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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

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Abstract. The employment of damage mitigation measures (DMMs) by individuals is an important component of integrated flood risk management. In order to promote efficient damage mitigation measures, accurate estimates of their damage mitigation potential are required. That is, for correctly assessing the damage mitigation measures' effectiveness from survey data, one needs to control for sources of bias. A biased estimate can occur if risk characteristics differ between individuals who have, or have not, implemented mitigation measures. This study removed this bias by applying an econometric evaluation technique called propensity score matching (PSM) to a survey of German households along three major rivers that were flooded in 2002, 2005, and 2006. The application of this method detected substantial overestimates of mitigation measures' effectiveness if bias is not controlled for, ranging from nearly EUR 1700 to 15 000 per measure. Bias-corrected effectiveness estimates of several mitigation measures show that these measures are still very effective since they prevent between EUR 6700 and 14 000 of flood damage per flood event. This study concludes with four main recommendations regarding how to better apply propensity score matching in future studies, and makes several policy recommendations.

Established in 1985, the Wharton Risk Management and Decision Processes Center develops and promotes effective corporate and public policies for low-probability events with potentially catastrophic consequences through the integration of risk assessment, and risk perception with risk management strategies. Natural disasters, technological hazards, and national and international security issues (e.g., terrorism risk insurance markets, protection of critical infrastructure, global security) are among the extreme events that are the focus of the Center's research. The Risk Center's neutrality allows it to undertake large-scale projects in conjunction with other researchers and organizations in the public and private sectors. Building on the disciplines of economics, decision sciences, finance, insurance, marketing and psychology, the Center supports and undertakes field and experimental studies of risk and uncertainty to better understand how individuals and organizations make choices under conditions of risk and uncertainty. Risk Center research also investigates the effectiveness of strategies such as risk communication, information sharing, incentive systems, insurance, regulation and public-private collaborations at a national and international scale. From these findings, the Wharton Risk Center's research team-over 50 faculty, fellows and doctoral students-is able to design new approaches to enable individuals and organizations to make better decisions regarding risk under various regulatory and market conditions.

Flood disasters severely impact human subjective well-being (SWB). Nevertheless, few studies have examined the influence of flood events on individual well-being and how such impacts may be limited by flood protection measures. This study estimates the long term impacts on individual subjective well-being of flood experiences, individual subjective flood risk perceptions, and household flood preparedness decisions. These effects are monetised and placed in context through a comparison with impacts of other adverse events on well-being. We collected data from households in flood-prone areas in France. The results indicate that experiencing a flood has a large negative impact on subjective well-being that is incompletely attenuated over time. Moreover, individuals do not need to be directly affected by floods to suffer SWB losses since subjective well-being is lower for those who expect their flood risk to increase or who have seen a neighbour being flooded. Floodplain inhabitants who prepared for flooding by elevating their home have a higher subjective well-being. A monetisation of the aforementioned well-being impacts shows that a flood requires €150,000 in immediate compensation to attenuate SWB losses. The decomposition of the monetised impacts of flood experience into tangible losses and intangible effects on SWB shows that intangible effects are about twice as large as the tangible direct monetary flood losses. Investments in flood protection infrastructure may be under funded if the intangible SWB benefits of flood protection are not taken into account.

There has been much research regarding the perceptions, preferences, behaviour, and responses of people exposed to flooding and other natural hazards. Cross-sectional surveys have been the predominant method applied in such research. While cross-sectional data can provide a snapshot of a respondent's behaviour and perceptions, it cannot be assumed that the respondent's perceptions are constant over time. As a result, many important research questions relating to dynamic processes, such as changes in risk perceptions, adaptation behaviour, and resilience cannot be fully addressed by cross-sectional surveys. To overcome these shortcomings, there has been a call for developing longitudinal (or panel) datasets in research on natural hazards, vulnerabilities, and risks. However, experiences with implementing longitudinal surveys in the flood risk domain (FRD), which pose distinct methodological challenges, are largely lacking. The key problems are sample recruitment, attrition rate, and attrition bias. We present a review of the few existing longitudinal surveys in the FRD. In addition, we investigate the potential attrition bias and attrition rates in a panel dataset of flood-affected households in Germany. We find little potential for attrition bias to occur. High attrition rates across longitudinal survey waves are the larger concern. A high attrition rate rapidly depletes the longitudinal sample. To overcome high attrition, longitudinal data should be collected as part of a multisector partnership to allow for sufficient resources to implement sample retention strategies. If flood-specific panels are developed, different sample retention strategies should be applied and evaluated in future research to understand how much-needed longitudinal surveying techniques can be successfully applied to the study of individuals threatened by flooding.

Kinetic data of the oxygen evolution reaction at Pt electrodes in alkaline solutions have shown two types of behavior, a Tafel slope of 60 mV/decade of current density at low applied current densities and a slope of 120 mV/decade at high current densities. At low current densities, and rate of the reaction was found to be independent of the thickness of the underlying Pt oxide film, while the electrode potential has a -120 mV dependence on solution pH. At high current densities, the rate is strongly dependent on film thickness and exhibits a -180 mV dependence on pH. A mechanism of the oxygen evolution reaction which is consistent with this data is presented. It involves a rate-determining first electron transfer step at high current densities. At low current densities, the chemical step following the now rapid first electron transfer step is rate limiting. The -180 mV pH dependence observed at high current densities implies a fractional reaction order of 3/2 with respect to the OH-ion. This has been explained in terms of a dual barrier model of the metal oxide film/solution interface. According to this model, the rates across each barrier are pH dependent. The fractional reaction order is due to the existence of these two dependences and is primarily related to the dependence of the potential difference across the outer Helmholtz layer on pH.