A comparison of social vulnerability indices specific to flooding in Ecuador: principal component analysis (PCA) and expert knowledge

• Autores: Bazo Zambrano, Juan Carlos, Bucherie, Agathe, Hultquist, Carolynne, Adamo, Susana, Neely, Colleen, Ayala, Fernanda, Kruczkiewicz, Andrew
• Formato: artículo
• Fecha de Publicación: 2022
• Institución: Universidad Tecnológica del Perú
• Repositorio: UTP-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.utp.edu.pe:20.500.12867/5797
• Enlace del recurso: https://hdl.handle.net/20.500.12867/5797; http://doi.org/10.1088/1755-1315/943/1/012003
• Nivel de acceso: acceso abierto
• Materia: Flood; Vulnerability social indicators; https://purl.org/pe-repo/ocde/ford#2.07.01

Social vulnerability is a key component of the risk equation alongside the context of the hazard and exposure. Increasingly, social vulnerability indices are used to better understand and predict the consequences of disasters, and support the development of improved disaster management policies. Humanitarian organisations particularly strive to capture social vulnerability in their decision processes relative to prioritisation of actions before disasters occur. This research sup- ports the Ecuadorian Red Cross in generating a flood-specific social vulnerability index to inform flash flood early action at the Parroquia level in Ecuador. This paper compares the results from the two most common approaches used to create composite indices, one using the weighting of variables from disaster experts’ judgments (referred to as Expert method) and the other using PCA analysis, with one or more components. While all outcomes reveal similar trends in areas where most indicators suggest the lowest (urban areas) or highest (the Amazon and northwest coastal regions) social vulnerability, the research shows that the choice of the method matters for assessing the social vulnerability in the rest of the country where there are less pronounced vulnerability signals. In those areas, PCA-driven indices suggest higher relative vulnerability levels than Expert outcomes. Further, in the Andes particularly, the PCA outcomes result in wider distribution than the Expert outcomes, and therefore more heterogeneity in the vulnerability assessment. While divergence in outcomes suggests particular attention with the use of composite indexes for decision making, our results provide support to understand the sensitivity in flood- specific social vulnerability outcomes spatially. To go further we emphasise the importance of using historical flood impact data to evaluate the contribution of each variable in the final social vulnerability scores.