Improvements in fast-response flood modeling: desktop parallel computing and domain tracking Page: 4 of 26
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or subtracted as the flood reaches or recedes from the subdomain boundary. Rather than
predefining subdomains, Bradbrook (2006) used an algorithm to dynamically track
individual inundated grid points, and the surrounding grid points. Obviously these
algorithms potentially reduce the computation time greatly (decrease is a function of
unnecessary cells in the domain), but large-scale flood events still present extreme
computational costs, especially when using high-resolution topographic data.
Because the majority of the computational cost in two-dimensional modeling
involves the computation of water surface elevation and velocities at grid points, parallel
computing is a time-saving solution, since these computations could be computed
simultaneously. Flood inundation models that have been implemented in a parallel
computing architecture (Hervouet 2000; Rao 2005; Pau and Sanders 2006; Villanueva
and Wright 2006).have followed the traditional parallel computing architecture which
consists of a cluster of computers (or nodes) linked together (Fig. 3.1).
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Judi, David R; Mcpherson, Timothy N & Burian, Steven J. Improvements in fast-response flood modeling: desktop parallel computing and domain tracking, article, January 1, 2009; [New Mexico]. (https://digital.library.unt.edu/ark:/67531/metadc933496/m1/4/: accessed April 16, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.