EAR-PF: Towards a robust understanding of the spatio-temporal evolution of foreshock sequences from the laboratory to the field

本奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。David C. Bolton被授予NSF EAR博士后奖学金，研究地震前震序列在时间和空间上的演变，通过自然和实验室断层带进行探索。估计未来地震的时间和地点一直是地震学研究的一个长期目标。然而，由于对地震起源和地震活动之间的联系了解不足，这一领域的进展一直缓慢。前震是发生在主震之前的小地震，被认为是断层接近破裂的间接证据。然而，前震并不是所有地震的一个容易观察到的特征，而且它们与即将发生的地震之间的联系也不是很清楚。这项工作将整合前震的实验室和实地观测，目的是提供对前震序列演化的连贯理解。一个重要的焦点将致力于研究前震性质是否编码了主震大小的信息。这项工作将为地震的准备阶段提供关键的见解，并将有助于推进地震预警系统和改进地震危害评估。该项目还将与德克萨斯大学奥斯汀分校杰克逊地球科学学院领导的GeoFORCE外展项目合作，为德克萨斯州西南部代表性不足的社区提供研究机会。该项目将实施新的机器学习和地震地震学技术，用于开发富含小震级事件的高保真地震目录。这些高分辨率的目录将阐明前震是如何相互作用的，它们在空间和时间上的演变，以及它们与主震的联系。该项目将利用带有声发射监测仪器的实验室实验来阐明驱动前震序列的致病过程。断层带的性质，如应力、滑动位移、应变，将与声发射的时空模式相结合，从而详细了解地震成核过程的物理特性与地震活动之间的联系。该项目的第二个关键要素将涉及通过探测和定位意大利亚平宁断层系统上特征明确且地震活跃的前震，将实验室观测扩大到与地质相关的条件。这个多尺度、综合的研究计划为从实验室到构造尺度研究地震过程提供了一个独特的机会，并将确定实验室前震的特征是否可以扩大到构造断裂带。这项工作对地震灾害分析具有重要意义，有助于提高我们对地震过程进行准确灾害预报和科学预测的能力。该奖项反映了美国国家科学基金会的法定使命，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。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).Dr. David C. Bolton has been awarded an NSF EAR Postdoctoral Fellowship to investigate the evolution of earthquake foreshock sequences in time and space, explored through natural and laboratory fault zones. Estimating the timing and location of future earthquakes has been a long-standing goal in the study of seismology. However, progress in this area has been slow due to a poor understanding of the connections between the origins of earthquakes and seismic activity. Foreshocks are small earthquakes that precede the main earthquake and are thought to be indirect evidence that a fault is close to failure. However, foreshocks are not an easily observed feature of all earthquakes, and their connection to the impending earthquake is not well understood. This work will integrate laboratory and field-based observations of foreshocks with an aim to provide a coherent understanding of the evolution of foreshock sequences. A significant focus will be devoted to investigating whether foreshock properties encode information about the mainshock size. This work will provide key insights into the preparatory phase of earthquakes and will help advance earthquake early warning systems and improve earthquake hazard assessment. The project will also join forces with the GeoFORCE outreach program led by the Jackson School of Geosciences at UT-Austin to provide research opportunities to underrepresented communities in southwest Texas. This project will implement novel machine learning and earthquake seismology techniques for developing high-fidelity earthquake catalogs that are rich in small magnitude events. These high-resolution catalogs will illuminate how foreshocks interact with each other, their evolution in space and time, and their connection to the mainshock. The project will utilize laboratory experiments instrumented with acoustic emission monitoring to shed light on the causative processes that drive foreshock sequences. Fault zone properties such as stress, slip displacement, strain, will be integrated with the spatio-temporal patterns of acoustic emissions, allowing for a detailed understanding of the connection between the physics of earthquake nucleation processes and seismic activity. A second key element of the project will involve scaling up the laboratory observations to geologically relevant conditions by detecting and locating foreshocks on the well-characterized and seismically active Apennine fault system in Italy. This multi-scale, integrated research plan represents a unique opportunity to study seismic processes from the laboratory to tectonic scale and will determine if characteristics of laboratory foreshocks can be scaled up to tectonic fault zones. The proposed work has important implications for seismic hazard analysis and could help improve our ability to make accurate hazard forecasts and scientific predictions about earthquake processes.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.