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    CALIBRATION AND VALIDATION OF AQUIFER MODELS

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    HWR-1973-017.pdf
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    Author
    Sagar, Budhi,1943-
    Affiliation
    Department of Hydrology & Water Resources, The University of Arizona
    Issue Date
    1973-06
    Keywords
    Groundwater -- Mathematical models.
    
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    Publisher
    Department of Hydrology and Water Resources, University of Arizona (Tucson, AZ)
    Rights
    Copyright © Arizona Board of Regents
    Collection Information
    This title from the Hydrology & Water Resources Technical Reports collection is made available by the Department of Hydrology & Atmospheric Sciences and the University Libraries, University of Arizona. If you have questions about titles in this collection, please contact repository@u.library.arizona.edu.
    Abstract
    The main aim of this study is to develop a suitable method for the calibration and validation of mathematical models of large and complex aquifer systems. Since the calibration procedure depends on the nature of the model to be calibrated and since many kinds of models are used for groundwater, the question of model choice is broached first. Various aquifer models are critically reviewed and a table to compare them as to their capabilities and limitations is set up. The need for a general calibration method for models in which the flow is represented by partial differential equations is identified from this table. The calibration problem is formulated in the general mathematical framework as the inverse problem. Five types of inverse problems that exist in modeling aquifers by partial differential equations are identified. These are, to determine (1) parameters, (2) initial conditions, (3) boundary conditions, (4) inputs, and (5) a mixture of the above. Various methods to solve these inverse problems are reviewed, including those from fields other than hydrology. A new direct method to solve the inverse problem (DIMSIP) is then developed. Basically, this method consists of transforming the partial differential equations of flow to algebraic equations by substituting in them the values of the various derivatives of the dependent variable (which may be hydraulic pressure, chemical concentration or temperature). The parameters are then obtained by formulating the problem in a nonlinear optimization framework. The method of sequential unconstrained minimization is used. Spline functions are used to evaluate the derivatives of the dependent variable. Splines are functions defined by piecewise polynomial arcs in such a way that derivatives up to and including the order one less than the degree of polynomials used are continuous everywhere. The natural cubic splines used in this study have the additional property of minimum curvature which is analogous to minimum energy surface. These and the derivative preserving properties of splines make them an excellent tool for approximating the dependent variable surfaces in groundwater flow problems. Applications of the method to both a test situation as well as to real -world data are given. It is shown that the method evaluates the parameters, boundary conditions and inputs; that is, solves inverse problem type V. General conditions of heterogeneity and anisotropy can be evaluated. However, the method is not applicable to steady flows and has the limitation that flow models in which the parameters are functions of the dependent variable cannot be calibrated. In addition, at least one of the parameters has to be preassigned a value. A discussion of uncertainties in calibration procedures is given. The related problems of model validation and sampling of aquifers are also discussed.
    Series/Report no.
    Technical Reports on Hydrology and Water Resources, No. 17
    Sponsors
    This study was supported primarily by funds from the Title II research grant on model choice questions in hydrology and water resources from the Office of Water Resources Research of the U.S. Department of the Interior, and partially (1) by funds from a contract with the City of Tucson for digital modeling of the hydraulic and chemical processes in the Tucson aquifer, and (2) by funds from a research grant on space -time sampling and the equations of hydrology from the U.S. National Science Foundation.
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