The efficiency of calibrating physically-based complex hydrologic models is a major concern in the application of those models to understand and manage natural and human activities that affect watershed systems. In this study, we developed a multi-core aware multi-objective evolutionary optimization algorithm (MAMEOA) to improve the efficiency of calibrating a worldwide used watershed model (Soil and Water Assessment Tool (SWAT)). The test results show that MAMEOA can save about 1-9%, 26-51%, and 39-56% time consumed by calibrating SWAT as compared with sequential method by using dual-core, quad-core, and eight-core machines, respectively. Potential and limitations of MAMEOA for calibrating SWAT are discussed. MAMEOA is open source software.
Revised: January 2, 2013 |
Published: August 20, 2012
Citation
Zhang X., R.C. Izaurralde, Z. Zong, K. Zhao, and A.M. Thomson. 2012.EVALUATING THE EFFICIENCY OF A MULTI-CORE AWARE MULTI-OBJECTIVE OPTIMIZATION TOOL FOR CALIBRATING THE SWAT MODEL.Transactions of the ASABE 55, no. 5:1723-1731.PNNL-SA-78804.