The safe development paradox:An agent-based model for flood risk under climate change in the European Union

With increasing flood risk due to climate change and socioeconomic trends, governments are under pressure to continue implementing flood protection measures, such as dikes, to reduce flood risk. However, research suggests that a sole focus on government-funded flood protection leads to an adverse increase in exposure as people and economic activities tend to concentrate in protected areas. Moreover, governmental flood protection can reduce the incentive for autonomous adaptation by local households, which paradoxically results in more severe consequences if an extreme flood event occurs. This phenomenon is often referred to as the ‘safe development paradox’ or ‘levee effect’ and is generally not accounted for in existing flood risk models used to assess developments in future flood risk under climate change. In this study we assess the impact of extreme flood events for the European Union using a large-scale agent-based model (ABM). We quantify how the safe development paradox affects (1) population growth and the increase in exposed property values, (2) the reduction in investments to flood-proof buildings as public protection increases, and (3) the increase in potential damage should a flood occur. For this analysis, we apply an ABM that integrates the dynamic behaviour of governments and residents into a large-scale flood risk assessment framework, in which we include estimates of changing population growth. We find that the impact of extreme flood events increases considerably when governments provide high protection levels, especially in large metropolitan areas. Moreover, we demonstrate how policy that stimulates the flood-proofing of buildings can largely counteract the effects of the safe development paradox

Coastal adaptation and migration dynamics under future shoreline changes

In this study, we present a novel modeling framework that provides a stylized representation of coastal adaptation and migration dynamics under sea level rise (SLR). We develop an agent-based model that simulates household and government agents adapting to shoreline change and increasing coastal flood risk. This model is coupled to a gravity-based model of migration to simulate coastward migration. Household characteristics are derived from local census data from 2015, and household decisions are calibrated based on empirical survey data on household adaptation in France. We integrate projections of shoreline retreat and flood inundation levels under two Representative Concentration Pathways (RCPs) and account for socioeconomic development under two Shared Socioeconomic Pathways (SSPs). The model is then applied to simulate coastal adaptation and migration between 2015 and 2080. Our results indicate that without coastal adaptation, SLR could drive the cumulative net outmigration of 13,100 up to as many as 21,700 coastal inhabitants between 2015 and 2080 under SSP2–RCP4.5 and SSP5–RCP8.5, respectively. This amounts to between 3.0 %–3.7 % of the coastal population residing in the 1/100-year flood zone in 2080 under a scenario of SLR. We find that SLR-induced migration is largely dependent on the adaptation strategies pursued by households and governments. Household implementation of floodproofing measures combined with beach renourishment reduces the projected SLR-induced migration by 31 %–36 % when compared to a migration under a scenario of no adaptation. A sensitivity analysis indicates that the effect of beach renourishment on SLR-induced migration largely depends on the level of coastal flood protection offered by sandy beaches. By explicitly modeling household behavior combined with governmental protection strategies under increasing coastal risks, the framework presented in this study allows for a comparison of climate change impacts on coastal communities under different adaptation strategies

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

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

Environmental, Social and Economic Sustainability of Biobased Plastics. Bio-polyethylene from Brazil and polylactic acid from the U.S.

SUMMARY Ever depleting fossil resources, growing fossil feedstock prices and global environmental impact associated with continuously rising greenhouse gas emissions have led to increased attention for biobased products as alternatives for the present fossil-based ones. It is therefore important for scientists and academics to provide knowledge and explore practical routes for the sustainable transition towards biobased alternatives. This research focuses on the replacement of fossil-based polyethylene (fossil-PE) by biobased PE (bio-PE) from Brazilian sugarcane and polylactic acid (PLA) from US corn. The report gives an outlook on such a shift towards a sustainable biobased economy. The aim of this research is to assess the characteristics of the biobased product supply chains which could provide in the demand for biobased polyethylene and polylactic acid for the Netherlands on environmental, social and economic aspects in order to contribute to the existing fundamental research on biobased products. This led to the main research question: How sustainable are the supply chains for biobased polyethylene and polylactic acid, which could meet the current demand for fossil-based polyethylene in the Netherlands, and how does this compare to the supply chain of fossil-based polyethylene? An analytical framework is developed along which the three dimensions of sustainability can be evaluated; environmental (greenhouse gas emissions, biodiversity and the local environment), social (competition for food, welfare and wellbeing) and economic sustainability (market price). The report focuses on the demand for bio-PE and PLA which could replace the current Dutch demand for PE of approximately 500 kiloton per year. The report shows that on environmental sustainability, bio-PE outperforms fossil-PE and PLA. Life cycle greenhouse gas emissions are particularly low for bio-PE due to the extensive use of bagasse as energy supply. PLA associated greenhouse gas emissions are slightly less than the greenhouse gas emissions for fossil-PE. Depending on the type of land that is converted to biomass feedstock, greenhouse gas emissions can increase due to the release of carbon from decaying biomass and the loss of soil organic carbon. This effect can be significant if rainforest is converted either by direct or indirect land use change. Even so, considering the relatively small demand, enough land is available in Brazil for the production of the biobased products without endangering bio-diverse regions. The main impact of biobased products on the local environment is the imbalance of NPK nutrients and for fossil-based products on- and offshore oil spills. The main concern with regard to the social sustainability was found in the exploitation of sugarcane and corn field workers. Case reports were found on slavery and exploitation, although no structural proof was found. For fossil-PE, decrease of the local welfare and wellbeing was found for several countries producing naphtha. Competition for food was considered as one of the main indicators. It is found that there is no competition for food if only the Dutch demand is considered, but a worldwide demand for multiple biobased products would inevitably lead to competition for food. This stresses the importance of alternative biomass sources that do not impact food supply, such as lignocelluloses. Even though bio-PE shows more favourable results than fossil-PE, biobased products are still unsustainable due to the high market price with respect to the biobased product. With current feedstock prices, market prices for bio-PE and PLA are respectively 40% to 60% more expensive than fossil-PE. The price imbalance can be partially explained by the fact that the costs of environmental degradation are externalized for fossil-based products. Internalizing these externalities by for instance green VAT or carbon tax would level the playing field for biobased products. A reduced green vat of 6% for “green” products (19% for normal products) would reduce the difference to 25% and 40% for bio-PE and PLA respectively. Additionally implementing a carbon tax of 50 USD/t CO2 would reduce the difference even further to 15% and 35% for bio-PE and PLA respectively.

Integrating household risk mitigation behaviour in flood risk analysis : An agent-based model approach

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

The effectiveness of flood risk communication strategies and the influence of social networks-Insights from an agent-based model

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

Advancing disaster policies by integrating dynamic adaptive behaviour in risk assessments using an agent-based modelling approach

Recent floods in the United States and Asia again highlighted their devastating effects, and without investments in adaptation, the future impact of floods will continue to increase. Key to making accurate flood-risk projections are assessments of how disaster-risk reduction (DRR) measures reduce risk and how much risk remains after adaptation. Current flood-risk-assessment models are ill-equipped to address this, as they assume a static adaptation path, implying that vulnerability will remain constant. We present a multi-disciplinary approach that integrates different types of adaptive behaviour of governments (proactive and reactive) and households (rational and boundedly rational) in a continental-scale risk-assessment framework for river flooding in the European Union. Our methodology demonstrates how flood risk and adaptation might develop, indicates how DRR policies can steer decisions towards optimal behaviour, and indicates how much residual risk remains that has to be covered by risk-transfer mechanisms. We find that the increase in flood risk due to climate change may be largely offset by adaptation decisions. Moreover, we illustrate that adaptation by households may be more influential for risk reduction than government protection in the short term. The results highlight the importance of integrating behavioural methods from social sciences with quantitative models from the natural sciences, as advocated by both fields