A Multiscale Exposure Model for Seismic Risk Assessment in Central Asia

Abstract

Seismic risk assessment is carried out combining hazard, exposure, and vulnerability models (United Nations Disaster Relief Organization [UNDRO], 1979). Exposure in this context refers to the elements at risk, which can be buildings, population, lifeline systems, or socioeconomic activities. Exposure data may vary depending on the scale of analysis, going from detailed descriptions of characteristics and locations of structural elements to composite models aggregated to larger geographical entities, such as administrative units, cities, or countries. When significant structural characteristics like the construction type or the building height are available, the vulnerability of structures here referred to as physical vulnerability, can be assessed by expert judgment, analytical modeling, or empirical analysis. A detailed overview of different methods for vulnerability assessment of structures is given in Calvi et al. (2006). The recently published Organization for Economic Cooperation and Development (OECD) Global Science Forum report on Global Modeling of Natural Hazard Risks 2012 (OECD, 2012) concludes, from the analysis of risk assessment practices worldwide, that exposure and vulnerability are critical elements for effective risk assessment and suggests that more efforts should be undertaken to identify and develop proxy measures to reduce uncertainties in these models and to consider their time dependency to improve assessments. Moreover, the report highlights that commonly used methods and data for risk assessments are strongly heterogeneous in format and quality, making it difficult to compare results between different methods, analysis scales, or across national borders. Despite its importance in risk assessment and its relative independence on the underlying hazard type, reliable information on exposed assets is frequently missing, incomplete, out‐dated, or strongly aggregated. This is especially the case in developing countries where commonly used exposure data capturing procedures can often not adequately cope with the rapid urban growth and increasingly high spatiotemporal variability in urban areas. Global exposure databases …