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Collaborative Research: Probabilistic Debris Modeling in Coastal Storm Events: A Case of Complex Coupling Between Human-Built-Natural Systems

合作研究：沿海风暴事件中的概率碎片建模：人造自然系统之间复杂耦合的案例

基本信息

批准号：
2002522
负责人：
Jamie Padgett
金额：
$ 27.61万
依托单位：
William Marsh Rice University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-15 至 2024-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2002522&HistoricalAwards=false
关键词：
Collaborative Research Probabilistic Debris Modeling

项目摘要

Natural disasters, like hurricanes, tropical storms, and flood events, can generate massive amounts of debris, posing significant challenges to coastal communities. Financial and logistical burdens related to debris removal account for nearly a third of reimbursed recovery costs, and threats to public safety range from impaired emergency response to health hazards. There is need for more accurate models to estimate debris presence and quantities after, and preferably prior to a storm, so communities can better prepare for and manage debris burdens. Knowledge about what drives debris patterns is limited, so current predictive models are not accurate enough to support planning or response, particularly for multi-hazard storm events. In addition, coastal landscapes are constantly changing, and as development patterns shift so do prospective debris volumes and locations. This project addresses the need for integrative models that reflect the complex coupling between human-built-natural systems that underpin debris generation in storm events and the cascading impacts on coastal communities. This project examines the drivers of debris patterns and also develops models that couple those insights with infrastructure, socio-demographic, and human health impacts, among others. Resulting insights can inform policy decisions, coastal planning and risk mitigation, and debris management. Synthesis of model outcomes and policy implications will be shared via web hosted interactive story mapping.This project will transform our understanding of debris generation from coastal storms and its cascading consequences on communities by deriving coupled models of the interactions between human-built-natural systems. New methods will be developed for probabilistic modeling of debris presence and volumes, harnessing and fusing empirical data from past events, storm simulations, and physics-based estimates of fragility. A significant departure from traditional debris prediction models will be afforded by introducing nested statistical surrogate models informed by multi-resolution land use/land cover characteristics, physical vulnerability of structures or vegetation, and multi-hazard storm intensities. As a result, coupled models of development and debris potential are enabled for the first time to explore current and future storm risks and policy scenarios. By integrating models of the cascading consequences of debris with socio-demographic characteristics, this project will also shed new light on relationships between regional debris effects and social vulnerability that can inform future planning, management and mitigation efforts. Knowledge co-production and the practical viability of research methods will be advanced by working with stakeholders in testbed communities, to increase the likelihood that resulting models will be useful for future plans and decisions.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.

飓风、热带风暴和洪水等自然灾害会产生大量残骸，对沿海社区构成重大挑战。与碎片清除相关的财务和后勤负担占报销恢复费用的近三分之一，对公共安全的威胁包括紧急响应受损和健康危害。有必要建立更准确的模型，以便在风暴之后，最好是在风暴之前，估计碎片的存在和数量，从而使社区能够更好地应对和管理碎片负担。关于碎片模式的驱动因素的知识有限，因此目前的预测模型不够准确，无法支持规划或应对，特别是对于多重灾害的风暴事件。此外，沿海景观不断变化，随着开发模式的转变，预期的碎片数量和位置也在变化。该项目解决了对综合模型的需求，这些模型反映了人为-自然系统之间的复杂耦合，这些系统是风暴事件中产生碎片的基础，也是对沿海社区的级联影响。该项目研究碎片模式的驱动因素，并开发模型，将这些见解与基础设施、社会人口和人类健康影响等结合起来。由此产生的见解可以为政策决策、沿海规划和风险缓解以及碎片管理提供信息。模型结果和政策影响的综合将通过网络托管的互动故事mapping.This project will transform our understanding of debris generation from coastal storms and its cascadation consequences on communities by deriving coupled models of interactions between human-built-natural systems.将制定新的方法，对碎片的存在和数量进行概率建模，利用和融合来自以往事件、风暴模拟和基于物理学的脆弱性估计的经验数据。采用嵌套式统计替代模型将大大偏离传统的碎片预测模型，这些模型以多分辨率土地使用/土地覆盖特征、结构或植被的物理脆弱性以及多灾害风暴强度为依据。因此，第一次能够利用发展和碎片潜力的耦合模型来探讨当前和未来的风暴风险和政策设想。通过将碎片的级联后果模型与社会人口特征相结合，该项目还将对区域碎片影响与社会脆弱性之间的关系提供新的认识，从而为今后的规划、管理和减缓努力提供信息。通过与试验台社区的利益相关者合作，将促进知识的共同生产和研究方法的实际可行性，以增加产生的模型对未来计划和决策有用的可能性。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知识价值和更广泛的影响审查标准进行评估来支持。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Performance-Based Coastal Engineering Framework

基于性能的海岸工程框架

DOI：
10.3389/fbuil.2021.690715
发表时间：
2021
期刊：
Frontiers in Built Environment
影响因子：
3
作者：
González-Dueñas, Catalina;Padgett, Jamie E.
通讯作者：
Padgett, Jamie E.

Knowledge-Informed Data-Driven Modeling of Coupled Human-Built–Natural Systems: The Case of Hurricane-Induced Debris

耦合人造自然系统的知识知情数据驱动建模：飓风引发的碎片案例

DOI：
10.1061/nhrefo.nheng-1705
发表时间：
2023
期刊：
Natural Hazards Review
影响因子：
2.7
作者：
González-Dueñas, Catalina;Meads, Mitchell M.;Padgett, Jamie E.;Highfield, Wesley E.
通讯作者：
Highfield, Wesley E.

A Data-Driven Approach to Hurricane Debris Modeling

数据驱动的飓风碎片建模方法