Improvements in fast-response flood modeling: desktop parallel computing and domain tracking

It is becoming increasingly important to have the ability to accurately forecast flooding, as flooding accounts for the most losses due to natural disasters in the world and the United States. Flood inundation modeling has been dominated by one-dimensional approaches. These models are computationally efficient and are considered by many engineers to produce reasonably accurate water surface profiles. However, because the profiles estimated in these models must be superimposed on digital elevation data to create a two-dimensional map, the result may be sensitive to the ability of the elevation data to capture relevant features (e.g. dikes/levees, roads, walls, etc...). Moreover, one-dimensional models do not explicitly represent the complex flow processes present in floodplains and urban environments and because two-dimensional models based on the shallow water equations have significantly greater ability to determine flow velocity and direction, the National Research Council (NRC) has recommended that two-dimensional models be used over one-dimensional models for flood inundation studies. This paper has shown that two-dimensional flood modeling computational time can be greatly reduced through the use of Java multithreading on multi-core computers which effectively provides a means for parallel computing on a desktop computer. In addition, this paper has shown that when desktop parallel computing is coupled with a domain tracking algorithm, significant computation time can be eliminated when computations are completed only on inundated cells. The drastic reduction in computational time shown here enhances the ability of two-dimensional flood inundation models to be used as a near-real time flood forecasting tool, engineering, design tool, or planning tool. Perhaps even of greater significance, the reduction in computation time makes the incorporation of risk and uncertainty/ensemble forecasting more feasible for flood inundation modeling (NRC 2000; Sayers et al. 2000)