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Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing

Author

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  • Xiaozhang Hu

    (Pearl River Hydraulic Research Institute)

  • Lixiang Song

    (Pearl River Hydraulic Research Institute)

Abstract

Numerical accuracy and computational efficiency are the two key factors for flash flood simulation. In this paper, a two-dimensional fully hydrodynamic model is presented for the simulation of flash floods in mountain watersheds. A robust finite volume scheme is adopted to accurately simulate the overland flow with wet/dry fronts on highly irregular topography. A graphics processing unit-based parallel method using OpenACC is adopted to realize high-performance computing and then improve the computational efficiency. Since the finite volume scheme is explicit which involves many computationally intensive loop structures without data dependence, the parallel flash flood model can be easily realized by using OpenACC directives in an incremental developing way based on the serial model codes, except that data structure and transportation should be optimized for parallel algorithm. Model accuracy is validated by benchmark cases with exact solutions and experimental data. To further analyze the performance of the model, we considered a real flash flooding-prone area in China using a NVIDIA Tesla K20c card and three grid division schemes with different resolution. Results show that the proposed model can fast simulate the rainfall−runoff process related to the rapid mountain watersheds response, and a higher speedup ratio can be achieved for finer grids resolution. The proposed model can be used for real-time prediction of large-scale flash flood on high-resolution grids and thus has bright application prospects.

Suggested Citation

  • Xiaozhang Hu & Lixiang Song, 2018. "Hydrodynamic modeling of flash flood in mountain watersheds based on high-performance GPU computing," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 567-586, March.
  • Handle: RePEc:spr:nathaz:v:91:y:2018:i:2:d:10.1007_s11069-017-3141-7
    DOI: 10.1007/s11069-017-3141-7
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    References listed on IDEAS

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    1. Wen-Cheng Liu & Wei-Bo Chen & Ming-Hsi Hsu & Jin-Cheng Fu, 2010. "Dynamic routing modeling for flash flood forecast in river system," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 52(3), pages 519-537, March.
    2. Amro Elfeki & Milad Masoud & Burhan Niyazi, 2017. "Integrated rainfall–runoff and flood inundation modeling for flash flood risk assessment under data scarcity in arid regions: Wadi Fatimah basin case study, Saudi Arabia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(1), pages 87-109, January.
    3. Ziyue Zeng & Guoqiang Tang & Di Long & Chao Zeng & Meihong Ma & Yang Hong & Hui Xu & Jing Xu, 2016. "A cascading flash flood guidance system: development and application in Yunnan Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(3), pages 2071-2093, December.
    4. Jijian Lian & Weichao Yang & Kui Xu & Chao Ma, 2017. "Flash flood vulnerability assessment for small catchments with a material flow approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(2), pages 699-719, September.
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    1. Weiwei Jiang & Jingshan Yu, 2022. "Impact of rainstorm patterns on the urban flood process superimposed by flash floods and urban waterlogging based on a coupled hydrologic–hydraulic model: a case study in a coastal mountainous river b," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 301-326, May.
    2. Wenchao Qi & Chao Ma & Hongshi Xu & Zifan Chen & Kai Zhao & Hao Han, 2021. "A review on applications of urban flood models in flood mitigation strategies," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 31-62, August.
    3. Jingming Hou & Nie Zhou & Guangzhao Chen & Miansong Huang & Guangbi Bai, 2021. "Rapid forecasting of urban flood inundation using multiple machine learning models," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(2), pages 2335-2356, September.
    4. Qinge Peng & Xingnian Liu & Er Huang & Kejun Yang, 2019. "Experimental study on the influence of vegetation on the slope flow concentration time," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 751-763, September.

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