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Title: A CONCURRENT SIMULATION MODEL FOR ANALYSIS OF WATER CONTROL STRUCTURES AT THE WATERSHED SCALE

Author
item NEILSEN, MITCHELL - KANSAS STATE UNIVERSITY
item Temple, Darrel

Submitted to: International Conference on Parallel and Distributed Processng Techniques
Publication Type: Proceedings
Publication Acceptance Date: 6/26/2000
Publication Date: 7/1/2000
Citation: Neilsen, M.L., Temple, D.M. 2000. A concurrent simulation model for analysis of water control structures at the watershed scale. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, June 2000, Las Vegas, Nevada. pp. 1565-1570.

Interpretive Summary: Information previously presented in another media; no new research information provided; no interpretive summary required.

Technical Abstract: The United States Department of Agriculture, Natural Resources Conservation Service (USDA, NRCS), Water Resource Site Analysis Software (SITES) is a distributed, event-oriented model used for hydraulic and hydrologic analysis of water control structures. SITES can be used to analyze the effect of various hydrologic or hydraulic conditions on a given spillway design, and to efficiently compare alternative spillway designs. This pape describes a concurrent simulation model that can be used to analyze structures and other hydrologic elements at the watershed scale. The model can also be used to better understand the structure, function, and dynamics of hydrologic elements within a watershed. Each element can be simulated using a different model, such as SITES. Synchronization constraints between elements are defined using an acrylic graph called a watershed schematic. This allows for fine-grained parallelism within each run. Also, within a project, several runs can be processed simultaneously, resulting in coarse grained parallelism. The concurrent model is extensible, and can easily incorporate additional hydrologic elements and models. Finally, the hydrologic simulation models, along with hundreds of data sets, are in the public domain. Consequently, they provide an interesting test case for empirical research.