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

这个项目解决了定义和建立对危险的复原力的国家挑战，这将使全国都参与进来。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，至关重要的是定义、设计和展示一个跨学科的动态过程，该过程将改变社会对风险的理解，并使自我组织的集体行动能够支持对危险的弹性管理。这项研究将确定发生在灾害紧急和应对中的物理、工程和社会技术系统之间的相互作用，并将其建模为复杂的适应性系统(CASO)，以增强实践中的复原力，并使社区能够在现有资源和时间限制的情况下管理灾害风险。它将在印度尼西亚西苏门答腊岛巴东这一容易发生这种风险的地点利用近场海啸(NFT；即在海岸200英里内产生的海浪)的威胁作为案例研究，以调查准确和有效地评估海底地震或山体滑坡在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寻找信息，以便为应对共同风险的多个行动级别的决策提供信息。五个基本研究问题推动了该项目：1.在使处于风险中的社区能够收集、访问和交换有关风险的信息方面，什么工具、指标、媒体、工具和技术是最有效的？2.什么类型的信息和什么形式的通信最有效地有助于集体认识风险，使公众意识到共同的安全威胁？3.在数据收集、分析、搜索和交换方面的投资在多大程度上能够在暴露于长期风险的社区环境中实现更明智的决策，并减少突发灾难造成的生态、社会和经济损失的可能性？4.什么因果模型，基于社会和物理系统的实时和存储数据的组合，为集体行动提供替代策略以保护社区人口、基础设施和资源？5.如何使用所提出的集体行动的复原力模型、方法和工具来准确和有效地评估由海底地震或山体滑坡产生的NFT的动态，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.对不确定条件下的复杂适应关系的计算建模增加了对海啸风险的集体理解，并增加了集体解决问题的能力。2.社区居民之间关于风险的多种信息传播模式提高了自组织集体行动的效率。3.海啸风险的准确传播提高了针对不同社区群体和不同暴露程度地区的疏散程序的效率。4.检测地震运动或震源慢度的时间比率，区分海啸地震和非海啸地震。广泛影响本研究设想的社区将学会评估环境地方性危险，并有能力在科学知识的指导下做出集体决策，从而及时、有效地降低风险。该项目的发现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，在其中他们共同评估、应对极端事件并从极端事件中恢复。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，以最大限度地减少损失，最大限度地采取行动，创新、可持续地减少风险。社会中最脆弱的群体--妇女、儿童、少数群体、老年人--将受益于社区启动减少风险措施，以及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。开发管理社会技术系统的动态方法将加强社会技术教育。在印度尼西亚部署和测试的Casos原型将造福全球社会。

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.