Social vulnerability to floods: Review of case studies and implications for measurement

By S. Rufat, Eric Tate, C. Burton, A. S. Maroof. 2015

752 citations recorded by the source corpus.

Abstract A leading challenge in measuring social vulnerability to hazards is for output metrics to better reflect the context in which vulnerability occurs. Through a meta-analysis of 67 flood disaster case studies (1997–2013), this paper profiles the leading drivers of social vulnerability to floods. The results identify demographic characteristics, socioeconomic status, and health as the leading empirical drivers of social vulnerability to damaging flood events. However, risk perception and coping capacity also featured prominently in the case studies, yet these factors tend to be poorly reflected in many social vulnerability indicators. The influence of social vulnerability drivers varied considerably by disaster stage and national setting, highlighting the importance of context in understanding social vulnerability precursors, processes, and outcomes. To help tailor quantitative indicators of social vulnerability to flood contexts, the article concludes with recommendations concerning temporal context, measurability, and indicator interrelationships.

Subfields: Global and Planetary Change, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/aaeba1caaa17497e2c9e3d473cf78f8c3338b9e9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Richard Sliuzas
2. C. Kuhlicke
3. Eric Tate
4. Heidi Kreibich
5. P. Bubeck
6. T. Grothmann
7. Jeroen C. J. H. Aerts

In Sociology and Political Science

1. A. Strong
2. Haoyi Xiong
3. Travis Kraus
4. A. Heidenreich
5. C. Kuhlicke
6. Eric Tate
7. C. Begg
8. Heidi Kreibich

Citations in the corpus

• Climate vulnerability mapping: A systematic review and future prospects (2019, background): “…a growing literature (Becker, Saisana, Paruolo, & Vandecasteele, 2017; Greco, Ishizaka, Tasiou, & Torrisil, 2018; Nardo et al., 2005; Reckien, 2018; Rufat et al., 2015; Tate, 2012), and issues at each stage of construction—the choice of indicators, analysis scale, measurement errors,…”
• Flood recovery and property acquisition in Cedar Rapids, Iowa (2016, methodology): “Based on these criteria, Rufat et al. (2015) identified sixty-seven empirical case studies, which we further winnowed in this research to only include those focused on the recovery stage from floods in more developed national settings.”
• The behavioral turn in flood risk management, its assumptions and potential implications (2020, background): “…adaptive capacities of individuals are shaped by a multitude of factors, most of them eluding from simple measurements by means of official statistical data (e.g., age, income, and gender) (Grothmann & Patt, 2005; Kuhlicke, Scolobig, Tapsell, Steinführer, & De Marchi, 2011a; Rufat et al., 2015).”