Transient Ground Deformation in Tectonically Active Regions and Implications for the Mechanical Behavior of the Crust and Upper Mantle

Geophysics;Geodesy;Transient deformation;Geology and Earth Sciences;Science;Earth and Environmental Sciences

Hines, TreverRitsema, Jeroen ;

University of Michigan

关键词: Geophysics;    Geodesy;    Transient deformation;    Geology and Earth Sciences;    Science;    Earth and Environmental Sciences;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/140888/hinest_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Modern-day geodetic tools, such as global navigation satellite systems (GNSS), detect tectonic ground deformation to within millimeter accuracy. In the past decade, our ability to resolve ground deformation in the Western United States has greatly improved with the Plate Boundary Observatory (PBO) project, which consists of about 1100 continuously operating GNSS stations. With this unprecedented quality and quantity of data, we can observe the subtle signal from transient tectonic processes. For example, we can detect ground deformation in the days to years following large earthquakes, which is caused by aseismic afterslip and/or ductile deformation in the upper mantle. The PBO has also allowed us to resolve transient deformation associated with slow slip events on the Cascadia subduction zone. In this dissertation, I discuss techniques for detecting transient deformation in geodetic data, and I analyze this transient deformation to better understand the mechanical behavior of the crust and upper mantle.Most studies of ground deformation throughout the earthquake cycle (i.e., interseismic deformation) indicate that the lower crust is orders of magnitude stronger (more viscous) than the upper mantle. In Chapter 2, I demonstrate that the methods used in these studies are biased towards inferring a more viscous lower crust and less viscous upper mantle. I conclude that these interseismic studies do not necessarily rule out the possibility that the lower crust can deform ductilely on earthquake cycle timescales. In Chapters 3 and 4, I introduce a method for discerning the physical mechanisms driving postseismic deformation, where I consider candidate mechanisms to be afterslip and viscous relaxation in the crust and upper mantle. I apply this method to postseismic deformation following the 2010 El Mayor-Cucapah earthquake in Baja California. I find that a Burgers rheology upper mantle is necessary to describe far-field deformation in the three years following the earthquake. In general, upper mantle viscosities inferred from interseismic deformation are larger than those estimated from postseismic deformation, which occurs over a much shorter timescale. By describing the upper mantle with a Burgers rheology, which contains a transient and steady-state phase of deformation, I am able to reconcile these conflicting studies. Chapters 5, 6, and 7 are on detecting transient geophysical signal in geodetic data. Before geophysical signal can be identified, the noise in geodetic data must be quantified. In Chapter 5, I point out a bias in the commonly used method for characterizing noise in geodetic data, and I propose an alternative unbiased method. In Chapter 6, I demonstrate that transient geophysical signal can be robustly detected by using a machine learning technique known as Gaussian process regression. Finally, in Chapter 7 I assess the utility of borehole strain meters (BSMs) for detecting transient deformation. I find that BSM data, which records strains over an 8.7 centimeter baseline, are difficult to reconcile with regional strains derived from GNSS data.