Laurentiu Danciu’s research while affiliated with ETH Zurich and other places

Earthquake hazard analyses rely on seismogenic source models. These are designed in various fashions, such as point sources or area sources, but the most effective is the three-dimensional representation of geological faults. We here refer to such models as fault sources. This study presents the European Fault-Source Model 2020 (EFSM20), which was one of the primary input datasets of the recently released European Seismic Hazard Model 2020. The EFSM20 compilation was entirely based on reusable data from existing active fault regional compilations that were first blended and harmonized and then augmented by a set of derived parameters. These additional parameters were devised to enable users to formulate earthquake rate forecasts based on a seismic-moment balancing approach. EFSM20 considers two main categories of seismogenic faults: crustal faults and subduction systems, which include the subduction interface and intraslab faults. The compiled dataset covers an area from the Mid-Atlantic Ridge to the Caucasus and from northern Africa to Iceland. It includes 1248 crustal faults spanning a total length of ∼95100 km and four subduction systems, namely the Gibraltar, Calabrian, Hellenic, and Cyprus arcs, for a total length of ∼2120 km. The model focuses on an area encompassing a buffer of 300 km around all European countries (except for Overseas Countries and Territories) and a maximum of 300 km depth for the subducting slabs. All the parameters required to develop a seismic source model for earthquake hazard analysis were determined for crustal faults and subduction systems. A statistical distribution of relevant seismotectonic parameters, such as faulting mechanisms, slip rates, moment rates, and prospective maximum magnitudes, is presented and discussed to address unsettled points in view of future updates and improvements. The dataset, identified by the DOI https://doi.org/10.13127/efsm20 (Basili et al., 2022), is distributed as machine-readable files using open standards (Open Geospatial Consortium).

Understanding seismic risk at both the national and sub-national level is essential for devising effective strategies and interventions aimed at its mitigation. The Earthquake Risk Model of Switzerland (ERM-CH23), released in early 2023, is the culmination of a multidisciplinary effort aiming to achieve for the first time a comprehensive assessment of the potential consequences of earthquakes on the Swiss building stock and population. Having been developed as a national model, ERM-CH23 relies on very high-resolution site-amplification and building exposure datasets, which distinguishes it from most regional models to date. Several loss types are evaluated, ranging from structural–nonstructural and content economic losses to human losses, such as deaths, injuries, and displaced population. In this paper, we offer a snapshot of ERM-CH23, summarize key details on the development of its components, highlight important results, and provide comparisons with other models.

The 2020 update of the European Seismic Hazard Model (ESHM20) is the most recent and up-to-date assessment of seismic hazard for the Euro-Mediterranean region. The new model, publicly released in May 2022, incorporates refined and cross-border harmonized earthquake catalogues, homogeneous tectonic zonation, updated active fault datasets and geological information, complex subduction sources, updated area source models, a smoothed seismicity model with an adaptive kernel optimized within each tectonic region, and a novel ground motion characteristic model. ESHM20 supersedes the 2013 European Seismic Hazard Model (ESHM13; Woessner et al., 2015) and provides full sets of hazard outputs such as hazard curves, maps, and uniform hazard spectra for the Euro-Mediterranean region. The model provides two informative hazard maps that will serve as a reference for the forthcoming revision of the European Seismic Design Code (CEN EC8) and provides input to the first earthquake risk model for Europe (Crowley et al., 2021). ESHM20 will continue to evolve and act as a key resource for supporting earthquake preparedness and resilience throughout the Euro-Mediterranean region under the umbrella of the European Facilities for Seismic Hazard and Risk consortium (EFEHR Consortium).

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.

The process of choosing ground motions typically relies on assembling a collection of ground motions that match a desired spectrum. This selection process is guided by specific seismological criteria, including factors like earthquake magnitude, distance from the epicenter, site soil type, and the range of spectral periods that need to fit with the target spectrum. The selection algorithm and the available dataset of waveforms obviously play significant roles in this process. In many engineering and site response applications, it is essential that the input ground motion is representative for the shaking at the free surface of the Earth, and at times also a specific soil type may be required. However, real waveform databases often lack sufficient and/or consistent metadata related to the installation type and soil characterization of recording stations, as well as to the earthquake seismological parameters. This deficiency can lead to the selection of inappropriate waveforms, such as those recorded by stations situated within manmade structures (buildings, bridges, dams) or on a soil type different than the intended one. To address this issue, our approach for creating an appropriate waveform database applicable to Switzerland starts with the computation of seismic hazard disaggregation for return periods of 475 and 975 years. This computation helps identifying the magnitude-distance scenarios most relevant for the five seismic hazard zones defined in the Swiss building code. Once these magnitude-distance ranges are identified, we adhere to established standards regarding the quality control of three-component waveforms and their associated metadata. We assemble a database of waveforms by collating and homogenizing data from available global databases. In the interest of comprehensiveness, we also incorporate data obtained from 3D physics-based numerical simulations of strong-motion near the seismic source. Finally, we employ an algorithm that integrates the Eurocode 8 waveform selection criteria. This algorithm allows us to select and scale waveforms suitable for microzonation and structural analysis studies within each of Switzerland’s five seismic hazard zones. Selecting waveforms compatible with the target design spectra proves to be challenging due to the stringent criteria imposed by Eurocode 8. This challenge arises from the scarcity of recorded waveforms with verified metadata and precise site characterization in the desired magnitude-distance ranges.

The primary aim of this research is to investigate how geodetic monitoring can offer valuable constraints to enhance the accuracy of the source model in probabilistic seismic hazard assessment. We leverage the release of geodetic strain rate maps for Europe, as derived by Piña-Valdès et al. (2022), and the ESHM20 source model by Danciu et al. (2024) to compare geodetic and seismic moment rates across Europe, a geographically extensive region characterized by heterogeneous seismic activity. Seismic moment computation relies on the magnitude-frequency distribution proposed in the ESHM20 source model logic tree, which is based on earthquake catalogs and fault datasets. This approach allows us to account for epistemic uncertainties proposed in ESHM20. On the geodesy side, we meticulously calculate the geodetic moment for each zone, considering associated epistemic uncertainties. Comparing the distributions of geodetic and seismic moments rates at different scales allows us to assess compatibility. The geodetic moment rate linearly depends of the seismogenic thickness, that is therefore a pivotal parameter contributing to the uncertainty. In high-activity zones, such as the Apennines, Greece, the Balkans, and the Betics, primary compatibility between seismic and geodetic moment rates is evident. However, local disparities underscore the importance of source zone scale; broader zones enhance the overlap between geodetic and seismic moment rate distributions. Discrepancies emerge in low-to-moderate activity zones, particularly in areas affected by Scandinavian Glacial Isostatic Adjustment, where geodetic moment rates exceed seismic moment rates significantly. Nevertheless, in some zones where ESHM20 recurrence models are well-constrained, by either enough seismic events in the catalogue or mapped active faults, we observe an overlap in the distributions of seismic and geodetic moments, suggesting the potential for integrating geodetic data even in regions with low deformation.

Current practice in strong ground motion modelling for probabilistic seismic hazard analysis (PSHA) requires the identification and calibration of empirical models appropriate to the tectonic regimes within the region of application, along with quantification of both their aleatory and epistemic uncertainties. For the development of the 2020 European Seismic Hazard Model (ESHM20) a novel approach for ground motion characterisation was adopted based on the concept of a regionalised scaled-backbone model, wherein a single appropriate ground motion model (GMM) is identified for use in PSHA, to which adjustments or scaling factors are then applied to account for epistemic uncertainty in the underlying seismological properties of the region of interest. While the theory and development of the regionalised scaled-backbone GMM concept have been discussed in earlier publications, implementation in the final ESHM20 required further refinements to the shallow-seismicity GMM in three regions, which were undertaken considering new data and insights gained from the feedback provided by experts in several regions of Europe: France, Portugal and Iceland. Exploration of the geophysical characteristics of these regions and analysis of additional ground motion records prompted recalibrations of the GMM logic tree and/or modifications to the proposed regionalisation. These modifications illustrate how the ESHM20 GMM logic tree can still be refined and adapted to different regions based on new ground motion data and/or expert judgement, without diverging from the proposed regionalised scaled-backbone GMM framework. In addition to the regions of crustal seismicity, the scaled-backbone approach needed to be adapted to earthquakes occurring in Europe's subduction zones and to the Vrancea deep seismogenic source region. Using a novel fuzzy methodology to classify earthquakes according to different seismic regimes within the subduction system, we compare ground motion records from non-crustal earthquakes to existing subduction GMMs and identify a suitable-backbone GMM for application to subduction and deep seismic sources in Europe. The observed ground motion records from moderate- and small-magnitude earthquakes allow us to calibrate the anelastic attenuation of the backbone GMM specifically for the eastern Mediterranean region. Epistemic uncertainty is then calibrated based on the global variability in source and attenuation characteristics of subduction GMMs. With the ESHM20 now completed, we reflect on the lessons learned from implementing this new approach in regional-scale PSHA and highlight where we hope to see new developments and improvements to the characterisation of ground motion in future generations of the European Seismic Hazard Model.

Exposure models for regional seismic risk assessment often place assets at the centroids of administrative units for which data are available. At best, a top-down approach is followed, where such data are spatially disaggregated over a denser spatial grid, using proxy datasets such as the distribution of population or the density of night-time lights. The resolution of the spatial grid is either dictated by the resolution of the proxy dataset, or by constraints in computational resources. On the other hand, if a building-by-building database is available, it often needs to be aggregated and brought to a resolution that ensures acceptable calculation runtimes and memory demands. Several studies have now investigated the impact of exposure aggregation on loss estimates. Herein, unlike previous attempts, we can leverage upon an extensive building-by-building database for the Swiss territory, which we can use as ground truth. We firstly proceed to assess the aggregation-induced errors of standard risk metrics at different spatial scales. Then a new strategy for performing said aggregation is proposed, relying on a K-means clustering of site parameters and a reduction of the loss ratio uncertainty for aggregated assets. These interventions are designed with the objective of minimizing errors, while keeping the computational cost manageable.

The Greek National Annex for current Eurocode 8 has adopted the seismic hazard zonation map published in 2003 as part of the modifications to the Greek Seismic Code EAK 2000 (EAK 2003). This map, which followed the catastrophic earthquakes that hit the country between 1978 and 2001, includes three seismic hazard zones with peak ground acceleration (PGA) ranging between 0.16 and 0.36 g. In this paper, following the significant progress that has been made worldwide in the last two decades towards the improvement of the definition of seismic actions and the seismic hazard maps using fully probabilistic models, we make a complete proposal for the Greek National Annex of the ongoing revision of Eurocode 8, which includes a new seismic hazard zonation map for Greece, as well as a novel site categorization scheme and related site amplification factors. To this end, we use the results of the European Seismic Hazard Model, ESHM20, as reported by Danciu et al. (The 2020 update of the European Seismic Hazard Model: Model Overview, 2021) which will be adopted as informative reference for the seismic hazard at European level in the forthcoming revision of Eurocode 8 (CEN/EC8). The herein proposed ground shaking zonation for rock conditions includes five zones with PGA values ranging between 0.13 and 0.37 g. For each zone, two newly proposed ground motion parameters, i.e., Sα,475 and Sβ,475, are provided, which are the two parameters used for anchoring the elastic response spectrum as defined in CEN/EC8, along with all the other necessary parameters for the definition of the elastic response spectrum, including site amplification. The proposal for the new seismic zonation is supported by a preliminary investigation of the impact of its adoption on the seismic design of new structures and on the seismic risk of the current building stock in Greece, to help gain a better insight on how important the differences imposed by the new zonation might be for the end-users and the administration.

When new seismic hazard estimates are published it is natural to compare them to existing results for the same location. This type of comparison routinely indicates differences amongst hazard estimates obtained with the various models. The question that then arises is whether these differences are scientifically significant, given the large epistemic uncertainties inherent in all seismic hazard estimates, or practically important, given the use of hazard models as inputs to risk and engineering calculations. A difference that exceeds a given threshold could mean that building codes may need updating, risk models for insurance purposes may need to be revised, or emergency management procedures revisited. In the current literature there is little guidance on what constitutes a significant or important difference, which can lead to lengthy discussions amongst hazard modellers, end users and stakeholders. This study reviews proposals in the literature on this topic and examines how applicable these proposals are, using, for illustration purposes, several sites and various seismic hazard models for each site, including the two European Seismic Hazard Models of 2013 and 2020. The implications of differences in hazard for risk and engineering purposes are also examined to understand how important such differences are for potential end users of seismic hazard models. Based on this, we discuss the relevance of such methods to determine the scientific significance and practical importance of differences between seismic hazard estimates and identify some open questions. We conclude that there is no universal criterion for assessing differences between seismic hazard results and that the recommended approach depends on the context. Finally, we highlight where additional work is required on this topic and that we encourage further discussion of this topic.