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Probabilistic seismic risk assessment of Africa

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  • GEM, EUCENTRE, University of Aveiro
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Since its inception in the 1960s, probabilistic seismic‐hazard analysis (PSHA) (Cornell, 1968; McGuire, 2004, 2008) has emerged as the principal methodology for assessing the potential hazard posed by earthquake ground motion in a broad range of contexts. Seismic‐hazard analysis serves different needs coming from a wide spectrum of users and applications. These may encompass engineering design, assessment of earthquake risk to portfolios of assets within the insurance and reinsurance sectors, engineering seismological research, and effective mitigation via public policy in the form of urban zoning and building design code formulation. End users of seismic‐hazard analyses from different sectors of industry may often have specific requirements in terms of the types of results and, as a consequence, in terms of the methodologies preferred for calculation. A large majority of studies for the analysis of structural and geotechnical systems require the calculation of a target response spectrum derived from PSHA results (e.g., Lin et al. , 2013). Often the calculation of uniform hazard spectra is performed in conjunction with a disaggregation analysis, which in the simplest cases highlights the combinations of magnitude and distances, providing the largest contributions to a specific level of hazard for a particular intensity measure type, such as the spectral acceleration for a period close to the fundamental elastic period of a structure (Bazzurro and Cornell, 1999; Pagani and Marcellini, 2007). In contrast, in the insurance sector it is more common to use stochastic methodologies (e.g., Weatherill and Burton, 2010; Musson, 2012) to produce multiple realizations of the likely earthquake activity that may be pertinent to a portfolio of assets. Monte Carlo–based methods can provide results in a form that offers a practical comparison with past events and can better account for the temporal and spatial variability of earthquake shaking occurring on a distributed set …
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Abstract Modern earthquake loss models make use of earthquake catalogs relevant to the seismic hazard assessment upon seismicity and seismotectonic analysis. The main objective of this paper is to investigate a recently compiled catalog (National Institute of Meteorology or INM catalog: 412-2011) and to generate seismic hazard maps through classical probabilistic seismic hazard assessment (PSHA) and smoothed-gridded seismicity models for Tunisia. It is now established with the local earthquake bulletin that the recent seismicity of Tunisia is sparse and moderate. Therefore, efforts must be undertaken to elaborate a robust hazard analysis for risk assessment and seismic design purposes. These recommendations follow the recently published reports by the World Bank that describe the seismic risk in Tunis City as being beyond a tolerable level with an MSK intensity level of VII. Some attempts were made during the past two decades to assess the seismic hazard for Tunisia and they have mostly failed to properly investigate the historical and instrumental seismicity catalog. This limitation also exists for the key aspect of epistemic and random uncertainties impact on the final seismic hazard assessment. This study also investigates new ground motion prediction equations suitable for use in Tunisia. The methodology applied herein uses, for the first time in PSHA of Tunisia, seismicity parameters integrated in logic tree framework to capture epistemic uncertainties through three different seismic source models. It also makes use of the recently released version of OpenQuake engine; an open-source tool for seismic hazard and risk assessment developed in the framework of the Global Earthquake Model.
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A regional seismic risk analysis for central-southern Malawi is conducted by focusing on the Bilila-Mtakataka Fault within the East African Rift System and by incorporating local information on population exposure and building vulnerability. The scenario-based earthquake risk assessments account for uncertainty in geometry , position, and rupture pattern of the Bilila-Mtakataka Fault as well as ground-motion variability and are based on the latest 2018 national census data. In addition, Malawi-specific seismic fragility functions, which were developed based on building surveys and laboratory tests of local construction materials, are implemented to reflect realistic seismic vulnerability of unreinforced masonry constructions in Malawi. The results from the earthquake risk assessments and sensitivity analyses based on alternative data and models highlight the importance of incorporating local information on seismic hazard characterisation, population data, and seismic vulnerability of buildings, in comparison with global data and models. For the considered case study region, individual effects of the above-mentioned model components tend to result in 20-30 % or greater differences in regional seismic risk metrics, such as the affected population experiencing a certain ground shaking intensity level or the number of collapsed housing units. The improved seismic hazard-risk assessments are more effective in informing future seismic risk mitigation policies and actions.
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In December 2018, at the conclusion of its second implementation phase, the Global Earthquake Model (GEM) Foundation released its first version of a map outlining the spatial distribution of seismic hazard at a global scale. The map is the result of an extensive, joint effort combining the results obtained from a collection of probabilistic seismic hazard models, called the GEM Mosaic. Together, the map and the underlying database of models provide an up-to-date view of the earthquake threat globally. In addition, using the Mosaic, a synopsis of the current state-of-practice in modeling probabilistic seismic hazard at national and regional scales is possible. The process adopted for the compilation of the Mosaic adhered to the maximum extent possible to GEM’s principles of collaboration, inclusiveness, transparency, and reproducibility. For each region, priority was given to seismic hazard models either developed by well-recognized national agencies or by large collaborative projects involving local scientists. The version of the GEM Mosaic presented herein contains 30 probabilistic seismic hazard models, 14 of which represent national or sub-national models; the remainder are regional-scale models. We discuss the general qualities of these models, the underlying framework of the database, and the outlook for the Mosaic’s utility and its future versions.
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Many years have passed since previous national seismic hazard maps were prepared for South Africa. In those maps, zone-less techniques were applied. The availability of more reliable seismicity and geological data has made it possible to update those maps using probabilistic seismic hazard analysis methodologies that take into consideration all available data. This paper presents a summary of the work conducted to produce the latest seismic hazard maps for South Africa. This involved the systematic compilation and homogenisation of an earthquake catalogue, which comprised both historical and instrumental events. The catalogue played a prominent role in the preparation and characterisation of the seismic source model. Two ground motion prediction equations were identified from available international models for regions that are tectonically similar to South Africa. These two models were then implemented in the hazard calculations, which were done using the OPENQUAKE software. Uncertainties associated with input parameters in both the seismic source and ground motion models were taken into account and implemented using the logic tree technique. Maps showing distribution of acceleration at three periods (0.0s, 0.15s and 2.0s) computed for 10% probability of exceedance in 50 years were produced.
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The typology classification of any building is essential to understand its structural and architectural configuration, to empirically evaluate its vulnerability, or to provide the basis for creating a structural model and to analytically study its dynamic performance. A typology classification may help structural engineers, architects and urban planners to understand a building's behavior and response to any type of natural or man-made hazard as well as further assists in defining improvement techniques and long-term sustainable regional planning. The division of a building stock into distinct classes of building typologies and hence the definition of a thorough building classification scheme is a major prerequisite for any vulnerability or loss assessment study. A building's typology largely depends upon the local geology and geography, climatic conditions, socio-economic status of the occupants or owners, and to a large extent the locally available construction skills as well as natural resources (with respect to construction materials). The type of natural hazards a region has experienced in the past may also influence its prevalent construction typologies, at least if these hazards frequently occur in a certain period of time. The introduction of new construction technologies, design codes and/or building byelaws have further implications on the question of which building typologies are prevalent in a certain region, given that these legal provisions are implemented in daily construction practice. Focusing on Central and South Asian conditions, large variations exist in above stated factors. The region the Disaster Risk Management Initiative programme (DRMI), led by the Aga Khan Development Network (AKDN), is focused on here comprises of the Central Asian countries Tajikistan and Kyrgyzstan as well as the South Asian countries Afghanistan, India and Pakistan. As strong variations in the characteristics of a certain building typology may exist between different regions or even countries, the definition of building typology classes at a regional scale is a daunting task. The present article attempts to categorize the Central and South Asian building stock into a manageable number of regional building typologies based on extensive field studies in the different regions. It further includes a thorough review of the relevant building classification schemes, discusses empirical data collection, and defines the criteria for building classification. By reviewing the buildings’ dynamic performances, a final building classification for the region and a customized visual screening-based vulnerability scale is presented.
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Probabilistic loss modeling can be used to develop risk reduction measures, such as the identification of regions more prone to human and economic losses, or to the development of financial mechanisms to transfer the earthquake risk from local governments to the private sector. This study addresses several critical issues in probabilistic loss modeling, and provides recommendations depending on the intended final use of the risk results. Modeling issues related with convergence in probabilistic event-based analysis; consideration of epistemic uncertainties within a logic tree; generation of different types of loss exceedance curves; and derivation of risk maps are thoroughly investigated. The Metropolitan Area of Lisbon is used to explore these issues, and it is demonstrated that different assumptions in the loss modeling process can lead to considerably different risk results. Furthermore, the findings and recommendations of this study are also relevant for institutions that promote the assessment of earthquake hazard and risk, such as the Global Earthquake Model Foundation.
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South America, and in particular the Andean countries are exposed to high levels of seismic hazard, which, when combined with the elevated concentration of population and properties, has led to an alarming potential for human and economic losses. Although several fragility models have been developed in recent decades for South America, and occasionally used in probabilistic risk analysis, these models have been developed using distinct methodologies and assumptions, which renders any direct comparison of the results across countries questionable, and thus application at a regional level unreliable. This publication aims at obtaining a uniform fragility model for the most representative building classes in the Andean region, for large-scale risk analysis. To this end, sets of single-degree-of-freedom oscillators were created and subjected to a series of ground motion records using non-linear time history analyses, and the resulting damage distributions were used to derive sets of fragility functions.
Chapter
The magnitude (M S )-6.2 earthquake that struck northwestern Guinea in late 1983 (Figure 1) killed nearly 300 people,sinjured about 1,500, destroyed more than 5,000 houses, and left some 18,000 people homeless. It serves as a recent example of the infrequent but oftentimes destructive nature of moderate to large earthquakes that occur in apparently aseismic to low-seismicity intraplate regions such as West Africa. These examples remind us of our vulnerability to natural hazards and particularly to uncommon events of this type.
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Located at the North-Eastern part of Algeria (Tellian Atlas), Constantine has crucial administrative, economic, scientific and cultural importance. It has continuously experienced significant urban evolutions during the different periods of its history. The city is located in an active seismic region within Algeria and has been struck in the past by several moderate and strong earthquakes. The strongest earthquake recorded since the beginning of instrumental seismology took place on October 27, 1985 with a magnitude M S=_\mathrm{S}= 5.9. Constantine presents a high seismic risk, because of its dense housing and high population density (2,374 inhabitants/km 2)^{2}) . This requires a risk assessment in order to take preventive measures and reduce the losses in case of potential major earthquake. For this purpose, a scenario based approach is considered. The building damage assessment methodology adopted for the Algerian context is adapted from HAZUS approach. In the present case, the effective Algerian seismic code response spectrum (RPA 99/2003) is considered as a seismic hazard model. The prediction of the expected damages is performed for a set of almost 29,000 buildings.