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In the field of disaster risk reduction (DRR), there existsa proliferation of research into different ways to measure, represent, andultimately quantify a population's differential social vulnerability tonatural hazards. Empirical decisions such as the choice of source data,variable selection, and weighting methodology can lead to large differencesin the classification and understanding of the "at risk" population. Thisstudy demonstrates how three different quantitative methodologies (based onCutter et al., 2003; Rygel et al., 2006; Willis et al., 2010) appliedto the same England and Wales 2011 census data variables in the geographicalsetting of the 2013/2014 floods of the River Parrett catchment, UK, lead tonotable differences in vulnerability classification. Both the quantificationof multivariate census data and resultant spatial patterns of vulnerabilityare shown to be highly sensitive to the weighting techniques employed ineach method. The findings of such research highlight the complexity ofquantifying social vulnerability to natural hazards as well as the largeuncertainty around communicating such findings to stakeholders in flood riskmanagement and DRR practitioners

A review of multivariate social vulnerability methodologies: a case study of the River Parrett catchment, UK