This dissertation consists of four chapters that are broadly related through the use of geophysical methods to investigate Earth processes.
In Chapter 1, an along-strike seismic reflection/refraction data set is used to investigate the plate boundary beneath the forearc offshore Costa Rica. The convergent margin offshore Costa Rica is representative of the 19,000 km of subduction zones that are considered to be erosive, or that experience a net mass loss over time. At these margins, sediments along with material that is tectonically eroded from the overlying plate are presumably carried down the subduction zones and recycled into the mantle. In addition to the mass that they represent, sediments, eroded upper-plate material, and subducted oceanic crust carry fluids into the subduction zone, which influence both magma generating processes and the chemical composition of arc lavas. Thus, understanding the ultimate fate of subducted material along these margins is critical for evaluating both the chemical and mass balances. Beneath the forearc offshore Costa Rica, we observe an ∼40 km long, 1-to-3 km-thick lens of material sitting directly above the subducting Cocos plate. Directly above this lens, the forearc shows evidence for long-term uplift consistent with the steady growth of this lens. Our results suggest that the convergent margin at Costa Rica experience simultaneous outer-forearc erosion and underplating beneath the inner forearc.
In Chapter 2, a combination of three-dimensional stress modeling and landscape scale geophysical imaging is used to test the hypothesis that topographic perturbations to regional stress fields control lateral variations in bedrock permeability. The permeability of bedrock fractures influences groundwater flow, water and nutrient availability for biota, chemical weathering rates, and the long-term evolution of life-sustaining layer at Earth’s surface commonly referred to as the “critical zone” (CZ). The results of this study indicate that to a first order, the permeability structure of the CZ can be predicted with knowledge of the regional tectonic stress field and local topography. In landscapes characterized by strongly compressive tectonic stresses or closely space ridges and valleys, deep zones of permeable bedrock are found beneath ridges, while the depth to impermeable bedrock beneath drainages is comparatively shallow. In landscapes characterized by weakly compressive tectonic stresses or widely spaced ridges and valleys, the depth to impermeable bedrock is approximately uniform throughout the landscape.
In Chapter 3, a semi-automated method of estimating snow water equivalent (SWE) in seasonal snow packs from common offset Ground Penetrating Radar (GPR) data is presented. Many mountainous regions of the world depend on seasonal snow for fresh water resources. Water forecasting relies principally on historical records that relate SWE observations at a limited number of locations to stream discharge. As climate change contributes to a wider range of variability in seasonal snow fall, water forecasts are likely to become less reliable, thus there is a need to find new methods of estimating how much water is stored in seasonal snow. GPR has been shown to be an effective tool for measuring SWE if the radar velocity can be measured. In this chapter, a method that was originally developed to measure seismic velocities from zero-offset seismic reflection data is applied to common-offset GPR data collected over seasonal snow. The method involves suppressing continuous reflections in the image so that the velocity information contained in diffracted energy can be exploited. The filtered images are migrated through a suite of velocities and the velocity that best focus the diffracted energy is chosen on the basis of the varimax norm, which measures how peaked the energy distribution is. GPR derived SWE estimates agree with manual measurements within the uncertainty bounds of both methods.
In Chapter 4, a travel-time tomography code written in Matlab is presented. Rays are traced using the shortest path algorithm, smoothness constraints are implemented with first and second order derivative operators, and the inversion is carried out with built in Matlab functions. The primary strength of this code lies is the ability to automate monte-carlo uncertainty analyses in which a data set is inverted many times with different starting models. The code is tested with a synthetic data set.
|Advisor:||Holbrook, W. Steven|
|Commitee:||Dueker, Ken, Kelleners, Thjis, Riebe, Clifford S., Zhang, Ye|
|School:||University of Wyoming|
|Department:||Geology & Geophysics|
|School Location:||United States -- Wyoming|
|Source:||DAI-B 77/06(E), Dissertation Abstracts International|
|Keywords:||Ground-penetrating radar, Middle American Trench, Snow, Subduction, Tomography, Weathering|
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