Suchergebnisse

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.

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.

Research reveals that liberals and conservatives in the United States diverge about their beliefs regarding climate change. We show empirically that political affiliation also matters with respect to climate related risks such as flooding from hurricanes. Our study is based on a survey conducted 6 months after Superstorm Sandy in 2012 of over 1,000 residents in flood-prone areas in New York City. Democrats' perception of their probability of suffering flood damage is significantly higher than Republicans' and they are also more likely to invest in individual flood protection measures. However, 50% more Democrats than Republicans in our sample expect to receive federal disaster relief after a major flood. These results highlight the importance of taking into account value-based considerations in designing disaster risk management policies.

Coastal cities are vulnerable to flooding, and flood risk to coastal cities will increase due to sea-level rise. Moreover, Asian cities in particular are subject to considerable population growth and associated urban developments, increasing this risk even more. Empirical data on vulnerability and the cost and benefits of flood risk reduction measures are therefore paramount for sustainable development of these cities. This paper presents an approach to explore the impacts of sea-level rise and socio-economic developments on flood risk for the flood-prone District 4 in Ho Chi Minh City, Vietnam, and to develop and evaluate the effects of different adaptation strategies (new levees, dry- and wet proofing of buildings and elevating roads and buildings). A flood damage model was developed to simulate current and future flood risk using the results from a household survey to establish stage-damage curves for residential buildings. The model has been used to assess the effects of several participatory developed adaptation strategies to reduce flood risk, expressed in expected annual damage (EAD). Adaptation strategies were evaluated assuming combinations of both sea-level scenarios and land-use scenarios. Together with information on costs of these strategies, we calculated the benefit-cost ratio and net present value for the adaptation strategies until 2100, taking into account depreciation rates of 2.5% and 5%. The results of this modelling study indicate that the current flood risk in District 4 is USD 0.31 million per year, increasing up to USD 0.78 million per year in 2100. The net present value and benefit-cost ratios using a discount rate of 5 % range from USD -107 to -1.5 million, and from 0.086 to 0.796 for the different strategies. Using a discount rate of 2.5% leads to an increase in both net present value and benefit-cost ratio. The adaptation strategies wet-proofing and dry-proofing generate the best results using these economic indicators. The information on different strategies will be used by the government of Ho Chi Minh City to determine a new flood protection strategy. Future research should focus on gathering empirical data right after a flood on the occurring damage, as this appears to be the most uncertain factor in the risk assessment. © 2014 Author(s).

MYRIAD-EU has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101003276.