NNA Track 2: Collaborative Research: Planning for Infrastructure Resiliency and Adaptation amid Increasing Mass-Movement Risks across the Cryosphere

NNA 轨道 2：协作研究：在整个冰冻圈大规模移动风险不断增加的情况下规划基础设施的弹性和适应

• 批准号: 2022438
• 负责人: Margaret Darrow
• 金额: $ 12.5万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2022438&HistoricalAwards=false
• 关键词: NNA; Track; Collaborative; Research; Planning

Navigating the New Arctic (NNA) is one of NSF's 10 Big Ideas. NNA projects address convergence scientific challenges in the rapidly changing Arctic. The Arctic research is needed to inform the economy, security and resilience of the Nation, the larger region and the globe. NNA empowers new research partnerships from local to international scales, diversifies the next generation of Arctic researchers, enhances efforts in formal and informal education, and integrates the co-production of knowledge where appropriate. This award fulfills part of that aim by supporting planning activities with clear potential to develop novel, leading edge research ideas and approaches to address NNA goals. It integrates aspects of the natural and built environments to address important societal challenges at this intersection, and engages internationally and with local communities.Changing climate conditions have increased the occurrence of mass-movement hazards in the cryosphere, such as landslides, debris flows, and slope failures resulting from thawing of ice-rich permafrost. Mass-movement hazards across the cryosphere pose a significant risk to people and infrastructure, such as highways and pipelines. This project brings together experts from diverse backgrounds, including engineers, geoscientists, computer scientists, and officials from a variety of academic institutions, public and government agencies, and industry, to discuss key challenges and formulate research priorities in 1) characterizing mass-movement hazards in the cryosphere, 2) mapping such hazards using machine learning, 3) forecasting such hazards using artificial intelligence, and 4) building climate-change-resilient infrastructure through flexible and adaptive approaches to reduce costs. The project outcomes enable planners and policy makers to identify critical infrastructure that is most threatened by mass-movement hazards in the Arctic, sub-Arctic, and mountainous regions, and high- and low-hazard areas when planning future infrastructure near urban and rural sites.This award funds the development and planning activities of a convergent research team to address infrastructure resilience and adaptation to increasing mass-movement risks across the cryosphere as the climate warms. Planning activities center around two annual workshops that will identify gaps in our current understanding and existing methodologies to develop: 1) more automated hazard mapping tools through remote sensing and machine learning, including well-established tools like convolutional neural networks; 2) compilations of datasets and databases and interactions with potential users; 3) more reliable artificial intelligence models including time series machine learning for hazard forecasting; and 4) more flexible and adaptive approaches to reduce costs for infrastructure resiliency and adaptation.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.

NSF的10个大创意之一是导航新北极（NNA）。 NNA项目应对北极快速变化的融合科学挑战。需要进行北极研究，以告知国家，较大地区和全球的经济，安全和弹性。 NNA赋予从本地量表到国际规模的新研究伙伴关系，使下一代北极研究人员多样化，加强了正规和非正式教育方面的努力，并在适当的情况下整合了知识的共同生产。该奖项通过支持规划活动具有明确的潜力来开发新颖的，领先的研究思想和方法来解决NNA目标，从而实现了这一目标的一部分。它整合了自然和建筑环境的各个方面，以应对此十字路口的重要社会挑战，并在国际上和当地社区参与。变化的气候条件增加了Cryosphere中质量移动危害的发生，例如滑坡，碎屑，碎屑流量和斜坡失败，导致造成的冰层造成的冰含有冰的富含冰层的Permafrost。整个Cryosphere的质量移动危害对人和基础设施（例如高速公路和管道）构成了重大风险。该项目汇集了来自各种背景的专家，包括工程师，地球科学家，计算机科学家以及来自各种学术机构，公共和政府机构以及行业的官员，讨论关键挑战并在1）表征Cryosphere中的质量运动危害的研究优先级，2）使用机器学习，3）绘制此类危害，3） - 3） - 3） - 3） - 3） - 3） - 3） - 3） - 3） - 3），4型危险范围，4个工具，4个工具，4个）。通过灵活和适应性方法降低成本的基础设施。该项目结果使计划人员和决策者能够确定受到北极，亚北极和山区群众运动危害的威胁最大的关键基础设施，以及在规划未来基础设施附近的城市和农村地点附近的基础设施时，这些奖励质量跨度的研究团队的发展和规划跨度的跨度活动，并规划跨越的范围，以促进跨度的研究团队的发展和规划，并将其促进跨度的研究团队的发展和计划。气候随着气候的温暖。规划活动集中在两个年度研讨会周围，这些研讨会将确定我们当前的理解和现有方法中的差距：1）通过遥感和机器学习更多的自动危险映射工具，包括备受公认的工具，例如卷积神经网络； 2）数据集和数据库的汇编以及与潜在用户的交互； 3）更可靠的人工智能模型，包括时间序列机器学习以进行危险预测； 4）更加灵活和适应性的方法来降低基础设施弹性和适应性的成本。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来提供支持。