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Description
Fluctuating flow releases on regulated rivers destabilize downstream riverbanks, causing unintended, unnatural, and uncontrolled geomorphologic changes. These flow releases, usually a result of upstream hydroelectric dam operations, create manmade tidal effects that cause significant environmental damage; harm fish, vegetation, mammal, and avian habitats; and destroy riverbank camping and boating areas. This work focuses on rivers regulated by hydroelectric dams and have banks formed by sediment processes. For these systems, bank failures can be reduced, but not eliminated, by modifying flow release schedules. Unfortunately, comprehensive mitigation can only be accomplished with expensive rebuilding floods which release trapped sediment back into the river. The contribution of this research is to optimize weekly hydroelectric dam releases to minimize the cost of annually mitigating downstream bank failures. Physical process modeling of dynamic seepage effects is achieved through a new analytical unsaturated porewater response model that allows arbitrary periodic stage loading by Fourier series. This model is incorporated into a derived bank failure risk model that utilizes stochastic parameters identified through a meta-analysis of more than 150 documented slope failures. The risk model is then expanded to the river reach level by a Monte Carlos simulation and nonlinear regression of measured attenuation effects. Finally, the comprehensive risk model is subjected to a simulated annealing (SA) optimization scheme that accounts for physical, environmental, mechanical, operations, and flow constraints. The complete risk model is used to optimize the weekly flow release schedule of the Glen Canyon Dam, which regulates flow in the Colorado River within the Grand Canyon. A solution was obtained that reduces downstream failure risk, allows annual rebuilding floods, and predicts a hydroelectric revenue increase of more than 2%.
ContributorsTravis, Quentin Brent (Author) / Mays, Larry (Thesis advisor) / Schmeeckle, Mark (Committee member) / Houston, Sandra (Committee member) / Arizona State University (Publisher)
Created2010
Description
This dissertation presents a new methodology for the sustainable and optimal allocation of water for a river basin management area that maximizes sustainable net economic benefit over the long-term planning horizon. The model distinguishes between short and long-term planning horizons and goals using a short-term modeling component (STM) and a long term modeling component (LTM) respectively. An STM optimizes a monthly allocation schedule on an annual basis in terms of maximum net economic benefit. A cost of depletion based upon Hotelling’s exhaustible resource theory is included in the STM net benefit calculation to address the non-use value of groundwater. An LTM consists of an STM for every year of the long-term planning horizon. Net economic benefits for both use and non-use values are generated by the series of STMs. In addition output from the STMs is measured in terms of sustainability which is quantified using a sustainability index (SI) with two groups of performance criteria. The first group measures risk to supply and is based on demand-supply deficits. The second group measures deviations from a target flow regime and uses a modified Hydrologic Alteration (HA) factor in the Range of Variability Approach (RVA). The STM is a linear programming (LP) model formulated in the General Algebraic Modeling System (GAMS) and the LTM is a nonlinear programming problem (NLP) solved using a genetic algorithm. The model is applied to the Prescott Active Management Area in north-central Arizona. Results suggest that the maximum sustainable net benefit is realized with a residential population and consumption rate increase in some areas, and a reduction in others.
ContributorsOxley, Robert Louis (Author) / Mays, Larry (Thesis advisor) / Fox, Peter (Committee member) / Johnson, Paul (Committee member) / Murray, Alan (Committee member) / Arizona State University (Publisher)
Created2015