Combining hazard, exposure and social vulnerability to provide lessons for flood risk management - Koks, Elco; Jongman, Brenden; Husby, Trond; Botzen, W. J. Wouter (Environmental Science & Policy, 2015)
Flood risk assessments provide inputs for the evaluation of flood risk management (FRM) strategies. Traditionally, such risk assessments provide estimates of loss of life and economic damage. However, the effect of policy measures aimed at reducing risk also depends on the capacity of households to adapt and respond to floods, which in turn largely depends on their social vulnerability. This study shows how a joint assessment of hazard, exposure and social vulnerability provides valuable information for the evaluation of FRM strategies. The adopted methodology uses data on hazard and exposure combined with a social vulnerability index. The relevance of this state-of-the-art approach taken is exemplified in a case-study of Rotterdam, the Netherlands. The results show that not only a substantial share of the population can be defined as socially vulnerable, but also that the population is very heterogeneous, which is often ignored in traditional flood risk management studies. It is concluded that FRM measures, such as individual mitigation, evacuation or flood insurance coverage should not be applied homogenously across large areas, but instead should be tailored to local characteristics based on the socioeconomic characteristics of individual households and neighborhoods.

An Empirical Social Vulnerability Map for Flood Risk Assessment at Global Scale (“GlobE‐SoVI”) - Reimann, Lena; Koks, Elco; De Moel, Hans; Ton, Marijn J.; Aerts, Jeroen C. J. H. (Earth's Future, 2024)
Abstract Fatalities caused by natural hazards are driven not only by population exposure, but also by their vulnerability to these events, determined by intersecting characteristics such as education, age and income. Empirical evidence of the drivers of social vulnerability, however, is limited due to a lack of relevant data, in particular on a global scale. Consequently, existing global‐scale risk assessments rarely account for social vulnerability. To address this gap, we estimate regression models that predict fatalities caused by past flooding events ( n = 913) based on potential social vulnerability drivers. Analyzing 47 variables calculated from publicly available spatial data sets, we establish five statistically significant vulnerability variables: mean years of schooling; share of elderly; gender income gap; rural settlements; and walking time to nearest healthcare facility. We use the regression coefficients as weights to calculate the “ Glob al‐ E mpirical So cial V ulnerability I ndex (GlobE‐SoVI)” at a spatial resolution of ∼1 km. We find distinct spatial patterns of vulnerability within and across countries, with low GlobE‐SoVI scores (i.e., 1–2) in for example, Northern America, northern Europe, and Australia; and high scores (i.e., 9–10) in for example, northern Africa, the Middle East, and southern Asia. Globally, education has the highest relative contribution to vulnerability (roughly 58%), acting as a driver that reduces vulnerability; all other drivers increase vulnerability, with the gender income gap contributing ∼24% and the elderly another 11%. Due to its empirical foundation, the GlobE‐SoVI advances our understanding of social vulnerability drivers at global scale and can be used for global (flood) risk assessments. , Plain Language Summary Social vulnerability is rarely accounted for in global‐scale risk assessments. We develop an empirical social vulnerability map (“GlobE‐SoVI”) based on five key drivers of social vulnerability to flooding, that is, education, elderly, income inequality, rural settlements and travel time to healthcare, which we establish based on flood fatalities caused by past flooding events. Globally, we find education to have a high and reducing effect on social vulnerability, while all other drivers increase vulnerability. Integrating social vulnerability in global‐scale (flood) risk assessments can help inform global policy frameworks that aim to reduce risks posed by natural hazards and climate change as well as to foster more equitable development globally. , Key Points We develop a global map of social vulnerability at ∼1 km spatial resolution based on five key vulnerability drivers (“GlobE‐SoVI”) We establish vulnerability drivers empirically based on their contribution to predicting fatalities caused by past flooding events Accounting for social vulnerability in global‐scale (flood) risk assessments can inform global policy frameworks that aim to reduce risk