The effects of alternative automatic calibration techniques on parameter estimation for HEC-1

Persistent Link:
http://hdl.handle.net/10150/191825
Title:
The effects of alternative automatic calibration techniques on parameter estimation for HEC-1
Author:
Walker, Mark(Mark Joseph)
Issue Date:
1984
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:
Four automatic calibration techniques were used to estimate parameters in the U.S. Army Corps of Engineers HEC rainfall-runoff simulation HEC-1. The techniques were tested with three strategies in synthetic data studies and verification studies with a small, semi-arid watershed. The automatic calibrations employed two versions of Newton-Raphson optimization algorithms and weighted least squares (WLS) and maximum-likelihood based estimation criteria. Strategies were determined by the U.S. Army Corps of Engineers (the HEC strategy), and designed to avoid parameter interaction (Methods A and B). Overall, automatic calibration using a multivariate Newton-Raphson optimization based on explicit derivatives and the HMLE with Method B performed best in the synthetic data study in terms of parameter recovery. Verification studies suggest the model may need a soil moisture accounting mechanism to make application to the small, semi-arid watershed under study practical.
Type:
Thesis-Reproduction (electronic); text
LCSH Subjects:
Hydrology.; Runoff -- Mathematical models.; Runoff -- Simulation methods.
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.titleThe effects of alternative automatic calibration techniques on parameter estimation for HEC-1en_US
dc.creatorWalker, Mark(Mark Joseph)en_US
dc.contributor.authorWalker, Mark(Mark Joseph)en_US
dc.date.issued1984en_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.abstractFour automatic calibration techniques were used to estimate parameters in the U.S. Army Corps of Engineers HEC rainfall-runoff simulation HEC-1. The techniques were tested with three strategies in synthetic data studies and verification studies with a small, semi-arid watershed. The automatic calibrations employed two versions of Newton-Raphson optimization algorithms and weighted least squares (WLS) and maximum-likelihood based estimation criteria. Strategies were determined by the U.S. Army Corps of Engineers (the HEC strategy), and designed to avoid parameter interaction (Methods A and B). Overall, automatic calibration using a multivariate Newton-Raphson optimization based on explicit derivatives and the HMLE with Method B performed best in the synthetic data study in terms of parameter recovery. Verification studies suggest the model may need a soil moisture accounting mechanism to make application to the small, semi-arid watershed under study practical.en_US
dc.description.notehydrology collectionen_US
dc.typeThesis-Reproduction (electronic)en_US
dc.typetexten_US
dc.subject.lcshHydrology.en_US
dc.subject.lcshRunoff -- Mathematical models.en_US
dc.subject.lcshRunoff -- Simulation methods.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.oclc213297556en_US
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