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Vitor Silva

Publications and source records attributed to Vitor Silva.

8 recordsLinked to original sources
USGS2026

Time for an updated macroseismic scale

Macroseismology plays a crucial role in earthquake hazard and risk analyses, linking past earthquake occurrences and impacts with those of the present and future. The popularity of internet-based community contributions and the usefulness of intensities for communicating seismic hazards, early warning, and impacts to the public have all bolstered the use of macroseismology beyond its traditional utility in characterizing sources and shaking from historical and modern earthquakes (Wald et al., 2023). Nevertheless, many modern approaches for collecting building damage data and assigning macroseismic intensities suffer limitations. Many countries do not or no longer routinely collect such data, and even after significant and even catastrophic earthquakes, building damage data are often not collected or shared systematically, nor are field-based macroseismic intensities professionally assigned. Additionally, the United States (U.S.), Canada, and other nations still use variations of the Modified Mercalli Intensity (MMI) scale (Wood and Neumann, 1931) for assigning macroseismic intensities. At nearly 100 years old, the MMI scale predates most modern building types. As a result, the scale is silent about and blind to building damage that now matters to most domestic occupants. It says nothing about single- or multi-unit wood-frame buildings, the predominant type of residential structure in the US and Canada, whose damage is a particularly important indicator of shaking intensity, nor about the collapse or safety of modern building types. Importantly, the dependence on the U.S. Geological Survey’s “Did You Feel It?” (DYFI) for domestic intensity data collection limits their accuracy type at higher, damaging intensity levels, where attention to building type is requisite. The MMI and some of its widely used variants are often poorly documented; there is no official version, nor is it even clear which version of the scale was employed in many studies (Musson, 2002). The MMI scale is consistent with—but is more limited than—the 1998 European Macroseismic Scale (EMS-98, Grünthal, 1998). The new International Macroseismic Scale of 2025 (IMS-25; Grünthal et al., 2025) builds on EMS-98—a well-documented, modern scale already widely used in Europe and well beyond. IMS-25 further expands EMS-98 internationally by enhancing the EMS-98 vulnerability table and damage grade collections to include more worldwide building types and their evolving design codes. Because the IMS requires well-defined vulnerability classes and damage grades specific to various structural types, its worldwide adoption will help unify post-event data collection on building damage. Similarly, the IMS requires statistical analyses of damage levels for specific structural types, ensuring that building damage sampling is sufficient for other important engineering analyses, such as the derivation of fragility functions, calibration of loss models, and the assessment of losses and damages after significant events

Seismological Research Letters↗
USGS2025

Potential benefits of seismic monitoring for ground-shaking estimation and loss assessment

Seismic networks are fundamental to compute ground shaking in regions affected by destructive events, which can then be used for damage and loss assessment. Ground‐motion data recordings can be used to estimate the event bias (or interevent residual) for one or multiple ground‐motion models, as well as to condition the ground‐shaking estimation process to reduce the intraevent residuals at sites near seismic stations. We evaluate how the error in the estimation of the event bias and ground shaking for a set of target sites can be reduced by incorporating an increasing number of seismic stations, using recordings from the 1999 M 7.7 Chi‐Chi, Taiwan, earthquake and a large set of ground‐motion fields for Taiwan using stochastic simulations. Then, we evaluate how the incorporation of data from seismic stations in the estimation of several impact metrics (i.e., economic losses, collapsed buildings, and fatalities) can reduce both the bias and the uncertainty, using the district of Lisbon (Portugal) as a case study. The results from this study indicate that the error in the estimation of the impact metrics can be reduced by one order of magnitude if at least 10 stations are considered, especially if the configuration of the seismic network considers the location of vulnerable buildings or the spatial distribution of earthquake risk.

Bulletin of the Seismological Society of America↗
USGS2021

Exploring probabilistic seismic risk assessment to monitor the Sendai Framework for Disaster Risk Reduction

The Sendai Framework for Disaster Risk Reduction (SFDRR) calls upon the systematic collection of damage and loss data between 2015 and 2030 to monitor a number of disaster indicators. These indicators include the number of deaths, number of injured people, number of people affected by disasters, and direct economic losses. These results can then be compared with previous periods in order to track progress in disaster risk reduction. However, there is an important limitation with such an approach when measuring disaster risk due to earthquakes. Even in countries with significant seismic risk, it is plausible to witness a 15 year period without any destructive earthquakes (e.g., Nicaragua, Haiti, Myanmar). This situation can lead to the perception that efficient measures are being undertaken to reduce the impact of earthquakes, when in reality the trend could be the opposite. An alternative approach to monitor the SFDRR indicators is through probabilistic risk models. These models allow the estimation of the indicators of the SFDRR probabilistically (e.g., average annual economic losses, average annual fatalities), which do not depend on the occurrence of destructive events during the period of interest. Although seismic activity can be assumed as stationary over several decades, in order to evaluate the evolution of the SFDRR over these time frames, the consistent updating of the risk model has to be considered in order to reflect the evolution and change of the built environment and its vulnerability, such as the introduction of new design regulations or the implementation of retrofitting campaigns. A comparison of the various risk indicators throughout time allows assessing whether the potential losses caused by earthquakes are decreasing or increasing, as well as where risk reduction measures should be prioritized. This study discusses how the global seismic risk model released in December 2018 by the Global Earthquake Model (GEM) Foundation and its partners can be explored to monitor the SFDRR, and more importantly, how it can be modified to assess which measures should be endorsed to respect the 2030 targets.

Extramural-Authored Publication Paper↗
USGS2020

Development of a global seismic risk model

Since 2015 the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake-engine, an open-source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures.

Earthquake Spectra↗
USGS2018

Global Earthquake Model (GEM) Risk Map

The Global Earthquake Risk Map (v2018.1) comprises four global maps. The main map presents the geographic distribution of average annual loss (USD) normalized by the average construction costs of the respective country (USD/m2 due to ground shaking in the residential, commercial and industrial building stock, considering contents, structural and non-structural components. The normalized metric allows a direct comparison of the risk between countries with widely different construction costs. It does not consider the effects of tsunamis, liquefaction, landslides, and fires following earthquakes. The loss estimates are from direct physical damage to buildings due to shaking, and thus damage to infrastructure or indirect losses due to business interruption are not included. The Global Earthquake Hazard Map depicts the geographic distribution of the Peak Ground Acceleration (PGA) with a 10% probability of being exceeded in 50 years, computed for reference rock conditions (shear wave velocity of 760-800 m/s). The Global Exposure Map depicts the geographic distribution of residential, commercial and industrial buildings. The Global Seismic Fatalities Map depicts an estimate of average annual human losses due to earthquake-induced structural collapse of buildings. The results for human losses do not consider indirect fatalities such as those from post­ earthquake epidemics. The average annual losses and number of buildings are presented on a hexagonal grid, with a spacing of 0.30 x 0.34 decimal degrees (approximately 1,000 km2 at the equator). The average annual losses were computed using the event-based calculator of the OpenQuake engine, an open-source software for seismic hazard and risk analysis developed by the GEM Foundation. The seismic hazard, exposure and vulnerability models employed in these calculations were provided by national institutions, or developed within the scope of regional programs or bilateral collaborations. These global maps and the underlying databases are based on best available and publicly accessible datasets and models. Due to possible limitations in the model, regions portrayed with low risk may experience potentially damaging earthquakes. The GEM Risk Map is intended to be a dynamic product, which will be updated when new datasets and models become available. Updated versions of the hazard, exposure, and average annual losses will be released on a regular basis. Additional metrics for each country can be explored at globalquakemodel.org/gem.

Report↗
USGS2018

Developing a global earthquake risk model

The understanding of earthquake risk is the first step towards the development and implementation of disaster risk reduction measures. However, in many countries, especially the countries of the developing world, earthquake risk models either do not exist or are publicly inaccessible. The Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programmes and bilateral collaborations to develop a global earthquake risk model, due by the end of 2018. This paper describes how the main components (seismic hazard, exposure models and vulnerability functions) of this global effort are being collected, developed or improved. The calculations are being performed using the OpenQuake-engine, the open-source software for seismic hazard and risk calculations supported by GEM. This model will be able to provide estimates of critical risk metrics such as annualized average economic and human losses or aggregated losses for particular return periods, which are fundamental to the development of efficient and effective mitigation planning.

Conference Paper↗
USGS2014

Global assessment of human losses due to earthquakes

Current studies have demonstrated a sharp increase in human losses due to earthquakes. These alarming levels of casualties suggest the need for large-scale investment in seismic risk mitigation, which, in turn, requires an adequate understanding of the extent of the losses, and location of the most affected regions. Recent developments in global and uniform datasets such as instrumental and historical earthquake catalogues, population spatial distribution and country-based vulnerability functions, have opened an unprecedented possibility for a reliable assessment of earthquake consequences at a global scale. In this study, a uniform probabilistic seismic hazard assessment (PSHA) model was employed to derive a set of global seismic hazard curves, using the open-source software OpenQuake for seismic hazard and risk analysis. These results were combined with a collection of empirical fatality vulnerability functions and a population dataset to calculate average annual human losses at the country level. The results from this study highlight the regions/countries in the world with a higher seismic risk, and thus where risk reduction measures should be prioritized.

Conference Paper↗