SCC-CIVIC-PG Track A: Human-centric, Data-driven Coastal Flood Resilience Strategies for Economically Disadvantaged Communities on Long Island

这项公民创新挑战（Civic）研究的重点是为沿海洪水缓解规划开发一种以社区为中心的混合建模方法。将最先进的高分辨率洪水模型与社区参与相结合，将能够根据社区的需求制定最佳缓解策略。通过扩大建模过程中考虑因素的范围，将提高其真实感，增强当地社区的规划能力，并获得当地社区的支持。在与长岛、纽约沿海社区和萨福克县规划部门的密切合作下，社区利益相关者将参与收集和生成关于社区关键社会经济特征和行为倾向的数据。采用一系列社会科学技术，这些数据将用于预测对极端洪水事件和潜在政策干预的社会和行为反应。预测的反应将反馈到模型中，以便对缓解战略进行更全面的评估。该项目将为居民、政策制定者和其他利益相关者提供强大的新工具，以便更好地评估未来极端事件的影响，并确定最佳的适应和缓解战略。这种包容性建模方法可应用于其他社区，根据其需求定制最佳工程解决方案，从而提高工程解决方案和市政规划的公平性和有效性，以缓解和适应洪水。该项目的新颖之处在于其以社区为中心的模拟方法，用于评估极端天气事件对沿海洪泛区基础设施、财产和当地企业的风险。具体而言，该项目将开发一个了解物理的社区规模高保真计算机模型，用于对这些风险进行定量评估，并将实施与当地社区共同编制的模型所提供的缓解战略，同时考虑到对当地企业的影响。除了传统的淹没深度信息外，该项目还将包括其他与洪水有关的因素，如侵蚀和对基础设施的破坏，从而增强当前的洪水预测能力。与当地社区和决策者接触的有力过程，用于改进和参数化模型，以更好地满足社区的需求，并考虑他们的行为反应，将有助于进一步实现环境正义和社会经济公平的目标。这种方法是独特的和创新的。它有可能节省大量成本，同时提高居住在沿海县的约占全国总人口40%的人的生活质量。该项目是对“公民创新挑战”项目（track a）的回应：在不断变化的气候中生活：围绕适应、恢复和缓解的灾前行动——是国家科学基金会、国土安全部和能源部之间的合作项目。该奖项反映了美国国家科学基金会的法定使命，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。

This Civic Innovation Challenge (CIVIC) research has a focus of developing a community-centric, hybrid modeling approach for coastal flooding mitigation planning. Combining state-of-the-art, high-resolution flood modeling with community engagement, the development of optimal mitigation strategies that are informed by the needs of the community, as they define them, will be enabled. By expanding the scope of the factors considered in the modeling process, its realism will be improved, enhancing the planning capacity of, and the buy-in from, the local community. In close collaboration with a Long Island, New York coastal community and the Suffolk County planning department, community stakeholders will be engaged in collecting and generating data on key socio-economic characteristics and behavioral propensities of the community. Employing a suite of social scientific techniques, these data will be used to predict the social and behavioral responses to extreme flooding events and potential policy interventions. The predicted responses will be fed back into the model to enable a more holistic assessment of the mitigation strategies. The project will provide residents, policymakers, and other stakeholders with powerful new tools to both better assess the impact of future extreme events and determine the optimal adaptation and mitigation strategies. This inclusive modeling approach can be applied to other communities, tailoring optimal engineering solutions to their needs and as a result, enhancing the equity and effectiveness of engineering solutions and municipal planning for flood mitigation and adaptation.The novelty of this project is its community-centric simulation-based approach for assessing risks to infrastructure, properties, and local businesses on coastal flood plains due to extreme weather events. Specifically, this project will develop a physics-informed community-scale high-fidelity computer model for quantitative assessment of these risks and will implement mitigation strategies informed by the model that have been co-produced with the local community, considering the implications for local businesses. In addition to traditional inundation-depth information, the project will enhance the current flood prediction capabilities by including other flood-related factors such as erosion and damage to infrastructure. The robust process of engaging with the local community and decision makers, used to refine and parameterize the model to better address the needs of the community and consider their behavioral responses, will help further the goals of environmental justice and socioeconomic equity. Such an approach is unique and innovative. It has the potential to save substantial costs while improving the quality of life for the ~40 percent of the nation’s total population who live in coastal counties.This project is in response to the Civic Innovation Challenge program—Track A. Living in a changing climate: pre-disaster action around adaptation, resilience, and mitigation—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.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.