CRISP 2.0 Type 2: Collaborative Research: Integrated Socio-Technical Modeling Framework to Evaluate and Enhance Resiliency in Islanded Communities (ERIC)

CRISP 2.0 类型 2：协作研究：评估和增强岛屿社区复原力的综合社会技术建模框架 (ERIC)

• 批准号: 1832576
• 负责人: Eric Harmsen
• 金额: $ 36.48万
• 依托单位: University of Puerto Rico Mayaguez
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832576&HistoricalAwards=false
• 关键词: CRISP; 2.0; Type; Collaborative; Research

Recent catastrophic events in the coastal tropics and sub-tropics highlight the impact of the interdependencies of critical infrastructure systems and how those interdependencies cause failures of physical assets, leading to adverse impacts on the health and socio-economic wellbeing of the communities in those regions. Islanded communities, defined as remote, self-contained regions, with low or intermittent physical (or cyber) connectivity, are especially vulnerable to natural disasters. A recent example is the extraordinary case of the island of Puerto Rico (PR), in the direct path of Hurricane Maria, and the near total failure of lifeline infrastructures. This event also exemplifies how extreme events compound endemic physical, social and economic vulnerabilities often present in remote or isolated communities. The associated cascading impacts, prior to and after Hurricane Maria, are clear evidence of our limited knowledge and readiness to anticipate risks in these complex engineered, physical and human systems. This reveals the urgent need to develop scientific and social frameworks and methodologies by which islanded communities can assess their existing preparedness to extreme climatic events, and through a multi-stakeholder engagement process and engineering analysis, evaluate and implement alternative measures to enhance the resiliency of such communities. Using PR as the case study, this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project will develop a data-driven modeling framework for understanding the complex physical and social vulnerabilities, and interdependencies that can and have resulted in near total failure of infrastructure systems.The research questions that will be addressed include: a) How do socio-economic stability, governance and baseline conditions of infrastructure impact performance and resiliency of critical interdependent infrastructure systems in extreme weather conditions? b) What knowledge and methods are needed to guide strategies for enhancing system resiliency and restoration in islanded communities? c) How can experts and stakeholders be engaged and informed about enhancing resiliency and effective failure mitigation strategies? The plan to achieve these objectives is by first implementing a data-driven process of gathering human narratives as social data and a source of information to recreate the timeline and experience of Hurricane Maria, before, during and after the event. Next, the project team will develop an integrated modeling and simulation framework, based on multi-layer distribution network theory. This framework will include structural-based assessment results in the modeling of infrastructure behavior during and after a disaster. The focus of study will be on the interdependencies of the electrical power, water distribution and communications systems. An objective is to recreate, via simulation, the event using a combination of system network models, geophysical data, and community data, to capture the sequence of the cascading failures and the corresponding societal impact as the event unfolded and during post-event recovery efforts. The project team seeks to arrive at a level of understanding of this system of systems that will lead to informed solutions and recommendations that will minimize adverse impact, disruption, loss of life and suffering, in the face of future extreme events. The research builds on a wealth of expertise in weather and climate processes in the Caribbean, understanding of local critical infrastructure, experience in mining community narrative, and from proven methodologies for rebuilding resilient communities in post-Hurricane Sandy in the New York and New Jersey Metro Area.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.

最近在沿海热带和亚热带的灾难性事件突出了关键基础设施系统相互依存的影响，以及这些相互依存的如何导致物理资产的失败，从而对这些地区的社区对健康和社会经济的不利影响产生不利影响。被定义为具有偏远，独立的区域的岛屿社区，具有较低或间歇性的身体（或网络）连通性，特别容易受到自然灾害的影响。最近的一个例子是波多黎各岛（PR），玛丽亚飓风的直接道路和生命线基础设施的几乎完全失败。这项事件还举例说明了极端事件如何使流行的物理，社会和经济脆弱性在遥远或孤立的社区中经常存在。在玛丽亚飓风之前和之后，相关的级联影响是我们有限的知识和准备，可以预见这些复杂的工程，物理和人类系统的风险。这揭示了迫切需要开发科学和社会框架和方法论，通过这些框架和方法论，岛屿社区可以评估其现有的对极端气候事件的准备，并通过多种利益相关者的参与过程和工程分析，评估和实施替代措施，以增强此类此类这种弹性社区。将PR作为案例研究，这种关键的弹性相互依存的基础架构系统和流程（CRISP）项目将开发一个以数据为导向的建模框架，以理解复杂的物理和社会脆弱性，以及可以并且可能导致基础架构系统几乎完全失败的相互依存关系。将解决的研究问题包括：a）基础设施基础设施的社会经济稳定，治理和基线条件如何影响绩效，以及在极端天气条件下关键相互依存的基础设施系统的弹性？ b）需要哪些知识和方法来指导策略来增强岛屿社区的系统弹性和恢复？ c）专家和利益相关者如何参与并了解提高弹性和有效的失败策略？实现这些目标的计划是首先实施以数据为基础的过程，将人类叙事作为社会数据和信息来源，以重新创建玛丽亚飓风的时间表和经验，此前，期间和之后。接下来，项目团队将基于多层分销网络理论开发一个集成的建模和仿真框架。该框架将包括基于结构的评估结果，以在灾难期间和之后的基础设施行为进行建模。研究的重点将放在电力，水分配和通信系统的相互依赖性上。一个目的是通过模拟来重现系统网络模型，地球物理数据和社区数据的组合，以捕获级联失败的顺序以及随着事件的展开以及事后恢复工作的相应的社会影响。项目团队试图对这种系统系统达成一定的了解，这将导致知情的解决方案和建议，以最大程度地减少面对未来极端事件的不利影响，破坏，生命和苦难。该研究以加勒比海的天气和气候过程的丰富专业知识为基础该奖项反映了NSF的法定任务，并使用基金会的智力优点和更广泛的影响标准来评估值得支持。

项目成果

A socio-technical approach for the assessment of critical infrastructure system vulnerability in extreme weather events

评估极端天气事件中关键基础设施系统脆弱性的社会技术方法

• DOI: 10.1038/s41560-023-01315-7
• 发表时间: 2023
• 期刊: Nature Energy
• 影响因子: 56.7
• 作者: Montoya-Rincon, Juan P.;Mejia-Manrique, Said A.;Azad, Shams;Ghandehari, Masoud;Harmsen, Eric W.;Khanbilvardi, Reza;Gonzalez-Cruz, Jorge E.
• 通讯作者: Gonzalez-Cruz, Jorge E.

Water and Energy Balance Model GOES-PRWEB: Development and Validation

• DOI: 10.3390/hydrology8030113
• 发表时间: 2021-08
• 期刊: Hydrology
• 影响因子: 3.2
• 作者: E. Harmsen;J. Mecikalski;Victor J. Reventos;Estefanía Álvarez Pérez;Sopuruchi S. Uwakweh;Christie Adorno García

Sensitivity of the Penman–Monteith Reference Evapotranspiration Equation to Meteorological Variables for Puerto Rico

• DOI: 10.3390/hydrology10050101
• 发表时间: 2023-04
• 期刊: Hydrology
• 影响因子: 3.2
• 作者: M. Irizarry-Ortiz;E. Harmsen