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A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations

  • Hao Han
  • , Jingming Hou
  • , Zhao Jin
  • , Pingping Luo
  • , Guodong Li
  • , Ye Zhang
  • , Jiahui Gong
  • , Da Luo
  • , Siqi Yang
  • CAS - Institute of Earth Environment
  • Xi'an University of Technology
  • National Observation and Research Station of Earth Critical Zone on the Loess Plateau in Shaanxi
  • Ministry of Natural Resources of the People's Republic of China
  • Chang'an University
  • Yulin University
  • Beijing Normal University

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and they improve the time and efficiency of urban flood emergency decision-making.

Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalJournal of Hydroinformatics
Volume26
Issue number1
DOIs
StatePublished - 10 Jan 2024

Keywords

  • accelerated computing efficiency
  • hydrodynamic model
  • multi-GPU parallel computation method
  • urban rainstorm inundation simulation

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