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Akmal Akmal Umar
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Anatomy of a Disaster
Mapping Multi-layered Typological Vulnerabilities Across European Flood Events
Flood vulnerability research often lacks empirical validation against observed damage and rarely compares events across countries. This thesis asks to what extent theoretical flood vulnerability indicators align with actual post-disaster impact zones to define spatial typologies across recent European flood events. Four cases are compared, the 2021 Ahr Valley floods in Germany, the 2023 Emilia-Romagna floods in Italy, the 2024 Kłodzko Valley floods in Poland, and the 2024 Valencia floods in Spain, using a literature-derived indicator set operationalized on a harmonized 100 m grid. Blockwise PCA, k-means clustering, and spatial-lag ordinal regression are applied to each case and compared. An urban core typology with high built mass, dense roads, and low vegetation cover recurs in all four countries and carries the highest damage share in every case. Road density shows a significant positive association with damage in all four regional models, and built mass in three, with Germany's reversal traced to local valley terrain. Socio-demographic and governance conditions shape damage severity but vary by country. The findings support built environment intensity as a transferable basis for flood risk screening, while socio-demographic dimensions require local calibration.
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Flood vulnerability research often lacks empirical validation against observed damage and rarely compares events across countries. This thesis asks to what extent theoretical flood vulnerability indicators align with actual post-disaster impact zones to define spatial typologies across recent European flood events. Four cases are compared, the 2021 Ahr Valley floods in Germany, the 2023 Emilia-Romagna floods in Italy, the 2024 Kłodzko Valley floods in Poland, and the 2024 Valencia floods in Spain, using a literature-derived indicator set operationalized on a harmonized 100 m grid. Blockwise PCA, k-means clustering, and spatial-lag ordinal regression are applied to each case and compared. An urban core typology with high built mass, dense roads, and low vegetation cover recurs in all four countries and carries the highest damage share in every case. Road density shows a significant positive association with damage in all four regional models, and built mass in three, with Germany's reversal traced to local valley terrain. Socio-demographic and governance conditions shape damage severity but vary by country. The findings support built environment intensity as a transferable basis for flood risk screening, while socio-demographic dimensions require local calibration.