1. Introduction

At the core of the Global Earthquake Model (GEM) is the development of state-of-the-art modeling capabilities and a suite of software tools that can be utilized worldwide for the assessment and communication of earthquake risk. For a more holistic assessment of the scale and consequences of earthquake impacts, a set of methods, metrics, and tools are incorporated into the GEM modelling framework to assess earthquake impact potential beyond direct physical impacts and loss of life. This is because with increased exposure of people, livelihoods, and property to earthquakes, the potential for social and economic impacts of earthquakes cannot be ignored. Not only is it vital to evaluate and benchmark the conditions within social systems that lead to adverse earthquake impacts and loss, it is equally important to measure the capacity of populations to respond to damaging events and to provide a set of metrics for priority setting and decision-making.

The employment of a methodology and workflow necessary for the evaluation of seismic risk that is integrated and holistic begins with the Integrated Risk Modelling Toolkit (IRMT). The IRMT is QGIS plugin that was developed by the Global Earthquake Model (GEM) Foundation and co-designed by GEM and the Center for Disaster Management and Risk Reduction Technology (CEDIM). The plugin allows users to form an integrated workflow for the construction of metrics used to assess characteristics within societies that affect earthquake risk by providing a GIS-based platform for the construction of indicators and composite indices to foster comparative assessments. Here, an indicator is defined as a piece of information that summarizes the characteristics of a system or highlights what is happening in a system. An indicator is a quantitative or qualitative measure derived from observed facts that simplify and communicate the reality of a complex situation. Indicators reveal the relative position of the phenomena being measured and when evaluated over time, can illustrate the magnitude of change (a little or a lot) as well as direction of change (up or down; increasing or decreasing). The mathematical combination (or aggregation as it is termed) of a set of indicators forms a composite indicator (or composite index or indices).

As part of the workflow, the IRMT facilitates the integration of composite indicators of socio-economic characteristics with measures of physical risk (i.e. estimations of human or economic loss) from the OpenQuake Engine (OQ-engine) ([PMW+14] and [SCP+14]), or other sources, to form what is referred to as an integrated risk assessment. Although the tool may be utilized for any type of indicator development, it is encouraged that composite indicators of social vulnerability are developed within this integrated risk framework. Social vulnerability is defined here as characteristics or qualities within social systems that create the potential for harm or loss from damaging hazard events. Given equal exposure to natural threats, such as an earthquake, two groups may vary in their social vulnerability due to their pre-existing social characteristics, where differences according to wealth, gender, race, class, history, and sociopolitical organization influence the patterns of loss, mortality, and the ability to reconstruct following damaging events.

The focus on the development of indicators of social vulnerability, and ultimately integrated risk, will allow researchers, decision-makers, and other relevant stakeholders to:

  • consider loss and damage as part of a dynamic system in which interactions between natural systems and societal factors redistribute risk before an event and redistribute loss after an event
  • mainstream socio-economic vulnerability and resilience in earthquake loss and damage policy discussions
  • evaluate loss and damage taking social factors into account at different time and space scales
  • use risk assessments in benchmarking exercises to monitor trends in earthquake risk over time
  • recognize that both causes and solutions for earthquake loss are found in human, environmental, and built-environmental interactions
  • help decision-makers develop a common dialog that pertains to the factors that they should concentrate on to reduce risk and strengthen resilience.

The development of composite indicators is not new to research fields and occupations requiring empirical measurement, and a vast literature on composite indicators exists that outline methodological approaches for index construction and validation. To accompany this manual we suggest the use of two popular resources ([NSST05] and [NSST08]) aimed at providing a guide for the construction and use of composite indicators.

This literature outlines the process of robust composite indicator construction that contains a number of steps. The IRMT leverages the QGIS platform to guide the user through the major steps for index construction. These steps include 1) the selection of variables; 2) data normalization/standardization; 3) weighting and aggregation to produce composite indicators; 4) risk integration using OpenQuake risk estimates; and 5) the presentation of the results. Brief descriptions of the tool’s components and the workflow to develop integrated risk models are outlined in the sections below.

[PMW+14]Pagani, M., Monelli, D., Weatherill, G., Danciu, L., Crowley, H., Silva, V., Henshaw, P., Butler, L., Nastasi, M., Panzeri, L., Simionato, M. and Vigano, V. OpenQuake Engine: An Open Hazard (and Risk) Software for the Global Earthquake Model. Seismological Research Letters, vol. 85 no. 3, 692-702
[SCP+14]Silva, V., Crowley, H., Pagani, M., Monelli, D., and Pinho, R., 2014. Development of the OpenQuake engine, the Global Earthquake Model’s open-source software for seismic risk assessment. Natural Hazards 72(3), 1409-1427.
[NSST05]Nardo, M., Saisana, M., Saltelli, A. and Tarantola, S. 2005. Tools for composite indicators Building. Ispara, Italy: Joint Research Center of the European Commission.
[NSST08]Nardo, M., Saisana, M., Saltelli, A. and Tarantola, S. 2008. Handbook on constructing composite indicators: Methodology and user guide. Paris, France: OECD Publishing.