Impacts of flooding are expected to increase, most notably in residential areas. As a consequence, private households are increasingly encouraged to engage in private flood mitigation complementary to public measures. Despite the growing literature on private flood mitigation, little is known about how social capital influences households' perception of and coping with flood risks. This study draws on survey data of 226 flood-prone households in two Austrian Alpine municipalities, both recently affected by riverine flooding. We show that social capital cuts both ways: on the positive side, social capital increases perceived self-efficacy and provides critical support during and most notably after flood events. On the negative side, social capital reduces flood risk perceptions of private households. While social ties are effective when responding to and recovering from floods, the expectation of social support downplays risk, making precautionary action by households less likely. The results also show that floodaffected households receive more social support than they provide to others. In the long-run, this can lead to a problematic reciprocity imbalance, challenging the long-term stability of the interpersonal exchanges underlying social capital. Among the various sources of social support, informal social networks (neighbours, friends and relatives) provide the most important workforce in the response and recovery phase of a flood event. It is therefore crucial for flood risk management to recognise and promote the protective quality of social capital alongside conventional structural and non-structural measures.

Flood preparedness of private households is regarded an essential building block of integrated flood risk management. In the past decade, numerous empirical studies have employed the protection motivation theory (PMT) to explain flood mitigation behavior at the household level. However, much of this research has produced mixed results and could not consistently confirm the strength and direction of the relationships between the PMT components. Based on a survey of 2,007 households in flood-prone areas, this study revisits the model structure of the PMT by means of structural equation modeling. Compared to the methods used in previous studies, this modeling technique allows us to capture the PMT components in greater detail and to comprehensively test their hypothesized interrelations. Our results point to two separate routes leading to two different response types: A protective route from coping appraisal to protective behavior, and a non-protective route from threat appraisal to non-protective responses. Risk perception is not found to be part of the protective route, neither are non-protective responses confirmed to undermine protection motivation. The two separate routes are observed consistently across all combinations of the six protective and four nonprotective responses assessed in this study. In the light of encouraging private flood adaptation, risk communication measures should specifically target the protective route and avoid (accidentally) providing incentives that fall within the non-protective route. This cross-sectional study, however, cannot establish how the two routes interrelate over time. More experimental and longitudinal research is required to address potential feedback effects and the role of decision stages.

The recent shift to individualisation of flood risk calls for a stronger involvement of private actors. Bottom‐up citizen initiatives (BUIs) may bring together governmental bodies with people at risk. Drawing on a screening of existing BUIs in Europe, North America, and Australia and an in‐depth analysis of three study sites, this paper maps BUI activities to stages in the risk management cycle and discusses the institutional, relational and social proximity between BUIs and other stakeholders. Flood BUIs often take over roles that the authorities are not willing or able to fulfil. BUIs emerge out of frustration with current risk policies, after a catastrophic flood event, government‐initiated engagement projects or targeted funding opportunities. BUIs can take different forms, ranging from oppositional pressure groups, self‐help movements for disaster response and recovery, to initiatives formally installed by law. While self‐organised BUIs benefit from high proximity to their home communities, formalised BUIs are deeper embedded in existing institutional structures. In order to gain a stronger voice in the risk debate, BUIs need to expand from the local level to catchment areas and exchange expertise and resources in nationwide or cross‐border networks. However, BUIs may create parallel political structures that are not democratically legitimised.

Previous research in non-disaster contexts has shown that the concept of collective efficacy, which is a group's sense of its ability to achieve a specific objective, assists understanding of community readiness and households' decisions to take preparedness actions. Collective efficacy expands the concept of social capital, which refers to social resources such as trust, norms and networks, by addressing how likely communities are to activate these resources for specific tasks. This paper empirically investigates the effect of three distinct collective efficacy components on risk perception, fear and self-efficacy regarding natural hazards in Austria. The three components have differing impacts on risk and coping beliefs: (1) Social cohesion decreases risk perception and fear but has no effect on self-efficacy; (2) Efficacy belief in social support increases self-efficacy; (3) Efficacy belief in citizen groups increases risk perception and fear. The combination of efficacy belief in social support and citizen groups seems to be most promising for stimulating protective action, as they together promote both risk and coping appraisal. However, overreliance on social support may have the undesirable effect of creating a false sense of safety among disaster-prone households. The findings demonstrate that collective efficacy provides a meaningful perspective from which to examine risk and coping beliefs but caution against treating it as an umbrella concept, given the differing effects of its components. Future studies are needed to investigate the impact of collective efficacy on other key explanatory factors of protective action, such as response efficacy or non-protective responses.

Self-efficacy is one of the strongest and most consistent drivers of private flood mitigation behavior; however, the factors influencing self-efficacy in the context of flooding remain unclear. The present study examines three potential antecedents of self-efficacy: personal and vicarious experiences of floods or building-related events, social norms for private flood preparedness, and personal competencies such as technical abilities and social skills. While controlling for other drivers in a protection motivation theory (PMT) framework, these antecedents are tested as precursors of self-efficacy and intentions to improve flood resilience. Structural equation modeling is applied to conduct mediation analyses with survey data of 381 floodprone households in Austria. Contrary to theoretical expectations, personal and vicarious experiences do not predict self-efficacy, presumably because rare flood events and changing hazard characteristics do not facilitate generalizable performance accomplishments. Social norms strongly and consistently influence self-efficacy, especially for actions observable by others, and also directly influence protective responses. Personal competencies increase self-efficacy and support protective action, particularly with regard to preventive and structural measures. The strength and direction of the antecedents of self-efficacy as well as of other PMT determinants vary between general and specific protective responses. This study provides important insights for risk managers, suggesting that interventions involving social norms and personal competencies can be effective in stimulating self-efficacy and, in turn, private flood mitigation. Interventions and research should clearly differentiate between general intention and the implementation of specific measures, and should address cumulative, synergistic, or tradeoff interrelations between multiple measures.