Water Quality Modeling in Kranji Catchment

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010. === "June 2010." Cataloged from PDF version of thesis. === Includes bibliographical references (p. 50-52). === This thesis describes the process and results of applying the Soil and...

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Bibliographic Details
Main Author: Granger, Erika C
Other Authors: Peter Shanahan.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/60762
Description
Summary:Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2010. === "June 2010." Cataloged from PDF version of thesis. === Includes bibliographical references (p. 50-52). === This 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. === by Erika C. Granger. === M.Eng.