NSFGEO-NERC: Collaborative Research: The central Apennines Earthquake cascade under a new microscope

NSFGEO-NERC：合作研究：新显微镜下的亚平宁中部地震级联

• 批准号: 1759810
• 负责人: William Ellsworth
• 金额: $ 21.34万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-15 至 2022-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1759810&HistoricalAwards=false
• 关键词: NSFGEO; NERC; Collaborative; Research; central

A series of powerful earthquakes rocked the Apennine mountains in central Italy, between August 2016 and January 2017 causing loss of life and inflicting heavy damage to the historic towns of Amatrice, Accumoli and Norcia. This sequence produced six strong earthquakes over a period of five months as response and recovery operations were underway. This rapidly evolving seismic crisis underscores the pressing need to better understand how earthquake sequences unfold. The goal of this joint project, funded by the National Science Foundation in the U.S. and the National Environmental Research Council in the U.K., in coordination with the Istituto Nazionale di Geofisica e Volcanologia in Italy, will deepen knowledge of earthquake interaction by studying these devastating earthquakes. An international team of earthquake expertss will use high-quality seismic data recorded during the sequences to develop new approaches that can address current obstacles that not only impede deep understanding of the earthquake processes, but also delay the scientific response in the post-earthquake disaster environment. The observational capability to detect, locate and characterize even the smallest magnitude events within few hours developed in this project will be directly applicable to tectonic, induced, geothermal and volcanic seismicity in the U.S. and around the world. Findings of this research will enable improved and scientifically-informed response to the next earthquake crisis to strike the U.S. through existing partnership with the U. S. Geological Survey and support international collaboration amongst US and European earthquake researchers.This study investigates the physics of complex earthquake sequences through the analysis of high-resolution earthquake catalogs to test increasingly sophisticated earthquake forecasting models. To reach this goal this project will: 1) Use state-of-the-art techniques to develop a comprehensive high-resolution earthquake catalog for the devastating earthquake sequence that struck the Italian Apennines in 2016-2017; 2) Investigate the physics of earthquake triggering and the evolution of large-magnitude events within this sequence; 3) Develop and provide testable forecast models that can support decision-making process for future earthquake sequences. The reseach will use the unparalleled seismic data set recorded by more than 85 high-quality broadband sensors deployed in the epicentral region to analyze how each earthquake in the sequence contributes to the evolution of seismicity in space and time. This sequence is particularly rich in this regard, with spatially intertwined episodes on August 24, 2016, October 26-28, 2016 and January 18, 2017. The seismograms of both large and small events will enable us to develop and test new full-waveform based algorithms for event detection, location and characterization that will yield precise source parameters and faulting mechanisms for even the smallest magnitude events. By improving the quality of seismic source parameters across the magnitude spectrum it will be possible to apply process-based models of earthquake nucleation and interaction, including the role of fault complexity, fault loading, relaxation, stress interaction, and fault susceptibility to stress perturbation to understand the evolution of this sequence. The improved fault mechanical understanding will help to develop innovative physics-based forecast models. Currently, real-time earthquake forecasts that describe short-term clustering probabilities are based predominantly on statistical/empirical models. However, these models lack an underlying physical model and therefore have limited predictability if no precursory seismicity exists. A common challenge for both physics- based and statistical forecasts that are based on routine catalogues is the low-probability and high-uncertainty nature of the resulting probabilities. Decision-making and scientific advice are all severely hampered under these conditions. Thus, using this new state-of the art earthquake catalog of the 2016-2017 Italian sequence to test physical, statistical and hybrid (physical and statistical) forecasts in space and time will help (a) to test physical models for earthquake occurrences in sequences, and (b) improve the resolution, accuracy and skill of the forecasts. The broader impacts of this project include improvement on seismic risk assessment as well as fostering collaboration between US and European seismologists.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.

2016 年 8 月至 2017 年 1 月期间，意大利中部的亚平宁山脉发生了一系列强烈地震，造成人员伤亡，并对历史名镇阿马特里切、阿库莫利和诺尔恰造成严重破坏。随着响应和恢复行动的进行，这一序列在五个月的时间内产生了六次强烈地震。 这场迅速演变的地震危机凸显了更好地了解地震序列如何展开的迫切需​​要。该联合项目由美国国家科学基金会和英国国家环境研究委员会资助，并与意大利国家地理和火山研究所协调，其目标是通过研究这些毁灭性的地震来加深对地震相互作用的了解。由地震专家组成的国际团队将利用序列期间记录的高质量地震数据来开发新方法，以解决当前的障碍，这些障碍不仅阻碍了对地震过程的深入了解，而且还延迟了震后灾难环境中的科学响应。该项目开发的在几小时内探测、定位和表征最小震级事件的观测能力将直接适用于美国和世界各地的构造地震、诱发地震、地热地震和火山地震活动。这项研究的结果将有助于通过与美国地质调查局的现有合作伙伴关系，对下一次袭击美国的地震危机做出改进和科学的反应，并支持美国和欧洲地震研究人员之间的国际合作。这项研究通过分析高分辨率地震目录来研究复杂地震序列的物理原理，以测试日益复杂的地震预测模型。 为了实现这一目标，该项目将： 1) 使用最先进的技术为 2016-2017 年袭击意大利亚平宁山脉的毁灭性地震序列开发全面的高分辨率地震目录； 2）研究地震触发的物理原理以及该序列中大震级事件的演化； 3）开发并提供可测试的预测模型，支持未来地震序列的决策过程。该研究将利用部署在震中地区的超过 85 个高质量宽带传感器记录的无与伦比的地震数据集来分析序列中的每次地震如何影响地震活动在空间和时间上的演变。 该序列在这方面特别丰富，在2016年8月24日、2016年10月26-28日和2017年1月18日发生了空间交织的事件。大型和小型事件的地震图将使我们能够开发和测试新的基于全波形的事件检测、定位和表征算法，即使是最小震级的事件也将产生精确的源参数和断层机制。通过提高整个震级谱的震源参数质量，将有可能应用基于过程的地震成核和相互作用模型，包括断层复杂性、断层载荷、松弛、应力相互作用以及断层对应力扰动的敏感性的作用，以了解该序列的演化。改进的断层力学理解将有助于开发基于物理的创新预测模型。目前，描述短期聚类概率的实时地震预报主要基于统计/经验模型。然而，这些模型缺乏基础物理模型，因此如果不存在前兆地震活动，其可预测性有限。基于常规目录的物理预测和统计预测面临的共同挑战是所得概率的低概率和高不确定性。在这种情况下，决策和科学建议都受到严重阻碍。因此，使用2016-2017年意大利序列的新的最先进的地震目录来测试空间和时间上的物理、统计和混合（物理和统计）预测将有助于（a）测试序列中地震发生的物理模型，以及（b）提高预测的分辨率、准确性和技能。该项目的更广泛影响包括改进地震风险评估以及促进美国和欧洲地震学家之间的合作。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Rapid Earthquake Association and Location

• DOI: 10.1785/0220190052
• 发表时间: 2019-11
• 期刊: Seismological Research Letters
• 影响因子: 3.3
• 作者: Miao Zhang;W. Ellsworth;G. Beroza