Seismic Risk Model Research Articles

Rapid damage assessment effectiveness for the 2023 Kahramanmaraş Türkiye earthquake sequence

The recent devastating 2023 Türkiye earthquakes underscored the urgent need for an early estimate of quantitative losses following destructive seismic events. This study aims to propose and validate a Rapid Damage Assessment (RDA) methodology based solely on open data and tools, easily and readily available globally immediately after a seismic event. In this context, the 2023 Türkiye earthquakes are used as a case study. For the application of the proposed methodology there are two prerequisites: (1) ground shaking data, herein obtained from the US Geological Survey (USGS) ShakeMap system, and (2) a predictive seismic risk model appropriate for the area of interest, consisting of an exposure and a vulnerability model, derived from the 2020 European Seismic Risk Model (ESRM20). Scenario-type analyses for the two major events, the M7.8 - Pazarcik and the M7.5 – Elbistan earthquake, are performed, and the results are compared with the officially reported damages. The main goal is to assess the accuracy of RDA immediately after an earthquake, and whether and to what extent the RDA results can be improved as the USGS ShakeMaps are updated with the incorporation of additional data, and with disaggregation of the exposure model at a finer resolution. The results indicate that the exposure model's disaggregation reduces the damage estimates' standard deviation. At the same time, the effect of the ShakeMap version is minimized when the complete fault rupture is incorporated into the model. The estimated damages are in good agreement with the officially announced data at large scale, which corroborates the proposed methodology, as well as the adopted components of ESRM20.

High-resolution 3D ambient noise tomography around the Meishan-Chiayi active fault system of western Taiwan

The Meishan-Chiayi area of western Taiwan has a large probability of producing a major earthquake in the near future. Historically, one of the largest and most damaging of Taiwan’s earthquakes occurred there. It is, therefore, important to have a well-constrained upper crustal 3-D shear-wave velocity model that can be used to accurately determine ground motion predictions and fault geometry models used in seismic hazard and risk modelling. In this study, we carried out an ambient noise tomography experiment using 100 seismometers deployed with a ∼2 km spacing on a 20 by 20 km grid. The reliable periods of phase velocity from Rayleigh waves are 0.6 to 6.8 s, providing a well-resolved Vs structure from the surface to a depth of around 4 km. The velocity model displays a prominent, roughly northeast-striking change in Vs that follows the projected surface trace of the blind Chiayi thrust. The uplift of relatively higher Vs rocks in its hanging wall, together with a negative to positive change in dVs suggests that it dips gently eastward across the study area. A northward thickening of the lower Vs crust, together with a high negative dVs in the north of the study area is related to an increased thickness of foreland basin rocks across the Meishan fault. The Vs and dVs models provide reasonable evidence that the Meishan fault can be traced at a high angle from its surface rupture to the base of the model at 4 km depth. It cuts the Chiayi thrust.

Comparing components for seismic risk modelling using data from the 2019 Le Teil (France) earthquake

Abstract. Probabilistic seismic hazard and risk models are essential to improving our awareness of seismic risk, to its management, and to increasing our resilience against earthquake disasters. These models consist of a series of components, which may be evaluated and validated individually, although evaluating and validating these types of models as a whole is challenging due to the lack of recognized procedures. Estimations made with other models, as well as observations of damage from past earthquakes, lend themselves to evaluating the components used to estimate the severity of damage to buildings. Here, we are using a dataset based on emergency post-seismic assessments made after the Le Teil 2019 earthquake, third-party estimations of macroseismic intensity for this seismic event, shake maps, and scenario damage calculations to compare estimations under different modelling assumptions. First we select a rupture model using estimations of ground motion intensity measures and macroseismic intensity. Subsequently, we use scenario damage calculations based on different exposure models, including the aggregated exposure model in the 2020 European Seismic Risk Model (ESRM20), as well as different site models. Moreover, a building-by-building exposure model is used in scenario calculations, which individually models the buildings in the dataset. Lastly, we compare the results of a semi-empirical approach to the estimations made with the scenario calculations. The post-seismic assessments are converted to EMS-98 (Grünthal, 1998) damage grades and then used to estimate the damage for the entirety of the building stock in Le Teil. In general, the scenario calculations estimate lower probabilities for damage grades 3–4 than the estimations made using the emergency post-seismic assessments. An exposure and fragility model assembled herein leads to probabilities for damage grades 3–5 with small differences from the probabilities based on the ESRM20 exposure and fragility model, while the semi-empirical approach leads to lower probabilities. The comparisons in this paper also help us learn lessons on how to improve future testing. An improvement would be the use of damage observations collected directly on the EMS-98 scale or on the damage scale in ESRM20. Advances in testing may also be made by employing methods that inform us about the damage at the scale of a city, such as remote sensing or data-driven learning methods fed by a large number of low-cost seismological instruments spread over the building stock.

Turkish earthquake death tolls: lessons from downward counterfactual analysis and informal construction

Earthquake death tolls are a basic statistical measure of the capability of a country to manage seismic risk. The extremely high Turkish death toll of 50,000 from the Kahramanmaraş earthquake doublet of 6 February 2023 is the product of a cascade of detrimental factors. These need to be explained if lessons from this disaster are to be learned. This is the purpose and objective of this paper, which is a contribution to the interdisciplinary Frontiers research topic on integrated perspectives on the 2023 Turkey and Syria earthquakes: advancing understanding and preparedness across earth sciences, engineering and public health. This paper covers these three disciplines by focusing on casualties, and identifying crucial aspects of earth sciences and engineering which contributed to the high death toll. First, there was a surprising combination of multiple fault segment ruptures, and a high level of ground motion relative to the risk-based Turkish code, indicative of the under-representation of the M7.5+ earthquake doublet event in the national probabilistic seismic hazard model. This combination of fault segment ruptures was missing from all seismic source models. Furthermore, the capability of buildings to cope with strong ground motion was much reduced by informal construction methods, which eroded the margin of safety needed to avoid building collapse. The extent of building code non-compliance was widely underestimated in seismic risk models. Non-compliance is often hard to identify, but construction amnesties make non-compliance more transparent and trackable. The disastrous outcome of the Kahramanmaraş earthquake doublet of 6 February 2023 has drawn global attention to systemic building code non-compliance, and the open official acceptance of informal housing. To demonstrate that this key systemic risk is far from being just a Turkish problem, notably in Istanbul, the challenge of Italian informal housing is highlighted within the context of international building code non-compliance.

Seismic Risk Model for the Beijing–Tianjin–Hebei Region, China: Considering Epistemic Uncertainty from the Seismic Hazard Models

This study presents a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China. The model comprises a township-level residential building exposure model, a vulnerability model derived from the Chinese building taxonomy, and a regional probabilistic seismic hazard model. The three components are integrated by a stochastic event-based method of the OpenQuake engine to assess the regional seismic risk in terms of average annual loss and exceedance probability curve at the city, province, and regional levels. The novelty and uniqueness of this study are that a probabilistic seismic risk model for the Beijing–Tianjin–Hebei region in China is developed by considering the impact of site conditions and epistemic uncertainty from the seismic hazard model.

Seismic risk model for regional buildings that considers the influence of temperature and intensity measures

Probability-based seismic risk and random ground motion theories are used to develop high-precision seismic risk functions and models of regional building portfolios. Seismic intensity measures and structural demand parameters are critical in developing seismic fragility models for building clusters. Earthquake damage data indicate that ambient temperature may influence structural fragility, but the effect of temperature on seismic risk is commonly ignored. A method for quantifying seismic intensity is proposed in this study and optimized using 450,000 acceleration records detected by 15 stations during the Luding earthquake in Sichuan, China, on September 5, 2022. Considering the influence of different temperature fields, the proposed seismic intensity quantification method was used to evaluate structural damage during two destructive earthquakes in Xinjiang, China (the Aktao earthquake on September 2, 2003 and the Zhaosu earthquake on December 1, 2003). Three structural empirical seismic risk matrices and cloud maps were developed, and a vulnerability membership curve was generated using fuzzy decision-making, a membership algorithm, and nonlinear regression. A structural seismic risk index function was proposed, and vulnerability cloud diagrams and curves based on actual structural seismic vulnerability datasets were generated. Together, these analyses demonstrated the impact of temperature and intensity measures on the seismic risk to regional buildings. A model was established to evaluate the seismic risk to typical structures and was validated using historical earthquake damage data from China. This method improves the accuracy of earthquake risk and vulnerability assessments for typical building clusters given the influence of temperature. The developed seismic risk prediction model enables the evaluation of vulnerability and resilience of typical structures under low and high temperatures.

Post-earthquake safety assessment of schools after the 2016 Ecuador M7.8 earthquake

The 2016 Muisne earthquake generated significant structural damage especially along the coast of Ecuador. Tests of concrete and reinforcing bars taken from collapsed buildings aided at assessing the impact of materials properties on the behavior of buildings. The paper describes the statistics of damage sustained by schools following the ATC-20 scheme. A set of statistics are developed describing the scaling of damage with distance and PGA. The analyses showed that 30% of the buildings surrounding schools performed “Better” than them, and approximately 33% performed “Worse” than them. For those schools tagged under RESTRICTED USE and with UNSAFE placards, 44% of the surrounding buildings behave “Better” than them, and only 16% behaved “Worse”, indicating the need for a strong public policy to reduce vulnerability of school in Ecuador. Georeferenced data allow a spatial cross-correlation of different levels of damage observed with the ground motion intensity. This information may serve as benchmark for calibration of seismic risk models, and for post-earthquake risk comparison. Furthermore, regional seismic risk assessment may be calibrated with the results of the spatial cross-correlation analyses presented.

Investigating the sensitivity of losses to time-dependent components of seismic risk modeling

Conventional earthquake risk modeling involves several notable simplifications, which neglect: (1) the effects on seismicity of interactions between adjacent faults and the long-term elastic rebound behavior of faults; (2) short-term hazard increases associated with aftershocks; and (3) the accumulation of damage in assets due to the occurrence of multiple earthquakes in a short time window, without repairs. Several recent earthquake events (e.g. 2010–2011 Canterbury earthquakes, New Zealand; 2019 Ridgecrest earthquakes, USA; and 2023 Turkey–Syria earthquakes) have emphasized the need for risk models to account for the aforementioned short- and long-term time-dependent characteristics of earthquake risk. This study specifically investigates the sensitivity of monetary loss (i.e. a possible earthquake-risk-model output) to these time dependencies, for a case-study portfolio in Central Italy. The investigation is intended to provide important insights for the catastrophe risk insurance and reinsurance industry. In addition to salient catastrophe risk insurance features, the end-to-end approach for time-dependent earthquake risk modeling used in this study incorporates recent updates in long-term time-dependent fault modeling, aftershock forecasting, and vulnerability modeling that accounts for damage accumulation. The sensitivity analysis approach presented may provide valuable guidance on the importance and appropriate treatment of time dependencies in regional (i.e. portfolio) earthquake risk models. We find that the long-term fault and aftershock occurrence models are the most crucial features of a time-dependent seismic risk model to constrain, at least for the monetary loss metrics examined in this study. Accounting for damage accumulation is also found to be important, if there is a high insurance deductible associated with portfolio assets.

The communication strategy for the release of the first European Seismic Risk Model and the updated European Seismic Hazard Model

Abstract. To design user-centred and scientifically high-quality outreach products to inform about earthquake-related hazards and the associated risk, a close collaboration between the model developers and communication experts is needed. In this contribution, we present the communication strategy developed to support the public release of the first openly available European Seismic Risk Model and the updated European Seismic Hazard Model. The backbone of the strategy was the communication concept in which the overall vision, communication principles, target audiences (including personas), key messages, and products were defined. To fulfil the end-users' needs, we conducted two user testing surveys: one for the interactive risk map viewer and one for the risk poster with a special emphasis on the European earthquake risk map. To further ensure that the outreach products are not only understandable and attractive for different target groups but also adequate from a scientific point of view, a two-fold feedback mechanism involving experts in the field was implemented. Through a close collaboration with a network of communication specialists from other institutions supporting the release, additional feedback and exchange of knowledge was enabled. Our insights, gained as part of the release process, can support others in developing user-centred products reviewed by experts in the field to inform about hazard and risk models.

Evaluation of 23rd November 2022 Düzce Earthquake with Current European Seismic Hazard and Risk Model

Sismik aktivitesi yüksek olan Kuzey Anadolu Fayı Zonu (KAFZ) üzerinde yer alan Düzce ili, deprem tehlikesi yüksek bir bölge durumundadır. Bu bölgede yaşanan 17 Ağustos 1999 MW 7.6 Kocaeli depremi sonrasında Bolu-Düzce arasındaki Düzce fayı üzerindeki gerilme enerjisi 12 Kasım 1999 tarihinde açığa çıkarak MW 7.2 Düzce depremini meydana getirmiştir. 23 yıl sonra, bu bölgede KAFZ–Karadere Segmenti’nde, 23 Kasım 2022 günü Mw=5.9 büyüklüğünde ve merkez üssü Düzce-Gölyaka olan bir deprem meydana gelmiştir. 6.81 kilometre derinlikte kaydedilen bu deprem başta İstanbul ve Ankara olmak üzere Bolu, Sakarya, Kocaeli, Kütahya, Bilecik, Bursa ve İzmir'e kadar geniş bir alanda hissedilmiştir. Gölyaka ve Cumayeri ilçelerinde ve faya yakın yerlerdeki bazı köylerde hafif, orta ve yer yer ağır yapısal hasar meydana gelmiştir. Bu çalışmada, Düzce ilinin depremselliği, Güncel Avrupa Sismik Tehlike Modeli (ESHM20) kullanılarak olasılıksal sismik tehlike analizleriyle değerlendirilmiştir. 23 Kasım 2022 Mw 5.9 Gölyaka’da gerçekleşen deprem, AFAD istasyonlarına ait kayıtlar, güncel deprem tehlike modeli ve tasarım spektrumlarıyla birlikte değerlendirilmiştir. Olasılıksal sismik tehlike analizine bağlı sismik risk analizinde, Güncel Avrupa Sismik Risk Modelinde (ESRM20) Düzce ili için tanımlanan eski yönetmelik ve yeni yönetmelik uyumlu az ve orta katlı betonarme yapı sınıfları dikkate alınmıştır. Sismik tehlike analizine bağlı olarak Düzce ili için sismik risk değerlendirmesi kayıp eğrileri aracılığıyla gerçekleştirilmiştir.

Development of a seismic vulnerability and risk model for typical bridges considering innovative intensity measures

Seismic intensity measures are one of the core parameters for estimating regional bridges’ seismic risk and vulnerability. Using macroscopic seismic intensity indicators to predict and assess the seismic vulnerability of bridges can contribute positively to establishing urban and rural earthquake risk models. However, the developed vulnerability model rarely considers the contribution of instrument intensity to its quantification results and ignores the influence of nondamage bridge samples on the development of bridge risk models and the membership relationship between seismic vulnerability levels, which makes the developed model somewhat localized and uncertain. This study proposes a quantitative method and innovative model considering composite seismic intensity (instrumental and macroseismic intensity) indicators. The model was updated and validated using 300,000 acceleration records monitored by ten seismic stations during the Luding earthquake on September 5, 2022, in China, and the features of seismic motion parameters were analysed. The established empirical vulnerability dataset of bridges during the 2008 Wenchuan earthquake in China was updated and optimized using the developed models and methods. The traditional vulnerability level of bridges has been expanded by adding and refining actual samples (2317 bridges) from different seismic intensity zones. A vulnerability prediction model based on an updated extended bridge database was developed using nonlinear regression methods. A fragility membership index calculation model for estimating the correlation features of bridge vulnerability levels is proposed by combining the probability risk and fuzzy membership correlation algorithm. The traditional method for calculating the seismic vulnerability index has been improved, and a multiparameter bridge vulnerability model validation and rationality analysis have been conducted using the newly developed bridge sample dataset.

Impact of the Uncertainty in the Parameters of the Earthquake Occurrence Model on Loss Estimates of Urban Building Portfolios

Abstract Understanding the potential socioeconomic losses due to natural hazards, such as earthquakes, is of foremost importance in the field of catastrophe risk management. The construction of a probabilistic seismic risk model is complex and requires the tuning of several parameters essential to represent the seismic hazard of the region, the definition of the exposed inventory characteristics, and its vulnerability to ground motion. Because significant uncertainties could be associated with each model component, the loss estimates are often highly volatile. Nevertheless, to reduce the conceptual complexity and the computational burden, in many real-life applications these uncertainties are either not adequately treated or neglected altogether. The false high fidelity of the ensuing loss estimates can mislead decision-making strategies. Hence, it is useful to assess the influence that the variability in the estimated values of the model input parameters may exert on the final risk results and their relevant contributions. To this purpose, we have performed a sensitivity analysis of the results of an urban seismic risk assessment for Isfahan (Iran). Systematic variations have been applied to the values of the parameters that control the earthquake occurrence in the probabilistic seismic hazard model. Curves of input–output relative variations were built for different risk metrics with the goal of identifying the parameters most sensitive to input uncertainty. Our findings can be useful to support risk managers and practitioners in the process of building seismic hazard and risk models. We found that the Gutenberg–Richter a and b values, the maximum magnitude, and the threshold magnitude are large contributors to the variability of important risk measures, such as the 475 yr and the average annual loss, with the more frequent losses being, in general, most sensitive.

Improved seismic intensity measures and regional structural risk estimation models

Seismic intensity measures are essential quantitative parameters for evaluating and predicting engineering structures’ seismic risk and vulnerability. Various regional earthquake analysis and vulnerability models with evaluation and prediction capabilities have been developed using macroseismic and instrumental intensity measures. These results have significant positive implications for evaluating large-scale regional earthquake resilience and predicting earthquake risks. However, the traditional determination of seismic intensity measures is based on given seismic station detection data and macroscopic intensity standards, and the developed seismic risk models are relatively outdated, resulting in relatively low accuracy in assessing the vulnerability of regional structures. This paper proposed an improved instrumental intensity calculation equation and updated the model using 216,000 acceleration records monitored by nine typical seismic stations in China during the Jiuzhaigou earthquake on August 8, 2017. The proposed calculation model was combined with the latest version of China’s macrointensity standard, and undamaged building samples were sufficiently considered. The vulnerability level of 1,499 buildings surveyed in the Jiuzhaigou earthquake was assessed. This paper innovatively proposed a membership index calculation model to estimate the impact relationship between different vulnerability levels. A comparative curve model was generated with the updated vulnerability databases of four typical regional structures, considering different vulnerability membership indices. Using the improved seismic intensity measures and nonlinear regression model, an improved vulnerability fitting model was developed to assess the seismic risk of regional structures. The model was analysed and verified using field survey data from the Jiuzhaigou earthquake.

A national seismic risk model for Canada: Methodology and scientific basis

Canada is exposed to rare but potentially destructive earthquakes that threaten densely settled metropolitan centers in many parts of the country. To assess the impacts and consequences of future natural-hazard events and help advance policy goals and objectives of the Sendai Framework for Disaster Risk Reduction, Natural Resources Canada, through a collaborative partnership with the Global Earthquake Model Foundation, produced a national seismic risk model. Developing this model has required the creation of a national exposure inventory, Canadian-specific fragility and vulnerability curves, and significant simplification of the Canadian Seismic Hazard Model which forms the basis for the design seismic hazard values of the National Building Code of Canada. Using the Global Earthquake Model Foundation’s OpenQuake Engine, probabilistic stochastic risk modeling is completed under baseline and simulated retrofit conditions to assess seismic risk at the neighborhood level for all settled areas in Canada. Output risk metrics include the expected immediate physical impacts of earthquake events such as building damage, casualties, and direct economic losses. This article documents the technical details of the modeling approach including a description of novel data sets in use, a summary of the extensive sensitivity testing undertaken, and characterization of quality control implemented in the absence of usable validating earthquake loss data. The results from this model, such as loss exceedance curves and annual average losses, provide an open, accessible and quantitative base of evidence for decision-making at local, regional, and national levels. As a large country with a complex seismic hazard model and dispersed populations, this Canadian study is unique. However, the challenges faced and solutions offered are likely to be of interest to other nations pursuing similar programs.

The age and potential causes of the giant Green Lake Landslide, Fiordland, New Zealand

Landslide deposits preserved in the geological record afford opportunities to better inform hillslope and seismic hazard and risk models, particularly in regions where observational records are short. In the Southern Alps of New Zealand, small coseismic landslides are frequent, but the geological record preserves several instances of more substantial (> 1 km3) but infrequent mass failures. With an estimated volume of 27 km3, the giant Green Lake Landslide represents one of the largest subaerial landslides on Earth. Previous work has suggested this deep-seated mass movement was most likely triggered by high-intensity seismic shaking, but that local structural weakness and/or glacial debuttressing may help to explain the anomalously large failure volume. Resolving the potential contribution of the latter is important given predictions concerning alpine deglaciation in the coming decades to centuries. Key to resolution are secure chronologies of landslide emplacement and past glacier change. Here we present in situ cosmogenic 10Be exposure ages from the Green Lake Landslide that suggest an emplacement age of 15.5 ± 0.7 ka. Recent work shows that glacial retreat in the region was underway by 19 ka, indicating that the Green Lake Landslide was emplaced 3–4 kyr after the onset of glacier retreat. Given the geometry of the former confining valley glacier, we expect that the deglaciation-landslide age gap is closer to the upper end of this estimate. If correct, this conclusion places greater weight on the roles of local geological structure and/or a great earthquake as factors contributing to the exceptionally large volume of this event.

Seismic Design Codes—Key Elements for Seismic Risk Perception and Reduction in Europe

Earthquakes are one of the most costly and deadliest natural disasters. This perspective paper presents a discussion focused on the role of seismic design codes in risk perception and seismic risk reduction in Europe. The seismic design codes are a key component for both the design of new buildings, as well as for the vulnerability assessment of existing ones. The impact of seismic design codes on seismic risk reduction is discussed using as case-study countries, Italy, Turkey, Greece, and Romania, which according to the recent European seismic risk model 2020 have the largest expected mean annual losses due to earthquakes. The evaluation of the seismic exposure of the four countries shows that from the entire population of more than 170 million people, about 130 million live in buildings designed using no or low level seismic design. The mean annual expected losses due to earthquakes are of the order of 0.1–0.2% of the national GDP. Moreover, the mean annual death probability due to earthquakes is 10−6 which represents a risk level not of great concern to the average people. However, large earthquakes in Europe from the past 50 years have produced losses in excess of 10 billion Euros and several hundred thousand affected people. A solution for a better communication of seismic risk in order to increase seismic risk perception might be to provide exceedance probabilities of specific macroseismic intensity levels for time frames of 10 or 20 years, instead of annual values. Macroseismic levels from past earthquakes might be used in order to have a better understanding of the results and should complement the seismic design maps. In addition, in the case of seismic vulnerability, the use of simple terms (e.g., inhabitable or uninhabitable) along with their associated occurrence probabilities in the same time frame as in the case of the seismic hazard, might be a solution. Financial incentives for seismic strengthening, as well as a clear definition of an earthquake-prone building are also very useful for increasing seismic risk perception.

Modelling site response at regional scale for the 2020 European Seismic Risk Model (ESRM20)

Quantitative estimation of seismic risk over a region requires both an underlying probabilistic seismic hazard model and a means to characterise shallow site response over a large scale. The 2020 European Seismic Risk Model (ESRM20) builds on the 2020 European Seismic Hazard Model (ESHM20), requiring additional information to firstly parameterise the local site condition across all of Europe, and subsequently determine its influence on the prediction of seismic ground motion. Initially, a harmonised digital geological database for Europe is compiled, alongside a model of topographic/bathymetric elevation and a database of 30 m averaged shearwave velocity measurements (V_{S30}), in order to produce separate 30 arc-second maps of inferred V_{S30} based on topography and on geology. We then capitalise on a large database of seismic recording stations in Europe for which site-to-site ground motion residuals (delta S2S_{S}) have been determined with respect to the shallow crustal ground motion model used in the ESHM20. These residuals allow us to incorporate site amplification functions into the European GMM calibrated upon either observed or inferred V_{S30}, or on the European geology and topography models. We present the resulting pan-European seismic site amplification model and assess its impact on seismic hazard and risk compared against other approaches. The new site amplification model fulfils the requirements of the ESRM20 and, providing uncertainty is fully propagated, yields estimates of seismic hazard and risk at a large space scale that may be comparable to other methods often applied at local/urban scale where better-constrained site information is available.

Ground-motion prediction models for induced earthquakes in the Groningen gas field, the Netherlands

Small-magnitude earthquakes induced by gas production in the Groningen field in the Netherlands have prompted the development of seismic risk models that serve both to estimate the impact of these events and to explore the efficacy of different risk mitigation strategies. A core element of the risk modelling is ground-motion prediction models (GMPM) derived from an extensive database of recordings obtained from a dense network of accelerographs installed in the field. For the verification of damage claims, an empirical GMPM for peak ground velocity (PGV) has been developed, which predicts horizontal PGV as a function of local magnitude, ML; hypocentral distance, Rhyp; and the time-averaged shear-wave velocity over the upper 30 m, VS30. For modelling the risk due to potential induced and triggered earthquakes of larger magnitude, a GMPM for response spectral accelerations has been developed from regressions on the outputs from finite-rupture simulations of motions at a deeply buried rock horizon. The GMPM for rock motions is coupled with a zonation map defining frequency-dependent non-linear amplification factors to obtain estimates of surface motions in the region of thick deposits of soft soils. The GMPM for spectral accelerations is formulated within a logic-tree framework to capture the epistemic uncertainty associated with extrapolation from recordings of events of ML ≤ 3.6 to much larger magnitudes.

Integrating Long and Short‐Term Time Dependencies in Simulation‐Based Seismic Hazard Assessments

AbstractConventional probabilistic seismic hazard analysis (PSHA) only considers mainshock events and uses a time‐independent earthquake rupture forecast to describe the occurrence of mainshocks. This approach neglects the long‐term time‐dependency of mainshocks on specific fault segments, the interaction of adjacent faults, and the spatial and temporal clustering of aftershocks. This study integrates a recently proposed advanced fault‐based PSHA framework with an aftershock simulator based on the Epidemic‐Type Aftershock Sequence (ETAS) model, to overcome the aforementioned limitations. Central Italy is used as a case study to illustrate the proposed framework. The case‐study hazard curves show that including state‐of‐the‐art advances in fault‐based PSHA may increase the ground‐motion amplitudes for low return periods, and decrease the ground‐motion amplitudes for high return periods, relative to a conventional PSHA approach. The magnitude of ground‐motion estimate increases due to aftershock inclusion is dependent on the selected site and return period. Sensitivity analyses of the results demonstrate that: (a) close to modeled faults, high‐return‐period hazard estimates are more affected by fault‐related inputs than the aftershock inclusion; (b) close to modeled faults, the influence of aftershock inclusion is higher for low return periods than high ones; (c) away from modeled faults, aftershocks inclusion greatly affects the variance of the hazard results; and (d) fault interaction has a limited effect on the variance of the hazard estimates compared to other analysis inputs. This study could help with the future implementation of complex fault modeling approaches and aftershock hazard in seismic risk models.

An automated machine learning approach for earthquake casualty rate and economic loss prediction

This study presents an automated machine learning (AutoML) framework to predict the casualty rate and direct economic loss induced by earthquakes. The AutoML framework enables automated combined algorithm selection and hyperparameter tuning (CASH), reducing the manual works in the model development. The proposed AutoML framework includes 5 modules: data collection, data preprocessing, CASH, loss prediction, and model analysis. The AutoML models are learned from the dataset that is composed of earthquake information and social indicators. The optimal algorithm and hyperparameter setting of models are determined by the CASH module. A two-step model including a classifier and a regression model is designed for the casualty rate to address zero-casualty cases and also minimize their impacts on data distribution. The proposed AutoML framework is implemented on the seismic loss dataset of mainland China to demonstrate its practicability. A comparison study is conducted to show the high predictive abilities of the AutoML model compared with the traditional seismic risk model and other AutoML models. Models learned from the complete dataset achieve the ultimate performance compared with subsets that are composed of partial features. The model interpretation results indicate that earthquake magnitude, position, and population density are leading indicators for loss prediction.