The Dominican Republic experiences moderate to high seismic hazard mostly caused by oblique convergence at the Caribbean/North American plate boundary that manifests as subduction zones, less-pronounced subduction-like trenches with thrust faulting, long strike-slip faults parallel to the plate boundary, and onshore deformation. Historical earthquakes have damaged the Dominican Republic’s large cities and those in neighboring Haiti, once requiring relocation. Given this, the Dominican Republic joined the “Training and Communication for Earthquake Risk Assessment” (TREQ) project funded by the United States Agency for International Development, which aimed to increase earthquake risk assessment capacity in Latin American cities. The TREQ project was the basis for developing an openly available probabilistic seismic hazard model for the Dominican Republic. The input model was developed from two main datasets: a homogenized earthquake catalog and an active faults database that combines results of recent local projects with a global database. The seismic source characterization used these to constrain source geometries and occurrence rates for active shallow crustal earthquakes, subduction interfaces and subduction-like thrusts, and intraslab earthquakes. Shallow crustal earthquakes, including those on subduction-like thrusts, are modeled by smoothed seismicity and fault sources, the latter using pre-defined geometries that permit multi-fault ruptures. Seismicity on the Puerto Rico Trench subduction interface is modeled as a fault source, while intraslab sources use pre-defined gridded ruptures inside the intraslab volume. The source characterization applies epistemic uncertainties to modeling assumptions affecting occurrence rates and maximum magnitudes. The ground motion characterization used residual analyses from past regional projects as a basis, updating some components with more recent ground motion models. Computed hazard results reinforce those from recent studies in terms of geographical hazard patterns and levels. For 475-year return periods, peak ground acceleration (PGA) in Santiago de los Caballeros reaches 0.50 g, controlled by the Septentrional Fault, while all tectonic region types contribute to the PGA 0.31 g computed for Santo Domingo.

The Global Earthquake Model (GEM) is an initiative that originally emerged from discussions and proposals made by the Global Science Forum of the Organization for Economic Co-operation and Development (OECD) in the early 2000’s. In 2009, GEM established itself as a non-profit legal entity, the GEM Foundation, and 15 years later, it continues to operate globally with a mission to provide transparent resources for seismic hazard and risk assessment, as well as to support disaster risk reduction for a wide range of natural hazards. This paper highlights the main milestones from the past 15 years and the vision of the foundation to 2030. An overview is also provided of the status of GEM products and services, all of which are made available for the benefit of society, under a strategy that aims to assure the continued financial sustainability of the organization.

Fault slip rates estimated from geodetic data are being integrated into seismic hazard models. The standard approach requires modeling velocities and relative (micro-)plate motions, which is challenging for fault-based models. We present a new approach to directly invert strain rates to solve for slip rates and distributed strain simultaneously. We generate velocity and strain rate fields over the southeastern Tibetan Plateau, utilizing Sentinel-1 Interferometric Synthetic Aperture Radar data spanning 2014–2023. We derive slip rates using block modeling and by inverting strain rates. Our results show a partitioning between localized strain on faults and distributed deformation. The direct inversion of strain rates matches the geodetic data best when incorporating distributed moment sources, accounting for a similar proportion to on-fault sources. The direct strain methodology also aligns best with the independent geological slip rates, especially near fault tips. As high-resolution strain rate fields become increasingly available, we recommend direct inversion as the preferred practice.

The assessment of earthquake risk at the national scale is crucial for the design and implementation of risk reduction measures. Due to its location in the southwest of the Eurasian plate, Portugal is exposed to moderate to strong seismic events, such as the well-known 1755 Lisbon earthquake. We reviewed existing studies covering exposure, seismic hazard, vulnerability, and risk assessment for Portugal, and performed probabilistic seismic hazard and risk analyses for the country using new model components. These include a new exposure model developed for the residential building stock using the 2021 national Building Census Survey, a recent exposure model for commercial and industrial buildings, updated vulnerability functions for 116 building classes, and the recently released European Probabilistic Seismic Hazard model. The seismic risk results include average annual economic losses, fatalities, buildings with complete damage, and population left homeless. These results allowed the identification of the regions in Portugal with the highest earthquake risk, as well as which building classes contribute the most to the overall impact.

Strong seismic events frequently strike Chile. The last three significant events that caused considerable damage and losses are the 2010 ( 8.8, Maule), 2014 ( 8.2, Iquique), and 2015 ( 8.3, Illapel) earthquakes. Therefore, reliable fragility curves are necessary to evaluate the threat of earthquakes to the built environment. This study aims to develop empirical fragility curves of Chilean houses using damage from the 2014 and 2015 earthquakes. The data from 9085 and 7431 damaged houses from the 2014 and 2015 earthquakes, respectively, was obtained by the government. The fragility curves were estimated for reinforced concrete, reinforced masonry, timber, and adobe houses. Additionally, the fragility curves were constructed using three different Peak Ground Acceleration (PGA) maps to quantify the variation of the fragility parameters based on the selected PGA map and to identify which PGA map generates the highest correlation with observed damage. Additionally, fragility curves obtained in this study are compared with curves from other studies. The median values of the fragility curves obtained in this study are larger than those from other reported studies.

Reliable, high-quality risk assessment is the basis for an objective understanding of risk; priority for action 1 of the Sendai framework for disaster risk reduction 2015-2030. It is the foundation of decisions and actions that effectively build resilience. Earthquake risk continues to rise, yet reliable data, risk information, and assessment tools are out of reach or under-utilised in many areas of the world. The Global Earthquake Model (GEM Foundation) was created to bridge these critical gaps. Through authentic collaboration across public and private stakeholders, the GEM community supports risk management and awareness by developing and implementing open risk assessment tools, compiling and generating risk information. GEM influences risk reduction by promoting technology transfer and developing risk assessment capacity. All GEM risk assessment resources are made freely available through its web-based OpenQuake platform. As input to the Sendai framework, this paper provides an overview of GEM's achievements to date, lessons learnt - emphasizing effective modes of collaboration and capacity development -, and presents opportunities and challenges in going forward. This paper is from the Global Risk Forum Davos Planet@Risk Journal, which is no longer available.

The southern East African Rift System (EARS) is an early-stage continental rift with a deep seismogenic zone. It is associated with a low-to-moderate seismic hazard, but due to its short and sparse instrumental record, there is a lack of ground-motion studies in the region. Instead, seismic hazard assessments have commonly relied on a combination of active crustal and stable continental ground-motion models (GMMs) from other regions without accounting for the unusual geological setting of this region and evaluating their suitability. Here, we use a newly compiled southern EARS ground-motion database to compare six active crustal GMMs and four stable continental GMMs. We find that the active crustal GMMs tend to underestimate the ground-motion intensities observed, while the stable continental GMMs overestimate them. This is particularly pronounced in the high-frequency intensity measures (>5 Hz). We also use the referenced empirical approach and develop a new region-specific GMM for southern EARS. Both the ranked GMMs and our new GMM result in large residual variabilities, highlighting the need for local geotechnical information to better constrain site conditions.

The impact of destructive earthquakes might exceed the local capacity to cope with disasters and lead to an increase in the reconstruction costs. This phenomenon is commonly termed as post-loss amplification, and its main causes include the increase in the cost of construction materials and labor due to the sudden demand, the need to reconstruct following higher standards, or other unexpected costs. We reviewed 70 past earthquakes to identify events where post-loss amplification was observed, and collected a set of seismogenic, socio-economic, geographical, and impact variables for those events. Using this database, we developed two models to predict post-loss amplification, using a composite indicator that reflects the level of destruction in the region, or a parameter that characterizes the frequency of the event. This study indicates increased costs (>10%) for events where the economic losses exceed 1% of the regional gross domestic product, or for events with an estimated return period of at least 10 years. These models can be applied directly in the amplification of economic losses in earthquake scenarios or in probabilistic seismic risk assessment.

The calculation of the spatial distribution of ground motion is one of the most important steps in earthquake scenarios. The advancements in machine learning algorithms and the release of new ground motion data can enable improvements in the reliability and accuracy of this component. We developed an artificial neural network (ANN) ground motion model using a compiled database from two subsets with measured Vs30 from the Pan-European strong motion database and the NGA-West2 database. The ANN model employs five input parameters: moment magnitude (Mw), hypocentral depth, Joyner–Boore distance (Rjb), shear wave velocity in the top 30 m (Vs30), and faulting type. The outputs of the ANN are the RotD50 horizontal components of common intensity measures used in seismic risk assessment: PGA, PGD, PGV, Arias Intensity, and 5% damped spectral acceleration at 27 periods from 0.01 to 4.0 s. A mixed-effects modelling approach was followed to train the ANN and partition the ground motion variability into between-event and between-site terms. The input parameter scaling relationships were studied and demonstrated physically sound trends of the ground motion with respect to Mw scaling, distance attenuation, and site amplification. The predicted median response spectra for several combinations of Mw and Rjb were compared to common ground motion models for Europe, and the results are discussed. The developed ANN is used in a companion study to calculate the hazard footprints for several historical earthquakes in the Balkan region.

Seismic risk assessment of building portfolios has been traditionally performed using empirical ground motion models, and scalar fragility and vulnerability functions. The advent of machine learning algorithms in earthquake engineering and ground motion modelling has demonstrated promising advantages. The aim of the present study is to explore the benefits of employing artificial neural networks (ANNs) in earthquake scenarios for spatially-distributed building portfolios. To this end, several recent major seismic events in the Balkan region were selected to assess damage and economic losses, considering different modelling approaches. For the assessment of the seismic demand, the ANN developed in the companion study and common ground motion models for Europe were adopted. For the vulnerability component, recent ANN models and existing scalar fragility and vulnerability functions for the Balkans were used. The estimates of all modelling cases were compared against the aggregated damage and economic loss data observed in the aftermath of these events. The findings of this study suggest that overall, the ANNs led to damage and economic loss estimates closer to the observations.