Calibration of the soil moisture accounting model using the adaptive random search algorithm

Persistent Link:
http://hdl.handle.net/10150/192059
Title:
Calibration of the soil moisture accounting model using the adaptive random search algorithm
Author:
Weinig, Walter Theodore,1960-
Issue Date:
1991
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:
Random search techniques are being applied to a variety of non-linear parameter estimation problems. Random search for global optimization has the potential to overcome many of the problems associated with direct or pattern search techniques. In this research, an adaptive random search algorithm was applied to a conceptual rainfall-runoff model to study the efficiency of the algorithm in locating an optimum set of model parameters. The goal of the study was to determine how changes in internal algorithm control variables and objective functions affected the efficiency of the algorithm. Results indicated that the value of internal control variables did not have a strong influence on algorithm efficiency. Neither objective function gave demonstrably better results in calibration runs. Variability in results due to the random number seed was observed. Recommendations for further research are presented.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Soil moisture -- Measurement.; Soil moisture -- Mathematical models.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology and Water Resources; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Sorooshian, Soroosh

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleCalibration of the soil moisture accounting model using the adaptive random search algorithmen_US
dc.creatorWeinig, Walter Theodore,1960-en_US
dc.contributor.authorWeinig, Walter Theodore,1960-en_US
dc.date.issued1991en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © 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.en_US
dc.description.abstractRandom search techniques are being applied to a variety of non-linear parameter estimation problems. Random search for global optimization has the potential to overcome many of the problems associated with direct or pattern search techniques. In this research, an adaptive random search algorithm was applied to a conceptual rainfall-runoff model to study the efficiency of the algorithm in locating an optimum set of model parameters. The goal of the study was to determine how changes in internal algorithm control variables and objective functions affected the efficiency of the algorithm. Results indicated that the value of internal control variables did not have a strong influence on algorithm efficiency. Neither objective function gave demonstrably better results in calibration runs. Variability in results due to the random number seed was observed. Recommendations for further research are presented.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshSoil moisture -- Measurement.en_US
dc.subject.lcshSoil moisture -- Mathematical models.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrology and Water Resourcesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairSorooshian, Sorooshen_US
dc.identifier.oclc220948583en_US
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