| Title: | Approximating SWAT model using artificial, neural network and support vector machine |
| Authors: | Zhang, X., R. Srinivasan, and M. Van Liew |
| Year: | 2009 |
| Journal: | Journal of the American Water Resources Association |
| Volume (Issue): | 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 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. |
| Language: | English |
| Keywords: | artificial neural network, computationally intensive, hydrologic modeling, soil and water assessment tool, support vector machine |