Please use this identifier to cite or link to this item: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/6373
Title: Developing a multi – facet social vulnerability measure for flood disasters at the micro – level assessment
Authors: Karunarathne, Y. A
Lee, Gunhak
Keywords: Social vulnerability
Flood inundation
Multi-facet composite social vulnerability index
Vulnerability mapping
Sri Lankan flood
Issue Date: 2020
Publisher: ELSEVIER
Citation: Karunarathne, Y. A. and Lee, Gunhak. (2020). Developing a multi – facet social vulnerability measure for flood disasters at the micro – level assessment. ELSEVIER
Abstract: Sri Lanka has experienced severe consequences of flood disasters in recent decades. Hundreds of thousands of people and their homes were affected by mass floods in 2016 and 2017. However, the quantification of social vulnerability to such calamities has not been examined, although this is critical to achieve more efficient response and recovery. In this context, we shed light on an influential mechanism in order to measure social vulnerability to flooding in both rural and urban areas. We developed the multi-facet composite social vulner- ability index (MFCSVI) by considering 31 robust variables drawn from five main components including socio- demographic, physical, financial, health, and social networks, as well as related social capital factors. We investigated 21 local administrative units by covering 405 affected households through a household survey. The results demonstrate diverse situations of social vulnerability to flooding between and within regions. The households from Kuruwita are significantly less vulnerable compared to those from Elapatha and Colombo. Our research provides empirical insight for policy makers who are interested in gauging social vulnerability and planning efficient solutions for response and recovery. Especially, this study contributes to the existing body of vulnerability research by elaborating traditional measures of social vulnerability by applying highly detailed survey data and various weight schemes of influential factors for the vulnerability assessment. Also, regional disparity between rural and urban areas is obviously worth to note for Sri Lankan vulnerability assessment.
URI: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/6373
Appears in Collections:Department of Geography

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