| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | August 23, 2022 |
| Latest Amendment Date: | August 23, 2022 |
| Award Number: | 2228490 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Shen
CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | October 1, 2022 |
| End Date: | September 30, 2024 (Estimated) |
| Total Intended Award Amount: | $50,000.00 |
| Total Awarded Amount to Date: | $50,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
W5510 FRANKS MELVILLE MEMORIAL LIBRARY STONY BROOK NY US 11794-0001 (631)632-9949 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
WEST 5510 FRANKS MELVILLE MEMORIAL LIBRARY STONY BROOK NY US 11794-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | S&CC: Smart & Connected Commun |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.041 |
ABSTRACT
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.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Project Overview
The goal of this project was to address the vulnerability of economically disadvantaged coastal communities on Long Island, specifically Mastic Beach, to flooding risks. By integrating engineering principles, socioeconomic analysis, and community engagement, the project sought to lay the groundwork for data-driven, human-centric strategies that enhance flood resilience.
This planning project successfully completed foundational work, including flood modeling, socioeconomic data analysis, and engagement with local stakeholders. These efforts informed a comprehensive approach to developing disaster management strategies that are equitable, efficient, and grounded in community needs.
Key Project Outcomes
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Overland Flood Modeling Framework Development
- A numerical flood modeling framework was developed for the Mastic Beach area, enabling detailed analysis of flooding impacts. This model serves as a foundation for assessing the vulnerabilities of critical infrastructure, businesses, and commuting routes within the community.
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Socioeconomic Analysis and Data Collection
- The project team conducted an exploratory analysis of existing data, identifying 130 business establishments in Mastic Beach that employed approximately 4% of the local population. Findings revealed that most residents commute to work, underscoring the need to assess the vulnerability of commuting routes to flood events.
- Approval was secured to access confidential employment and wage data from New York State’s Department of Labor, further enhancing the team’s ability to analyze economic impacts.
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Community Engagement and Site Visits
- A research team site visit and community tour in Mastic Beach were conducted to gather firsthand insights and engage with stakeholders. These activities provided a clearer understanding of community priorities, enabling the integration of local knowledge into the project framework.
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Development of Social Science Data Instruments
- Surveys and data collection tools were developed to measure critical factors such as place attachment, risk perceptions, trust in government, and social capital. These instruments are essential for capturing community perspectives and behaviors in response to flooding risks.
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Graduate Student Support and Training
- The project provided academic and financial support to two graduate students (Civil Engineering and Political Science), offering hands-on research experience in flood modeling and social science data analysis.
Intellectual Merit
This project combined engineering-based flood modeling with social science methodologies to create a holistic understanding of flood vulnerability in Mastic Beach. By identifying gaps in infrastructure resilience and socioeconomic factors, the project highlights the importance of integrating technical and community-driven approaches to disaster management. The numerical flood modeling framework developed through this project provides a critical tool for evaluating flooding risks in economically disadvantaged coastal areas.
Broader Impacts
The project’s outcomes contribute to broader societal goals by emphasizing equity and resilience in disaster planning. The focus on economically disadvantaged communities ensures that flood mitigation strategies prioritize those most vulnerable to environmental risks. Community engagement activities have helped build trust and foster collaboration between local residents, stakeholders, and researchers. Additionally, the project supported student training and education, preparing the next generation of engineers and social scientists to address pressing climate challenges.
Although the full implementation proposal was not funded, the groundwork laid through this project provides a valuable foundation for future flood resilience initiatives on Long Island and beyond.
Conclusion
This project successfully developed tools, frameworks, and strategies to address coastal flood resilience for underserved communities. By combining data-driven engineering solutions with social science insights and community engagement, the project represents an essential step toward creating equitable and effective disaster management plans. Moving forward, these efforts can be scaled to address similar challenges in other vulnerable coastal regions.
Last Modified: 12/16/2024
Modified by: Ali Farhadzadeh
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