基于耦合机理模型与数据模型的城市管网运行风险预测

龙岩; 曲佳; 左向阳; 李韫昱; 刘子维; 陆寅飞

doi:10.13928/j.cnki.wrahe.2025.04.002

水利水电技术（中英文） ›› 2025, Vol. 56 ›› Issue (4) : 12 -24. DOI: 10.13928/j.cnki.wrahe.2025.04.002

复合极端天气气候事件与洪涝灾害机理专栏

基于耦合机理模型与数据模型的城市管网运行风险预测

龙岩 ¹^,² ,
曲佳 ¹^,² ,
左向阳 ¹^,² ,
李韫昱 ³ ,
刘子维 ¹^,² ,
陆寅飞 ⁴

作者信息 +

Operational risk prediction of urban pipe network based on coupling mechanism model and data model

Yan LONG ¹^,² ,
Jia QU ¹^,² ,
Xiangyang ZUO ¹^,² ,
Yunyu LI ³ ,
Ziwei LIU ¹^,² ,
Yinfei LU ⁴

Author information +

文章历史 +

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摘要

【目的】全球极端气候事件频发、城市化进程加快，致使城市内涝问题日益严峻，城市管网排水压力显著增大，及时判断管网运行状况显得尤为重要。【方法】以广州市黄埔区文涌排涝片为研究对象，基于SWMM模型构建洪涝过程分析机理模型，研判不同降雨情景管段充满度情况；然后，基于单井、多井计算模式构建数据模型，对城市管段充满度进行预测，并选最适合的数据模型；最后，基于改进的层次分析法和综合风险指数法，对城市管网运行风险进行评价。【结果】结果表明：(1)基于多井计算模式的决策树模型精度最优，RMSE为0.077,MAE为0.030,单次工况运行时间较SWMM模型提升60万倍。(2)在敏感点聚集区社会因素对管网运行风险影响最大，所占权重为0.72;在敏感点非聚集区经济因素对管网运行风险影响最大，所占权重为0.68。【结论】基于多井计算模式的决策树模型可满足城市内涝应急响应的精度和时效性要求；城市不同区域对管网运行风险的约束因素不同，需要因地制宜提出改进措施。

Abstract

[Objective] The frequent occurrence of global extreme climate events and the rapid pace of urbanization have resulted in increasingly severe urban waterlogging issues, leading to a significant rise in drainage pressure within urban pipe networks. It is of utmost importance to promptly assess the operational status of these pipe networks. [Methods] The flood process analysis mechanism model of the Wenchong drainage system in Huangpu District, Guangzhou, was established based on the SWMM model to determine the hydraulic capacity of pipeline sections under different rainfall scenarios. Subsequently, a data model incorporating both single-well and multi-well computing models was developed to predict the hydraulic capacity of urban pipe sections, with careful selection of the most suitable data model. Finally, an evaluation of operational risk for the urban pipe network was conducted using an improved analytic hierarchy process and comprehensive risk index method. [Results] The results show that:(1) The decision tree model based on the multi-well calculation mode has the highest accuracy, with an RMSE of 0.077 and a MAE of 0.030, and the single-well calculation time is 600,000 times faster than the SWMM model.(2) In the area where sensitive points are concentrated, social factors exert the most significant influence on the operational risk of the pipe network, with a weightage of 0.72. In contrast, in the area where sensitive points are not concentrated, economic factors play a dominant role in determining the operational risk of the pipe network, carrying a weightage of 0.68. [Conclusion] The decision tree model based on the multi-well calculation mode can meet the precision and timeliness requirements for urban flood emergency response. The risk of pipe network operation varies across different areas of the city, necessitating the proposal of improvement measures tailored to local conditions.