Ground Motion Prediction Equations Research Articles

Bayesian maximum entropy interpolation analysis for rapid assessment of seismic intensity using station and ground motion prediction equations

In this paper, we explored the combination of seismic station data and ground motion prediction equations (GMPE) to predict seismic intensity results by using Bayesian Maximum Entropy (BME) method. The results indicate that: 1) In earthquake analysis in Japan, soft data has predicted higher values of intensity in disaster areas. BME corrected this phenomenon, especially near the epicenter. Meanwhile, for earthquakes in the United States, BME corrected the erroneous prediction of rupture direction using soft data. 2) Compared with other spatial interpolation methods, the profile results of Japan earthquake and Turkey earthquake show that BME is more consistent with ShakeMap results than IDW and Kriging. Moreover, IDW has a low intensity anomaly zone. 3) The BME method overcomes the phenomenon that the strength evaluation results do not match the actual failure situation when the moment magnitude is small. It more accurately delineates the scope of the disaster area and enriches the post-earthquake processing of disaster area information and data. BME has a wide range of applicability, and it can still be effectively used for interpolation analysis when there is only soft data or few sites with data available.

On-Site Earthquake Early Warning Model for Selected Records in the NGA-West2 Dataset Using S- and P-Wave Spectral Ratios

ABSTRACT On-site earthquake early warning (EEW) requires the best estimates of earthquake magnitude and distance parameters within a few seconds after the P-wave arrival for estimating the subsequent S-wave parameters. The errors in the estimates of the earthquake P-wave parameters will propagate into the estimates of the S-wave parameters. To solve this problem, we used the methodology by Zhao and Zhao (2019), which uses the spectral ratio R3P between the response spectral values of the first 3 s of the S wave and that of the first 3 s of the P wave, referred to as the R3P model. The modeling presented here was based on strong-motion records from the Next Generation Attenuation (NGA)-West2 dataset. We also used the spectral ratio RFP between the response spectral values from the full records from the S-wave arrival time to the end of the record and that of the first 3 s P wave to develop a second EEW model (the RFP model). An advantage of these two models is that the magnitude and hypocentral distance are not required in considerable magnitude and distance ranges. This means that the errors in the estimated source and path parameters from the first 3 s of the P wave will not affect the model predictions. A theoretical justification for these results is that the magnitude and the distance scaling rates for the first 3 s of the P wave are similar to those of the first 3 s of the S wave. This may also apply to the full S-wave window within useful EEW magnitude and distance ranges. We also found that when the estimated magnitude and distance for a record are necessary, the effect of the corresponding errors would be smaller than using a ground-motion prediction equation (GMPE), because the magnitude and distance scaling rates from this study are smaller than those of many GMPEs.

Rapid determination of source parameters of the M6.2 Jishishan earthquake in Gansu Province and its application in emergency response

In this study, we swiftly determined the focal parameters (focal mechanism, seismic imaging process, magnitude) of the Jishishan earthquake, leveraging a solved fault model to promptly assess the intensity field and casualties. The investigation began by retrieving the source mechanism through the P-wave initial motion and W-phase method. This enabled us to chart the spatial and temporal distribution of energy release in the source area via the back-projection technique. Following this, we estimated the earthquake’s intensity field by merging the source inversion findings with the ground motion prediction equation. This analysis facilitated the evaluation of earthquake casualties, utilizing the theoretical intensity field and a casualty assessment model.Our findings indicate that the fault type is a thrust fault, characterized by a unilateral rupture in the direction of NW, with a rupture length spanning approximately 10-15 km and a duration ranging between 8-10 seconds. The earthquake’s magnitude varied from M 5.9 to M 6.2. The demarcated high-intensity areas, as per our intensity assessment, align closely with the actual survey results. Furthermore, the predicted total casualties and identified critical rescue zones closely match the real-world casualty figures. These insights offer crucial technical support for governmental emergency command and rescue operations.

Vertical Ground Motion Prediction Equations for Interplate and Intermediate-Depth Intraslab Earthquakes at Mexico City’s Hill Zone

ABSTRACT We present ground motion prediction models for spectral pseudo acceleration (5% damping), peak ground velocity, and peak ground acceleration values from interplate and intermediate-depth intraslab earthquakes at the so-called hill zone of Mexico City for the vertical component and the vertical-to-horizontal ratio case. There are no previous models for the vertical component from these events in Mexico City. The prediction equations were developed as a function of magnitude and also as a function of distance to the fault surface of earthquakes by using 30 and 26 seismic recordings from interplate (1965–2022) and intermediate-depth intraslab (1964–2017) earthquakes at the hill zone of the city by using Bayesian regression analyses. The attenuation models are developed for interplate events for distances ranging from 280 km to over 500 km and Mw from 6 to 8.1, and for intraslab events for distances to the fault surface ranging from 100 km up to about 600 km, focal depths from 40 km to over 120 km and Mw from 5 to 8.2. Nevertheless, since at large distances ground motions are generally weak, we recommend the applicability of the proposed models to be restricted to up to 400 km. The models are adequate to estimating the seismic hazard at the hill zone of Mexico City, as proved by contrasting analytical versus empirical seismic exceedance rates for the vertical component.

Analysis of impulsive ground motions from February 2023 Kahramanmaraş earthquake sequence

AbstractOn the 6th of February 2023, a large magnitude earthquake (Pazarcık earthquake), $$M_{w}=$$ M w = 7.7, occurred in southeast Türkiye, which caused significant destruction in Türkiye and Syria. Relatively large magnitude aftershocks followed the main shock, and after 9 hours of the main event, another large magnitude earthquake (Elbistan earthquake) occurred, $$M_{w}=$$ M w = 7.6, on a nearby fault. This study analyzes the near-fault seismic signals from earthquakes larger than 5.5 recorded between the main shock and the 31st of March 2023. More than 60 impulsive motions are detected in 3 earthquakes, mostly concentrated in the Pazarcık and Elbistan earthquakes. In the Pazarcık earthquake, many impulsive motions are recorded in near-fault stations with periods of up to 14 s. In contrast, in the Elbistan earthquake, impulsive motions are spatially distributed, with pulse periods of up to 11 s and at distances greater than 150 km. Pulse periods mostly correlate with the magnitude of the earthquake, but pulse probability models do not predict impulsive motions over long distances. The presence of strong impulsive motions in vertical components is also observed. For both earthquakes, peak ground velocities (PGVs) are larger than predicted by ground motion prediction equations. The observation of long-period, large amplitude signals may indicate the presence of a directivity effect for both earthquakes. In some stations, spectral periods exceed the 2018 Turkish building design codes for long periods ($$\ge$$ ≥ 1 s).

Prediction of Fourier Amplitude Spectrum of Ground Motion in Mexico City from Subduction Thrust Earthquakes

Mexico City, one of the largest cities in the world, experiences frequent, devastating interplate earthquakes that originate on the subduction thrust along the Pacific coast of Mexico more than 250 km away. A notorious example is the 19 September 1985 Michoacán earthquake (Mw 8.0) which killed ~ 10,000 persons and caused wide-spread destruction in the city. The main cause of seismic damage in Mexico City is its subsoil that amplifies the ground motion. In view of the seismic hazard faced by the city, a reliable estimation of ground motion during future earthquakes is of vital importance. We present a new ground motion prediction equation (GMPE) for the Fourier amplitude acceleration spectrum (FAS) from subduction thrust earthquakes along the Pacific coast of Mexico at the reference station, CU, located in the firm zone of Mexico City. The GMPE is derived via Bayesian regression analysis and is based on an enlarged set of recordings (1965-2020; 40 earthquakes; 250 ≤ R≤ 500 km; 5 ≤ Mw ≤ 8.0). An important feature of the new GMPE is that it includes a term to model different attenuation along different ray paths. The inclusion of this term leads to a reduction in the aleatory variability of the GMPE, particularly at high frequencies. Since spectral amplification of seismic waves with respect to CU is known at many sites in the city, the FAS at these sites can be computed if it is known at CU. The new GMPE has been incorporated in a fully Fourier-based probabilistic seismic hazard analysis of Mexico City.

The Main Factors Controlling Probabilistic Seismic Hazard Variability Due to Epistemic Uncertainty in Greece: Results from a One-Factor-at-a-Time Analysis

Abstract We present a one-factor-at-a-time (OFAT) sensitivity study for the Probabilistic Seismic Hazard Assessment (PSHA) in Greece. The analysis examines several PSHA controlling factors, such as seismic source model (geometry, etc.), active tectonics (faulting type, etc.), as well as the employed ground-motion prediction equations (GMPEs). We have considered only peak ground acceleration (PGA) and peak ground velocity (PGV) for a typical PSHA scenario (10% probability of exceedance in 50 yr). OFAT results are presented using Tornado diagrams for 42 major urban centers of Greece that cover the study area revealing regions of different PSHA uncertainty. In general, the most critical factors controlling PSHA uncertainties are the Gutenberg–Richter (G-R) parameters (a and b), as well as the employed GMPE. However, significant spatial variability of these factors is observed with large differences between high- and low-seismicity regions, as well as between PGA and PGV. The results not only provide an objective assessment of the variability of PSHA uncertainties but also verify the need for additional work to minimize epistemic PSHA uncertainties, focusing on the most critical factors that control PSHA.

The influence of aftershocks on seismic hazard analysis: a case study from Xichang and the surrounding areas

Abstract. In some instances, a strong aftershock can cause more damage than the mainshock. Ignoring the influence of aftershocks may lead to the underestimation of the seismic hazard of some areas. Taking Xichang and its surrounding areas as an example and based on the Seismic ground motion parameters zonation map of China (GB 18306-2015), this study used the Monte Carlo method to simulate synthetic mainshock sequences. Additionally, the Omi–Reasenberg–Jones (Omi–R–J) aftershock activity model is used to simulate the aftershock sequences that follow mainshocks above a certain magnitude threshold. Then, the mainshock and the aftershocks are combined to calculate the regional seismic hazard using ground motion prediction equations (GMPEs). Finally, the influence of aftershocks on seismic hazard analysis is examined and considered. The results show that in areas with moderate to strong seismic backgrounds, the influence of aftershocks on probabilistic seismic hazard analysis can exceed 50 %. These results suggest that the impact of aftershocks should be properly considered for future probabilistic seismic hazard analyses, especially in areas with moderate to strong seismic activity backgrounds and in areas prone to secondary disasters such as landslides and mudslides.

WITHDRAWAL – Administrative Duplicate Publication: From Source to Building Fragility: Post-event Assessment of the 2013 M7.1 Bohol Philippines Earthquake

We use ground motion simulations of the 2013 Bohol Philippines earthquake along with a new post-disaster exposure/damage database to constrain building fragility and vulnerability. The large number of damaged buildings (>70,000) and the wide spread of seismic intensities caused by this earthquake make it an ideal candidate for such a study. An extensive survey was conducted leading to a robust description of over 25,000 damaged and undamaged structures. Ground motion fields were simulated using ground motion prediction equations and stochastic modeling, and the estimated and observed values were compared. The finite source model used in the simulation was based on the analysis of aftershocks and SAR data. The ground motions were associated with the empirical database to derive fragility and vulnerability models. Results indicate that the pattern of damage is best captured in the stochastic simulation. Constraints were placed on seismic building fragility and vulnerability models, which can promote more effective implementation of construction regulations and practices.

Rapid Earthquake Damage Assessment System in the Black Sea Basin: Selection/Adoption of Ground Motion Prediction Equations with Emphasis in the Cross-Border Areas

In the present study, an effort to propose and adopt appropriate Ground Motion Prediction Equations (GMPEs) for the Rapid Earthquake Damage Assessment System (REDAS) in the Black Sea basin is attempted. Emphasis of GMPE harmonization in the cross-border areas (CBA) is given. For this reason, two distinct sub-areas are investigated, taking into consideration their seismotectonic regime. One sub-area refers to active shallow crustal earthquakes (Greece-Turkey, CBA) and the other to intermediate-depth and shallow crustal earthquakes (Romania-Moldova, Western Black Sea CBA). Testing and ranking of pre-selected GMPEs has been performed using strong motion data of the broader CBA regions of both sub-areas. The final proposed GMPEs to feed the REDA System may assure the effective estimation of ShakeMaps and—in combination with the appropriate vulnerability curves—reliable near-real-time damage assessment in the cross-border earthquake affected areas.

The assessment of probabilistic seismic risk using ground-motion simulations via a Monte Carlo approach

AbstractAccurately characterizing ground motions is crucial for estimating probabilistic seismic hazard and risk. The growing number of ground-motion models, and increased use of simulations in hazard and risk assessments, warrants a comparison between the different techniques available to predict ground motions. This research aims at investigating how the use of different ground-motion models can affect seismic hazard and risk estimates. For this purpose, a case study is considered with a circular seismic source zone and two line sources. A stochastic ground-motion model is used within a Monte Carlo analysis to create a benchmark hazard output. This approach allows the generation of many records, helping to capture details of the ground-motion median and variability, which a ground motion prediction equation may fail to properly model. A variety of ground-motion models are fitted to the simulated ground motion data, with fixed and magnitude-dependant standard deviations (sigmas) considered. These include classic ground motion prediction equations (with basic and more complex functional forms), and a model using an artificial neural network. Hazard is estimated from these models and then we extend the approach to a risk assessment for an inelastic single-degree-of-freedom-system. Only the artificial neural network produces accurate hazard results below an annual frequency of exceedance of 1 × 10–3 years−1. This has a direct impact on risk estimates—with ground motions from large, close-to-site events having more influence on results than expected. Finally, an alternative to ground-motion modelling is explored through an observational-based hazard assessment which uses recorded strong-motions to directly quantify hazard.

Comparison and selection of ground motion prediction equations for the Sichuan–Yunnan area, southwest China

The Sichuan–Yunnan area is one of the most seismically active regions in China. As ground-motion models form a key component of seismic hazard analysis, it is important to select (or develop) appropriate models for this area. The increasing number of digital ground-motion records of earthquakes in this area has allowed the development of local ground motion prediction equations (GMPEs). This study compares and, later, recommends appropriate GMPEs for the Sichuan–Yunnan area. We first evaluate the inherent quality of local GMPEs, with respect to their underlying datasets, the variables used and their functional forms, to determine a set of candidate GMPEs. Then we investigate how well the predictions from the GMPEs match observations computed from strong-motion records of recent earthquakes in this area. The fit between predictions and observations varies significantly amongst the GMPEs. The results suggest that some recent local GMPEs would lead to biased ground-motion estimates due to limitations of their underlying datasets and functional forms. Based on both evaluations of inherent quality and compatibility with observations, only one local GMPE is recommended. A comparison of the predictions from three widely-used non-local GMPEs indicates that ground motions in the Sichuan–Yunnan area appear more variable than those in other regions but that predictions from these non-local GMPEs are generally unbiased. We recommend use of a mixture of robust local and non-local GMPEs within seismic hazard analyses to capture the epistemic uncertainty in ground-motion prediction for this area.

Comparison of peak ground acceleration using deterministic and probabilistic approach in the coastal area of Loh Buaya, Rinca Island, Indonesia

An area located near an active volcano, subduction zone, and/or active fault has a risk of an earthquake. Earthquakes can cause damage to buildings with a large number of losses. One of the earthquake-related parameters required in planning an earthquake-resistant building is the Peak Ground Acceleration (PGA). The objective of this study is to compare the PGA value at the coastal area of Loh Buaya, Rinca Island, Indonesia, using Probabilistic Seismic Hazard Analysis (PSHA) and Deterministic Seismic Hazard Analysis (DSHA). The DSHA is calculated based on earthquake data series from the United States Geological Survey (USGS) in the period between 1922 to 2022. Also, it is calculated using 10 data of Ground Motion Prediction Equation (GMPE). Data from the USGS is constrained with magnitude > 5.0 MW and earthquake distance < 200 km from the study site. The PSHA is based on the Indonesian earthquake hazard map and the de-aggregation map from the National Earthquake Study Centre of Indonesia with a probability exceeding 2% in 50 years. Based on the parameters of PGA maximum, distance, and magnitude, the DSHA by Kanno method has the closest result to the PSHA. It is concluded that this area has a high earthquake risk with a PGA maximum of more than 0.5 g.

Compatible Ground Motion Models for South Korea Using Moderate Earthquakes

Due to a heightened interest in the field of earthquakes after two moderately sized earthquakes occurred in Gyeongju and Pohang, this study explores which ground motion prediction equations are compatible for the South Korea region. Due to data availability, ground motions from five earthquakes of moderate magnitude were used for comparing against selected ground motion models. Median rotated response spectral ordinates at a period of 0.2 s were extracted from these ground motions, which served as a basis for comparison. Twelve ground motion models were considered from the Next Generation Attenuation West, West2, and East programs due to their extensive databases and robust analytical techniques. A comparison of relative residuals, z-score, and each event found that the subset of Next Generation Attenuation—East ground motion prediction equations did not perform as well as the suite of Next Generation Attenuation—West2 ground motion prediction equations, most likely due to the regional simulations involved in developing the database. Interestingly, the ground motion models that performed relatively well were from the set designed for rock conditions.

Probabilistic seismic hazard assessment framework for Uganda: a stochastic event-based modelling approach

Uganda lies between the eastern and western arms of the East African Rift System, the largest seismically active rift above sea level. With increasing population, urbanisation and rapid construction, seismic risk in the country is escalating fast and is compounded by the high vulnerability of the building stock and inadequate disaster prevention and mitigation strategies. Hence, there is an urgent need to assess Uganda’s resilience against seismic risks. This paper presents a Monte-Carlo based probabilistic seismic hazard model for Uganda, as the first step towards the development of a seismic risk and resilience assessment framework for the country. In addition to fault segment data, earthquake catalogues are compiled for the period between 1900 and 2022 to estimate recurrence parameters for source zones in the area of interest. Area source zones incorporating focal mechanisms are used to stochastically model a national hazard framework for Uganda. A logic tree approach is applied to implement four ground motion prediction equations for both stable continental and active shallow crust geologies. Mean hazard curves, uniform hazard spectra, earthquake disaggregation and spectral pseudo-accelerations for major Ugandan cities are derived in addition to hazard maps for the country. The findings are largely consistent with previous regional studies and confirm that western Uganda is exposed to the highest level of seismicity. The model presented herein can be used to kick-start the update and continuous improvement of Uganda Seismic Design Code and the National Policy for Disaster Preparedness and Management.

Ground-motion simulations using two-dimensional convolution condition adversarial neural network(2D-cGAN)

In this paper, an integrated framework based on conditional adversarial neural network (cGAN) is established to simulate ground motions for earthquake scenarios with different magnitude, distance, and local site conditions. A ground motion dataset is created for training the network, within which most data are observed accelerograms collected from PEER and gaps for certain magnitude-site conditions are filled with accelerograms simulated using stochastic finite-fault modeling. During the learning of cGAN, the dataset is classified first with multi-labels according to local site conditions, and the multi-labels are set to be the conditional information Y for the network. Effects of using one-dimensional convolution (Conv1D) and two-dimensional convolution (Conv2D) in cGAN are tested in terms of the time-domain and frequency-domain characteristics of the generated ground motion. The test proves the strengths of Conv2D in capturing high-dimensional temporal and spectral characteristics from one-dimensional time series of ground motion. Ground motions generated using 2D-cGAN network are compared to the measures predicted by widely-used ground motion prediction equations, through which the reliability of 2D-cGAN network on ground motion simulation is verified.

Suitability Analysis of Ground Motion Prediction Equations for Western and Central Himalayas and Indo-Gangetic Plains

ABSTRACT Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical, and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region have become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical, and geotectonical nature. The dataset comprises 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions.

Evaluation of November 23, 2022, Duzce Earthquake data with Ground Motion Prediction Equations

An earthquake with a magnitude of 5.9 Mw occurred in Düzce (Gölyaka) on November 23, 2022. A rupture occurred on the Karadere Segment, which is a section of the North Anatolian Fault zone. According to the investigations, an 8 km section that was not broken in the 1999 Gölcük Earthquake was broken by this earthquake and caused the earthquake. Station number 8105, one of the stations of the Disaster and Emergency Presidency, measured the maximum ground acceleration of the earthquake as 0.6g. This value is above the PGA value taken from the hazard map of the region. This earthquake in the Marmara region attracts the attention of researchers both because it is close to the 1999 Gölcük Earthquake and because there is an earthquake expectation in Istanbul and its surroundings. Ground motion prediction equations are created by researchers to predict the effects of future earthquakes. The aim of this study is to compare the earthquake data considered in the study with 5 of the ground motion equations developed for Turkey. PGA data were collected and compared with the 5 attenuation relations used from the stations taking measurements from the earthquake, and the compatibility of the earthquake with the 5 existing models was examined. As a result of the study, it was determined that among these attenuation relations, the attenuation relations prepared using the data in the region where the earthquake occurred showed a higher fit. In addition, it has been observed that low pga values at stations farther from the epicenter of the earthquake fit better with the curves obtained from the attenuation relations. The number of data sets used in attenuation relations and the study area increase the possibility of estimating earthquake parameters. The data set used in the AR4 attenuation relationship used in the study and the fact that the region taken into consideration is the region where the earthquake occurred increased the data-model compatibility. It was concluded that existing attenuation relationships should be updated in order to better predict future earthquakes and their effects.

Assessing seismic risk in the built environment of Istanbul: High-resolution hazard mapping and ground motion analysis in the sea of Marmara region

This research scrutinizes the seismic threat looming over Istanbul, potentially subject to a substantial earthquake. We analyze six plausible earthquake scenarios, utilizing six ground motion prediction equations (GMPEs), to forge high-resolution seismic hazard maps. These maps reveal not only peak horizontal ground accelerations but also spectral acceleration values across varying temporal frames, integrating the amplification effects of softer sediments. Our approach delineates that Istanbul’s western shoreline faces heightened risk, with median spectral accelerations at 0.3 s approaching 1 g, signifying intense shaking potential. In contrast, the area encompassing the financial district exhibits lower values, around 0.3 g. The granularity of these findings lays bare the seismic vulnerabilities of the region, offering a window into the risks and potential damages facing this bustling metropolis. This enhanced understanding paves the way for strategic urban planning and risk mitigation efforts aimed at safeguarding Istanbul’s populace and infrastructure. This article succinctly condenses our study’s pivotal conclusions, presenting a clarion call for proactive measures to diminish earthquake impacts on this dynamic urban landscape.

Ground motion prediction model for shallow crustal earthquakes in Japan based on XGBoost with Bayesian optimization

Ground motion prediction is an important and complex research subject in earthquake engineering and traditional approaches based on statistical regression have much room for improvement in prediction accuracy. Utilizing the 67,164 ground motion records from KiK-net and K-Net for 777 shallow crustal earthquakes between 1997 and 2019 in Japan, this paper proposes a ground motion prediction model XGBoost-SC based on the machine learning algorithm of eXtreme Gradient Boosting (XGBoost) for Japan. Magnitude, focal depth, hypo-central distance, Vs30, site altitude, and focal mechanism were used as the feature parameters, and XGBoost, Random Forest, and Deep Neural Networks (DNN) algorithms were selected for model training while Bayesian optimization was used to search for optimized hyperparameters to improve the prediction accuracy. XGBoost algorithm was selected for further study based on the comparison of results from the three algorithms. Residual change with magnitude and hypo-central distance, the probability distribution of residuals, residual standard deviation (σ), residual mean squared error (MSE), and Pearson correlation coefficient (R) were used as the evaluation parameters, and a comparison study was performed against the ground motion prediction equation based on traditional approaches. Actual earthquake events were selected to compare the prediction results against the observation records. To further validate and explain the proposed model, SHapley Additive exPlanations (SHAP) analysis was performed to explain the impact of selected feature parameters on the proposed model. The results demonstrate that the proposed XGBoost-SC model has good prediction stability for all periods, and its residual errors are smaller than those of other models. Therefore, the proposed model can better reflect the ground motion attenuation for shallow crustal earthquakes in Japan and can serve as a better model for ground motion prediction in future aseismic design and earthquake disaster mitigation efforts.