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" Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2) "
Nasim Shojaei
Wells, Scott
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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803133
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| Doc. No
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TL47909
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| Call number
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1614531571; 1564754
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| Main Entry
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Mahani, Sepideh
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| Title & Author
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Automatic Calibration of Water Quality and Hydrodynamic Model (CE-QUAL-W2)\ Nasim ShojaeiWells, Scott
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| College
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Portland State University
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| Date
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2014
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| Degree
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M.S.
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| field of study
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Civil and Environmental Engineering
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| student score
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2014
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| Page No
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107
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| Note
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Committee members: Berger, Chris; Talke, Stefan; Wells, Scott
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| Note
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Place of publication: United States, Ann Arbor; ISBN=978-1-321-18006-0
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| Abstract
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One of the most important purposes of surface water resource management is to develop predictive models to assist in identifying and evaluating operational and structural measures for improving water quality. To better understand the effects of external and internal nutrient and organic loading and the effects of reservoir operation, a model is often developed, calibrated, and used for sensitivity and management simulations. The importance of modeling and simulation in the scientific community has drawn interest towards methods for automated calibration. This study addresses using an automatic technique to calibrate the water quality model CEQUAL-W2 (Cole and Wells, 2013). CE-QUAL-W2 is a two-dimensional (2D) longitudinal/vertical hydrodynamic and water quality model for surface water bodies, modeling eutrophication processes such as temperature-nutrient-algae-dissolved oxygen-organic matter and sediment relationships. The numerical method used for calibration in this study is the particle swarm optimization method developed by Kennedy and Eberhart (1995) and inspired by the paradigm of birds flocking. The objective of this calibration procedure is to choose model parameters and coefficients affecting temperature, chlorophyll a, dissolved oxygen, and nutrients (such as NH<sub>4</sub>, NO<sub>3</sub>, and PO<sub>4</sub>). A case study is presented for the Karkheh Reservoir in Iran with a capacity of more than 5 billion cubic meters that is the largest dam in Iran with both agricultural and drinking water usages. This algorithm is shown to perform very well for determining model parameters for the reservoir water quality and hydrodynamic model. Implications of the use of this procedure for other water quality models are also shown.
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| Subject
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Civil engineering; Water Resource Management; Environmental engineering
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| Descriptor
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Applied sciences;Earth sciences;Automatic calibration;Ce-qual-w2;Karkhey reservoir;Particle swarm inteligence;Water quality and hydrodynamic modeling
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| Added Entry
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Wells, Scott
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| Added Entry
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Civil and Environmental EngineeringPortland State University
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