RAPID: Collaborative Research: Building Digital Infrastructure and Communities to Assess Risk of Drinking Water Hazards Caused by Hurricanes

RAPID：合作研究：建设数字基础设施和社区以评估飓风造成的饮用水危害风险

• 批准号: 1902537
• 负责人: W. Christopher Lenhardt
• 金额: $ 4.17万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1902537&HistoricalAwards=false
• 关键词: RAPID; Collaborative; Research; Building; Digital

After a hurricane, responders need information to address immediate human needs. Among the most important needs is to ensure that drinking water is not contaminated by flooding or system failure. Information is also needed to learn from past events to reduce the impacts in the future. This project will compile environmental and related information from Hurricane Maria in Puerto Rico and Hurricane Florence in North Carolina to create a cohesive data system. A web platform will enable the sharing of these data to help understand how hurricanes and flooding impact physical and digital infrastructure. Increased public access to environmental and health data will help communities prevent drinking water contamination to protect human health, as well as plan for future events. Impacts from hurricanes and floods are increasing; there is growing interest by communities to engage in research with outcomes usable to protect and educate themselves against water hazards. The recovery period is an important opportunity to engage the public in research to assess drinking water related health risks and better prepare for future water security for the most vulnerable populations. This project will create a synthesized data and software system to advance our understanding of how digital and physical infrastructure information reduce the impact of disasters using an integrated collaborative platform for ongoing research. Current data collection includes assessment of data and cyberinfrastructure needs as well as training for archiving new datasets for Hurricane Florence and Hurricane Maria. Datasets include hurricane observations, flood maps, storm track forecasts, National Water Model forecasts, de-identified drinking water quality sampling, and other public data sources including from non-profit, government, and open and crowd-sourced datasets. The hydrologic research community repository, HydroShare, will provide a point of access for research findings, with interoperability designed to link to data models and repositories used by natural hazards, environmental health, and environmental engineering communities in a consistent, documented format. Networks disaster coordination data collection and information dissemination are sharing educational tools to generate analyses and visualization of hurricane impacts to address ongoing needs and prepare for the next hurricane season. Public user engagement, research community support, and ongoing software operations and maintenance are key to continuous development and usability of the analysis tools and datasets. Our study uses Hurricanes Florence and Maria datasets and case studies from North Carolina and Puerto Rico to improve how we share knowledge and build capacity to support communities around the world who may use digital infrastructure to foster self-resiliency.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.

飓风过后，响应者需要信息来满足直接的人类需求。最重要的需求之一是确保不会因洪水或系统故障而污染饮用水。还需要信息从过去的事件中学习，以减少将来的影响。该项目将收集波多黎各飓风玛丽亚和北卡罗来纳州佛罗伦萨飓风的环境和相关信息，以创建一个凝聚力的数据系统。 Web平台将使这些数据共享，以帮助了解飓风和洪水如何影响物理和数字基础设施。公众获得环境和健康数据的机会增加将有助于社区防止饮用水污染以保护人类健康，并计划未来的活动。飓风和洪水的影响正在增加；社区越来越有兴趣进行研究，以保护和教育自己免受水危害。恢复期是使公众参与研究以评估饮用水与健康风险的重要机会，并为最脆弱的人群做好准备。该项目将创建一个综合的数据和软件系统，以提高我们对数字和物理基础架构信息如何使用综合协作平台进行正在进行的研究来减少灾害的影响。当前的数据收集包括评估数据和网络基础设施需求，以及培训佛罗伦萨飓风和玛丽亚飓风的新数据集。数据集包括飓风观察，洪水图，风暴轨道预测，国家水模型预测，去识别的饮用水质量采样以及其他公共数据来源，包括非营利性，政府，开放和拥挤的数据集。水文研究社区存储库HydroShare将为研究结果提供访问点，互操作性旨在将自然危害，环境健康和环境工程社区使用的数据模型和存储库以一致的，有记录的格式链接。网络灾难协调数据收集和信息传播正在共享教育工具，以产生分析和可视化飓风影响，以满足持续的需求并为下一个飓风季节做准备。公共用户参与度，研究社区支持以及正在进行的软件操作和维护是分析工具和数据集的持续开发和可用性的关键。我们的研究使用北卡罗来纳州和波多黎各的飓风佛罗伦萨和玛丽亚数据集以及案例研究，以提高我们如何共享知识和建立能力，以支持世界各地的社区，这些社区可以使用数字基础设施来促进自我弥补。这奖反映了NSF的法规使命，并通过评估基础的智力效果和宽阔的范围来评估支持，并以此为基础的智力效果，并具有评估。