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Dissertation/Thesis Abstract

Deciphering the seismic signal of sediment transport in rivers
by Roth, Danica L., Ph.D., University of California, Santa Cruz, 2016, 149; 10140264
Abstract (Summary)

Bedload sediment transport is at once one of the most important and challenging quantities to measure or predict in geomorphology. As the primary mechanism controlling river erosion and morphology, sediment transport impacts a wide range of interdsciplinary topics. However, because transport is a nonlinear and stochastic process that tends to occur mainly during large floods, it is difficult to model through laboratory experiments or measure in situ. Recent work has pointed to the potential for using seismometers to monitor sediment transport in natural river settings. Here we present three studies that highlight the strengths and weaknesses of this technique and develop our ability to use seismometers as a tools for understanding sediment transport. In our first two studies we use independent constraints to examine the previously held assumption that hysteresis in seismic signals is generated by hysteresis in sediment transport rates. In Chapter 2, we confirm that—in some settings—seismic hysteresis does correlate with and can even be used to qualitatively track spatiotemporal changes in sediment transport. Conversely, in Chapter 3 we find that seismic hysteresis can also be anticorrelated with sediment transport in other settings, and can instead be generated by hysteresis in water turbulence caused by changes in the river bed. These results bespeak the difficulty in deconvolving the signal of sediment transport from the changes that sediment transport imparts to the bed: a major challenge to the quantitative interpretation of seismic hysteresis. In Chapter 4, however, we show that with enough independent constraints, we can avoid relying on seismic hysteresis and instead estimate sediment transport rates directly from seismic spectra. Collectively, these studies demonstrate the power of seismology as a tool for bedload analysis, and prove that we can successfully decode seismic signals to learn about sediment transport.

Indexing (document details)
Advisor: Finnegan, Noah J., Brodsky, Emily E.
Commitee: Sklar, Leonard S.
School: University of California, Santa Cruz
Department: Earth Science
School Location: United States -- California
Source: DAI-B 77/11(E), Dissertation Abstracts International
Subjects: Geophysics, Geotechnology, Geomorphology
Keywords: Bedload, Dam removal, Fluvial seismology, Hysteresis, Sediment transport, Seismology
Publication Number: 10140264
ISBN: 978-1-339-95683-1
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