance can retrieve the overall pattern of slip, but the estimated amplitude of slip can vary by 30% for high-slip regions due to small variations in station location. In addition, we find that the distance range that accurately resolves the overall pattern of slip is the one that contains the takeoff angles of 45°–65°. Concerning azimuthal coverage, a network with >270° performs similarly to having complete coverage. The choice of EGF can shift the location of resolved areas of slip and their amplitude, depending on its similarity in location and radiation pattern to the target earthquake.

Modified Partial Capacity Design (M-PCD): achieving partial sidesway mechanism by using two steps design approach

Partial Capacity Design (PCD) has been developed by using magnification factor to keep some columns undamaged during major earthquake. By doing so, the structures will experience the partial side sway mechanism which is also stable, instead of the beam sidesway mechanism. However, in some cases, structures designed by PCD method failed to show the partial side sway mechanism since unexpected damages were still occurred at some columns. In this research, modification of PCD method is proposed by using two structural models in the design process. The first model is used to design beams and columns which are allowed to experience plastic damages, while the second model is used to design columns which are intended to remain elastic when the structure is subjected to a target earthquake. Two nominal earthquakes corresponding to Elastic Design Response Spectrum (EDRS) level with seismic modification factors (R) of 8.0 and 1.6 are used in the first and second structural models, respectively. It should be noted that the second model is identical to the first model except that the stiffnesses are reduced for elements to simulate potential plastic damages. This proposed method is applied to symmetrical 6 and 10 storey buildings with seismic load according SNI 1726:2012 and with soil classification of SE in Surabaya city. A Non-linear Static Procedure (NSP) or pushover analysis and Non-linear Dynamic Procedure (NDP) or time history analysis are employed to evaluate the performance of the structure. The evaluation is conducted at three earthquake levels which are nominal earthquake that is used in second model, earthquake corresponding to EDRS level, and maximum considered earthquake (MCER) specified by the code (50% higher than EDRS level). The building performances satisfy the drift criteria in accordance with FEMA 273. However, the partial side sway mechanism was not achieved at NDP analysis at maximum seismic load, MCER.

Space–Time Trade-Off of Precursory Seismicity in New Zealand and California Revealed by a Medium-Term Earthquake Forecasting Model

The ‘Every Earthquake a Precursor According to Scale’ (EEPAS) medium-term earthquake forecasting model is based on the precursory scale increase (Ψ) phenomenon and associated scaling relations, in which the precursor magnitude MP is predictive of the mainshock magnitude Mm, precursor time TP and precursory area AP. In early studies of Ψ, a relatively low correlation between TP and AP suggested the possibility of a trade-off between time and area as a second-order effect. Here, we investigate the trade-off by means of the EEPAS model. Existing versions of EEPAS in New Zealand and California forecast target earthquakes of magnitudes M > 4.95 from input catalogues with M > 2.95. We systematically vary one parameter each from the EEPAS distributions for time and location, thereby varying the temporal and spatial scales of these distributions by two orders of magnitude. As one of these parameters is varied, the other is refitted to a 20-year period of each catalogue. The resulting curves of the temporal scaling factor against the spatial scaling factor are consistent with an even trade-off between time and area, given the limited temporal and spatial extent of the input catalogue. Hybrid models are formed by mixing several EEPAS models, with parameter sets chosen from points on the trade-off line. These are tested against the original fitted EEPAS models on a subsequent period of the New Zealand catalogue. The resulting information gains suggest that the space–time trade-off can be exploited to improve forecasting.

An Operational Earthquake Forecasting Experiment for Israel: Preliminary Results

Operational Earthquake Forecasting (OEF) aims to deliver timely and reliable forecasts that may help to mitigate seismic risk during earthquake sequences. In this paper, we build the first OEF system for the State of Israel, and we evaluate its reliability. This first version of the OEF system is composed of one forecasting model, which is based on a stochastic clustering Epidemic Type Earthquake Sequence (ETES) model. For every day of the forecasting time period, January 1, 2016 - November 15, 2020, the OEF-Israel system produces a weekly forecast for target earthquakes with local magnitudes greater than 4.0 and 5.5 in the entire State of Israel. Specifically, it provides space-time-dependent seismic maps of the weekly probabilities, obtained by using a fixed set of the model’s parameters, which are estimated through the maximum likelihood technique based on a learning period of about 32 years (1983–2015). According to the guidance proposed by the Collaboratory for the Study of Earthquake Predictability (CSEP), we also perform the N- and S-statistical tests to verify the reliability of the forecasts. Results show that the OEF system forecasts a number of events comparable to the observed one, and also captures quite well the spatial distribution of the real catalog with the exception of two target events that occurred in low seismicity regions.

P-wave picking for earthquake early warning: refinement of aTpdmethod

SUMMARYDetecting P-wave onsets for online processing is an important component for real-time seismology. As earthquake early warning systems around the world come into operation, the importance of reliable P-wave detection has increased, since the accuracy of the earthquake information depends primarily on the quality of the detection. In addition to the accuracy of arrival time determination, the robustness in the presence of noise and the speed of detection are important factors in the methods used for the earthquake early warning. In this paper, we tried to improve the P-wave detection method designed for real-time processing of continuous waveforms. We used the new Tpd method, and proposed a refinement algorithm to determine the P-wave arrival time. Applying the refinement process substantially decreases the errors of the P-wave arrival time. Using 606 strong motion records of the 2011 Tohoku earthquake sequence to test the refinement methods, the median of the error was decreased from 0.15 to 0.04 s. Only three P-wave arrivals were missed by the best threshold. Our results show that the Tpd method provides better accuracy for estimating the P-wave arrival time compared to the STA/LTA method. The Tpd method also shows better performance in detecting the P-wave arrivals of the target earthquakes in the presence of noise and coda of previous earthquakes. The Tpd method can be computed quickly, so it would be suitable for the implementation in earthquake early warning systems.

Simulation of Strong Ground Motion in the National Capital Region, India, from a Future 8.5 Magnitude Earthquake Using Two-Step Empirical Green’s Function Method

ABSTRACT In this study, I simulate high-frequency ground motions at five stations in the National Capital Region (NCR) of India for a large hypothetical Mw 8.5 earthquake in the Himalayan central seismic gap, at fault-distances of about 200–300 km. A smaller magnitude earthquake (22 July 2007 Mw 4.9 Kharsali) is used as the first-step empirical Green’s function (EGF) for the synthesis of an intermediate-sized earthquake of magnitude Mw 6.8 (1991 Uttarkashi earthquake). In the second step, the records of Mw 6.8 synthetics are further used as the EGF in the simulation of the postulated Mw 8.5 earthquake. Because the target region for the postulated earthquake is devoid of the necessary information on the geophysical constraints, I perform a suite of simulations for plausible scenarios of fault dimensions, stress-drop ratios, C, and scaling factor, N (between the EGF and target earthquake). This article uses heterogeneous slip distributions and variable stress drops on the rupture plane to simulate the target earthquake, based on the power spectral density of the von Karman correlation function. The estimated values of the ground-motion intensity measure (GMIM) such as peak ground acceleration, along with the engineering parameters such as the 5% damped, pseudospectral acceleration (Sa), Arias intensity (IA), and significant duration (TD), are compared for both the recorded and the simulated time histories. The estimated GMIMs of the Mw 6.8 synthetics are examined with those of the 1991 Mw 6.8 Uttarkashi earthquake, whereas the Mw 8.5 simulations are compared with those predicted by prevalent ground-motion prediction equations for rock sites. The Mw 8.5 earthquake scenarios indicate higher GMIMs and seismic hazard in the NCR, principally due to the area being underlain by sediment layers and fluvial deposits.