Evaluating three fitting criteria for the calibration of the U.S. Geological Survey precipitation runoff modeling system (PRMS)
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azu_td_hy_e9791_1986_212_sip1_w.pdf
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azu_td_hy_e9791_1986_212_sip1_w.pdf
Author
Smith, Christopher,1956-Issue Date
1986Committee Chair
Sorooshian, Soroosh
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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 automatic calibration, a fitting criteria, which is some function of the difference between the observed and the model generated flows, is optimized to get the best parameter set. The purpose of this investigation was to calibrate the U. S. Geological Survey Precipitation Runoff Modeling System (PRMS) model using three different fitting criteria; ordinary least squares (OLS), Ln transformation of the discharges using the OLS on the transformed flows (LOG), and maximum likelihood estimator for the heteroscedastic errors (HMLE). The performance of each criteria in terms of their ability to produce reliable forecasts was examined. The results of the research showed that the winter storms were reproduced best by the parameter sets chosen by the OLS fitting criteria and the summer storms were reproduced best by the HMLE parameter sets. However, the performance in terms of percent bias in different flow groups suggests that HMLE estimator is superior.Type
Thesis-Reproduction (electronic)text
Degree Name
M.S.Degree Level
mastersDegree Program
Hydrology and Water ResourcesGraduate College