GAST-SWMM耦合数值模型在大尺度城区致涝风险评估中的应用

银雅伦; 侯精明; 李欣怡; 栾广学; 高徐军; 王添; 沈健; 乔梦曦

doi:10.13205/j.hjgc.202404010

GAST-SWMM耦合数值模型在大尺度城区致涝风险评估中的应用

doi: 10.13205/j.hjgc.202404010

1.西安理工大学省部共建西北旱区生态水利国家重点实验室,西安 710048;
2.中规院北京规划设计有限公司,北京 100044

基金项目:

中德合作国际交流项目(M-0427)

陕西省科技创新团队(2020TD-023)

国家自然科学基金项目(52009104,52079106)

详细信息

作者简介:
银雅伦(1998-),女,硕士研究生,主要研究方向为城市水利学。806287682@qq.com

通讯作者:
侯精明(1982-),男,教授,主要研究方向为地表水及其附随过程数值模型研究。jingming.hou@xaut.edu.cn

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出版历程
- 收稿日期: 2022-10-21
- 网络出版日期: 2024-06-01

APPLICATION OF GAST-SWMM COUPLED NUMERICAL MODEL IN LARGE-SCALE URBAN INUNDATION RISK ASSESSMENT

1. State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China, Xi’an University of Technology,Xi’an 710048, China;
2. China Planning Institute (Beijing) Planning and Design Co., Ltd.,Beijing 100044, China

摘要

摘要: 开展城区暴雨致涝风险评估对内涝整治及城市安全发展至关重要,以银川市310 km²主城区为例,建立基于GPU加速技术的城市地表积涝及地下管网排水过程的GAST-SWMM高效高分辨率耦合模型。通过实测内涝积水点信息对模型进行验证,分别模拟20年和30年一遇24 h长历时暴雨条件下研究区域规划前后的内涝区位及风险等级,并分析其内涝削减情况,绘制内涝风险图。结果表明:与实测值相比,模型模拟误差<6%,具有较高的模拟精度;规划后与规划前相比,积水面积峰值削减率的平均值分别达到41.6%和45.03%,积水水深峰值削减率的平均值分别达到51.74%和56.05%,且高风险积水点全部降低为中风险与低风险。耦合数值模型在大尺度城区暴雨致涝风险评估中应用效果较好,研究结果对银川市暴雨易涝点防治及消除具有重要的参考价值。
- 一二维耦合模型 /
- 数值模拟 /
- GPU并行计算技术 /
- 内涝风险评估 /
- 大尺度城区
Abstract: It is very important to carry out the risk assessment of rainstorm-induced inundation in urban areas for inundation regulation and urban security development. This study took the 310 km² main urban area of Yinchuan as an example, to establish an efficient and high-resolution coupled GAST-SWMM model of urban surface inundation and drainage process of underground pipe network based on GPU acceleration technology. The model was verified by the measured information of inundation points. The inundation location and risk level before and after the planning of the study area were simulated respectively under the condition of 24-hour rainstorms with a return period of 20 years and 30 years. The inundation reduction was analyzed and the inundation risk map was drawn. The results showed that compared with the measured values, the simulation error of the model was less than 6%, and the simulation accuracy was higher. After planning, compared with the situation before planning, the average value of the peak water area reduction rate and peak water depth reduction rate reached 41.6% and 45.03%, respectively, and the average value of the peak water depth reduction rate reached 51.74% and 56.05%, respectively, and the high-risk water points were all reduced to medium risk and low risk. The coupled numerical model has a good application effect in the large-scale urban rainstorm-induced inundation risk assessment, and the research results have important reference value for the prevention and elimination of rainstorm-prone inundation points in Yinchuan.
- one-two-dimensional coupled model /
- numerical simulation /
- GPU parallel computing technology /
- inundation risk assessment /
- large-scale urban area

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参考文献(30)

[1]	扈海波. 城市暴雨积涝灾害风险突增效应研究进展[J]. 地理科学进展, 2016, 35(9):1075-1086.
[2]	李昌文,黄艳,严凌志.变化环境下长江流域超标准洪水灾害特点研究[J].人民长江,2022,53(3):29-43.
[3]	侯精明, 康永德, 李轩, 等. 西安市暴雨致涝成因分析及对策[J]. 西安理工大学学报, 2020, 36(3):269-274.
[4]	张鑫,刘康琦,王克树,等.2021年全球典型极端降雨灾害事件对比及综合防御[J].人民长江,2022,53(8):23-29 ,35.
[5]	赵广英,李晨,刘淑娟.城市内涝问题的规划改善途径研究:以湖南省为例[J]. 现代城市研究, 2016(12):51-61.
[6]	胡伟贤,何文华,黄国如.城市雨洪模拟技术研究进展[J]. 水科学进展, 2010, 21(1):137-144.
[7]	宋晓猛,张建云,王国庆,等.变化环境下城市水文学的发展与挑战:Ⅱ.城市雨洪模拟与管理[J].水科学进展, 2014, 25(5):752-764.
[8]	李娜,孟雨婷,王静,等.低影响开发措施的内涝削减效果研究:以济南市海绵试点区为例[J].水利学报, 2018,49(12):1489-1502.
[9]	侯精明,郭凯华,王志力,等.设计暴雨雨型对城市内涝影响数值模拟[J]. 水科学进展, 2017, 28(6):820-828.
[10]	马超,赵凯,齐文超,等.基于示踪方法的沿海城市内涝防灾方案研究[J].水资源保护,2022,38(1):91-99.
[11]	吕金燕,沈旭,赵梦阳.基于SWMM模型的城市排水能力与内涝风险评估[J].市政技术,2022,40(7):237-241.
[12]	张菲菲,谭琳珊,赵强强,等.基于水动力模型的城市内涝灾害研究:以宁波市白鹤社区为例[J].自然灾害学报,2021,30(6):209-218.
[13]	张爽,杨翠巧,邵薇薇,等.基于Mike Urban的高度城市化地区内涝交通风险分析[J].水利水电技术,2021,52(11):10-18.
[14]	SMITH L S,LIANG Q. Towards a generalised GPU/CPU shallow-flow modelling tool[J]. Computers & Fluids,2013,88(12):334-343.
[15]	ZHANG L L, LIANG Q H, WANG Y L, et al. A robust coupled model for solute transport driven by severe flow conditions[J]. Journal of Hydro-Environment Research,2015, 9(1): 49-60.
[16]	HOU J M, LIANG Q H, SIMONS F, et al. A 2D well-balanced shallow flow model for unstructured grids with novel slope source term treatment[J]. Advances in Water Resources, 2013, 52(2): 107-131.
[17]	HOU J M, LIANG Q H, LI Z B, et al. Numerical error control for second-order explicit TVD scheme with limiters in advection simulation[J]. Computers & Mathematics with Applications, 2015, 70(9):2197-2209.
[18]	HOU J M, LIANG Q H, ZHANG H B, et al. An efficient unstructured MUSCL scheme for solving the 2D shallow water equations[J]. Environmental Modelling & Software, 2015, 66: 131-152.
[19]	HOU J M,SIMONS F,MAHGOUB M,et al. A robust well-balanced model on unstructured grids for shallow waterflows with wetting and drying over complex topography[J]. Computer Methods in Applied Mechanics & Engineering,2013,257(15):126-149.
[20]	LIANG Q H,XIA X L,HOU J M. Catchment-scale high-resolution flash flood simulation using the GPU-based Technology[J]. Procedia Engineering,2016,154(6):975-981.
[21]	姚焕玫,卢燕南,王石.基于SWMM模型的南宁市海绵城市建设优化模拟[J].环境工程,2019,37(11):102-109 ,188.
[22]	刘耀台. 城市排水管网模拟评价与径流控制方案优化[D].哈尔滨:哈尔滨工业大学,2021.
[23]	覃钊. 基于SWMM的精细化水文模拟及LID布设研究[D].广州:广东工业大学,2021.
[24]	吴俊毅, 秦华鹏. 基于一二维耦合内涝模型的城市道路积水来源量化分析[J]. 北京大学学报(自然科学版), 2021, 57(4):716-722.
[25]	栾广学, 侯精明, 郭敏鹏, 等. 海绵改造对城市内涝过程的时空影响分析[J]. 中国防汛抗旱, 2021, 31(10):5-9 ,41.
[26]	何佳琪. 合流制排水管网溢流模拟及优化研究[D].合肥:安徽建筑大学,2017.
[27]	聂铁锋. 广州市城区暴雨径流非点源污染负荷核算技术研究[D].广州:华南理工大学,2012.
[28]	黄绵松,杨少雄,齐文超,等.固原海绵城市内涝削减效果数值模拟[J].水资源保护,2019,35(5):13-18 ,39.
[29]	冯嘉宝,许欢,王婷.广州城市内涝的分布特征及其模拟[J].广东气象,2023,45(3):1-6.
[30]	潘文俊,柳树票,徐嫣,等.基于多维耦合模型的城区内涝模拟及风险评估[J].陕西水利,2022(10):19-22.