An urban flood inundation model accelerated by the parallel acceleration technology

IF 4.6 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2025-03-24 DOI:10.1016/j.envsoft.2025.106441
Wei Zhu , Zhe Cao , Pingping Luo , Shuangtao Wang , Chengyi Xv , Yongxing Ji
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Abstract

Due to factors such as changes in land use and climate change, floods are increasingly occurring worldwide, resulting in excessive property damage and casualties in urban areas. Numerical simulation techniques can provide valuable support in mitigating urban flood risks. This study developed a coupled flood inundation model for one-dimensional sewer and two-dimensional surface based on parallel acceleration technology. The main findings include: 1. The model was validated in Omihachiman City and Shanghai City, demonstrating satisfactory results in flood inundation simulations and confirming the model's reliability in simulating flood processes. 2. A comparison of simulation times between the surface inundation model's serial version, CPU-accelerated version, and GPU-accelerated version was conducted. The GPU-accelerated version showed significant speed-up compared to the CPU model using the same numerical algorithms, with better performance as computational units increased. 3. The performance of the model is significantly influenced by the underground sewer model.
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基于并行加速技术的城市洪水淹没模型
由于土地利用变化和气候变化等因素,洪水在世界范围内日益频繁地发生,造成了城市地区过多的财产损失和人员伤亡。数值模拟技术可以为减轻城市洪水风险提供有价值的支持。基于平行加速技术,建立了一维下水道与二维地表的耦合洪水淹没模型。主要研究结果包括:1。该模型在大八幡市和上海市进行了验证,在洪水模拟中取得了满意的结果,验证了该模型在模拟洪水过程中的可靠性。2. 对比了地表淹没模型串行版、cpu加速版和gpu加速版的模拟次数。与使用相同数值算法的CPU模型相比,gpu加速版本显示出显著的速度提升,随着计算单元的增加,性能也会更好。3. 模型的性能受地下管网模型的影响较大。
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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