Title: Effect of Local Context on Flood Vulnerability Identification
Description: Flood occurrences are on the increase all over the world and large numbers of people are constantly exposed to the risk associated with these disasters. Vulnerability assessment is integral to flood risk management. It helps identify areas with high flood risk and guides resilience policies. Vulnerability, being an intangible notion, is difficult to assess. Many municipalities resort to field-survey and community outreach based assessment processes. These tools are sensitive to local context, but are time and resource intensive. Consequently, many municipalities with limited resources, especially those in developing countries, cannot adopt this methodology. Moreover, this tool is susceptible to political biases and corruption. Another widely used assessment method is indicator-based, which involves developing Flood Vulnerability Indices (FVIs) by using available data to provide a logical image of a region's vulnerability to disaster. The quantitative nature of this tool makes it quicker, cost effective, and objective.

But this attempt to measure a qualitative concept like vulnerability exposes these indices to statistical fallacies, leading to inadequate results. Moreover, these one-size-fits-all indices fail to acknowledge the distinct characteristics of a society. This study aims to investigate the effectiveness of FVIs and find out if their quantitative nature, by ignoring the intangible local characteristics of society, compromises the credibility of outcomes derived. Purpose is to learn if these indices can provide with adequate understanding of vulnerability in areas where governments either don’t have the time and capital to invest in extensive field surveys, or are plagued by corruption. As a case study, this thesis examines the application of Bathi and Das’ flood vulnerability index on New Orleans’ socio-economic and environmental data and compares the results to those of assessment methods developed by the city of New Orleans. This helps understand how flood risk identification through local tools differs from FVIs, and the extent to which this influences the flood mitigation and adaptation policies made.

The research concludes with recommendations to statistically improve FVIs and, when necessary, use a combination of local knowledge based qualitative techniques and FVIs to get adequate results, in turn making better informed decisions when devising flood resilience policies.