Electronic Theses and Dissertations

Date of Award


Document Type


Degree Name

M.S. in Engineering Science


Mechanical Engineering

First Advisor

Cristiane Q. Surbeck

Second Advisor

Daniel Wren

Third Advisor

Erik Hurlen

Relational Format



There has long been an interest in monitoring the movement of large particle sediments traveling through fast-moving streams and rivers. However, there have been numerous challenges concerning the methodology best suited to collect these data. Many studies have been done to alleviate this problem, both through physical and surrogate methods. Physical methods include bed load traps that provide data over a specific time frame, but the fluctuation of sediment can change drastically over hours; thus, bed load traps are unable to provide a reliable predictive model. Since studies have shown a relationship between acoustic energy and particle impacts, the field of acoustics has shown potential in providing real-time measurements. These systems employ acoustic sensors such as geophones, sonar, and hydrophones. The research presented here utilizes a passive hydrophone system developed for field deployment. Laboratory testing of the system, utilizing tosets of rocks, was used to compare acoustic energy to known transport rates and provided a basis for acoustic data processing. A robust field-ready unit was produced to evaluate the capability hydrophones in real world monitoring of bed load transport. The unit was tested in conjunction with bed load traps to evaluate a relationship between surrogate and physical methods. Tests were conducted on Halfmoon Creek located near Leadville, Colorado. This thesis will center on the background leading to field deployment as well as extensive testing of the passive acoustic system, initial results from data collected, and comparison to physical measurements made alongside the unit. Data collected from field evaluations was processed through a MATLAB® program to produce a root mean square (RMS) average of the acoustic intensity. RMS data was compared with bed load flux collected by physical samplers and flow discharge provided by a U.S. Geological Survey (USGS) gauging station. Results show that RMS and physical sediment data from this field test are not related due to the presence of flow noise. A more clear relationship was found between RMS and flow discharge. Observation of this indicates that flow noise is a major factor in passive listening for sediment monitoring and additional work should be focused on optimizing data filtering and low-noise installation

Included in

Engineering Commons



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