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
{"title":"A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations","authors":"Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang","doi":"10.2166/hydro.2023.152","DOIUrl":null,"url":null,"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 it improves the time and efficiency of urban flood emergency decision-making.","PeriodicalId":507813,"journal":{"name":"Journal of Hydroinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydroinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/hydro.2023.152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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 it improves the time and efficiency of urban flood emergency decision-making.
基于 GPU 的城市暴雨淹没模拟流体力学数值模型
通过加强城市洪水数值模型的计算能力,可以提高城市洪水预报和风险控制的响应能力。本研究开发了基于 GPU 的水动力模型,用于模拟城市暴雨洪水。通过模拟西咸新区某区域的暴雨洪水,所建立的模型可以实现高分辨率的城市暴雨洪水模拟,计算性能明显加快。定量分析了 5 米和 2 米分辨率下不同暴雨事件模拟的加速计算效率,结果表明,在所有场景下,应用两个 GPU 的绝对加速比和相对加速比分别是 CPU 和单个 GPU 的 10.8 至 12.6 倍和 1.32 至 1.68 倍。大规模暴雨淹没模拟的应用表明,与之前的研究相比,该模型具有出色的加速性能。此外,模拟中包含的计算网格数量越多,对加速计算性能的影响越明显。所提出的模型能有效预测淹没水深的空间变化。模拟结果为城市暴雨淹没管理提供了指导,提高了城市洪水应急决策的时间和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信