A computational framework for spatially explicit agroecosystem modeling: Application to regional simulation

D. Wang, S. Kang, J. Nichols, W. Post, S. Liu, Z. Zhao

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Site-based agroecosystem model has been applied at regional and state level to enable comprehensive analyses of environmental sustainability of food and biofuel production. However, spatially explicit ecosystem simulations over large landscape present computational challenges. This paper presents a framework to support spatially explicit agroecosystem modeling and data analysis over large landscape, which includes four major phases of agroecosystem simulation: simulation data preparation, site-based simulation on high performance computers, data management and data analysis. Then, a case study on a regional intensive modeling area (RIMA) was presented as an application to demonstrate the system implementation and capability.

Original languageEnglish (US)
Pages (from-to)386-392
Number of pages7
JournalJournal of Computational Science
Volume4
Issue number5
DOIs
StatePublished - 2013
Externally publishedYes

Bibliographical note

Funding Information:
The research was funded by the Great Lake Bioenergy Research Center (GLBRC) as well as the Office of Science of the U.S. Department of Energy (DOE) . Oak Ridge National Laboratory is managed by UT-Battelle LLC for the Department of Energy under contract DE-AC05-00OR22725. We also would like to acknowledge Terry Copeland Pfeiffer for her assistance with manuscript editing.

Keywords

  • Agroecosystem
  • Data management
  • Environmental software system design
  • High performance computing
  • Spatially explicit simulation

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