Adapting to Climate: A Case Study on Riverine Flood Risks in the Netherlands

Climate change may well lead to an increased risk of river floods in the Netherlands. However, the impacts of changes in water management on river floods are larger, either enhancing or reducing flood risks. Therefore, the abilities of water-management authorities to learn that climate and river flows are changing, and to recognize and act upon the implications, are of crucial importance. At the same time, water-management authorities respond to other trends, such as the democratization of decision making, which alter their ability to react to climate change. These complex interactions are illustrated with changes in river flood risk management for the Rhine and the Meuse in the Netherlands over the last 50 years. A scenario study is used to seek insight into the question of whether current water-management institutions and their likely successors are capable of dealing with plausible future flood risks. The scenarios show that new and major infrastructure is needed to keep flood risks at their current level. Such a structural solution to future flood risks is feasible, but requires considerable political will and institutional reform, both for planning and implementation. It is unlikely that reform will be fast enough or the will strong enough.     

Simulating Behavioral Influences on Community Flood Risk under Future Climate Scenarios

Flood risk is a function of both climate and human behavior, including individual and societal actions. For this reason, there is a need to incorporate both human and climatic components in models of flood risk. This study simulates behavioral influences on the evolution of community flood risk under different future climate scenarios using an agent-based model (ABM). The objective is to understand better the ways, sometimes unexpected, that human behavior, stochastic floods, and community interventions interact to influence the evolution of flood risk. One historic climate scenario and three future climate scenarios are simulated using a case study location in Fargo, North Dakota. Individual agents can mitigate flood risk via household mitigation or by moving, based on decision rules that consider risk perception and coping perception. The community can mitigate or disseminate information to reduce flood risk. Results show that agent behavior and community action have a significant impact on the evolution of flood risk under different climate scenarios. In all scenarios, individual and community action generally result in a decline in damages over time. In a lower flood risk scenario, the decline is primarily due to agent mitigation, while in a high flood risk scenario, community mitigation and agent relocation are primary drivers of the decline. Adaptive behaviors offset some of the increase in flood risk associated with climate change, and under an extreme climate scenario, our model indicates that many agents relocate.     

Dangerous Climate Change: The Role for Risk Research

The notion of "dangerous climate change" constitutes an important development of the 1992 United Nations Framework Convention on Climate Change. It persists, however, as an ambiguous expression, sustained by multiple definitions of danger. It also implicitly contains the question of how to respond to the complex and multi-disciplinary risk issues that climate change poses. The invaluable role of the climate science community, which relies on risk assessments to characterize system uncertainties and to identify limits beyond which changes may become dangerous, is acknowledged. But this alone will not suffice to develop long-term policy. Decisions need to include other considerations, such as value judgments about potential risks, and societal and individual perceptions of "danger," which are often contested. This article explores links and cross-overs between the climate science and risk communication and perception approaches to defining danger. Drawing upon nine articles in this Special Issue of Risk Analysis, we examine a set of themes: limits of current scientific understanding; differentiated public perceptions of danger from climate change; social and cultural processes amplifying and attenuating perceptions of, and responses to, climate change; risk communication design; and new approaches to climate change decision making. The article reflects upon some of the difficulties inherent in responding to the issue in a coherent, interdisciplinary fashion, concluding nevertheless that action should be taken, while acknowledging the context-specificity of "danger." The need for new policy tools is emphasised, while research on nested solutions should be aimed at overcoming the disjunctures apparent in interpretations of climate change risks.     

Adaptive Governance,Uncertainty, and Risk: Policy Framing and Responses to Climate Change,Drought, and Flood

As climate change impacts result in more extreme events (such as droughts and floods), the need to understand which policies facilitate effective climate change adaptation becomes crucial. Hence, this article answers the question: How do governments and policymakers frame policy in relation to climate change, droughts, and floods and what governance structures facilitate adaptation? This research interrogates and analyzes through content analysis, supplemented by semi‐structured qualitative interviews, the policy response to climate change, drought, and flood in relation to agricultural producers in four case studies in river basins in Chile, Argentina, and Canada. First, an epistemological explanation of risk and uncertainty underscores a brief literature review of adaptive governance, followed by policy framing in relation to risk and uncertainty, and an analytical model is developed. Pertinent findings of the four cases are recounted, followed by a comparative analysis. In conclusion, recommendations are made to improve policies and expand adaptive governance to better account for uncertainty and risk. This article is innovative in that it proposes an expanded model of adaptive governance in relation to “risk” that can help bridge the barrier of uncertainty in science and policy.     

The Impact of Climate Variability on Flood Risk in Poland

This article examines the role of climatic and hydrological variability in assessing the cumulative risk of flood events in Poland over a T-year period. In a broad sense flood-risk estimation combines a frequency analysis of extreme hydrological phenomena with an evaluation of flood-induced damages. The damage from floods depends on the critical values of the river discharges. The probabilistic flood analysis usually includes an estimation of the expected annual probability of the critical discharge Qcr being exceeded and the equivalent long-term risk of it being exceeded over the next T years. If, however, the process is nonstationary, the T-year risk of flood damage may depend importantly on the variation of hydrological processes. As a possible explanation for the variations observed in snowmelt-induced floods in Polish rivers, this article investigates the possible impact of the North Atlantic Oscillation (NAO) on surface air temperature T and precipitation P. The spatial distribution of the correlation coefficients between NAO and T, as well as NAO and P, show very significant differences in the NAO impact on meteorological variables in various parts of Europe. To assess the implications of NAO variations on spring flood discharges, a simple model of Snow Cover Water Equivalent (SCWE) was applied to selected Polish river catchments. The conclusion of this analysis is that the yearly maximum of SCWE values significantly decreases with increasing NAO. This leads to a temporal redistribution of winter and spring runoff. The question of spring flood characteristics being stationary or nonstationary may therefore be linked with stochastic properties of the NAO index time series.     

Climate Change Risk Perception and Communication: Addressing a Critical Moment?

Climate change is an increasingly salient issue for societies and policy‐makers worldwide. It now raises fundamental interdisciplinary issues of risk and uncertainty analysis and communication. The growing scientific consensus over the anthropogenic causes of climate change appears to sit at odds with the increasing use of risk discourses in policy: for example, to aid in climate adaptation decision making. All of this points to a need for a fundamental revision of our conceptualization of what it is to do climate risk communication. This Special Collection comprises seven papers stimulated by a workshop on “Climate Risk Perceptions and Communication” held at Cumberland Lodge Windsor in 2010. Topics addressed include climate uncertainties, images and the media, communication and public engagement, uncertainty transfer in climate communication, the role of emotions, localization of hazard impacts, and longitudinal analyses of climate perceptions. Climate change risk perceptions and communication work is critical for future climate policy and decisions.     

Cultural Circuits of Climate Change in U.K. Broadsheet Newspapers, 1985–2003

This article argues for a cultural perspective to be brought to bear on studies of climate change risk perception. Developing the "circuit of culture" model, the article maintains that the producers and consumers of media texts are jointly engaged in dynamic, meaning-making activities that are context-specific and that change over time. A critical discourse analysis of climate change based on a database of newspaper reports from three U.K. broadsheet papers over the period 1985-2003 is presented. This empirical study identifies three distinct circuits of climate change-1985-1990, 1991-1996, 1997-2003-which are characterized by different framings of risks associated with climate change. The article concludes that there is evidence of social learning as actors build on their experiences in relation to climate change science and policy making. Two important factors in shaping the U.K.'s broadsheet newspapers' discourse on "dangerous" climate change emerge as the agency of top political figures and the dominant ideological standpoints in different newspapers.     

Rural Nevada and Climate Change: Vulnerability,Beliefs, and Risk Perception

In this article, we present the results of a study investigating the influence of vulnerability to climate change as a function of physical vulnerability, sensitivity, and adaptive capacity on climate change risk perception. In 2008/2009, we surveyed Nevada ranchers and farmers to assess their climate change‐related beliefs, and risk perceptions, political orientations, and socioeconomic characteristics. Ranchers’ and farmers’ sensitivity to climate change was measured through estimating the proportion of their household income originating from highly scarce water‐dependent agriculture to the total income. Adaptive capacity was measured as a combination of the Social Status Index and the Poverty Index. Utilizing water availability and use, and population distribution GIS databases; we assessed water resource vulnerability in Nevada by zip code as an indicator of physical vulnerability to climate change. We performed correlation tests and multiple regression analyses to examine the impact of vulnerability and its three distinct components on risk perception. We find that vulnerability is not a significant determinant of risk perception. Physical vulnerability alone also does not impact risk perception. Both sensitivity and adaptive capacity increase risk perception. While age is not a significant determinant of it, gender plays an important role in shaping risk perception. Yet, general beliefs such as political orientations and climate change‐specific beliefs such as believing in the anthropogenic causes of climate change and connecting the locally observed impacts (in this case drought) to climate change are the most prominent determinants of risk perception.     

Benefits of and strategies to update premium rates in the US National Flood Insurance Program under climate change

The United States’ National Flood Insurance Program (NFIP) has accumulated over $20 billion in debt to the US Treasury since 2005, partly due to discounted premiums on homes in flood-prone areas. To address this issue, FEMA introduced Risk Rating 2.0 in October 2021, which is able to assess and charge more accurate and equitable rates to homeowners. However, rates must be continually updated to account for increasing flood damage caused by sea level rise and more intense hurricanes due to climate change. This study proposes a strategy to adopt updated premium rates that account for climate change effects and address affordability and risk mitigation issues with a means-tested voucher program. The strategy is tested in a coastal community, Ortley Beach, NJ, by projecting its future flood risk under sea level rise and storm intensification. Compared with using static rates for all the properties in Ortley Beach, the proposed strategy is shown to reduce the NFIP's potential losses to the community from 2020 to 2050 by half (from $4.6 million to $2.3 million), improve the community's flood resistance, and address affordability concerns. Sensitivity analysis of varying incomes, loan interest rates, and conditions for a voucher indicates that the strategy is feasible and effective under a wide range of scenarios. Thus, the proposed strategy can be applied to various communities along the US coastline as an effective way of updating risk-based premiums while addressing affordability and resilience concerns.     

Climate Change and Human Health: Estimating Avoidable Deaths and Disease

Human population health has always been central in the justification for sustainable development but nearly invisible in the United Nations Framework Convention on Climate Change negotiations. Current scientific evidence indicates that climate change will contribute to the global burden of disease through increases in diarrhoeal disease, vector-borne disease, and malnutrition, and the health impacts of extreme weather and climate events. A few studies have estimated future potential health impacts of climate change but often generate little policy-relevant information. Robust estimates of future health impacts rely on robust projections of future disease patterns. The application of a standardized and established methodology has been developed to quantify the impact of climate change in relation to different greenhouse gas emission scenarios. All health risk assessments are necessarily biased toward conservative best-estimates of health effects that are easily measured. Global, regional, and national risk assessments can take no account of irreversibility, or plausible low-probability events with potentially very high burdens on human health. There is no "safe limit" of climate change with respect to health impacts as health systems in some regions do not adequately cope with the current climate variability. Current scientific methods cannot identify global threshold health effects in order for policymakers to regulate a "tolerable" amount of climate change. We argue for the need for more research to reduce the potential impacts of climate change on human health, including the development of improved methods for quantitative risk assessment. The large uncertainty about the future effects of climate change on human population health should be a reason to reduce greenhouse gas emissions, and not a reason for inaction.     

Projections of Future Extreme Weather Losses Under Changes in Climate and Exposure

Many attempts are made to assess future changes in extreme weather events due to anthropogenic climate change, but few studies have estimated the potential change in economic losses from such events. Projecting losses is more complex as it requires insight into the change in the weather hazard but also into exposure and vulnerability of assets. This article discusses the issues involved as well as a framework for projecting future losses, and provides an overview of some state‐of‐the‐art projections. Estimates of changes in losses from cyclones and floods are given, and particular attention is paid to the different approaches and assumptions. All projections show increases in extreme weather losses due to climate change. Flood losses are generally projected to increase more rapidly than losses from tropical and extra‐tropical cyclones. However, for the period until the year 2040, the contribution from increasing exposure and value of capital at risk to future losses is likely to be equal or larger than the contribution from anthropogenic climate change. Given the fact that the occurrence of loss events also varies over time due to natural climate variability, the signal from anthropogenic climate change is likely to be lost among the other causes for changes in risk, at least during the period until 2040. More efforts are needed to arrive at a comprehensive approach that includes quantification of changes in hazard, exposure, and vulnerability, as well as adaptation effects.     

Insurance Against Climate Change and Flooding in the Netherlands: Present, Future, and Comparison with Other Countries

Climate change is projected to cause severe economic losses, which has the potential to affect the insurance sector and public compensation schemes considerably. This article discusses the role insurance can play in adapting to climate change impacts. The particular focus is on the Dutch insurance sector, in view of the Netherlands being extremely vulnerable to climate change impacts. The usefulness of private insurance as an adaptation instrument to increased flood risks is examined, which is currently unavailable in the Netherlands. It is questioned whether the currently dominant role of the Dutch government in providing damage relief is justified from an economic efficiency perspective. Characteristics of flood insurance arrangements in the Netherlands, the United Kingdom, Germany, and France are compared in order to identify possible future directions for arrangements in the Netherlands. It is argued that social welfare improves when insurance companies take responsibility for part of the risks associated with climate change.     

An Integrated Approach for Assessing the Impact of Large-Scale Future Floods on a Highway Transport System

The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.     

Risk Perceptions,General Environmental Beliefs,and Willingness to Address Climate Change

The research reported here examines the relationship between risk perceptions and willingness to address climate change. The data are a national sample of 1225 mail surveys that include measures of risk perceptions and knowledge tied to climate change, support for voluntary and government actions to address the problem, general environmental beliefs, and demographic variables. Risk perceptions matter in predicting behavioral intentions. Risk perceptions are not a surrogate for general environmental beliefs, but have their own power to account for behavioral intentions. There are four secondary conclusions. First, behavioral intentions regarding climate change are complex and intriguing. People are neither nonbelievers who will take no initiatives themselves and oppose all government efforts, nor are they believers who promise both to make personal efforts and to vote for every government proposal that promises to address climate change. Second, there are separate demographic sources for voluntary actions compared with voting intentions. Third, recognizing the causes of global warming is a powerful predictor of behavioral intentions independent from believing that climate change will happen and have bad consequences. Finally, the success of the risk perception variables to account for behavioral intentions should encourage greater attention to risk perceptions as independent variables. Risk perceptions and knowledge, however, share the stage with general environmental beliefs and demographic characteristics. Although related, risk perceptions, knowledge, and general environmental beliefs are somewhat independent predictors of behavioral intentions.     

Flood Protection Diversification to Reduce Probabilities of Extreme Losses

Recent catastrophic losses because of floods require developing resilient approaches to flood risk protection. This article assesses how diversification of a system of coastal protections might decrease the probabilities of extreme flood losses. The study compares the performance of portfolios each consisting of four types of flood protection assets in a large region of dike rings. A parametric analysis suggests conditions in which diversifications of the types of included flood protection assets decrease extreme flood losses. Increased return periods of extreme losses are associated with portfolios where the asset types have low correlations of economic risk. The effort highlights the importance of understanding correlations across asset types in planning for large‐scale flood protection. It allows explicit integration of climate change scenarios in developing flood mitigation strategy.     

Climate change knowledge influences attitude to mitigation via efficacy beliefs

Theories proposing climate change apathy is explained by inadequate knowledge do not account for why many informed and concerned Americans fail to act. While correlations between knowledge, efficacy for climate change, and attitude to mitigation have been observed, few studies have examined efficacy for climate change as a mediator. This study aimed to investigate the influence of specific climate change knowledge on attitude to mitigation via efficacy beliefs. A cross-sectional survey of 205 US adults recruited from Amazon's Mechanical Turk assessed participants’ climate change knowledge, efficacy for climate change, and attitude to mitigation. Indirect effects of self-efficacy for climate change were observed in three mediation models, suggesting efficacy for climate change explains some of the relationship between specific climate change knowledge and attitude to mitigation. The findings suggest risk communication can motivate pro-environmental attitudes with interventions that deliver information about climate change and develop efficacy for mitigation behavior.     

A Method for Computing the Fraction of Attributable Risk Related to Climate Damages

The recent decision of the U.S. Supreme Court on the regulation of CO₂ emissions from new motor vehicles^{( 1 )} shows the need for a robust methodology to evaluate the fraction of attributable risk from such emissions. The methodology must enable decisionmakers to reach practically relevant conclusions on the basis of expert assessments the decisionmakers see as an expression of research in progress, rather than as knowledge consolidated beyond any reasonable doubt.^{( 2,3,4 )} This article presents such a methodology and demonstrates its use for the Alpine heat wave of 2003. In a Bayesian setting, different expert assessments on temperature trends and volatility can be formalized as probability distributions, with initial weights (priors) attached to them. By Bayesian learning, these weights can be adjusted in the light of data. The fraction of heat wave risk attributable to anthropogenic climate change can then be computed from the posterior distribution. We show that very different priors consistently lead to the result that anthropogenic climate change has contributed more than 90% to the probability of the Alpine summer heat wave in 2003. The present method can be extended to a wide range of applications where conclusions must be drawn from divergent assessments under uncertainty.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

Risk of Extreme Events Under Nonstationary Conditions

The concept of the return period is widely used in the analysis of the risk of extreme events and in engineering design. For example, a levee can be designed to protect against the 100-year flood, the flood which on average occurs once in 100 years. Use of the return period typically assumes that the probability of occurrence of an extreme event in the current or any future year is the same. However, there is evidence that potential climate change may affect the probabilities of some extreme events such as floods and droughts. In turn, this would affect the level of protection provided by the current infrastructure. For an engineering project, the risk of an extreme event in a future year could greatly exceed the average annual risk over the design life of the project. An equivalent definition of the return period under stationary conditions is the expected waiting time before failure. This paper examines how this definition can be adapted to nonstationary conditions. Designers of flood control projects should be aware that alternative definitions of the return period imply different risk under nonstationary conditions. The statistics of extremes and extreme value distributions are useful to examine extreme event risk. This paper uses a Gumbel Type I distribution to model the probability of failure under nonstationary conditions. The probability of an extreme event under nonstationary conditions depends on the rate of change of the parameters of the underlying distribution.     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.