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V. Silva

Publications and source records attributed to V. Silva.

3 recordsLinked to original sources

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

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

GEM Building Taxonomy (Version 2.0)

This report documents the development and applications of the Building Taxonomy for the Global Earthquake Model (GEM). The purpose of the GEM Building Taxonomy is to describe and classify buildings in a uniform manner as a key step towards assessing their seismic risk, Criteria for development of the GEM Building Taxonomy were that the Taxonomy be relevant to seismic performance of different construction types; be comprehensive yet simple; be collapsible; adhere to principles that are familiar to the range of users; and ultimately be extensible to non-buildings and other hazards. The taxonomy was developed in conjunction with other GEM researchers and builds on the knowledge base from other taxonomies, including the EERI and IAEE World Housing Encyclopedia, PAGER-STR, and HAZUS. The taxonomy is organized as a series of expandable tables, which contain information pertaining to various building attributes. Each attribute describes a specific characteristic of an individual building or a class of buildings that could potentially affect their seismic performance. The following 13 attributes have been included in the GEM Building Taxonomy Version 2.0 (v2.0): 1.) direction, 2.)material of the lateral load-resisting system, 3.) lateral load-resisting system, 4.) height, 5.) date of construction of retrofit, 6.) occupancy, 7.) building position within a block, 8.) shape of the building plan, 9.) structural irregularity, 10.) exterior walls, 11.) roof, 12.) floor, 13.) foundation system. The report illustrates the pratical use of the GEM Building Taxonomy by discussing example case studies, in which the building-specific characteristics are mapped directly using GEM taxonomic attributes and the corresponding taxonomic string is constructed for that building, with "/" slash marks separating attributes. For example, for the building shown to the right, the GEM Taxonomy string is: DX 1 /MUR+CLBRS+MOCL 2 /LWAL 3 / DY/MUR+CLBRS+MOCL/LWAL/YPRE:1939 4 /HEX:2 5 /RES 6 / 7 / 8 /IRRE 9 /10/RSH3+RWO2 11 /FW 12 / 13 / which can be read as (1) Direction = [DX or DY] (the building has the same lateral load-resisting system in both directions); (2) Material = [Unreinforced Masonry + solid fired clay bricks + cement: lime mortar]; (3) Lateral Load-Resisting System = [Wall]; (4) Date of construction = [pre-1939]; (5) Heaight = [exactly 2 storeys]; (6) Occupancy = [residential, unknown type]; (7) Building Position = [unknown = no entry]; (8) Shape of building plan = [unknown = no entry]; (9) Structural irregularity = [regular]; (10) Exterior walls = [unknown = no entry]; (11) Roof = [Shape: pitched and hipped, Roof covering: clay tiles, Roof system material: wood, Roof system type: wood trusses]; (12) Floor = [Floor system: Wood, unknown]; (13) Foundation = [unknown = no entry]. Mapping of GEM Building Taxonomy to selected taxonomies is included in the report -- for example, the above building would be referenced by previous structural taxonomies as: PAGER-STR as UFB or UFB4, by the World Housing Encyclopedia as 7 or 8 and by the European Macroseismic Scale (98) as M5. The Building Taxonomy data model is highly flexible and has been incorporated within a relational database architecture. Due to its ability to represent building typologies using a shorthand form, it is also possible to use the taxonomy for non-database applications, and we discuss possible application of adaptation for Building Information Modelling (BIM) systems, and for the insurance industry. The GEM Building Taxonomy was independently evaluated and tested by the Earthquake Engineering Research Institute (EERI), which received 217 TaxT reports from 49 countries, representing a wide range of building typologies, including single and multi-storey buildings, reinforced and unreinforced masonry, confined masonry, concrete, steel, wood, and earthern buildings used for residential, commercial, industrial, and educational occupancy. Based on these submissions and other feedback, the EERI team validated that the GEM Building Taxonomy is highly functional, robust and able to describe different buildings around the world. The GEM Building Taxonomy is accompanied by supplementary resources. All terms have been explained in a companion online Glossary, which provides both text and graphic descriptions. The Taxonomy is accompanied by TaxT, a computer application that enables a user record information about a building or a building typology using the attributes of the GEM Building Taxonomy v2.0. TaxT can generate a taxonomy string and enable a user to generate a report in PDF format which summarizes the attribute values (s)he has chosen as representative of the building typology under consideration. The report concludes with recommendations for future development of the GEM Building Taxonomy. Appendices provide the detailed GEM Building Taxonomy tables and additional resource, as well as mappings to other taxonomies.

GEM Technical Report