{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86058"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86058","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling Phosphorus Transport in a River Under Unsteady Flow Conditions","abstract":"There exist possible problems of numerical dispersion and instability in the solutions, which may occur due to varying velocity under unsteady flow condition. To solve this problem, various numerical methods were tested and the implicit Lagrangian method was selected, which showed least numerical dispersion, given a computational grid size. The model is applied to a 55-km stretch of the River Swale in Yorkshire, UK, within the framework of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The GLUE methodology is a Bayesian Monte Carlo simulation-based technique, in which multivariate information on the model system can be easily integrated. Utilizing this property, sequential conditioning corresponding to simulation dependency was carried out. In-stream dynamics was identified by comparing the model predicted results with the observed variables. Various forms of phosphorus flux between the flow and sediment were also simulated, showing the effect of sediment particle size on phosphorus transport. Finally, model parameter sensitivity analysis was carried out within the GLUE framework. Results indicate that the in-stream dynamics of phosphorus can be successfully investigated by the modeling approach.","abstract_html":"There exist possible problems of numerical dispersion and instability in the solutions, which may occur due to varying velocity under unsteady flow condition. To solve this problem, various numerical methods were tested and the implicit Lagrangian method was selected, which showed least numerical dispersion, given a computational grid size. The model is applied to a 55-km stretch of the River Swale in Yorkshire, UK, within the framework of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The GLUE methodology is a Bayesian Monte Carlo simulation-based technique, in which multivariate information on the model system can be easily integrated. Utilizing this property, sequential conditioning corresponding to simulation dependency was carried out. In-stream dynamics was identified by comparing the model predicted results with the observed variables. Various forms of phosphorus flux between the flow and sediment were also simulated, showing the effect of sediment particle size on phosphorus transport. Finally, model parameter sensitivity analysis was carried out within the GLUE framework. Results indicate that the in-stream dynamics of phosphorus can be successfully investigated by the modeling approach.","abstract_has_math":false,"creators":["Kim, Kyunghyun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Agricultural and Biological Engineering","degree_department":null,"school":null,"contributors":["Kalita, Prasanta K."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T14:53:47Z","date_published":"2015-09-28T14:53:47Z","updated_at":"2026-07-22T22:26:26Z","subjects":["Environmental Sciences"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3182294"],"render_values":[{"text":"(MiAaPQ)AAI3182294","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86058","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kalita, Prasanta K."]},{"key":"dc:creator","label":"Author","values":["Kim, Kyunghyun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T14:53:47Z","10000-01-01","2005"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Agricultural and Biological Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Environmental Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/86058","(MiAaPQ)AAI3182294"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["There exist possible problems of numerical dispersion and instability in the solutions, which may occur due to varying velocity under unsteady flow condition. To solve this problem, various numerical methods were tested and the implicit Lagrangian method was selected, which showed least numerical dispersion, given a computational grid size. The model is applied to a 55-km stretch of the River Swale in Yorkshire, UK, within the framework of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The GLUE methodology is a Bayesian Monte Carlo simulation-based technique, in which multivariate information on the model system can be easily integrated. Utilizing this property, sequential conditioning corresponding to simulation dependency was carried out. In-stream dynamics was identified by comparing the model predicted results with the observed variables. Various forms of phosphorus flux between the flow and sediment were also simulated, showing the effect of sediment particle size on phosphorus transport. Finally, model parameter sensitivity analysis was carried out within the GLUE framework. Results indicate that the in-stream dynamics of phosphorus can be successfully investigated by the modeling approach.","Made available in DSpace on 2015-09-28T14:53:47Z (GMT). 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To solve this problem, various numerical methods were tested and the implicit Lagrangian method was selected, which showed least numerical dispersion, given a computational grid size. The model is applied to a 55-km stretch of the River Swale in Yorkshire, UK, within the framework of the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. The GLUE methodology is a Bayesian Monte Carlo simulation-based technique, in which multivariate information on the model system can be easily integrated. Utilizing this property, sequential conditioning corresponding to simulation dependency was carried out. In-stream dynamics was identified by comparing the model predicted results with the observed variables. Various forms of phosphorus flux between the flow and sediment were also simulated, showing the effect of sediment particle size on phosphorus transport. Finally, model parameter sensitivity analysis was carried out within the GLUE framework. 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