Collaborative Research: High-resolution receiver function imaging of crustal structure in the Southern Great Basin, Nevada

合作研究:内华达州南部大盆地地壳结构的高分辨率接收函数成像

基本信息

项目摘要

The western United States is continuously being deformed by plate tectonic forces. In this study area centered on the southern half of Nevada, the characteristic alternating ranges and valleys of Nevada were formed in the past by stretching of the Earth's crust, and more recently, the northwestward motion of the western US coastal regions relative to the core of the continent. Northwestward plate motion responsible for the San Andreas Fault is partly also accommodated by a fault system in the California/Nevada border area. At 15 to 30 km depth, lower crustal rocks are under high enough temperature and pressure to deform without brittle failure. How faulting and surface motions relate to lower crustal deformation is largely unknown. Our study will use seismic recordings from the University of Nevada, Reno Southern Great Basin Digital Seismic Network to study this process. This network detects signals from worldwide earthquakes after they are modified by the structure of the crust under the study area. By looking at the differences between earthquake signals arriving from different directions, the researchers can find signs of the deformation processes occuring in the lower crust. There are several ways in which the lower crust could behave during stretching and shearing of the crust. mong methods to estimate Moho depth and to detect and measure crustal anisotropy, receiver functions offer one of the best options. Using a data set collected by the University of Nevada, Reno's short-period, dense, long-running Southern Great Basin Digital Seismic Network, they performed a pilot study showing that high-quality receiver functions can be obtained from the data. The receiver functions show arrivals from the Moho as well as from crustal structure, and indicate the presence of anisotropy, scattering, and 3-dimensional structure. The project plan is to apply multichannel stacking techniques, including ones specific to anisotropy detection, a new bootstrap windowing technique for receiver function calculation, and numerical forward modeling in order to distinguish scattering from anisotropic conversions and to detect crustal structures associated with tectonic processes. Receiver functions will be calibrated against permanent and temporary broadband stations in the area, including a handful of broadband stations colocated with the short-period sensors in the same network. Crustal structure and anisotropy findings will be interpreted in the context of the tectonic history and development of southwest Nevada and eastern California in particular, and lower crustal deformation in general. Distinguishing which processes are operating in this study area may help other geoscientists who look at deforming continental crust understand similar activity in their field areas. Understanding crustal deformation, including what happens in the lower crust, is foundational for studies of faulting and earthquakes in the US and elsewhere.
美国西部在板块构造力的作用下不断变形。在以内华达州南半部为中心的研究区域,内华达特有的交替山脉和山谷是在过去由地壳的拉伸形成的,最近是美国西部沿海地区相对于大陆核心的西北运动形成的。导致圣安德烈亚斯断层的西北板块运动部分也被加利福尼亚/内华达边境地区的断层系统所容纳。在15到30千米深的地方,下地壳岩石在足够高的温度和压力下变形而不会发生脆性破坏。断裂和地表运动与下地壳变形之间的关系在很大程度上是未知的。我们的研究将使用内华达大学里诺南部大盆地数字地震台网的地震记录来研究这一过程。这个网络检测来自世界各地地震的信号,这些信号经过研究区域下地壳结构的修改。通过观察来自不同方向的地震信号之间的差异,研究人员可以找到下地壳发生变形过程的迹象。在地壳的拉伸和剪切过程中,下地壳可能表现出几种方式。在估计莫霍深度和探测和测量地壳各向异性的方法中,接收函数是最好的选择之一。利用内华达大学里诺分校的短周期、密集、长期运行的南部大盆地数字地震网络收集的数据集,他们进行了一项初步研究,表明可以从数据中获得高质量的接收函数。接收函数显示了来自莫霍和地壳结构的到达,并表明了各向异性、散射和三维结构的存在。该项目计划应用多通道叠加技术,包括各向异性探测技术、接收函数计算的新自提加窗技术和数值正演模拟,以区分散射和各向异性转换,并探测与构造过程相关的地壳结构。接收器的功能将根据该地区的永久和临时宽带站进行校准,包括在同一网络中与短周期传感器共存的少数宽带站。地壳结构和各向异性的发现将在内华达州西南部和加利福尼亚州东部的构造历史和发展的背景下进行解释,特别是在地壳下部变形的背景下。区分哪些过程在这个研究区域起作用,可能有助于其他研究大陆地壳变形的地球科学家了解他们研究区域的类似活动。了解地壳变形,包括下地壳发生了什么,是研究美国和其他地方的断层和地震的基础。

项目成果

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Glenn Biasi其他文献

Panel Review of the USGS 2023 Conterminous U.S. Time-Independent Earthquake Rupture Forecast
美国地质调查局 2023 年美国连续地震破裂预报小组审查
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Thomas H. Jordan;Norman Abrahamson;John G. Anderson;Glenn Biasi;Ken Campbell;Tim Dawson;H. DeShon;Matthew C. Gerstenberger;Nick Gregor;Keith Kelson;Yajie Lee;N. Luco;W. Marzocchi;B. Rowshandel;David Schwartz;Nilesh Shome;Gabriel Toro;Ray J. Weldon;Ivan Wong
  • 通讯作者:
    Ivan Wong

Glenn Biasi的其他文献

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