SWAT Literature Database for Peer-Reviewed Journal Articles

Title:
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Approximating SWAT model using artificial, neural network and support vector machine 
Authors:
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Zhang, X., R. Srinivasan, and M. Van Liew 
Year:2009 
Journal:Journal of the American Water Resources Association 
Volume:45(2) 
Pages:460-474 
Article ID: 
DOI:10.1111/j.1752-1688.2009.00302.x 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic only 
Primary Application Category:model comparison 
Secondary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Watershed Description:
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334 km^2 Little River Experimental Watershed Tifton, Georgia and 7 km^2 Mahantango Creek Experimental Watershed in Central Pennsylvania 
Calibration Summary:
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Validation Summary: 
General Comments:Results between the two models are shown in terms of different parameter dimensions, training sample sizes, cross-validation schemes, etc. 
Language:English 
Keywords:artificial neural network, computationally intensive, hydrologic modeling, soil and water assessment tool, support vector machine