Open AccessA HIGH-PERFORMANCE METHOD FOR SIMULATING SURFACE RAINFALL-RUNOFF DYNAMICS USING PARTICLE SYSTEM
Author(s) -
Fangli Zhang,
Qiming Zhou,
Qingquan Li,
Guofeng Wu,
Jun Li
Publication year - 2016
Publication title -
isprs annals of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 38
eISSN - 2194-9042
pISSN - 2196-6346
DOI - 10.5194/isprsannals-iii-2-109-2016
Subject(s) - surface runoff , computer science , flow (mathematics) , process (computing) , path (computing) , triangulated irregular network , cluster (spacecraft) , terrain , environmental science , distributed computing , simulation , ecology , biology , programming language , operating system , geometry , mathematics
The simulation of rainfall-runoff process is essential for disaster emergency and sustainable development. One common disadvantage of the existing conceptual hydrological models is that they are highly dependent upon specific spatial-temporal contexts. Meanwhile, due to the inter-dependence of adjacent flow paths, it is still difficult for the RS or GIS supported distributed hydrological models to achieve high-performance application in real world applications. As an attempt to improve the performance efficiencies of those models, this study presents a high-performance rainfall-runoff simulating framework based on the flow path network and a separate particle system. The vector-based flow path lines are topologically linked to constrain the movements of independent rain drop particles. A separate particle system, representing surface runoff, is involved to model the precipitation process and simulate surface flow dynamics. The trajectory of each particle is constrained by the flow path network and can be tracked by concurrent processors in a parallel cluster system. The result of speedup experiment shows that the proposed framework can significantly improve the simulating performance just by adding independent processors. By separating the catchment elements and the accumulated water, this study provides an extensible solution for improving the existing distributed hydrological models. Further, a parallel modeling and simulating platform needs to be developed and validate to be applied in monitoring real world hydrologic processes.