Flood risk assessment approaches have traditionally been dominated by measures of economic damage. However, the importance of understanding the social impacts of flooding are increasingly being acknowledged. Social vulnerability indices have been constructed in various geographical contexts to understand the relative susceptibility of different social groups to flood hazards. However, integrated assessments of social vulnerability, exposure, and hazard information are lacking. Here, we construct a national social vulnerability index (SVI) for Denmark and combine this with direct and indirect social exposure data and coastal flood hazard data to construct a national social flood risk index (SFRI). Results show the spatial distribution of social flood vulnerability and social flood risk in Denmark. Our findings illustrate that including social data in flood risk assessment could significantly change our understanding of flood risk on a national scale. Methodologically, our work introduces a comprehensive flood risk modeling approach that explicitly considers the social impacts of flooding in all model components. The application of this model in Denmark reveals that the social impacts of flooding extend far beyond flooded areas, thus highlighting the importance of explicitly considering direct and indirect social exposure in addition to social vulnerability in flood risk assessment. By introducing a comprehensive, socially specific approach to flood risk assessment that is usable within existing risk management frameworks such as the EU Floods Directive, our work aims to mainstream social wellbeing, resilience, and justice as central considerations in decision making on flood risk management.
Marine Spatial Planning (MSP) requires the analysis of the spatial distribution of marine uses and environmental conditions. Such analyzes can be carried out with GIS, but standard GIS programs do not feature a toolbox that combines the most needed functionalities for such analyses. The SPACEA toolbox presented here was created to bundle and adapt existing functionalities in one toolbox. SPACEA consists of several script tools that have been designed to be user-friendly and applicable to different analyzes for MSP. This includes the processing of different input layers with regard to marine uses and environmental conditions. The main functionalities of SPACEA are exemplified in a fictional case study in the Baltic Sea, where the tools are applied to find potentially suitable areas for mussel farming. The tools feature a user-friendly interface and more experienced users may also use the provided sample codes to run it from the python window or as a stand-alone script. As such, the tools can be applied by users with different levels of GIS knowledge and experience.