Flood Risk Management: US Army Corps of Engineers and Layperson Perceptions

Recent severe storm experiences in the U.S. Gulf Coast illustrate the importance of an integrated approach to flood preparedness planning that harmonizes stakeholder and agency efforts. Risk management decisions that are informed by and address decision maker and stakeholder risk perceptions and behavior are essential for effective risk management policy. A literature review and two expert models/mental models studies were undertaken to identify areas of importance in the flood risk management process for layperson, non‐USACE‐expert, and two USACE‐expert groups. In characterizing and mapping stakeholder beliefs about risks in the literature onto current risk management practice, recommendations for accommodating and changing stakeholder perceptions of flood risks and their management are identified. Needs of the U.S. Army Corps of Engineers (USACE) flood preparedness and response program are discussed in the context of flood risk mental models.     

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.     

An Agent‐Based Model of Evolving Community Flood Risk

Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent‐based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near‐miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high‐risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in‐depth behavioral and decision rules at the individual and community level.     

Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.     

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.     

基于前景理论的跨市场状态转移多阶段资产配置研究

在行为金融前景理论框架下研究跨市场间的状态转移资产配置问题,构建隐Markov——混合正态分布模型描述股票、债券和商品混合市场间的状态特征,用Baum-Welch算法估计模型参数,并利用状态转移思想进行情景生成建立多阶段随机优化模型。进一步,以我国股票、债券和商品混合市场的实际数据为背景,利用滚动窗口方法实证分析基于状态转移的多阶段随机模型的表现,并与忽略状态转移特征的基准模型、等权重组合、沪深300指数的结果进行对比。结果表明,与其他组合相比,基于状态转移的投资组合有助于规避风险,且混合市场间的状态转移信息能够对前景理论投资者的最优投资决策产生影响。     

Adoption of Individual Flood Damage Mitigation Measures in New York City: An Extension of Protection Motivation Theory

This study offers insights into factors of influence on the implementation of flood damage mitigation measures by more than 1,000 homeowners who live in flood‐prone areas in New York City. Our theoretical basis for explaining flood preparedness decisions is protection motivation theory, which we extend using a variety of other variables that can have an important influence on individual decision making under risk, such as risk attitudes, time preferences, social norms, trust, and local flood risk management policies. Our results in relation to our main hypothesis are as follows. Individuals who live in high flood risk zones take more flood‐proofing measures in their home than individuals in low‐risk zones, which suggests the former group has a high threat appraisal. With regard to coping appraisal variables, we find that a high response efficacy and a high self‐efficacy play an important role in taking flood damage mitigation measures, while perceived response cost does not. In addition, a variety of behavioral characteristics influence individual decisions to flood‐proof homes, such as risk attitudes, time preferences, and private values of being well prepared for flooding. Investments in elevating one's home are mainly influenced by building code regulations and are negatively related with expectations of receiving federal disaster relief. We discuss a variety of policy recommendations to improve individual flood preparedness decisions, including incentives for risk reduction through flood insurance, and communication campaigns focused on coping appraisals and informing people about flood risk they face over long time horizons.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Quantifying Riverine and Storm‐Surge Flood Risk by Single‐Family Residence: Application to Texas

The development of catastrophe models in recent years allows for assessment of the flood hazard much more effectively than when the federally run National Flood Insurance Program (NFIP) was created in 1968. We propose and then demonstrate a methodological approach to determine pure premiums based on the entire distribution of possible flood events. We apply hazard, exposure, and vulnerability analyses to a sample of 300,000 single‐family residences in two counties in Texas (Travis and Galveston) using state‐of‐the‐art flood catastrophe models. Even in zones of similar flood risk classification by FEMA there is substantial variation in exposure between coastal and inland flood risk. For instance, homes in the designated moderate‐risk X500/B zones in Galveston are exposed to a flood risk on average 2.5 times greater than residences in X500/B zones in Travis. The results also show very similar average annual loss (corrected for exposure) for a number of residences despite their being in different FEMA flood zones. We also find significant storm‐surge exposure outside of the FEMA designated storm‐surge risk zones. Taken together these findings highlight the importance of a microanalysis of flood exposure. The process of aggregating risk at a flood zone level—as currently undertaken by FEMA—provides a false sense of uniformity. As our analysis indicates, the technology to delineate the flood risks exists today.     

Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis

In this article, we propose an integrated direct and indirect flood risk model for small‐ and large‐scale flood events, allowing for dynamic modeling of total economic losses from a flood event to a full economic recovery. A novel approach is taken that translates direct losses of both capital and labor into production losses using the Cobb‐Douglas production function, aiming at improved consistency in loss accounting. The recovery of the economy is modeled using a hybrid input‐output model and applied to the port region of Rotterdam, using six different flood events (1/10 up to 1/10,000). This procedure allows gaining a better insight regarding the consequences of both high‐ and low‐probability floods. The results show that in terms of expected annual damage, direct losses remain more substantial relative to the indirect losses (approximately 50% larger), but for low‐probability events the indirect losses outweigh the direct losses. Furthermore, we explored parameter uncertainty using a global sensitivity analysis, and varied critical assumptions in the modeling framework related to, among others, flood duration and labor recovery, using a scenario approach. Our findings have two important implications for disaster modelers and practitioners. First, high‐probability events are qualitatively different from low‐probability events in terms of the scale of damages and full recovery period. Second, there are substantial differences in parameter influence between high‐probability and low‐probability flood modeling. These findings suggest that a detailed approach is required when assessing the flood risk for a specific region.     

基于时间价值的交通出行方式选择行为研究

通勤出行是城市居民最基本和最重要的出行目的,通勤出行时间价值是评价通勤出行者对交通方式选择的重要参数之一,以累积前景理论为基础,将通勤出行时间价值引入广义出行成本函数中,以权重函数和改进的广义出行成本函数作为交通方式选择模型的依据,并在模型中自定义广义出行成本参考点,选择累积前景值最大的前景作为出行者最优决策。分别基于“期望效用最大化理论”和“累积前景理论”对通勤出行者在三种不同出行场景下进行仿真模拟,研究最优交通方式选择行为。研究结果表明:期望效用理论框架下,通勤出行者的交通方式选择行为不受出行场景的影响,累积前景理论更适用于出行方式选择行为的研究。构建以通勤出行时间价值为核心变量的交通方式选择模型,可帮助通勤出行者选择合理的交通方式,并为政府及相关部门制定交通管理规划和实施缓解交通拥堵政策提供依据。     

Determinants of Probability Neglect and Risk Attitudes for Disaster Risk: An Online Experimental Study of Flood Insurance Demand among Homeowners

Little is known about why individuals place either a high or a very low value on mitigating risks of disaster‐type events, like floods. This study uses panel data methods to explore the psychological factors affecting probability neglect of flood risk relevant to the zero end‐point of the probability weighting function in Prospect Theory, and willingness‐to‐pay for flood insurance. In particular, we focus on explanatory variables of anticipatory and anticipated emotions, as well as the threshold of concern. Moreover, results obtained under real and hypothetical incentives are compared in an experiment with high experimental outcomes. Based on our findings, we suggest several policy recommendations to overcome individual decision processes, which may hinder flood protection efforts.     

A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods

Scour (localized erosion by water) is an important risk to bridges, and hence many infrastructure networks, around the world. In Britain, scour has caused the failure of railway bridges crossing rivers in more than 50 flood events. These events have been investigated in detail, providing a data set with which we develop and test a model to quantify scour risk. The risk analysis is formulated in terms of a generic, transferrable infrastructure network risk model. For some bridge failures, the severity of the causative flood was recorded or can be reconstructed. These data are combined with the background failure rate, and records of bridges that have not failed, to construct fragility curves that quantify the failure probability conditional on the severity of a flood event. The fragility curves generated are to some extent sensitive to the way in which these data are incorporated into the statistical analysis. The new fragility analysis is tested using flood events simulated from a spatial joint probability model for extreme river flows for all river gauging sites in Britain. The combined models appear robust in comparison with historical observations of the expected number of bridge failures in a flood event. The analysis is used to estimate the probability of single or multiple bridge failures in Britain's rail network. Combined with a model for passenger journey disruption in the event of bridge failure, we calculate a system‐wide estimate for the risk of scour failures in terms of passenger journey disruptions and associated economic costs.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

考虑排污权市场价格不确定性的企业生产决策

目前有关不确定情境下排污权交易企业生产决策问题研究通常都是采纳的期望效用理论。针对排污权市场价格不确定性普遍存在的客观事实,重点引入前景理论,考察排污权市场价格不确定情境下的企业生产决策问题。首先通过建立特定排污权市场价格下的生产决策优化模型,提取了企业在产品生产、污染削减、排污权交易等方面决策行为与排污权市场价格之间的关联性;基于此,运用前景理论分析框架,分析、推导了排污权市场价格不确定情境下企业生产决策的价值函数、主观概率与决策权重函数,建立了考虑心理参考点与决策偏好的生产决策模型。结果表明：由于受信息局限、资源禀赋、心理预期、行为偏好等多方面的影响,企业的实际生产决策会系统性地偏离期望最优决策;算例分析也从多个角度清晰刻画了企业面向排污权市场价格不确定性的复杂决策行为,所得结果更贴近现实情景,并充分说明了基于前景理论的模型分析能够更好地描述排污权交易企业的实际生产决策行为。     

A Review of Risk Perceptions and Other Factors that Influence Flood Mitigation Behavior

In flood risk management, a shift can be observed toward more integrated approaches that increasingly address the role of private households in implementing flood damage mitigation measures. This has resulted in a growing number of studies into the supposed positive relationship between individual flood risk perceptions and mitigation behavior. Our literature review shows, however, that, actually, this relationship is hardly observed in empirical studies. Two arguments are provided as an explanation. First, on the basis of protection motivation theory, a theoretical framework is discussed suggesting that individuals’ high‐risk perceptions need to be accompanied by coping appraisal to result in a protective response. Second, it is pointed out that possible feedback from already‐adopted mitigation measures on risk perceptions has hardly been considered by current studies. In addition, we also provide a review of factors that drive precautionary behavior other than risk perceptions. It is found that factors such as coping appraisal are consistently related to mitigation behavior. We conclude, therefore, that the current focus on risk perceptions as a means to explain and promote private flood mitigation behavior is not supported on either theoretical or empirical grounds.     

A Probabilistic Analysis of Surface Water Flood Risk in London

Flooding in urban areas during heavy rainfall, often characterized by short duration and high‐intensity events, is known as “surface water flooding.” Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively.     

Flood Risk Perceptions and Insurance Choice: Do Decisions in the Floodplain Reflect Overoptimism?

In the presence of rare disasters, risk perceptions may not always align with actual risks. These perceptions can nevertheless influence an individual's willingness to mitigate risks through activities such as purchasing flood insurance. In a survey of Maryland floodplain residents, we find that stated risk perceptions predict voluntary flood insurance take‐up, while perceptions themselves varied widely among surveyed residents, owing in large part to differences in past flood experience. We use a formal test for overoptimism in risk perceptions and find that, on aggregate, floodplain residents are overly optimistic about flood risks.     

You Have Been Framed! How Antecedents of Information Need Mediate the Effects of Risk Communication Messages

This study investigates the processes that mediate the effects of framing flood risks on people's information needs. Insight into the effects of risk frames is important for developing balanced risk communication that explains both risks and benefits of living near water. The research was inspired by the risk information seeking and processing model and related models. In a web‐based survey, respondents (n = 1,457) were randomly assigned to one of three communication frames or a control frame (experimental conditions). Each frame identically explained flood risk and additionally refined the message by emphasizing climate change, the quality of flood risk management, or the amenities of living near water. We tested the extent to which risk perceptions, trust, and affective responses mediate the framing effects on information need. As expected, the frames on average resulted in higher information need than the control frame. Attempts to lower fear appeal by stressing safety or amenities instead of climate change were marginally successful, a phenomenon that is known as a “negativity bias.” Framing effects were mediated by negative attributes (risk perception and negative affect) but not by positive attributes (trust and positive affect). This finding calls for theoretical refinement. Practically, communication messages will be more effective when they stimulate risk perceptions and evoke negative affect. However, arousal of fear may have unwanted side effects. For instance, fear arousal could lead to lower levels of trust in risk management among citizens. Regular monitoring of citizens’ attitudes is important to prevent extreme levels of distrust or cynicism.