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Selection of modeling and monitoring strategies for estuarine water quality management

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dc.contributor.authorSivakumaran, Kumaraswamy, author
dc.contributor.authorGrigg, N. S., advisor
dc.contributor.authorWard, Robert C., advisor
dc.contributor.authorSanders, T. G., committee member
dc.contributor.authorFontane, Daniel G., committee member
dc.date.accessioned2021-09-23T21:30:13Z
dc.date.available2021-09-23T21:30:13Z
dc.date.issued1989
dc.description.abstractEstuarine water quality management is challenging owing to the complex hydrodynamics, water quality kinetics, international and domestic legislation, and human impact that take place in an estuarine environment. Scientists respond to this challenge by 'observing, hypothesizing and predicting' the behavior of the estuary. This is accomplished via developing water quality models which are idealizations of the behavior and by water quality monitoring. As most of the water quality models were developed for research, they did not serve the purposes of management. Because scientific methods were not widely known, the direction by Congress to collect water quality data led to non-scientific methods of collecting data. The research (with the objective of using water quality models effectively) embarked on designing a water quality monitoring system using a model. A model based on the hypothesis of conservation of mass was expressed as a one dimensional convective diffusion equation. The convective-diffusion equation was then solved recursively. Field observations from the Potomac estuary were obtained from government agencies and reports. An algorithm developed by Kalman was used to combine the model predictions and field measurements. In order to design the monitoring system the term 'TRACE OF ESTUARY' (TOE) was defined. The relative value of TOE determined the optimum number of sampling locations for an ongoing water quality monitoring program. The approach resulted in the reduction of sampling locations in the Potomac estuary from 12 to 5. It also showed that water quality data must be representative of similar sized segments. The concept of using the physical behavior of the system to design a water quality monitoring network was established. It was further established that the use of "better and accurate" models (not necessarily complex models) will reduce the number of sampling points. The significance of the research is that: (i) modeling and monitoring are used in an integrated fashion; (ii) a scientific approach is used to determine the number of sampling locations; and (iii) an accurate model will lead to a reduction in the sampling locations necessary for water quality management.
dc.format.mediumdoctoral dissertations
dc.identifier.urihttps://hdl.handle.net/10217/233934
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relationCatalog record number (MMS ID): 991016162399703361
dc.relationTD365.S54 1989
dc.relation.ispartof1980-1999
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subject.lcshWater quality management
dc.subject.lcshWater quality management -- Mathematical models
dc.titleSelection of modeling and monitoring strategies for estuarine water quality management
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineCivil Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D)

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