Controls on ground surface deformation in thrust and reverse fault earthquakes

大地震中的地表破裂对美国和世界其他地区的城市环境、关键信息和能源传输基础设施、交通系统以及其他敏感设施构成重大危害。这项研究将对控制逆冲断层和反向断层地震期间地表破裂的类型、分布和强度的因素有一个强有力的物理理解。这将为更好地预测未来地震期间地表变形的模式提供基础，以帮助减少生命和财产损失。这项研究还将支持本科生和研究生的培训，研究成果将被纳入新的大学课程、K-12教育计划以及通过哈佛大学自然历史博物馆进行的公众推广。研究将使用离散单元法(DEM)生成一套大型二维模型(约6000个)，以确定各种属性(如断层倾角、沉积物强度、沉积物厚度)在控制地表变形模式中的作用。此外，这项研究将开发三维模型，解决沿走向的地表变形模式的内在变异性。DEM方法非常适合于这一目的，因为它有效地再现了深部断裂和褶皱的地质过程，以及浅层土壤和沉积物变形的颗粒力学。数字高程模型能够发展新的特征，如断裂/裂隙、次级断层、弯曲滑动面和褶皱，这些特征构成了大地震期间的地表变形模式。通过系统地改变模型中的断层和沉积物参数，研究人员将发展一种基于力学的对地表破裂模式控制的理解，这有助于评估特定地点的危险。通过大量的模型，他们将对地表变形的模式进行统计评估，以告知和改进概率断层位移危险分析(PFDHA)方法。PFDHA被确立为与地表破裂相关的危险预测的标准，但由于这些破裂的复杂性和可用于校准的历史事件的缺乏，逆冲和逆断层地震尤其对其构成挑战。他们的结果将提供一个强大的数据库，以评估在直接断层位移和分布的地表变形中，深部滑动是如何明显的。这将有助于校准用于预测破裂位置、位移和其他对关键基础设施构成风险的特征的PFDHA方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Ground surface rupture during large earthquakes poses significant hazards to urban environments, critical information and energy transmission infrastructure, transportation systems, as well as other sensitive facilities in the United States and other parts of the world. This research will develop a robust physical understanding of the factors that control the style, distribution, and intensity of ground surface ruptures during thrust and reverse faults earthquakes. This will provide a basis for better forecasting the patterns of ground surface deformation during future earthquakes, with the goal of helping to reduce the loss of life and property. The research will also support the training of undergraduate and graduate students, and research results will be incorporated in new college classes, K-12 education programs, and public outreach through the Harvard Museum of Natural History.The study will employ the discrete element method (DEM) to generate a large suite of 2-dimensional models (~6,000) that will identify the role of various properties (e.g., fault dip, sediment strength, sediment thickness) in controlling the patterns of ground surface deformation. In addition, the study will develop 3-dimensional models that address inherent variability in surface deformation patterns along strike. The DEM method is well suited to this purpose as it effectively reproduces both the geologic processes of faulting and folding at depth, as well as the granular mechanics of soil and sediment deformation in the shallow subsurface. DEM enables the development of emergent features, such as fractures/fissures, secondary faults, flexural slip surfaces, and folds that comprise ground surface deformation patterns during large earthquakes. By systematically varying fault and sediment parameters in their models, the researchers will develop a mechanics-based understanding of controls on ground surface rupture patterns that can help to assess site-specific hazards. Through large suites of models, they will statistically assess the patterns of ground surface deformation to inform and enhance Probabilistic Fault Displacement Hazard Analysis (PFDHA) methods. PFDHA is established as the standard for hazard forecasting related to ground surface rupture, but is particularly challenged by thrust and reverse fault earthquakes due to the complexity of these ruptures and the paucity of historic events to use for calibration. Their results will provide a robust database to assess how slip at depth is manifest in both direct fault displacements and distributed ground surface deformation. This will help to calibrate PFDHA methods used in forecasting rupture locations, displacements, and other characteristics that pose risks to critical infrastructure.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.