Parallelization of the flow-path network model using a particle-set strategy

ABSTRACT

High-performance simulation of flow dynamics remains a major challenge in the use of physical-based, fully distributed hydrologic models. Parallel computing has been widely used to overcome efficiency limitation by partitioning a basin into sub-basins and executing calculations among multiple processors. However, existing partition-based parallelization strategies are still hampered by the dependency between inter-connected sub-basins. This study proposed a particle-set strategy to parallelize the flow-path network (FPN) model for achieving higher performance in the simulation of flow dynamics. The FPN model replaced the hydrological calculations on sub-basins with the movements of water packages along the upstream and downstream flow paths. Unlike previous partition-based task decomposition approaches, the proposed particle-set strategy decomposes the computational workload by randomly allocating runoff particles to concurrent computing processors. Simulation experiments of the flow routing process were undertaken to validate the developed particle-set FPN model. The outcomes of hourly outlet discharges were compared with field gauged records, and up to 128 computing processors were tested to explore its speedup capability in parallel computing. The experimental results showed that the proposed framework can achieve similar prediction accuracy and parallel efficiency to that of the Triangulated Irregular Network (TIN)-based Real-Time Integrated Basin Simulator (tRIBS).

KEYWORDS:

• Terrain analysis
• flow process
• parallel computing
• digital elevation model
• distributed hydrologic model

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation program under Grant numbers 41301403 and 41471340; the Research Grants Council (RGC) of Hong Kong General Research Fund (GRF) under Grant number 203913; and the Hong Kong Baptist University Faculty Research Grant under Grant number FRG2/14-15/073

Notes on contributors

Fangli Zhang

Fangli Zhang is a lecturer in the field of geographical information sciences at School of Geosciences in Yangtze University, and he has been an assistant research fellow at School of Geography and Ocean Science, Nanjing University after his PhD study at Hong Kong Baptist University in 2018. He designed and implemented the simulation platform, conducted the experiments, written the manuscript. Phone: [phone]; Email: [email protected].

Qiming Zhou

Qiming Zhou is a professor at Department of Geography, Hong Kong Baptist University, Hong Kong. He put forward the original idea of particle-set model for hydrologic modelling, provided guidance on the whole research project, reviewed the manuscript as the principle supervisor. Phone: [phone]; Email: [email protected].