考虑地下管网健康状态的城市内涝韧性评估模型研究

鹿伟 ,  孟凌霄 ,  刘春雷 ,  宋晓龙 ,  胡晓旭 ,  许英东 ,  张艺文

山东农业大学学报(自然科学版) ›› 2026, Vol. 57 ›› Issue (4) : 583 -597.

PDF (58234KB)
山东农业大学学报(自然科学版) ›› 2026, Vol. 57 ›› Issue (4) : 583 -597. DOI: 10.3969/j.issn.1000-2324.2026.04.001

考虑地下管网健康状态的城市内涝韧性评估模型研究

作者信息 +

Research on Urban Flooding Resilience Assessment Model Considering the Health Status of Underground Pipeline Network

Author information +
文章历史 +
PDF (59631K)

摘要

随着降雨持续加强与城市化快速发展,城市内涝已成为全球范围内广泛关注的城市治理难题。在此背景下,韧性城市已成为指导城市建设与设施运维的重要理念。本文针对城市地下排水管网健康状态与降雨-内涝演化过程的动态耦合关系,采用InfoWorks ICM模拟与熵权法相结合的方法,量化分析了排水管网病害对局部城市区域内涝韧性的影响规律。研究结果表明: (1)将管网病害作为重要因素纳入内涝韧性指标体系后,压力层权重由0.206 0大幅提升至0.402 1,成为主导性准则层,其中管网淤堵数、管网断裂数权重值分别为0.162 0、0.067 3,成为核心的消极指标,合计贡献总权重的22.93%。可见,排水管网病害是城市内涝积水的重要诱因; (2)内涝韧性指数与区域排水管网健康状态呈正相关,即区域排水管网病害程度越低,内涝韧性指数越高,该区域对内涝的消纳韧性水平越高。 (3)针对不同韧性等级区域的内涝防控,提出差异化韧性提升策略,高韧性区域需以精细化常态运维为主;中韧性区域需聚焦管网病害修复与雨污分流改造;低韧性区域则应开展生态化改造,根本性地提升区域蓄洪能力。本研究所构建的评估方法可为类似区域的韧性评估奠定基础,为更科学的城市规划、管网改造与内涝应急响应决策提供依据。

Abstract

As rainfall continues to intensify and urbanization rapidly advances, urban flooding has become a widely concerned urban governance challenge globally. In this context, resilient cities have emerged as a crucial concept guiding urban construction and infrastructure maintenance. Focusing on the dynamic coupling between the health status of urban drainage networks and the evolution process of rainfall-induced waterlogging, this study quantitatively analyzes the impact of drainage network defects on the waterlogging resilience within local urban areas by combining InfoWorks ICM simulation with the entropy weight method. The research findings indicate that: (1) After incorporating network defects as an important factor into the waterlogging resilience index system, the weight of the pressure layer increases significantly from 0.206 0 to 0.402 1, making it the dominant criterion layer. Specifically, the weights of network blockage count and network fracture count are 0.162 0 and 0.067 3, respectively, serving as core negative indicators, contributing 22.93% to the overall weight. Evidently, drainage network defects are a significant cause of urban waterlogging; (2) The waterlogging resilience index is positively correlated with the health status of regional drainage networks, meaning that the lower the degree of network defects, the higher the waterlogging resilience index, indicating a higher level of resilience to waterlogging in the area. (3) For waterlogging prevention and control in areas with different resilience levels, differentiated resilience enhancement strategies are proposed. High-resilience areas should prioritize refined routine operation and maintenance; medium-resilience areas should focus on network defect repair and rainwater-sewage diversion renovation; low-resilience areas should undertake ecological renovation to fundamentally enhance regional flood storage capacity. The evaluation method established in this study can lay a foundation for resilience assessment in similar areas and provide a basis for more scientific urban planning, pipe network renovation, and emergency response decision-making for waterlogging.

关键词

内涝韧性 / 管网病害 / InfoWorks ICM / 熵权法 / 韧性指标

Key words

Urban flood resilience / pipeline defects / infoWorks ICM / entropy weight method / resilience indicators

引用本文

引用格式 ▾
鹿伟,孟凌霄,刘春雷,宋晓龙,胡晓旭,许英东,张艺文. 考虑地下管网健康状态的城市内涝韧性评估模型研究[J]. 山东农业大学学报(自然科学版), 2026, 57(4): 583-597 DOI:10.3969/j.issn.1000-2324.2026.04.001

登录浏览全文

4963

注册一个新账户 忘记密码

参考文献

[1]

Lin J Y, He P T, Yang L, et al. Predicting future urban waterlogging-prone areas by coupling the maximum entropy and flus model[J]. Sustainable Cities and Society, 2022, 80: 103812.

[2]

Güneralp B, Reba M, Hales B U, et al. Trends in urban land expansion, density, and land transitions from 2070 to 2010: A global synthesis[J]. Environmental Research Letters, 2020, 15(4): 044015.

[3]

Chocat B, Ashley R, Marsalek J, et al. Toward the sustainable management of urban storm-water[J]. Indoor and Built Environment, 2007, 16(3): 273-285.

[4]

Kundzewicz Z W, Su B, Wang Y, et al. Flood risk and its reduction in China[J]. Advances in Water Resources, 2019(AUG.), 130: 37-45.

[5]

Jiang L, Yu J, Wen J H, et al. Risk assessment of extreme flood in the north bank of the hangzhou bay under land use change scenarios[J]. Progress In Geography, 2021, 8: 1355-1370.

[6]

中华人民共和国水利部. 中国水旱灾害防御公报[M]. 北京: 中国水利水电出版社, 2024: 132.

[7]

AJiménez E, Bodoque J M, García J A. An Integrated Multidimensional Resilience Index for urban areas prone to flash floods: Development and validation[J]. Science of The Total Environment, 2023, 894: 164935.

[8]

任捷, 王子航, 梁学琴, 等. 基于PSR框架的黄河流域中心城市洪涝韧性研究[J]. 人民黄河, 2025, 47(03): 62-68.

[9]

代鑫, 黄弘, 于富才, 等. 暴雨内涝灾害下社区韧性压力测试方法研究[J]. 清华大学学报(自然科学版), 2024, 64(09): 1587-1596.

[10]

Liu J, Wang X Y, Gao G J. Spatiotemporal evolution and determinants of urban flood resilience: A case study of Yellow River Basin[J]. Sustainability, 2025, 17 (4): 1433.

[11]

Wang L Y, Li R Y, Dong X. Integrated modeling of urban mobility, flood inundation, and sewer hydrodynamics processes to support resilience assessment of urban drainage systems[J]. Water Science and Technol, 2024, 90(1): 124-141.

[12]

Xu T, Xie Z Q, Jiang F S, et al. Urban flooding resilience evaluation with coupled rainfall and flooding models: a small area in Kunming City, China as an example[J]. Water Sci Technol, 2023, 87(11): 2820-2839.

[13]

Bertilsson L , Wiklund K , Tebaldi I D M , et al. Urban flood resilience - A multi-criteria index to integrate flood resilience into urban planning[J]. Journal of Hydrology, 2019, 573: 970-982.

[14]

Yu S Y, Kong X S, Wang Q, et al. A new approach of Robustness-Resistance-Recovery (3Rs) to assessing flood resilience: A case study in Dongting Lake Basin [J]. Landscape and Urban Planning, 2023, 230: 104605.

[15]

徐宗学, 舒心怡, 叶陈雷. 融合自然-社会属性的城市洪涝韧性评估[J]. 人民黄河, 2025, 47(09): 55-61+ 69.

[16]

王银堂, 苏鑫, 王磊之, 等. 城市洪涝灾害应对韧性精细化评估[J]. 水科学进展, 2025, 36(06): 933-948.

[17]

肖凤林, 卜王超, 屠飞翔, 等. 城市街道尺度下洪涝灾害韧性评估——以江苏宜兴市宜城街道为例[J]. 中国防汛抗旱, 2025, 35(08): 1-11.

[18]

中华人民共和国住房和城乡建设部. 室外排水设计标准: GB 50014-2021[S]. 北京: 中国计划出版社, 2021.

[19]

Yang Y Y, Guo H X, Wang D Y, et al. Flood vulnerability and resilience assessment in China based on super-efficiency DEA and SBM-DEA methods[J]. Journal of Hydrology, 2021, 600: 126470.

[20]

Wu Y W, Yu G Y, Shao Q X. Resilience benefit assessment for multi-scale urban flood control programs[J]. Journal of Hydrology, 2022, 573(A): 128349.

[21]

况诗祥, 王渲, 刘志鹏, 等. 规划场景下基于涝水特征的城市洪涝韧性评估研究[J]. 给水排水, 2025, 61(02): 43-49.

基金资助

中建股份科技研发计划资助(CSCEC-2024-Z-31)

国家自然科学基金(52309132)

AI Summary AI Mindmap
PDF (58234KB)

0

访问

0

被引

详细

导航
相关文章

AI思维导图

/

〈 〉