SWAT Literature Database for Peer-Reviewed Journal Articles

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