Social Vulnerability to Coastal Floods in Denmark: investigating the spatial patterns among the Danish municipalities
Author
Pappa, Maria
Term
4. term
Education
Publication year
2019
Submitted on
2019-06-06
Pages
58
Abstract
Klimaændringer forventes at forværre kystoversvømmelser i Danmark. Mange risikovurderinger fokuserer på, hvor vandet kan nå; dette studie undersøger, hvem der er mest udsat og hvorfor. Det kaldes social sårbarhed—borgeres og lokalsamfunds evne til at forberede sig på, håndtere og komme sig efter oversvømmelser. Med kommunale socioøkonomiske data konstruerede vi et Socialt Sårbarhedsindeks med SoVI-Lite, en forenklet udgave af SoVI, og beregnede resultater for 97 kommuner. De fleste kommuner har moderat sårbarhed. Tyve kommuner scorer højt og danner to klynger: (1) de fire mest befolkede, urbane kommuner; og (2) tyndt befolkede, landlige øer i landets indre farvande. Kommuner med lavest sårbarhed samler sig omkring Københavns Kommune. En faktoranalyse—en statistisk metode, der grupperer beslægtede variable—identificerede tre komponenter med størst betydning; tilsammen forklarer de 83% af variationen i data. Resultaterne peger på, at sårbarhed hænger sammen med de enkelte kommuners særlige socio-demografiske udfordringer. Indsigterne kan indgå i eksisterende oversvømmelsesrisikovurderinger, understøtte lokal planlægning og øge opmærksomheden om kystoversvømmelsernes sociale konsekvenser.
Climate change is expected to increase coastal flooding in Denmark. Many risk assessments focus on where water might go; this study asks who is most at risk and why. That is social vulnerability—the ability of people and communities to prepare for, cope with, and recover from floods. Using municipal-level socio-economic data, we built a Social Vulnerability Index with SoVI-Lite, a simplified version of the SoVI approach, and calculated scores for 97 municipalities. Most municipalities show moderate vulnerability. Twenty scored high, forming two clusters: (1) the four most populated urban municipalities; and (2) sparsely populated rural islands in the country’s inner coastal areas. Municipalities with the lowest vulnerability tend to cluster around Copenhagen Municipality. A factor analysis—a statistical technique that groups related variables—identified three components that most strongly influence vulnerability; together they explain 83% of the variation in the data. The findings suggest vulnerability is linked to each municipality’s specific socio-demographic challenges. These insights can be integrated into existing flood risk assessments, support local planning, and raise awareness of the social impacts of coastal flooding.
[This abstract was generated with the help of AI]
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