Calibration of the soil moisture accounting model using a gradient-type algorithm and analytic derivatives
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azu_td_hy_e9791_1987_207_sip1_w.pdf
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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
In the pest, derivative-based optimization algorithms have not frequently been used to calibrate conceptual rainfall-runoff (CRR) models, partially due to difficulties associated with obtaining the required derivatives. This research applies a recently-developed technique of analytically computing derivatives of a CRR model to a complex, widely-used CRR model. The resulting least squares response surface was found to contain numerous discontinuities in the surface and derivatives. However, the surface and its derivatives were found to be everywhere finite, permitting the use of derivative-based optimization algorithms. Finite difference numeric derivatives were computed and found to be virtually identical to analytic derivatives. A comparison was made between gradient (Newton-Raphson) and direct (pattern search) optimization algorithms. The pattern search algorithm was found to be more robust. The lower robustness of the Newton-Raphson algorithm was thought to be due to discontinuities and a rough texture of the response surface.Type
Thesis-Reproduction (electronic)text
Degree Name
M.S.Degree Level
mastersDegree Program
Hydrology and Water ResourcesGraduate College