Physical Sciences and Mathematics Commons^™

Fluvial Processes In Motion: Measuring Bank Erosion And Suspended Sediment Flux Using Advanced Geomatic Methods And Machine Learning, Scott Douglas Hamshaw

Graduate College Dissertations and Theses

Excessive erosion and fine sediment delivery to river corridors and receiving waters degrade aquatic habitat, add to nutrient loading, and impact infrastructure. Understanding the sources and movement of sediment within watersheds is critical for assessing ecosystem health and developing management plans to protect natural and human systems. As our changing climate continues to cause shifts in hydrological regimes (e.g., increased precipitation and streamflow in the northeast U.S.), the development of tools to better understand sediment dynamics takes on even greater importance. In this research, advanced geomatics and machine learning are applied to improve the (1) monitoring of streambank erosion, (2) …

Smart Classifiers And Bayesian Inference For Evaluating River Sensitivity To Natural And Human Disturbances: A Data Science Approach, Kristen Underwood

Graduate College Dissertations and Theses

Excessive rates of channel adjustment and riverine sediment export represent societal challenges; impacts include: degraded water quality and ecological integrity, erosion hazards to infrastructure, and compromised public safety. The nonlinear nature of sediment erosion and deposition within a watershed and the variable patterns in riverine sediment export over a defined timeframe of interest are governed by many interrelated factors, including geology, climate and hydrology, vegetation, and land use. Human disturbances to the landscape and river networks have further altered these patterns of water and sediment routing.

An enhanced understanding of river sediment sources and dynamics is important for stakeholders, and …