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This is the first study that shifts the narrative of climate policy evaluation from one of GDP growth to a message of improving social welfare, as captured by the HDI. This could make it easier for political leaders and climate negotiators to publicly commit themselves to ambitious carbon emission reduction goals, such as limiting global warming to 2°C, as in the (non-binding) agreement made at COP 21 in Paris in 2015. We find that if impacts are framed in terms of growth in HDI per t CO

Most cost-benefit analysis (CBA) textbooks and guidelines recognize the objective of CBAs to improve social welfare—a function of well-being of all individuals, conceptualized by utility. However, today's common practice to value flood risk management benefits as the reduction of the expected annual damages does not comply with this concept of social welfare, since it erroneously focuses on money instead of well-being (utility). Diminishing marginal utility of money implies that risk aversion and income differences should be taken into account while calculating the social welfare benefits of flood risk management. This is especially important when social vulnerability is high, damage compensation is incomplete and the distribution of income is regarded as unfair and income is not redistributed in other ways. Disagreement, misconception, complexity, untrained professionals, political economy and failing guidance are potential reasons why these concepts are not being applied. Compared to the common practice, a theoretically more sound social welfare approach to CBA for flood risk management leads to different conclusions on who to target, what to do, how much to invest and how to share risks, with increased emphasis on resiliency measures for population segments with low income and high social vulnerability. The social welfare approach to CBA, illustrated in this study in the context of floods, can be applied to other climate risks as well, such as storms, droughts, and landslides. WIREs Clim Change 2017, 8:e446. doi:10.1002/wcc.446. For further resources related to this article, please visit the WIREs website.

Most cost-benefit analysis (CBA) textbooks and guidelines recognize the objective of CBAs to improve social welfare—a function of well-being of all individuals, conceptualized by utility. However, today's common practice to value flood risk management benefits as the reduction of the expected annual damages does not comply with this concept of social welfare, since it erroneously focuses on money instead of well-being (utility). Diminishing marginal utility of money implies that risk aversion and income differences should be taken into account while calculating the social welfare benefits of flood risk management. This is especially important when social vulnerability is high, damage compensation is incomplete and the distribution of income is regarded as unfair and income is not redistributed in other ways. Disagreement, misconception, complexity, untrained professionals, political economy and failing guidance are potential reasons why these concepts are not being applied. Compared to the common practice, a theoretically more sound social welfare approach to CBA for flood risk management leads to different conclusions on who to target, what to do, how much to invest and how to share risks, with increased emphasis on resiliency measures for population segments with low income and high social vulnerability. The social welfare approach to CBA, illustrated in this study in the context of floods, can be applied to other climate risks as well, such as storms, droughts, and landslides

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks.

This paper examines the problem of "charity hazard", which is the crowding out of private insurance demand by government compensation. In the context of flood insurance and disaster financing, charity hazard is particularly worrisome given current trends of increasing flood risks as a result of climate change and more people choosing to locate in high-risk areas. We conduct an experimental analysis of the influence on flood insurance demand of risk and ambiguity preferences and the availability of different forms of government compensation for disaster damage. Certain and risky government compensation crowd out demand, confirming charity hazard, but this is not observed for ambiguous compensation. Ambiguity averse subjects have higher insurance demand when government compensation is ambiguous relative to risky. Policy recommendations are discussed to overcome charity hazard

Flood risk management is becoming increasingly important, because more people are settling in flood-prone areas, and flood risk is increasing in many regions due to extreme weather events associated with climate change. It has been proposed that appropriately designed flood risk communication campaigns can stimulate floodplain inhabitants to prepare for flooding, and encourage adaptation to climate change. However, such campaigns do not always result in the desired action, and the effectiveness of communication in raising flood risk awareness and improving flood preparedness has hardly been studied. We evaluate different flood risk communication strategies, using an agent-based modelling approach, which is especially suitable for examining the effect of communication on each individual, and how flood risk communication can propagate through an individual's social network. Our modelling results show that tailored, people-centred, flood risk communication can be significantly more effective than the common approach of top-down government communication, even when tailored communication reaches fewer individuals. Furthermore, communication on how to protect against floods, in addition to providing information about flood risk, is much more effective than the traditional strategy of communicating only about flood risk. Another main finding is that a person's social network can have a significant effect on whether or not individuals take protective action. This leads to the recommendation that flood risk communication should aim at exploiting this natural amplifying effect of social networks, for instance, through the use of social media.

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks.