Earthquake Early Warning (EEW) systems aim to alert users in advance of imminent shaking, enabling them to take action. In collaboration with local seismic agencies, the Swiss Seismological Service (SED), has developed national EEW systems across Central America. Public EEW alerts are now available, considering the frequent seismic activity and the vulnerability of the building stock, EEW has the potential to reduce casualties (i.e. fatalities and injuries). In this study, we build upon a probabilistic framework to quantify the potential benefits of EEW systems in reducing casualties. For each event generated in the stochastic catalog (100,000 event sets), we estimate the number of casualties in the absence of EEW. The framework evaluates the potential casualty reduction attributable to an operational EEW system, considering the expected warning times in each event at the target site, the subsequent actions taken upon receiving the alert, and system performance. For a return period of 475 years, the fatality reduction could reach ∼14% to 17% corresponding to hundreds fewer fatalities in Costa Rica and Nicaragua, and thousands fewer fatalities in El Salvador and Guatemala. From this baseline scenario, we explore strategies to improve casualty reduction: (1) increase warning time by densifying the seismic network; and (2) compare the effectiveness of Drop, Cover, And Hold On (DCHO) versus evacuation as recommended protective actions. Our results suggest that evacuation is a suitable strategy for reducing fatalities in this region, given the prevalence of single-story structures. Given the available warning time, evacuation is advised for occupants on the first floor, and those on upper floors should adopt DCHO. Our findings indicate that the implementation of EEW leads to a ∼10% reduction in average annual fatalities. A cost–benefit analysis reveals that the economic benefits of public EEW systems significantly outweigh the associated costs, making EEW a cost-effective mitigation strategy.

Abstract. 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.

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.

With seismic risk assessments becoming more available and reliable over the last years, the need to communicate seismic risk emerged. Seismic risk allows people to understand what impacts earthquakes can have and how they could affect their lives. In Switzerland, a nation-wide seismic risk model (ERM-CH23) was published in 2023 demanding sophisticated communication products to inform about its results. Since only limited research has been conducted on how to best communicate earthquake risk information to societies including the general public, key elements of the outreach activities were tested before the model release. To this end, we, an interdisciplinary group, conducted a nationwide survey in Switzerland in December 2022 to test different earthquake risk map designs by varying the color scale and the legend type. We analyzed the effects of the map and legend design on people's correct interpretation of the risk information, perceived usefulness, risk perception, and motivation to take action. Our survey revealed that (i) a legend with the combination of qualitative and quantitative labels leads to more accurate interpretations of the information presented on the map and is preferred by the public; (ii) the color scale determines how people perceive the spatial risk; and (iii) personal factors influence people's interpretation skills, risk perception, and intention to take action. Our study thus provides insights and recommendations on how to best design user-centered earthquake risk maps as a key outreach product to ensure their effective use by the public, consequently enhancing society's resilience to earthquakes in the long term.

Risk-based earthquake scenarios and rapid impact assessments can meaningfully improve how societies prepare for and deal with earthquakes. However, this is only the case when they are understood and perceived as useful to support mitigation and recovery actions. In this study, we are among the first to empirically assess how to best design earthquake scenarios and rapid impact assessment meeting the needs of different target audiences. We applied a transdisciplinary, iterative process involving a literature review, expert interviews, workshops with professional stakeholders, and internal reviews to design and improve the scenario and rapid impact assessment that were then tested in a representative survey with the Swiss public (N = 580). The results demonstrate a high perceived importance among all users groups for these products as well as advanced levels of comprehension. A focus was set on depicting uncertainties showing that the most simple visualization only using ranges was best understood and most liked. This supposes that the histograms predominantly used in existing outlets need to be reconsidered. Professional stakeholders and the public were further similarly challenged by more complex visualizations. The public survey further revealed the importance of the cartographic information as a supposedly relevant proxy to answer questions with a geographical reference and a requirement to improve the current version.

Earthquake early warning systems (EEWSs) aim to rapidly detect earthquakes and provide timely alerts, so that users can take protective actions prior to the onset of strong ground shaking. The promise and limitations of EEWSs have both been widely debated. On one hand, an operational EEWS could mitigate earthquake damage by triggering potentially cost- and life-saving actions. These range from automated system responses such as slowing down trains to the actions of individuals that receive the alerts and take protective measures. On the other hand, the effectiveness of an EEWS is conditional on the ability to issue warnings that are sufficiently accurate and timely to facilitate an appropriate action. The refinement of earthquake early warning (EEW) algorithms and the installation of denser and faster seismic networks have improved performance; however, the benefit in risk reduction that an EEWS could achieve remains unquantified. In this study, we leverage upon regional event-based probabilistic seismic risk assessment to devise a quantitative and fully customizable framework for evaluating the effectiveness of EEW in mitigating seismic risk. We demonstrate this framework using Switzerland as a testbed, for which we compute and contrast human loss exceedance curves with and without EEW.

Abstract Subaqueous mass movements can trigger tsunami waves not only in the oceans, but also on lakes. For a few Swiss perialpine lakes, tsunamis have been documented in historical reports (e.g. Cysat 1969; Favrod 1991), mainly caused by earthquake-triggered subaqueous mass movements. In addition, results from numerical modelling show that tsunamis may occur again on perialpine lakes (e.g. Hilbe and Anselmetti 2015). To be prepared for such events, a quantitative risk assessment is essential. Although several authors have tried to quantify marine tsunami risk, the possible impact of lake tsunamis remains understudied. Herein, we leverage recent work that modeled possible earthquake-triggered mass movement tsunami scenarios on the well-investigated Lake Lucerne in Switzerland and proceed to obtain some fist-order estimates of possible earthquake- and tsunami-induced economic losses. We use tsunami intensity footprints, in terms of flow depth and momentum flux, conditional on subaqueous mass movements triggered by 475- and 2475-year ground motions. These are overlaid with the built exposure at the village of Buochs-Ennetbürgen, located at the shore of Lake Lucerne. Earthquake and tsunami damage is computed based on fragility and consequence information retrieved from the Earthquake Risk Model of Switzerland (ERM-CH23) and the HAZUS tsunami model. Earthquake and tsunami losses are further contrasted and discussed. This work provides a first analysis of the tsunami risk around perialpine lakes.

ABSTRACT Traditionally, probabilistic seismic hazard analysis (PSHA) considers only mainshock events and models their temporal occurrence through a homogeneous Poisson process. Thus, it disregards foreshocks and aftershocks, assuming they have a minor effect on PSHA. However, recent earthquake sequences, such as those in 2016–2017 in Central Italy and 2010–2011 in Christchurch, New Zealand, exposed the shortcomings of such a universally used but unconservative approach. Our efforts to quantify the bias in seismic hazard and risk estimates follow from these considerations. Herein, we investigate the epidemic-type aftershock sequence (ETAS) model’s ability to reproduce the statistical features of long-term historical seismicity in Italy in two different regions. In addition, we calculate and compare the seismic hazard at two sites in Central Italy using different approaches: (1) with seismicity clustering modeled using the ETAS model; (2) with only mainshocks modeled by means of the Poissonian approach; and (3) with seismicity clustering modeled via a combination of Poisson and modified Omori law. We consider two cases: (1) the “unconditional case,” which uses years of varying seismicity as initial conditions and, therefore, can be considered as a tool for predicting the long-term average hazard, and (2) “conditional case,” in which the hazard is estimated after a specific period, in our case higher than average seismicity. We scrutinize the different modeling assumptions during the process and investigate the effect of using different declustering methods in Poisson-based models. As expected, we find that using the mainshock-only seismicity models yields lower hazard estimates compared to those obtained with the Omori and ETAS model. In addition, we show that Omori and ETAS model predict similar results in the unconditional case, but the Omori model considerably underpredicts the hazard in the conditional case, for a site close to the sequences, when temporal variations in seismic hazard are accounted for.

ABSTRACT The goal of earthquake early warning (EEW) is to issue an alert before the damaging seismic waves of an earthquake hit a given exposure. We develop a framework to evaluate the EEW performance in a loss-based context. We use warning time as a key performance indicator and determine statistics of warning time by loss severity to assess the rate and consistency with which an EEW system can deliver timely alerts. In the second part of this work, we develop a Genetic Algorithm approach to optimize an existing sensor network by proposing sites for new stations to enhance the EEW performance in damaging earthquakes. We demonstrate this framework for Switzerland using 2000 realizations of a 50-yr-long stochastic earthquake catalog, which samples the earthquake rate forecast of the Swiss Hazard Model in space and time. For each of the almost 24k earthquake scenario ruptures (5.0 ≤ M ≤ 7.4), we predict shaking intensities and losses (here, fatalities and injuries) at the largest Swiss cities. We find that the current Swiss Seismic Network could provide positive warning times to the affected sites for about 80% of very damaging earthquakes (≥100 fatalities) and for around 85% of earthquakes with ≥10 fatalities. Warning times of >5 s could be achieved for about 40%–55% of very damaging earthquakes and >10 s for about 35%. For around 50% of events with ≥1 fatality (≥10 injuries), EEW could provide >15 s of warning. The greatest benefit of EEW is expected in Zürich, where the population density and, consequently, absolute long-term expected losses are highest and the warning times for damaging earthquakes are often long (>15 s). Densifying the Swiss Seismic Network with additional stations can increase warning times in selected scenarios by up to 5 s. However, because it is already very dense (7 ± 5 km interstation distance), decreasing data latencies (currently ∼2 s) may be more important.

AbstractMathematical risk assessment models based on empirical data and supported by the principles of physics and engineering have been used in the insurance industry for more than three decades to support informed decisions for a wide variety of purposes, including insurance and reinsurance pricing. To supplement scarce data from historical events, these models provide loss estimates caused to portfolios of structures by simulated but realistic scenarios of future events with estimated annual rates of occurrence. The reliability of these estimates has evolved steadily from those based on the rather simplistic and, in many aspects, semi-deterministic approaches adopted in the very early days to those of the more recent models underpinned by a larger wealth of data and fully probabilistic methodologies. Despite the unquestionable progress, several modeling decisions and techniques still routinely adopted in commercial models warrant more careful scrutiny because of their potential to cause biased results. In this chapter we will address two such cases that pertain to the risk assessment for earthquakes. With the help of some illustrative but simple applications we will first motivate our concerns with the current state of practice in modeling earthquake occurrence and building vulnerability for portfolio risk assessment. We will then provide recommendations for moving towards a more comprehensive, and arguably superior, approach to earthquake risk modeling that capitalizes on the progress recently made in risk assessment of single buildings. In addition to these two upgrades, which in our opinion are ready for implementation in commercial models, we will also describe an enhancement in ground motion prediction that will certainly be considered in the models of tomorrow but is not yet ready for primetime. These changes are implemented in example applications that highlight their importance for portfolio risk assessment. Special consideration will be given to the potential bias in the Average Annual Loss estimates, which constitutes the foundation of insurance and reinsurance policies’ pricing, that may result from the application of the traditional approaches.

In current practice, most earthquake risk models adopt a “declustered” view of seismicity, that is, they disregard foreshock, aftershock, and triggered earthquakes and model seismicity as a series of independent mainshock events, whose occurrence (typically) conforms to a Poisson process. This practice is certainly disputable but has been justified by the false notion that earthquakes of smaller magnitude than the mainshock cannot induce further damage than what was caused by the latter. A companion paper makes use of the epidemic-type aftershock sequence (ETAS) model fitted to Central Italy seismicity data to describe the full earthquake occurrence process, including “dependent” earthquakes. Herein, loss estimates for the region of Umbria in Central Italy are derived using stochastic event catalogs generated by means of the ETAS model and damage-dependent fragility functions to track damage accumulation. The results are then compared with estimates obtained with a conventional Poisson-based model. The potential gains of utilizing a model capable of capturing the spatiotemporal clustering features of seismicity are illustrated along with a discussion on the various details and challenges of such considerations.

We present correlation coefficient estimates between a number of ground motion intensity measures ( IM s), as measured from the NGA-West2 database, with focus on the correlation of vertical–vertical and vertical–horizontal ground motion components. The IM s considered include spectral accelerations with periods from 0.01 to 10 s, peak ground acceleration, peak ground velocity, and significant duration (for 5%–75% and 5%–95% definitions). To facilitate their use, parametric equations are also fitted to the correlation models. Finally, the dependence of the obtained correlation coefficients to magnitude, distance, and Vs 30 is evaluated.

In recent years, the additional risk posed to the built environment due to aftershock sequences and triggered events has been brought to attention, and several efforts have been directed towards developing fragility functions for structures in damaged conditions. Despite this rise of interest, a rather fundamental component for such tasks, namely that of aftershock ground motion record selection, has remained under-scrutinized. Herein, we propose a pragmatic procedure that can be applied for the selection of mainshock-aftershock ground motion pairs using consistent causal parameters and accounting for the correlation between their spectral accelerations. In addition, a structural analysis strategy that can be employed for the analytical derivation of damage-dependent fragility functions is outlined and presented through a case study. A more conventional back-to-back IDA analysis is also carried out in order to compare the derived damage-dependent fragility functions with the ones obtained with the proposed procedure. The results indicate that record selection remains a crucial factor even when assessing the structural vulnerability of damaged buildings, and should thus be treated cautiously.

This study examines the statistical correlation between the spectral accelerations of mainshock-aftershock ground motion pairs in the NGA-West2 ground motion database. Aftershock spectral accelerations are found mildly correlated with their mainshock counterparts for closely spaced periods of vibration and are weakly correlated over the rest of the period range. We further investigate for potential differences between the interperiod correlations of mainshock and aftershock spectral accelerations, finding no substantial evidence to support the use of different models for the two cases. Furthermore, the impact of different rupture scenario parameters on correlation is examined and discussed. The derived correlation estimates are expected to aid in aftershock seismic hazard assessment and/or in record selection for risk assessment applications by using the mainshock spectral ordinates to obtain better predictions for the aftershock ground motion.

The quantification of seismic performance, using metrics meaningful to both engineers and stakeholders, has been a focal point of research in performance-based earthquake engineering. The prevalent paradigm is currently offered by the FEMA P-58 guidelines in the form of a component-by-component approach that provides detailed assessment capabilities at the cost of requiring a complete inventory of the structural, nonstructural, and content components. In an attempt for simplification, a fully compatible story-by-story approach is offered instead, where story loss functions are employed to directly relate monetary losses to engineering demand parameters given the story area. These functions can be adjusted for application to different situations, assuming the ratio of cost and quantity of each component category inventory remains relatively constant. As an example, they are generated for a standard inventory makeup, characteristic of low/mid-rise steel office buildings. They are shown to offer a favorable compromise of simplicity and accuracy that lies between the component-by-component and building-level approaches that are currently prevalent in building-specific and regional loss assessment, respectively.

Earthquake occurrence in probabilistic seismic hazard analysis (PSHA) is routinely modeled by means of a Poisson process. The latter is a “memory-less” process, i.e. it maintains a constant rate in time and space. To this end, aftershock and triggered events, whose occurrence is strongly timeand space-dependent, are typically removed from the catalogues of past seismicity employed in most PSHA studies. This practice may be justifiable when applied to produce ground motion hazard maps for design but the notion that mainshock events can be considered representative of the damage potential of seismic sequences is questionable. Herein, we model seismicity as an epidemic-type aftershock sequence (ETAS) process which has been established as a standard tool for short-term seismicity forecasts. Regional loss estimates for the region of Umbria in Central Italy are calculated by means of ETAS-generated catalogues and compared with the results of a conventional, seismically fully consistent Poisson-based model. We further explore different forms and parameterizations of the ETAS model and investigate how some modelling choices, routinely applied in the literature, affect the final risk metrics. Preliminary results show that accounting for aftershock and triggered events in seismic risk assessment can lead to a substantial increase in loss estimates.

Since their release in 2012, the FEMA P-58 guidelines for seismic performance assessment of buildings have been regarded as the state-of-the-art paradigm for buildingspecific risk assessment and loss estimation.The latter is carried out through a rigorous component-by-component procedure that requires a complete component inventory, along with fragility and repair cost information.A fully compatible story-based approach is investigated herein as a simplified alternative that can potentially reduce the required input data with only a minor drop in accuracy.As an example, a set of story loss functions relating story repair cost with story-level engineering demand parameters are derived for standard inventory makeups of low/midrise steel office buildings.Preliminary results for a 4-story steel building show a promising balance between accuracy and simplicity.