The 2007 European Union Floods Directive encouraged member nations to pursue a more integrated view of flood risks and management strategies, taking into account social vulnerabilities of residents. To date, most flood-risk analyses conducted by the Dutch government have focused on physical risk. This study utilizes fine-scale data to construct a social vulnerability index for 147 districts of the Dutch province of Zeeland, located in the Southwestern Delta and the scene of widespread devastation following the 1953 North Sea Flood. Factor analysis of 25 indicators of social vulnerability selected from related research in Europe and the United States results in seven factors explaining roughly 66% of the total variance. These factors of social vulnerability in Zeeland are urban density, low-income households, recent population change, female gender, train access, and self-employed and service-sector employment. The index was constructed using the toploading variable in each of these factors, with weights determined by the variance explained by each factor. Scores range from a low of 0.20 in Schore, municipality of Kapelle, to the highest score of 0.64 in Oudelandse Hoeve of Terneuzen. The most vulnerable districts are located in South Zeeland, with eight of the 10 found in Terneuzen. The majority of less vulnerable districts are located in Zeeland's central region.

No abstract

Residents of south Louisiana face a range of increasing, climate-related flood exposure risks that could be reduced through local floodplain management and hazard mitigation planning. A major incentive for community planning to reduce exposure to flood risks is offered by the Community Rating System (CRS) of the National Flood Insurance Program (NFIP). The NFIP encourages local collective action by offering reduced flood insurance premiums for individual policy holders of communities where suggested risk-reducing measures have been implemented. This preliminary analysis examines the extent to which parishes (counties) in southern Louisiana have implemented the suggested policy actions and identifies key factors that account for variation in the implementation of the measures. More measures implemented results in higher CRS scores. Potential influences on scores include socioeconomic attributes of residents, government capacity, average elevation and past flood events. The results of multiple regression analysis indicate that higher CRS scores are associated most closely with higher median housing values. Furthermore, higher scores are found in parishes with more local municipalities that participate in the CRS program. The number of floods in the last five years and the revenue base of the parish does not appear to influence CRS scores. The results shed light on the conditions under which local adaptive planning to mitigate increasing flood risks is more likely to be implemented and offer insights for program administrators, researchers and community stakeholders.

No abstract