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

合作研究：SAI-R：与沿海防洪屏障相关的不断变化和条件风险下的决策

• 批准号: 2228485
• 负责人: Meri Davlasheridze
• 金额: $ 44万
• 依托单位: Texas A&M University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228485&HistoricalAwards=false
• 关键词: Collaborative; Research; SAI; Decision; making

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.

加强美国基础设施（SAI）是NSF的一项计划，旨在促进以人为本的基础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改善生活质量奠定了坚实的基础。强大、可靠和有效的基础设施刺激私营部门创新，促进经济增长，创造就业机会，提高公共部门服务提供的效率，加强社区建设，促进机会平等，保护自然环境，增强国家安全，并推动美国的领导地位。为了实现这些目标，需要来自科学和工程学科的专业知识。SAI专注于人类推理和决策，治理以及社会和文化过程的知识如何使建设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的进步基础上。人们根据许多考虑因素决定在哪里居住。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有关的风险。地点因洪水风险而异。气候变化和政府对防洪基础设施的投资导致了这种风险的演变。这个SAI研究项目研究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的威胁时，关于他们的居住地点选择的决策。对防洪基础设施的投资可以将以前危险的地区变成更安全的地方。沿海防洪屏障提供的安全性可能反过来增加对当地住房的需求。一个社会后果是，真实的房地产价格被推高，中低阶层居民被赶出去。这一结果可能会进一步加剧各收入阶层在拥有住房方面的差距，并导致出现新的社会不平等根源。该项目开发了一个框架，将风险建模与经济决策和社会行为模型相结合。这种综合办法使人们在面对气候不确定性的情况下能够明确各种沿海保护备选办法。它还有助于了解不同的风险降低策略的决策如何能够最好地满足种族，民族和社会经济多样化人口的需求。防洪基础设施的设计通常由水力和结构工程模型驱动，以评估和验证基线条件，并模拟地块级别的未来风险。该项目通过整合来自社会和行为科学的两个额外视角来扩展这种方法。一个是计量经济学排序模型，该模型使用风险概况来模拟基于自住住宅物业销售数据的位置选择偏好。另一种是基于社会行为模型，识别居民的风险感知，并揭示风险偏好如何受到信念，信息和其他因素的影响，而这些因素没有被经济分类模型捕获。这些方法被整合，以量化总人口的福利变化和一套风险概况情景的分配公平性，涉及不同的风暴潮屏障类型和当前及未来的风暴气候和海平面。进一步完善风险简介和福利指标，以满足最终用户和参与沿海屏障系统设计决策的关键利益攸关方的需求。该奖项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和不断变化的风险所带来的不平等问题。经济（SBE）该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的学术价值和更广泛的影响审查标准。