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Self-protective behavior by residents of flood-prone urban areas can reduce monetary flood damage by 80%, and reduce the need for public risk management. But, research on the determinants of private households' prevention of damage by natural hazards is rare, especially in Germany. To answer the question of why some people take precautionary action while others do not, a socio-psychological model based on Protection Motivation Theory (PMT) is developed, explaining private precautionary damage prevention by residents' perceptions of previous flood experience, risk of future floods, reliability of public flood protection, the efficacy and costs of self-protective behavior, their perceived ability to perform these actions, and non-protective responses like wishful thinking. The validity of the proposed model is explored by means of representative quantitative telephone surveys and regression analyses, and compared with a socio-economic model (including residents' age, gender, income, school degree and being owner or tenant). Participants were 157 residents of floodprone homes in Cologne, Germany, a city that has traditionally been subject to minor and major flood events. Results of the study show the explanatory power of the socio-psychological model, with important implications for public risk communication efforts. To motivate residents in flood-prone areas to take their share in damage prevention, it is essential to communicate not only the risk of flooding and its potential consequences, but also the possibility, effectiveness and cost of private precautionary measures.

The article introduces the notion of adaptiveness and discusses the role of social learning in it. Adaptiveness refers to the capacity of a social actor or socialecological system to adapt in response to, or in anticipation of, changes in the environment. We explore arguments both from a theoretical perspective and through illustrations from case studies of water management in the Alps of Europe and Mekong in southeast Asia. We propose and illustrate that social learning processes are important for building adaptiveness in several ways and at different scales. Social learning can help cope with informational uncertainty; reduce normative uncertainty; build consensus on criteria for monitoring and evaluation; empower stakeholders to take adaptive actions; reduce conflicts and identify synergies between adaptations; and improve fairness of decisions and actions. Findings in the case studies provide some support for these generalizations but often with caveats related to diversity of stakeholder interests, levels of shared understanding versus contested knowledge and scale of coordination. For this reason, we suggest that future work pays greater attention to issues of agency, knowledge and scale: What strategies have individuals and organizations pursued in successful examples of social learning? How are the boundaries and interactions between science, policy and practice managed? How does social learning occur across spatial and temporal scales?

Recent policy changes highlight the need for citizens to take adaptive actions to reduce flood-related impacts. Here, we argue that these changes represent a wider behavioral turn in flood risk management (FRM). The behavioral turn is based on three fundamental assumptions: first, that the motivations of citizens to take adaptive actions can be well understood so that these motivations can be targeted in the practice of FRM; second, that private adaptive measures and actions are effective in reducing flood risk; and third, that individuals have the capacities to implement such measures. We assess the extent to which the assumptions can be supported by empirical evidence. We do this by engaging with three intellectual catchments. We turn to research by psychologists and other behavioral scientists which focus on the sociopsychological factors which influence individual motivations (Assumption 1). We engage with economists, engineers, and quantitative risk analysts who explore the extent to which individuals can reduce flood related impacts by quantifying the effectiveness and efficiency of household-level adaptive measures (Assumption 2). We converse with human geographers and sociologists who explore the types of capacities households require to adapt to and cope with threatening events