Evaluating the Efficiency of a Multi-core Aware Multi-objective Optimization Tool for Calibrating the SWAT Model

Journal Article · Mon Aug 20 00:00:00 EDT 2012 · Transactions of the ASABE

DOI:https://doi.org/10.13031/2013.42363· OSTI ID:1059623

Zhang, X. ^[1]; Izaurralde, R. C. ^[1]; Zong, Z. ^[1]; Zhao, K. ^[1]; Thomson, A. M. ^[1]

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1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

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.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1059623
• Report Number(s): PNNL-SA-78804; KP1703030
• Journal Information: Transactions of the ASABE, Vol. 55, Issue 5; ISSN 2151-0040
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING