SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Use of a Beowulf cluster for estimation of risk using SWAT 
Authors:Whittaker, G.R 
Journal:Agronomy Journal 
Volume (Issue):96(5) 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:hydrologic and pollutant 
Primary Application Category:calibration, sensitivity, and/or uncertainty analysis 
Secondary Application Category:hydrologic assessment 
Watershed Description:Calapooia River, located in the Willamette Valley in Oregon, U.S. 
Calibration Summary: 
Validation Summary: 
General Comments:A Beowulf Cluster, consisting of a server & 12 computational nodes, was used to perform a Monte-Carlo set of 1200 102-year SWAT2000 simulations. A varying number of processers were used for the simulations for speed comparisons. The simulations were performed with the "R statistical computing environment" to provide uncertainity analysis. A Linux operating system was used for the Cluster. 
Abstract:Estimation of uncertainty using agronomic models typically requires a Monte Carlo study with a large number of simulations. Parallel computation dramatically speeds repetitive computation of this sort. The use of a Beowulf cluster parallel computer offers a low cost method of parallel computing that is fairly simple to construct, but application information is specialized, with little concerning agronomic model simulation. The objective in this note is to present a method of simulation using an agronomic model on a Beowulf cluster. To facilitate the analysis of uncertainty, the method performs the simulations within the R statistical computing environment. The Soil and Water Assessment Tool (SWAT) was run for 1200 annual simulations on varying numbers of processors for speed comparisons. The cluster achieved close to the theoretical speed increase as the simulation results were stored in an R object. Two examples of nonparametric estimation of uncertainty are presented.