First Advisor

David C. Burnett

Term of Graduation

Summer 2025

Date of Publication

9-10-2025

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Language

English

Subjects

Acoustics, Bedload Transport, Frequency Analysis, Machine Learning, Signal Integrity, Underwater

Physical Description

1 online resource (ix, 78 pages)

Abstract

Bedload transport is defined as the amount of sediment, including gravel and rocks, traveling down stream. Monitoring bedload transport is important for river safety, hydrological studies and conservation efforts. Existing methods of directly measuring bedload transport (or bedload flux) involve lowering a collection device into a river and measuring the sediment collected; which can be expensive and time consuming. Hydroacoustic sensors, such as hydrophones, have had success tracking bedload flux remotely. This works by measuring the relatively high frequency of sediment impacts to map onto total bedload transported. No perfected method for detection of sediment generated noise (SGN) currently exists.

This study involves four investigations into over 700 GB of audio from hydrophones deployed in the North Santiam River. The first paper compares two hydrophones recording at different sampling rates. The second paper uses supervised machine learning to detect rainfall from the acoustic recordings. The third paper utilizes state of the art techniques in SGN detection to approximate the minimum sampling rate and bit depth necessary for accurate bedload estimation. The final paper develops a novel workflow utilizing audio suppression techniques and unsupervised machine learning to cluster potentially SGN related impulses before identifying them via secondary characteristics.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Persistent Identifier

https://archives.pdx.edu/ds/psu/44131

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