Collaborative Research: SAI-R: Decision-making Under Evolving and Conditional Risk Associated with Coastal Flood Barriers

加强美国基础设施(SAI)是一项NSF计划，旨在刺激以人类为中心的基础性研究和潜在的变革性研究，以加强美国的基础设施。有效的基础设施为社会经济活力和广泛的生活质量改善提供了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，增长经济，创造就业机会，提高公共部门服务提供效率，加强社区力量，促进机会均等，保护自然环境，增强国家安全，推动美国的领导地位。要实现这些目标，需要来自科学和工程学科的专业知识。SAI侧重于人类推理和决策、治理以及社会和文化过程的知识如何能够建立和维护有效的基础设施，改善生活和社会，并建立在技术和工程进步的基础上。人们根据许多考虑因素来决定住在哪里。除了预算限制外，这可能包括公共产品的可用性、环境和当地气候等特征。一个非常重要的考虑因素是与洪水相关的风险。地点因洪水风险而异。这种风险是由于气候变化和政府对防洪基础设施的投资而产生的。这项SAI研究项目考察了居住在沿海社区的人们在受到不断变化的洪水风险条件威胁时对居住地点选择的决策。对防洪基础设施的投资可以将以前有风险的地区变成更安全的地方。沿海防洪堤提供的安全反过来可能会增加对当地住房的需求。一个社会后果是，房地产价格被推高，中低阶层居民被赶走。这一结果可能会进一步加剧不同收入阶层的住房拥有率差距，并导致新的社会不平等来源的出现。该项目开发了一个将风险建模与经济决策和社会行为模型相结合的框架。在气候不确定的情况下，综合办法使各种沿海保护选择变得清晰。它还有助于理解关于不同降低风险战略的决策如何最好地满足种族、民族和社会经济多元化人群的需求。防洪基础设施的设计通常由水利工程和结构工程模型驱动，以评估和验证基线条件以及模拟地块级别的未来风险。该项目通过整合从社会科学和行为科学中提取的两个额外视角来扩展这一方法。一种是计量经济学分类模型，它根据业主自住住宅的销售数据，使用风险概况来建模对地点选择的偏好。另一种是基于社会行为模型的，该模型识别居民的风险认知，并揭示风险偏好如何受到信念、信息和其他经济分类模型没有涵盖的因素的影响。综合这些方法，以量化总人口福利的变化和一系列风险概况情景的分配公平性，这些情景涉及不同的风暴潮屏障类型以及当前和未来的风暴气候学和海平面。进一步完善了风险概况和福利衡量标准，以满足参与沿海屏障系统设计决策的最终用户和主要利益攸关方的需要。这项活动旨在帮助政策制定者评估一系列可能的干预措施，从公共住房投资到更容易获得的参与性规划，这些措施可能会解决与洪水相关的有条件的和不断变化的风险所产生的不公平问题。该奖项得到了社会、行为和经济委员会(SBE)和地球科学委员会的支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.People make decisions on where to live based on many considerations. In addition to budget constraints, this may include such features as availability of public goods, the environment, and local climate. One very important consideration is the risk associated with flooding. Locations vary by flood risk. Such risk evolves because of changing climate and because of government investments in flood control infrastructure. This SAI research project examines the decision making of people residing in coastal communities regarding their residential location choices when threatened by changing flood risk conditions. Investments in flood control infrastructure can turn previously risky areas into safer locations. The safety provided by coastal flood barriers may, in turn, increase the demand for local housing. A societal consequence is that real estate prices are driven up, and low- and middle-class residents are driven out. This outcome may further exacerbate disparities in home ownership across income strata and lead to the emergence of a new source of social inequity. This project develops a framework integrating risk modeling with economic decisions and social behavioral models. The integrative approach brings clarity to various coastal protection options in the face of climate uncertainty. It also helps to understand how decisions regarding different risk reduction strategies can best address the needs of racially, ethnically, and socioeconomically diverse populations.The design of flood control infrastructure is often driven by hydraulic and structural engineering models to assess and validate baseline conditions as well as simulate future risk at the parcel level. This project extends that approach by integrating two additional perspectives drawn from the social and behavioral sciences. One is an econometric sorting model that uses risk profiles to model preferences for location choices based on sales data of owner-occupied residential properties. The other is based on social behavior models that identify residents’ risk perceptions and uncover how risk preferences are affected by beliefs, information and other factors not captured by the economic sorting model. These approaches are integrated to quantify the change in welfare of the total population and the distributional equity for a set of risk profile scenarios involving different storm surge barrier types and current and future storm climatology and sea levels. The risk profiles and welfare metrics are further refined to address the needs of end-users and key stakeholders involved in making decisions about the design of a coastal barrier system. This engagement seeks to help policy makers evaluate a range of possible interventions, from investment in public housing to more accessible participatory planning, that may address inequities emerging from conditional and evolving risk associated with flooding.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Geosciences.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.