The Netherlands is a kingdom known for resisting the perils of natural disaster and keeping records of how these great feats were accomplished. The Dutch have measured physical risk through methods such as the intricate VNK models to predict flood scenarios, but little research has been conducted to examine how the people living in affected areas could be impacted from a natural disaster event. This study employs fine-scale data to construct a social vulnerability index for the 164 districts of the low-lying delta province of Zeeland. The methodology used to measure social vulnerability is built on recent social vulnerability and resilience research that has been conducted in North America, Asia, and Europe. Specific attention is paid to methods used previously and how they can be improved from a statistical standpoint. Factor Analysis of 35 variables selected from the resilience and social vulnerability literature results in nine factors explaining about 72% of the total variance. The factors of vulnerability in Zeeland include Density of the Built Environment and Public Support, Reduced Wealth and Single Households, Infrastructure Accessibility and Career Qualifications, Recovery Capacity and Female Gender, Personal Wealth, Occupation, Residential Quality, Access to Healthcare, and Evacuation Potential. The index is constructed using data for all 35 variables with weight decided by the variance explained by each factor. Relative index scores range from a low social vulnerability score of 0.248 in the district Kattendijk, Goes, to the highest social vulnerability score of 0.458 found in Oudelandse Hoeve, Ternuezen. The highest-scoring districts are located towards the South of Zeeland. Eight of the ten most vulnerable districts located in Terneuzen. The Municipality of Goes contains more low-scoring districts than any other municipality. The majority of low scoring, less vulnerable districts are located on the Central lobe of Zeeland. The results of the social vulnerability analysis provide new insights for policy makers, researchers, and community stakeholders that could be combined with Dutch flood-scenario models to guide planning efforts in the Netherlands to mitigate the damaging impacts of future floods. The study provides an example for adaptation of a social vulnerability index for a fine level of analysis.
| Identifer | oai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-04132015-145548 |
| Date | 12 May 2015 |
| Creators | Kirby, Ryan Hamilton |
| Contributors | Dismukes, David E, Lam, Nina S, Reams, Margaret Anne |
| Publisher | LSU |
| Source Sets | Louisiana State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lsu.edu/docs/available/etd-04132015-145548/ |
| Rights | restricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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