Construction of an integrated social vulnerability index in urban areas prone to flash flooding

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Abstract

Among the natural hazards, flash flooding is the leading cause of weather-related deaths. Flood risk management (FRM) in this context requires a comprehensive assessment of the social risk component. In this regard, integrated social vulnerability (ISV) can incorporate spatial distribution and contribution and the combined effect of exposure, sensitivity and resilience to total vulnerability, although these components are often disregarded. ISV is defined by the demographic and socio-economic characteristics that condition a population's capacity to cope with, resist and recover from risk and can be expressed as the integrated social vulnerability index (ISVI). This study describes a methodological approach towards constructing the ISVI in urban areas prone to flash flooding in Castilla y León (Castile and León, northern central Spain, 94 223 km-2, 2 478 376 inhabitants). A hierarchical segmentation analysis (HSA) was performed prior to the principal components analysis (PCA), which helped to overcome the sample size limitation inherent in PCA. ISVI was obtained from weighting vulnerability factors based on the tolerance statistic. In addition, latent class cluster analysis (LCCA) was carried out to identify spatial patterns of vulnerability within the study area. Our results show that the ISVI has high spatial variability. Moreover, the source of vulnerability in each urban area cluster can be identified from LCCA. These findings make it possible to design tailor-made strategies for FRM, thereby increasing the efficiency of plans and policies and helping to reduce the cost of mitigation measures.

Figures

  • Figure 1. Location of the region of Castilla y León. Sources: IGN raster cartography (available WMS server: http://www.ign.es/wms-inspire/ mapa-raster?request=GetCapabilities&service=WMS&; accessed on 4 December 2016); digital terrain model 200 m (available online: http: //www.ign.es; accessed on 3 December 2016); regional boundaries (available online: http://www.ign.es; accessed on 7 December 2016); municipal boundaries (available online: http://www.ign.es; accessed on 5 December 2016); rivers (available online: http://www.mapama. gob.es; accessed on 5 December 2016); APSFRs (available online: http://www.mapama.gob.es; accessed on 5 December 2016); 500-year flood areas (available online: http://www.mapama.gob.es; accessed on 5 December 2016).
  • Figure 2. Methodological outline containing the different steps followed in the construction of the ISVI and the social vulnerability patterns.
  • Table 1. Set of variables used in the exploratory analysis of social vulnerability dimensions.
  • Figure 3. Dendrogram resulting from the HSA. Each rectangle corresponds to an identified group, with a total of five groups (G1, G2, G3, G4 and G5).
  • Table 2. Vulnerability factors identified with the PCA and additional statistical information (PCA results). The sign of the variable loadings indicates whether the correlation among variables making up a certain vulnerability factor is positive or negative.
  • Figure 4. Factor scores for identified vulnerability factors. For exposure and sensitivity factors, very high categories are coloured in red, while, for resilience factors, very high categories are coloured in blue. Source: municipal boundaries (available online: http://www.ign.es; accessed on 5 December 2016).
  • Figure 5. ISVI values and its decomposition into vulnerability components. Source: municipal boundaries (available online: http://www.ign. es; accessed on 5 December 2016).
  • Table 3. Model fit summary of the latent class cluster models initially considered.

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CITATION STYLE

APA

Aroca-Jimenez, E., Bodoque, J. M., Antonio Garcia, J., & Diez-Herrero, A. (2017). Construction of an integrated social vulnerability index in urban areas prone to flash flooding. Natural Hazards and Earth System Sciences, 17(9), 1541–1557. https://doi.org/10.5194/nhess-17-1541-2017

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