کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4577506 | 1630011 | 2011 | 14 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment Real-world hydrologic assessment of a fully-distributed hydrological model in a parallel computing environment](/preview/png/4577506.png)
SummaryA major challenge in the use of fully-distributed hydrologic models has been the lack of computational capabilities for high-resolution, long-term simulations in large river basins. In this study, we present the parallel model implementation and real-world hydrologic assessment of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS). Our parallelization approach is based on the decomposition of a complex watershed using the channel network as a directed graph. The resulting sub-basin partitioning divides effort among processors and handles hydrologic exchanges across boundaries. Through numerical experiments in a set of nested basins, we quantify parallel performance relative to serial runs for a range of processors, simulation complexities and lengths, and sub-basin partitioning methods, while accounting for inter-run variability on a parallel computing system. In contrast to serial simulations, the parallel model speed-up depends on the variability of hydrologic processes. Load balancing significantly improves parallel speed-up with proportionally faster runs as simulation complexity (domain resolution and channel network extent) increases. The best strategy for large river basins is to combine a balanced partitioning with an extended channel network, with potential savings through a lower TIN resolution. Based on these advances, a wider range of applications for fully-distributed hydrologic models are now possible. This is illustrated through a set of ensemble forecasts that account for precipitation uncertainty derived from a statistical downscaling model.
► We quantify the performance of a new parallelization method for a distributed model.
► Parallel model performance is found to be dependent on the hydrologic variability.
► Load balancing methods improve parallel performance in particular for large domains.
► A wider range of distributed applications is now possible through parallelization.
Journal: Journal of Hydrology - Volume 409, Issues 1–2, 28 October 2011, Pages 483–496