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dc.contributor.advisorPeter Shanahan.en_US
dc.contributor.authorGranger, Erika Cen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.en_US
dc.coverage.spatiala-si---en_US
dc.date.accessioned2011-01-26T14:20:26Z
dc.date.available2011-01-26T14:20:26Z
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/60762
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010.en_US
dc.description"June 2010." Cataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 50-52).en_US
dc.description.abstractThis thesis describes the process and results of applying the Soil and Water Assessment Tool (SWAT) to characterize bacterial fate and transport in the Kranji Catchment of Singapore. The goal of this process is to predict bacterial loading to Kranji Reservoir under the forcing of weather and other variables. Necessary data and input values were collected or estimated and input into the model. One of the most important of these values is the bacterial die-off rate. This rate must be accurate for the model to provide accurate predictions of bacterial loadings. In order to obtain a value for the bacterial die-off rate, an attenuation study was conducted. The results of this study were not typical. Bacterial growth was observed to occur during dark hours, and decay was observed to occur during sunlit hours. The resulting light and dark decay constants were combined for use in the model. The specific bacterial loading rates associated with the various agricultural activities occurring in the catchment are not available and thus were roughly estimated. Point source loadings were also estimated. Four years of model simulation daily output were analyzed, and results for specific subcatchments with differing character are discussed. This application of SWAT shows a good ability to make qualitative predictions of the presence or absence of bacteria; however, quantitative agreement between model predictions and field observations is poor. This run of the model is like a first draft-more refinement and more information are needed before it will make accurate predictions; however, the framework is in place.en_US
dc.description.statementofresponsibilityby Erika C. Granger.en_US
dc.format.extent64 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleWater Quality Modeling in Kranji Catchmenten_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.identifier.oclc693557819en_US


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