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    Model Structure Estimation and Correction Through Data Assimilation

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    Author
    Bulygina, Nataliya
    Issue Date
    2007
    Keywords
    Bayesian estimation of model structure
    Advisor
    Gupta, Hoshin V
    Committee Chair
    Gupta, Hoshin V
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    The main philosophy underlying this research is that a model should constitute a representation of both what we know and what we do not know about the structure and behavior of a system. In other words it should summarize, as far as possible, both our degree of certainty and degree of uncertainty, so that it facilitates statements about prediction uncertainty arising from model structural uncertainty. Based on this philosophy, the following issues were explored in the dissertation: Identification of a hydrologic system model based on assumption about perceptual and conceptual models structure only, without strong additional assumptions about its mathematical structure Development of a novel data assimilation method for extraction of mathematical relationships between modeled variables using a Bayesian probabilistic framework as an alternative to up-scaling of governing equations Evaluation of the uncertainty in predicted system response arising from three uncertainty types: o uncertainty caused by initial conditions, o uncertainty caused by inputs, o uncertainty caused by mathematical structure Merging of theory and data to identify a system as an alternative to parameter calibration and state-updating approaches Possibility of correcting existing models and including descriptions of uncertainty about their mapping relationships using the proposed method Investigation of a simple hydrological conceptual mass balance model with two-dimensional input, one-dimensional state and two-dimensional output at watershed scale and different temporal scales using the method
    Type
    text
    Electronic Dissertation
    Degree Name
    PhD
    Degree Level
    doctoral
    Degree Program
    Hydrology
    Graduate College
    Degree Grantor
    University of Arizona
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