SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python 
Authors:Zhang, X., P. Beeson, R. Link, D. Manowitz, R.C. Izaurralde, A. Sadeghi, A.M. Thomson, R. Sahajpal, R. Srinivasan and J.G. Arnold 
Year:2013 
Journal:Environmental Modelling & Software 
Volume:46 
Pages:208–218 
Article ID: 
DOI:10.1016/j.envsoft.2013.03.013 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:computational approaches 
Primary Application Category:computational efficiency 
Secondary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Watershed Description:334 km^2 Little River Experimental in southwestern Georgia, U.S. and the 788 km^2 South Fork of the Iowa River in north central Iowa, U.S. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Language:English 
Keywords:Parallel processing, Evolutionary multi-objective optimization, High performance computer, Soil and water assessment tool, Parameter calibration