Date of Award:

5-2013

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Civil and Environmental Engineering

Committee Chair(s)

David Stevens

Committee

David Stevens

Committee

Peter Wilcock

Committee

Mevin Hooten

Committee

Gilberto Urroz

Committee

David Mooney

Abstract

The science of fluvial sediment transport studies the processes involved in the movement of river sediments. It is commonly understood that when rivers flood they have a great capacity to move sand, gravel, and even larger cobbles and boulders. This process is not only limited to the big floods that usually attract so much attention, but also the more common river flows play a very important role in forming a river. As engineers and scientists, we like to be able to develop equations and relationships that describe some natural phenomenon—in this case, fluvial sediment transport. While we are able to generally characterize these processes using these equations it is not too difficult to understand why there is usually very high uncertainty surrounding the scientific description of this process. The focus of the research in this dissertation is to use the knowledge we have gained from the equations and relationships and try to marry those concepts with statistics so that we can not only generally describe the process of rocks moving in a river, but also have an idea of how certain we are of our predictions as well as the value of our equations. Naturally, we try to use our knowledge to make predictions of what could happen in rivers if they flood so that we can design facilities—recreational, commercial, and protective—to some level of risk tolerance. This research uses a statistical framework called Bayesian statistics that allows us to use the equations and relationships that focus on the approximate physics of sediment transport a in statistical framework to realize predictions with estimates of certainty (or uncertainty, as the case may be). The chapters that follow use simulated (fake) data as well as laboratory flume and data collected from the Snake River to develop an equation-based statistical sediment transport model. This model is tested and evaluated throughout the dissertation and it is concluded that this methodology shows great promise in solving the matter of measuring/estimating uncertainty in the processes of sediment movement in rivers and streams.

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