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dc.contributorPaul Montagna
dc.contributorAlexey Sadovski
dc.creatorTurner, Evan L.
dc.date2015-04-17T18:41:53Z
dc.date2015-04-17T18:41:53Z
dc.date2014-12
dc.identifierhttp://hdl.handle.net/1969.6/598
dc.descriptionSubmitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY in COASTAL MARINE SYSTEM SCIENCE Texas A&M University-Corpus Christi, Corpus Christi, Texas
dc.descriptionThe declining health of estuary waters from nutrient pollution is a concern globally as human populations increase. The objective of this dissertation is to understand how nutrient inputs to estuary waters affect the estuary ecosystem. Field samplings (Chapter II), computational simulation code (Chapter III), and comprehensive model testing (Chapter IV) were used to accomplish the dissertation objectives. Inorganic nutrient concentrations were measured in Corpus Christi Bay, Texas for a continuous year to determine patterns of annual nutrient dynamics. Nutrient loading from runoff caused by precipitation affects estuary water quality along the shoreline. Corpus Christi Bay was found to have spatially dependent and seasonally driven nutrient dynamics. A robust computational programming toolkit was written to aid in the development and implementation of mathematical models. The toolkit, called EasyModel, contains a graphical utility to simulate a series of differential equations. The system is extendable for advanced users to calibrate mathematical models to ecological observation data. Five different models of nutrient dynamics were used to simulate nutrient dynamics of Copano Bay and San Antonio Bay, Texas. The complexity of the model equations was not related to how well measurements in the study area compared to simulated results. Including benthic components to the model design had the most positive affect on model performance. This research demonstrates that each estuary has a unique combination of biogeochemical characteristics that affect nutrient dynamics both spatially and temporally. Estuary responses to nutrient input were found to be non-linear, but predicable with the appropriate modeling techniques. Ensemble models can improve the accuracy of these predictions.
dc.descriptionPhysical and Environmental Sciences
dc.descriptionCollege of Science and Engineering
dc.languageen_US
dc.rightsThis material is made available for use in research, teaching, and private study, pursuant to U.S. Copyright law. The user assumes full responsibility for any use of the materials, including but not limited to, infringement of copyright and publication rights of reproduced materials. Any materials used should be fully credited with its source. All rights are reserved and retained regardless of current or future development or laws that may apply to fair use standards. Permission for publication of this material, in part or in full, must be secured with the author and/or publisher.
dc.subjectCoastal
dc.subjecteutrophication
dc.subjectlagoon
dc.subjectmodel
dc.subjectnpz
dc.subjectnutrients
dc.titleModeling Nutrient Dynamics in Coastal Lagoons
dc.typeText
dc.typeDissertation


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