Agent-based modeling of incentives to encourage pre-disaster relocation in anticipation of coastal flooding

基于主体的激励模型，鼓励在沿海洪水预测中进行灾前搬迁

• 批准号: 2017544
• 负责人: Vicki Bier
• 金额: $ 40.38万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-11-15 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017544&HistoricalAwards=false
• 关键词: Agent; based; modeling; incentives; encourage

Extreme storms such as Hurricanes Katrina and Sandy have made clear that forced relocation due to floods is a major and growing problem. By contrast to short-term evacuation, relatively little is known about how to manage long-term relocation. Extensive social-science research has documented the advantages of voluntary vs. forced relocation. Strategies for encouraging voluntary retreat from at-risk coastal areas prior to catastrophic flooding can reduce the number of people affected, the resulting disruption and property loss, and the costs for emergency relief. Moreover, the relatively predictable nature of sea-level rise makes it possible to know well in advance which geographic areas are most likely to face increasing flooding hazards. This predictability facilitates proactive planning and anticipatory relocation as one way of reducing projected increases in flood damage, as recommended by the Federal Emergency Management Agency. However, many responses to sea-level rise can be problematic. Anticipatory relocation of entire communities is extremely costly (roughly $1 million per person). Furthermore, the effectiveness of many community and household-scale flood-protection efforts can be limited. For example, buying out flood-damaged properties after a flood does not prevent disruption and loss of personal property; similarly, protective barriers, such as seawalls, frequently encourage development in at-risk areas. Taken together, these observations suggest that it is worth exploring methods to encourage voluntary relocation before severe flooding. We study possible ways to incentivize relocation prior to flooding, focusing on two areas vulnerable to coastal flooding (Brooklyn, NY, and Galveston, TX) with different housing costs and with socioeconomic/demographic characteristics. Many studies examining mitigation of risks in vulnerable coastal areas adopt the viewpoint of a single decision maker (either a prototypical resident, or a local government), without considering different stakeholder goals, values, or preferences. In this work, game theory is used to model interactions between government vs. private citizens, to identify solutions whereby government can incentivize residents to relocate before they otherwise might. Agent-based modeling is used to enhance the realism of the game, address decision-maker heterogeneity, and explore behavior that may be difficult to model analytically (such as emergent network effects influenced by the behavior of other residents). Few researchers to date have approached the issue of relocation as a problem that can be addressed using formal methods such as game theory. The proposed project explicitly considers the different discount rates of stakeholders involved in relocation decisions (government vs. private individuals), making it possible to frame the problem as a multiplayer game rather than merely a decision problem for a single decision maker. A game-theoretic perspective facilitates the identification of “win-win” solutions whereby government can encourage relocation sooner than would otherwise occur. Sensitivity analyses will address uncertainty about flooding risks, network effects (such as cascading or tipping), free-rider effects (e.g., residents who take advantage of government subsidies but would have relocated even without subsidies), and differing behavioral models of resident decision-making. The project contributes to improved societal understanding of mechanisms for reducing vulnerability to coastal flooding from sea-level rise.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

卡特里娜飓风和桑迪飓风等极端风暴已经清楚地表明，因洪水而被迫搬迁是一个重大且日益严重的问题。与短期疏散相比，人们对如何管理长期搬迁知之甚少。 广泛的社会科学研究已经证明了自愿搬迁相对于强迫搬迁的优势。 鼓励在发生灾难性洪水之前自愿撤离危险沿海地区的战略可以减少受灾人数、由此造成的破坏和财产损失以及紧急救济费用。 此外，海平面上升的相对可预测性使人们能够提前很好地了解哪些地理区域最有可能面临日益严重的洪水危害。 正如联邦紧急事务管理局所建议的那样，这种可预测性有助于积极主动地进行规划和预期的搬迁，作为减少预计的洪水损失增加的一种方式。 然而，对海平面上升的许多反应可能是有问题的。 整个社区的预期搬迁费用极高（每人约100万美元）。此外，许多社区和家庭规模的防洪工作的效力可能有限。例如，在洪水后买断被洪水破坏的财产并不能防止个人财产的破坏和损失;同样，海堤等保护性屏障经常鼓励风险地区的发展。 综上所述，这些观察结果表明，值得探讨鼓励在严重洪水之前自愿搬迁的方法。 我们研究可能的方式来激励搬迁前洪水，重点是两个地区容易受到沿海洪水（布鲁克林，纽约州和加尔维斯顿，得克萨斯州）不同的住房成本和社会经济/人口特征。许多研究考察脆弱沿海地区风险缓解的研究都采用了单一决策者（原型居民或地方政府）的观点，而没有考虑不同利益相关者的目标、价值观或偏好。在这项工作中，博弈论被用来模拟政府与私人公民之间的互动，以确定政府可以激励居民搬迁之前，否则可能会解决方案。 基于代理的建模用于增强游戏的真实性，解决决策者的异质性，并探索可能难以分析建模的行为（例如受其他居民行为影响的紧急网络效应）。 迄今为止，很少有研究人员将搬迁问题视为可以使用博弈论等正式方法解决的问题。 拟议的项目明确考虑了参与搬迁决策的利益相关者（政府与私人）的不同折扣率，使其有可能将问题框定为多人游戏，而不仅仅是一个决策者的决策问题。 博弈论的观点有助于确定“双赢”的解决方案，政府可以鼓励搬迁早于否则会发生。 敏感性分析将解决洪水风险、网络效应（如级联或小费）、搭便车效应（如，利用政府补贴但即使没有补贴也会搬迁的居民），以及居民决策的不同行为模式。 该项目有助于提高社会对减少海平面上升导致的沿海洪水脆弱性机制的理解。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。