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Full-Text Articles in Physical Sciences and Mathematics
Smart Classifiers And Bayesian Inference For Evaluating River Sensitivity To Natural And Human Disturbances: A Data Science Approach, Kristen Underwood
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 …