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: 1759782
• 负责人: Felix Waldhauser
• 金额: $ 16.67万
• 依托单位: Columbia 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=1759782&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月之间，一系列强大的地震震撼了意大利中部的亚平宁山脉，造成了生命丧失，并对历史悠久的阿马特里斯（Amatrice），累加艾科利（Accumoli）和诺西亚（Norcia）造成了巨大的破坏。随着响应和恢复操作的进行，该序列在五个月内产生了六次强烈地震。 这种快速发展的地震危机强调了紧迫的需求，以更好地了解地震序列的发展方式。该联合项目的目标是由美国国家科学基金会和英国国家环境研究委员会资助，与意大利的Istituto Nazionale di Geofisica e Volcanologia协调，将通过研究这些破坏性的地震来加深对地震互动的了解。国际地震专家团队将使用序列中记录的高质量地震数据来开发新方法，这些方法可以解决当前的障碍，不仅会阻碍对地震过程的深刻理解，而且还会延迟地球后灾难环境中的科学反应。在该项目中开发的几个小时内检测，定位和表征最小的事件的观察能力将直接适用于美国和世界各地的构造，诱导，地热和火山地震性。这项研究的结果将能够改善对下一次地震危机的反应，通过与美国和欧洲地震研究人员之间的国际合作进行现有伙伴关系，以触动美国。这项研究研究了复杂地震序列的物理学，通过分析高分辨率地震序列分析高分辨率地震序列，以测试越来越多的地震序列化的地震序列化的模型。 为了实现这一目标，该项目将：1）使用最先进的技术为毁灭性地震序列开发全面的高分辨率地震目录，该地震序列在2016 - 2017年袭击了意大利亚平宁山脉； 2）研究地震触发的物理学和该序列中大型事件的演变； 3）开发和提供可测试的预测模型，以支持未来地震序列的决策过程。该研究将使用在地下中央区域中部署的85多个高质量宽带传感器记录的无与伦比的地震数据集，以分析序列中的每个地震如何有助于时空中地震性的演变。 这个序列在这方面尤其丰富，在2016年8月24日，2016年8月24日，2016年10月26日至28日和2017年1月18日，大型和小型事件的地震图将使我们能够开发和测试基于全波形的新算法，以使事件检测，位置检测，将产生精确的源参数机械的机构，甚至可以为您带来的事件，甚至会产生多种事件，甚至将使我们开发和测试新的全波形算法。通过提高幅度光谱中的地震源参数的质量，可以应用基于过程的地震成核和相互作用的基于过程的模型，包括断层复杂性，断层负载，放松，压力相互作用，压力相互作用以及压力扰动的作用，以了解该序列的演变。改进的故障机械理解将有助于开发基于创新的物理预测模型。当前，描述短期聚类概率的实时地震预测主要基于统计/经验模型。但是，这些模型缺乏潜在的物理模型，因此，如果不存在前保质性地震性，则具有有限的可预测性。基于常规目录的基于物理和统计预测的共同挑战是所得概率的低概率和高确定性。在这些条件下，决策和科学建议都受到严重阻碍。因此，使用2016 - 2017年意大利序列的这种新的最先进的地震目录来测试时空中的物理，统计和混合动力和混合（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）改善预测的分辨率，准确性和技巧。该项目的更广泛影响包括改善地震风险评估，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的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估来审查标准的评估。

项目成果

High-precision Aftershock Locations and Fault Planes of the 2016-2017 Central Italy Sequence

2016-2017年意大利中部序列高精度余震位置和断层面

• DOI: 10.5281/zenodo.5091137
• 发表时间: 2021
• 期刊: Zenodo
• 作者: Waldhauser, Felix;Michele, Maddalena;Chiaraluce, Lauro;Stefano, Raffaele Di;Schaff, David
• 通讯作者: Schaff, David

Machine-Learning-Based High-Resolution Earthquake Catalog For the 2016-2017 Central Italy Sequence

2016-2017 年意大利中部序列基于机器学习的高分辨率地震目录

• DOI: 10.5281/zenodo.4662870
• 发表时间: 2021
• 期刊: Zenodo
• 作者: Tan, Yen Joe;Waldhauser, Felix;Ellsworth, William
• 通讯作者: Ellsworth, William

Fault Planes, Fault Zone Structure and Detachment Fragmentation Resolved With High‐Precision Aftershock Locations of the 2016–2017 Central Italy Sequence

2016-2017年意大利中部序列高精度余震位置解决断层面、断层带结构和拆离破碎问题

• DOI: 10.1029/2021gl092918
• 发表时间: 2021
• 期刊: Geophysical Research Letters
• 影响因子: 5.2
• 作者: Waldhauser, Felix;Michele, Maddalena;Chiaraluce, Lauro;Di Stefano, Raffaele;Schaff, David P.
• 通讯作者: Schaff, David P.