Hazards SEES Type 2: From Sensors to Tweeters: A Sustainable Sociotechnical Approach for Detecting, Mitigating, and Building Resilience to Hazards

危害 SEES 类型 2：从传感器到高音扬声器：用于检测、缓解和增强危害抵御能力的可持续社会技术方法

• 批准号: 1331463
• 负责人: Louise Comfort
• 金额: $ 300万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1331463&HistoricalAwards=false
• 关键词: Hazards; SEES; Type; Sensors; Tweeters

Technical DescriptionThis project addresses the national challenge of defining and building resilience to hazards that would engage the ?whole nation,? including scientists, governmental agencies at all levels of jurisdiction, private and nonprofit organizations, and communities. To meet this challenge, it is essential to define, design, and demonstrate an interdisciplinary, dynamic process that will transform societal understanding of risk and enable self-organized, collective action to support the resilient management of hazards. This study will identify and model the interactions among physical, engineered, and sociotechnical systems that occur in hazard emergence and response as a complex, adaptive system of systems (CASoS) to enhance resiliency in practice and enable communities to manage the risk of hazards within existing resource and time constraints. It will use the threat of Near-Field Tsunamis (NFTs; i.e., waves generated within 200 miles of shore) in a location prone to this risk, Padang, West Sumatra, Indonesia as a case study to investigate methods of assessing accurately and efficiently the dynamics of NFTs generated by undersea earthquakes or landslides as they impact human communities. This process is an iterative search for information under evolving conditions to inform decisions at multiple levels of action in response to shared risk. Five basic research questions drive this project:1.What instruments, metrics, media, tools, and technologies are most effective in enabling communities at risk to collect, access, and exchange information about risk?2.What types of information and what forms of communication contribute most effectively to collective recognition of risk, creating public awareness of a shared threat to safety?3.To what extent does investment in data collection, analysis, search, and exchange enable more informed decision making in community environments exposed to long-term risk, and reduce the potential for ecological, social, and economic losses from episodic catastrophes?4.What causal models, based on combined real-time and stored data for social and physical systems, offer alternative strategies for collective action to protect community population, infrastructure, and resources?5.How can the proposed resilience models, methods and tools for collective action be used to assess accurately and efficiently the dynamics of NFTs generated by undersea earthquakes or landslides and enable collective action to manage the impact of hazards on coastal communities?This research will test the following four hypotheses:1.Computational modeling of complex adaptive relationships under uncertain conditions increases collective understanding of tsunami risk and increases collective problem solving capacity. 2.Multiple patterns of information dissemination regarding risk among community residents increase the efficiency of self-organized collective action.3.Timely, accurate transmission of tsunami risk increases efficiency in targeting evacuation procedures to diverse community groups and areas with different degrees of exposure.4.Detecting the temporal rate of seismic motion, or source slowness, discriminates tsunami earthquakes from non-tsunami earthquakes.Broader ImpactsThis study envisions communities that learn to assess hazards endemic to the environment and that have the capacity to make collective decisions informed by scientific knowledge, leading to timely, effective risk reduction. Findings from this project will redefine the science of community resilience and enable at-risk communities to create learning environments in which they collectively assess, respond, and recover from extreme events. Models for collective action demonstrated in this project will increase collective problem solving capacity for minimizing losses and maximizing actions for innovative, sustainable risk reduction. The most vulnerable groups in society--women, children, minorities, elderly?will benefit as communities initiate risk reduction measures, and as leaders trained in interdisciplinary skills guide citizens in responsible management of resources and risk assessment. Developing dynamic methods for managing sociotechnical systems will enhance SEES education. The CASoS prototype, deployed and tested in Indonesia, will benefit the global society.

技术描述本项目解决了国家的挑战，定义和建设抗灾能力的危害，将从事？全国，？包括科学家、各级政府机构、私人和非营利组织以及社区。为了应对这一挑战，必须定义、设计和展示一个跨学科的动态过程，这一过程将改变社会对风险的理解，并使自组织的集体行动能够支持灾害的弹性管理。本研究将识别和建模的物理，工程和社会技术系统之间的相互作用，发生在灾害的出现和响应作为一个复杂的，适应性系统的系统（CASoS），以提高在实践中的弹性，使社区管理现有的资源和时间限制内的灾害风险。它将利用近场海啸（NFT;即，在印度尼西亚西苏门答腊岛巴塘的一个容易发生这种风险的地点，在距离海岸200英里范围内产生的波浪），作为一个案例研究，以研究准确有效地评估海底地震或滑坡影响人类社区时产生的NFT动态的方法。这一过程是在不断变化的条件下反复搜索信息，以便为应对共同风险的多层次行动决策提供信息。 5个基本的研究问题驱动这个项目：1.什么样的工具，指标，媒体，工具和技术是最有效的，使社区在风险中收集，访问和交换有关风险的信息？2.什么类型的信息和什么形式的沟通最有效地促进了对风险的集体认识，使公众认识到共同的安全威胁？3.在何种程度上，对数据收集、分析、搜索和交换的投资能够在面临长期风险的社区环境中做出更明智的决策，并减少偶发性灾难造成的生态、社会和经济损失？4.基于社会和物理系统的组合实时和存储数据的因果模型，为保护社区人口，基础设施和资源的集体行动提供了替代战略？5.如何利用拟议的复原力模型、方法和集体行动工具，准确和有效地评估海底地震或滑坡产生的非森林转移动态，并使集体行动能够管理灾害对沿海社区的影响？本研究将检验以下四个假设：1.不确定条件下复杂适应关系的计算建模增加了集体对海啸风险的理解，提高了集体解决问题的能力。2. 3.及时、准确地传递海啸风险信息，提高了针对不同社区群体和不同受灾程度地区的疏散程序的效率。4.检测地震运动的时间速率，或震源慢度，更广泛的影响本研究设想社区学会评估环境特有的危害，并有能力根据科学知识做出集体决策，从而及时，有效降低风险。该项目的研究结果将重新定义社区复原力的科学，并使处于风险中的社区能够创造学习环境，使他们能够集体评估，应对和从极端事件中恢复过来。本项目中展示的集体行动模式将提高集体解决问题的能力，以尽量减少损失，并最大限度地采取创新的、可持续的减少风险行动。社会中最脆弱的群体-妇女、儿童、少数民族、老年人？随着社区启动减少风险措施，并随着受过跨学科技能培训的领导人指导公民负责任地管理资源和进行风险评估，将受益匪浅。发展管理社会技术系统的动态方法将加强SEES教育。在印度尼西亚部署和测试的CASoS原型将使全球社会受益。