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Advances in the application of the SWAT model for water resources management

✍ Scribed by R. Jayakrishnan; R. Srinivasan; C. Santhi; J. G. Arnold


Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
914 KB
Volume
19
Category
Article
ISSN
0885-6087

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✦ Synopsis


Abstract

Developments in computer technology have revolutionized the study of hydrologic systems and water resources management. Several computer‐based hydrologic/water quality models have been developed for applications in hydrologic modelling and water resources studies. Distributed parameter models, necessary for basin‐scale studies, have large input data requirements. Geographic information systems (GIS) and model–GIS interfaces aid the efficient creation of input data files required by such models. One such model available for the water resources professional is the Soil and Water Assessment Tool (SWAT), a distributed parameter model developed by the United States Department of Agriculture. This paper describes some recent advances made in the application of SWAT and the SWAT–GIS interface for water resources management. Four case studies are presented. The Hydrologic Unit Model for the United States (HUMUS) project used SWAT to conduct a national‐scale analysis of the effect of management scenarios on water quantity and quality. Integration of the SWAT model with rainfall data available from the WSR‐88D radar network helps us to incorporate the spatial variability of rainfall into the modelling process. This study demonstrates the usefulness of radar rainfall data in distributed hydrologic studies and the potential of SWAT for application in flood analysis and prediction. A hydrologic modelling study of the Sondu river basin in Kenya using SWAT indicates the potential for application of the model in African watersheds and points to the need for development of better model input data sets in Africa, which are critical for detailed water resources studies. The application of SWAT for water quality analysis in the Bosque river basin, Texas demonstrates the strength of the model for analysing different management scenarios to minimize point and non‐point pollution, and its potential for application in total maximum daily load (TMDL) studies. Copyright © 2005 John Wiley & Sons, Ltd.


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