PREEVENTS Track 2: Collaborative Research: Development and testing of volcanic eruption models and forecasts through multidisciplinary data synthesis at Alaska volcanoes

预防事件轨道 2：协作研究：通过阿拉斯加火山的多学科数据综合开发和测试火山喷发模型和预测

• 批准号: 1855007
• 负责人: Ronni Grapenthin
• 金额: $ 11.07万
• 依托单位: New Mexico Institute of Mining and Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1855007&HistoricalAwards=false
• 关键词: PREEVENTS; Track; Collaborative; Research; Development

Explosive volcanic eruptions pose an increasing hazard to a growing, globally connected population. Alaska has roughly fifty-four historically active volcanoes with multiple explosive eruptions per year that threaten local populations, infrastructure, and air traffic. For example, the 1989-1990 eruption of Redoubt volcano caused failure of all four engines of a commercial jet, resulting in more than two vertical miles of airplane free-fall. Fortunately in that instance the aircraft made a safe landing, but accurate forecasting of volcanic eruptions remains challenging many years later. Accurate volcanic eruption forecasting is hampered by the complex and dynamic nature of volcanoes. Recent studies, however, have shown that combining multidisciplinary observations of past unrest can yield accurate forecasts of eruptions from well-monitored volcanoes. In this project the re-analysis and combination of multidisciplinary observations of past volcanic unrest for eight Alaska volcanoes will help to develop a suite of eruption forecast models. These models will be provided to the Alaska Volcano Observatory (AVO) for operational use to improve AVO's eruption forecasting capabilities and mitigate eruption hazards. Additionally, by developing and sharing education modules and courses with teachers from communities near active volcanoes, the populations most directly impacted by volcanic eruptions will be better prepared.This project will capitalize on the wealth of AVO data, the multidisciplinary expertise of volcano observatory scientists, and the analytical power provided by a team of graduate students, postdoctoral fellows and researchers. Our target Alaska volcanoes encompass a range of eruptive behaviors and signs of unrest. Through data reanalysis and multidisciplinary synthesis we will advance our understanding of these dynamic systems and identify commonalities in unrest signatures. Our project will build valuable eruption models for each target volcano, including one complex physics-based model and eight multicomponent ensemble models. These models will be used as input parameters into a probabilistic eruption forecasting framework that will incorporate geologically-derived eruption histories, geophysical and geochemical monitoring data, and expert elicitation to forecast the possible eruption outcomes and threats. This project will advance our understanding of the fundamental processes that lead to volcanic unrest or eruption and improve our capabilities to forecast eruptions and mitigate associated hazards. These results will be applicable to a range of volcanoes worldwide.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.

火山爆发对不断增长的全球人口构成越来越大的危险。阿拉斯加大约有54座历史上活跃的火山，每年都会有多次爆发，威胁当地人口，基础设施和空中交通。例如，1989年至1990年的里道特火山爆发导致一架商用喷气式飞机的所有四个发动机失灵，导致飞机垂直自由落体超过两英里。幸运的是，飞机在那次事故中安全着陆，但多年后，对火山爆发的准确预测仍然具有挑战性。准确的火山爆发预测受到火山复杂和动态性质的阻碍。然而，最近的研究表明，结合对过去动荡的多学科观察，可以对监测良好的火山喷发做出准确的预测。在这个项目中，对阿拉斯加八座火山过去火山动荡的多学科观测结果进行重新分析和组合，将有助于开发一套火山喷发预测模型。这些模型将提供给阿拉斯加火山观测站（AVO）供操作使用，以提高AVO的喷发预测能力并减轻喷发危险。此外，通过与活火山附近社区的教师开发和分享教育模块和课程，受火山爆发最直接影响的人口将得到更好的准备，该项目将利用丰富的AVO数据、火山观测站科学家的多学科专业知识以及研究生、博士后研究员和研究人员团队提供的分析能力。我们的目标阿拉斯加火山包括一系列的喷发行为和动荡的迹象。通过数据再分析和多学科综合，我们将推进我们对这些动态系统的理解，并确定动荡特征的共性。我们的项目将为每个目标火山建立有价值的喷发模型，包括一个复杂的基于物理的模型和八个多组分集合模型。这些模型将被用作概率喷发预测框架的输入参数，该框架将纳入地质学派生的喷发历史、地球物理和地球化学监测数据以及专家启发，以预测可能的喷发结果和威胁。该项目将增进我们对导致火山动荡或喷发的基本过程的了解，并提高我们预测喷发和减轻相关危害的能力。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。