Increasing pressure to meet the food, water, and energy demands of our growing society in a changing climate has strained the physical, chemical, and biological functioning of watersheds to maintain ecosystem services, such as providing clean water, and to sustain a productive and diverse ecosystem. Confronted with multifaceted environmental issues, watershed managers could use a simple first-order approach for understanding how physical, chemical, and biological processes operate within a watershed to guide watershed-management decisions. This research advances a network-based modeling framework for guiding effective landscape management decisions towards sustainability focusing on understanding large-scale system functioning and predicting the emergence of vulnerabilities, “hotspots” of change, and unexpected system behavior. Based on a combination of mathematical theory, field-data analysis, and numerical simulations applied to the dynamics of bed-material sediment (i.e., the sediment composing the riverbed) on river networks, we (1) identify a resonant frequency of sediment supply from network topology and sediment-transport dynamics that could lead to an unexpected downstream amplification of sedimentological response in the Minnesota River Basin; (2) identify hotspots of likely sediment-driven fluvial geomorphic change where sediment has a tendency to persist and exacerbate channel migration on the Greater Blue Earth River Network; and (3) elucidate the hierarchical role of river-network structure on bed-material sediment dynamics in propagating, altering, and amalgamating the emergent large temporal fluctuations and periodicities of bed-sediment thickness. By embedding small-scale bed-material sediment dynamics on a river network, this research shows that it is possible to gain a better understanding of the large-scale system functioning whereby management actions that target the identified critical times, places, and processes in the landscape will be most effective at improving water quality and the health of the aquatic ecosystem.
University of Minnesota Ph.D. dissertation. May 2016. Major: Civil Engineering. Advisor: Efi Foufoula-Georgiou. 1 computer file (PDF); xvii, 150 pages.
A Network-Based Framework for Hydro-Geomorphic Modeling and Decision Support with Application to Space-Time Sediment Dynamics, Identifying Vulnerabilities, and Hotspots of Change.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital Conservancy may be subject to additional license and use restrictions applied by the depositor.