Abstract
Abstract. Current methods to estimate evacuation time during a natural disaster do not consider the socioeconomic and demographic characteristics of the population. This article develops the Response Time by Social Vulnerability Index (ReTSVI). ReTSVI combines a series of modules that are pieces of information that interact during an evacuation, such as evacuation rate curves, mobilization, inundation models, and social vulnerability indexes, to create an integrated map of the evacuation rate in a given location. We provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 min of the evacuation, the population that lives in neighborhoods with a high social vulnerability evacuates 15 % and 22 % fewer people than the blocks with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning, and social vulnerability becomes less relevant after 30 min. The results of the application example have no statistical significance, which should be considered in a real case of application. Using a methodology such as ReTSVI could make it possible to combine social and physical vulnerability in a qualitative framework for evacuation, although more research is needed to understand the socioeconomic variables that explain the differences in evacuation rate.
Highlights
The costs associated with health, food security, and the physical environment produced by climate change are expected to reach between USD 2 and 4 trillion by 2030 (Hallegatte, 2014)
Previous research recognizes the relevance of social vulnerability in risk assessments; in general, the methodologies available fail to connect the physical vulnerability or the characteristics of an inundation event with social vulnerability in a quantitative framework
Such an analysis might show that there are distinct differences in the percentage of people evacuated in Huaraz for blocks that are close to each other, which could be explained by the social vulnerability indexes (SVIs) since their exposure to the physical hazard and the distance to escape are similar
Summary
The costs associated with health, food security, and the physical environment produced by climate change are expected to reach between USD 2 and 4 trillion by 2030 (Hallegatte, 2014). EWSs should consider the socalled physical dimensions such as exposure and intensity, and the human or social dimensions that help us understand differences in response to similar stresses (Basher, 2006; Bouwer, 2011; Nagarajan et al, 2012; Nicholls and Klein, 1999) Individual characteristics such as race, age, gender, education, income, and type of job influence the susceptibility to exposure of certain groups or communities and define their ability to respond to a natural hazard (Cutter et al, 2003; Gaillard and Dibben, 2008). A real improvement in our understanding of emergency evacuations will depend on the integration of both (Basher, 2006; Couling, 2014; Santos and Aguirre, 2004)
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