Brief communication: Sendai framework for disaster risk reduction – success or warning sign for Paris?

In March 2015, a new international blueprint for disaster risk reduction (DRR) was adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14–18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading the Sendai Framework for DRR (SFDRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change

Reflections on the current debate on how to link flood insurance and disaster risk reduction in the European Union

Flood insurance differs widely in scope and form across Europe. Against the backdrop of rising flood losses a debate about the role of EU policy in shaping the future of this compensation mechanism is led by policy makers and industry. In this paper we investigate if and how current EU policies influence flood insurance. While the question of supply and demand is at the core of the debate, we argue that another key dimension is often overlooked: how to use insurance as a lever for risk reduction and prevention efforts. We investigate if and how current EU policies interplay with these two dimensions and then reflect on the national policy level. We illustrate two conflicting cases of flood insurance: the United Kingdom (UK), where flood insurance provision is widely available, but subject to current reform, and the Netherlands, where efforts to introduce a broad flood insurance coverage have only recently failed. In analysing the current positions on the role of the EU in shaping flood insurance we conclude that there is wide agreement that a complete harmonisation of flood insurance offering across the EU is unlikely to be effective. We determine that there is clear scope for the EU to play a greater role in linking risk transfer and prevention, beyond existing channels, to ensure an integrated approach to flood risk management across the EU

Regional Inequalities in Flood Insurance Affordability and Uptake under Climate Change

Flood insurance coverage can enhance financial resilience of households to changing flood risk caused by climate change. However, income inequalities imply that not all households can afford flood insurance. The uptake of flood insurance in voluntary markets may decline when flood risk increases as a result of climate change. This increase in flood risk may cause substantially higher risk-based insurance premiums, reduce the willingness to purchase flood insurance, and worsen problems with the unaffordability of coverage for low-income households. A socio-economic tipping-point can occur when the functioning of a formal flood insurance system is hampered by diminishing demand for coverage. In this study, we examine whether such a tipping-point can occur in Europe for current flood insurance systems under different trends in future flood risk caused by climate and socio-economic change. This analysis gives insights into regional inequalities concerning the ability to continue to use flood insurance as an instrument to adapt to changing flood risk. For this study, we adapt the “Dynamic Integrated Flood and Insurance” (DIFI) model by integrating new flood risk simulations in the model that enable examining impacts from various scenarios of climate and socio-economic change on flood insurance premiums and consumer demand. Our results show rising unaffordability and declining demand for flood insurance across scenarios towards 2080. Under a high climate change scenario, simulations show the occurrence of a socio-economic tipping-point in several regions, where insurance uptake almost disappears. A tipping-point and related inequalities in the ability to use flood insurance as an adaptation instrument can be mitigated by introducing reforms of flood insurance arrangements

Flood Vulnerability Models and Household Flood Damage Mitigation Measures: An Econometric Analysis of Survey Data

Flood events are expected to increase in their frequency and severity, which results in higher flood risk without additional adaptation measures. The information gained from flood risk models is essential in effective disaster risk management. However, vulnerability estimations are often a large driver of uncertainty, and flood damage is rarely estimated due to a lack of empirical damage data from flood events. This study uses a unique data set with experienced damages and the implementation of flood damage mitigation (FDM) measures on the household level, collected after the flood event in the Netherlands in 2021. Flood damage models that control for several hazard, exposure, and vulnerability indicators are estimated and allow for additional input in flood risk models. Previous estimates of the effectiveness of FDM measures are prone to a selection bias, as households that do, and do not implement FDM measures systematically differ in their risk profiles. By using an instrumental variable-estimation, this study overcomes this selection bias and finds significant reductions in flood damage due to FDM measures. These reductions can be incorporated in multivariate flood vulnerability estimations, which indicate that FDM measures significantly reduce flood damage. Providing information on flood hazard, as well as implementing early warning systems, is crucial for ensuring effective flood risk management

A look into our future under climate change?: Adaptation and migration intentions following extreme flooding in the Netherlands

Worldwide, increased flood risk from climate change prompts adaptive behavior of households in situ or through migration. Both can be sensible adaptation responses involving tradeoffs, and understanding their drivers is important for effective climate policy. However, in-situ adaptation and migration are rarely studied in combination and research on how extreme events trigger adaptive behavior in originally low-risk areas is lacking. We analyze survey data from residents affected by the extreme summer floods of 2021 in the Netherlands to contribute to fill this research gap. Our results indicate that current low levels of flood-related migration are likely to increase under higher flood risk. Undertaken in-situ adaptation may act as a barrier for further insitu adaptation or migration behavior. Where in-situ adaptation is mostly related to cognitive factors including risk perceptions, response efficacy and self-efficacy, migration seems to be driven by flood-related emotions. Personal flood experience, mediated by worry, is strongly associated with both types of adaptive behavior. We discuss how policymakers can use these insights to guide and anticipate household adaptation behavior

A coupled agent-based model for France for simulating adaptation and migration decisions under future coastal flood risk

In this study, we couple an integrated flood damage and agent-based model (ABM) with a gravity model of internal migration and a flood risk module (DYNAMO-M) to project household adaptation and migration decisions under increasing coastal flood risk in France. We ground the agent decision rules in a framework of subjective expected utility theory. This method addresses agent's bounded rationality related to risk perception and risk aversion and simulates the impact of push, pull, and mooring factors on migration and adaptation decisions. The agents are parameterized using subnational statistics, and the model is calibrated using a household survey on adaptation uptake. Subsequently, the model simulates household adaptation and migration based on increasing coastal flood damage from 2015 until 2080. A medium population growth scenario is used to simulate future population development, and sea level rise (SLR) is assessed for different climate scenarios. The results indicate that SLR can drive migration exceeding 8000 and 10,000 coastal inhabitants for 2080 under the Representative Concentration Pathways 4.5 and 8.5, respectively. Although household adaptation to flood risk strongly impacts projected annual flood damage, its impact on migration decisions is small and falls within the 90% confidence interval of model runs. Projections of coastal migration under SLR are most sensitive to migration costs and coastal flood protection standards, highlighting the need for better characterization of both in modeling exercises. The modeling framework demonstrated in this study can be upscaled to the global scale and function as a platform for a more integrated assessment of SLR-induced migration