The assessment of the seismic risk at a national scale represents an important resource in order to introduce measures that may reduce potential losses due to future earthquakes. This evaluation results from the combination of three components: seismic hazard, structural vulnerability and exposure data. In this study, a review of existing studies focusing on each one of these areas is carried out, and used together with data from the 2011 Building Census in Portugal to compile the required input models for the evaluation of seismic hazard and risk. In order to better characterize the epistemic uncertainty in the calculations, several approaches are considered within a logic tree structure, such as the consideration of different seismic source zonations, the employment of vulnerability functions derived based on various damage criteria and the employment of distinct spatial resolutions in the exposure model. The aim of this paper is thus to provide an overview of the recent developments regarding the different aspects that influence the seismic hazard and risk in Portugal, as well as an up-to-date identification of the regions that are more vulnerable to earthquakes, together with the expected losses for a probability of exceedance of 10 % in 50 years. The results from the present study were obtained through the OpenQuake engine, the open-source software for seismic risk and hazard assessment developed within the global earthquake model (GEM) initiative.

The lack of empirical data regarding earthquake damage or losses has propelled the development of dozens of analytical methodologies for the derivation of fragility and vulnerability functions. Each method will naturally have its strengths and weaknesses, which will consequently affect the associated risk estimates. With the purpose of sharing knowledge on vulnerability modeling, identifying shortcomings in the existing methods, and recommending improvements to the current practice, a group of vulnerability experts met in Pavia (Italy) in April 2017. Critical topics related to the selection of ground motion records, modeling of complex real structures through simplified approaches, propagation of aleatory and epistemic uncertainties, and validation of vulnerability results were discussed, and suggestions were proposed to improve the reliability and accuracy in vulnerability modeling.

The Philippine archipelago is tectonically complex and seismically hazardous, yet few seismic hazard assessments have provided national coverage. This article presents an updated probabilistic seismic hazard analysis for the nation. Active shallow crustal seismicity is modeled by faults and gridded point sources accounting for spatially variable occurrence rates. Subduction interfaces are modeled with faults of complex geometry. Intraslab seismicity is modeled by ruptures confined to the slab volume. Source geometries and earthquake rates are derived from seismicity catalogs, geophysical data sets, and historic-to-paleoseismic constraints on fault slip rates. The ground motion characterization includes models designed for global use, with partial constraint by residual analysis. Shallow crustal faulting near metropolitan Manila, Davao, and Cebu dominates shaking hazard. In a few places, peak ground acceleration with 10% probability of exceedance in 50 years on rock reaches 1.0g. The results of this study may have utility for defining the design base shear in the National Structural Code of the Philippines.

Building exposure and vulnerability models for seismic risk assessment have been the focus of a number of European projects in recent years, but there has never been a concerted effort among the research community to produce a uniform European risk model. The European Commission’s Horizon 2020 SERA project has a work package that is dedicated to that objective, through the development of an exposure model, an associated set of fragility/vulnerability models, and a database of socioeconomic indicators in order to calculate probabilistic integrated seismic risk at a European scale. This article provides details of the development of the first versions of the European exposure model that describe the distribution of the main residential, industrial and commercial building classes across all countries in Europe, as well as their occupants and replacement costs. The v0.1 of the European exposure model has been integrated within the Global Earthquake Model’s global exposure and risk maps. Preliminary analyses using the model show that almost 35% of the residential population in Europe is exposed to a 475-year return period peak ground acceleration (PGA) hazard of at least 0.1 g, thus highlighting the importance of European seismic risk modeling and mitigation.

This study presents a seismic risk assessment and a set of earthquake scenarios for the residential building stock of the three largest metropolitan centers of Colombia: Bogotá, Medellín and Cali (with 8.0, 2.5, and 2.4 million inhabitants, respectively). A uniform methodology was followed for the development of the seismic hazard, vulnerability, and exposure models, thus allowing a direct comparison between the seismic risk of the different cities. Risk metrics such as exceedance probability curves and average annual losses were computed for each city. The earthquake scenarios were selected considering events whose direct economic impact is similar to the aggregated loss for a probability of exceedance of 10% in 50 years. Results show a higher mean aggregate loss ratio for Cali and similar mean aggregate loss ratios for Bogotá and Medellín. All of the models used in this study are openly accessible, enabling risk modelers, engineers, and stakeholders to explore them for disaster risk management.

In risk assessment, the exposure component describes the elements exposed to the natural hazards and susceptible to damage or loss, while the vulnerability component defines the likelihood to incur damage or loss conditional on a given level of hazard intensity. In this article, we propose a novel adaptive approach to exposure modeling which exploits Dirichlet-Multinomial Bayesian updating to implement the incremental assimilation of sparse in situ survey data into probabilistic models described by compositions (proportions). This methodology is complemented by the introduction of a custom spatial aggregation support based on variable-resolution Central Voronoidal Tessellations. The proposed methodology allows for a more consistent integration of empirical observations, typically from engineering surveys, into large-scale models that can also efficiently exploit expert-elicited knowledge. The resulting models are described in a probabilistic framework, and as such allow for a more thorough analysis of the underlying uncertainty. The proposed approach is applied and discussed in five countries in Central Asia.

This study presents a comprehensive open probabilistic seismic risk model for India. The proposed model comprises a nationwide residential and non-residential building exposure model, a selection of analytical seismic vulnerability functions tailored for Indian building classes, and the open implementation of an existing probabilistic seismic hazard model for India. The vulnerability of the building exposure is combined with the seismic hazard using the stochastic (Monte Carlo) event-based calculator of the OpenQuake engine to estimate probabilistic seismic risk metrics such as average annual economic losses and the exceedance probability curves at the national, state, district, and subdistrict levels. The risk model and the underlying datasets, along with the risk metrics calculated at different scales, are intended to be used as tools to quantitatively assess the earthquake risk across India and also compare with other countries to develop risk-informed building design guidelines, for more careful land-use planning, to optimize earthquake insurance pricing, and to enhance general earthquake risk awareness and preparedness.

As part of the development of a European Seismic Risk Model 2020 (ESRM20), the spatial and temporal evolution of seismic design across Europe has been studied in order to better classify reinforced concrete buildings (which represent more than 30% of the approximately 145 million residential, commercial and industrial buildings in Europe) and map them to vulnerability models based on simulated seismic design. This paper summarises the model that has been developed to assign the years when different seismic design levels (low code, moderate code and high code) were introduced in a number of European countries and the associated lateral forces that were specified spatially within each country for the low and moderate codes for typical reinforced concrete mid-rise buildings. This process has led to an improved understanding of how design regulations evolved across Europe and how this has impacted the vulnerability of the European residential building stock. The model estimates that ~ 60% of the reinforced concrete buildings in Europe have been seismically designed, and of those buildings ~ 60% have been designed to low code, ~ 25% to moderate code and 15% to high code. This seismic design model aims at being a dynamic source of information that will be continuously updated with additional feedback from local experts and datasets. To this end, all of the data has been made openly available as shapefiles on a GitLab repository.

In the last five centuries, Portugal was affected by several earthquakes of strong magnitude (M > 7) that caused widespread destruction and a significant death toll. Due to the geographical distribution of moderate-to-strong magnitude events along the Tagus Valley and Southwest of the country, an earthquake early warning system might potentially provide precious warning time ahead of the arrival of the destructive seismic waves. We used a probabilistic seismic hazard model to generate a large stochastic event set for the country, and evaluated the probability of triggering correct and false alerts considering different ground shaking thresholds. We propagated the aleatory variability related to the estimation of the location and event magnitude, as well as the variability in the ground shaking across the Portuguese territory. For the events for which a correct alert would be expected, we estimated the warning time for each district, considering various sources of latency. These analyses were performed considering the current seismic network of the country, as well as the potential installation of submarine sensors as part of the forthcoming renewal of the communication cables between mainland Portugal and the archipelagos of Azores and Madeira. The results indicate that for the districts located in the Southwest of the country, an earthquake early warning system might provide sufficient warning time for risk mitigation measures to be followed.

The exposure model is a key component of a seismic risk model, which captures the spatial distribution of population and built assets along with their structural characteristics and valuation that are required for seismic risk assessment. Current and available exposure models for China have various limitations that make them less suitable for use in risk assessment, including low spatial resolution of building inventory and the limited identification of key structural characteristics. This study describes the development of a residential buildings’ township-level exposure model for mainland China, containing information about the geographical distribution, structural characteristics, age, ductility, number of stories, number of dwellings, average built-up area, and replacement cost at the township level. This exposure model is intended to be used for risk assessment and to support emergency planning, risk management, and decisions. The geographical distribution’s detailed analysis of the building typologies, heights, and construction vintage at the national, regional, and provincial levels is provided to better aid in understanding country exposure. The results indicate that based on the method, flow, and data from the 6th National Population Census of the People's Republic of China, we can generate key information used for seismic risk analysis, representing a significant step toward a better understanding of risk due to seismic hazards in mainland China.