PDF(6107 KB)
Risk Analysis of Urban Public Transit System under Multiple Rainstorm Waterlogging Scenarios: A Case Study of Tianjin
CHEN Jing, LUO Hong-lei, LI Yu-jie, YANG Jie, JIANG Song, LIN Yi
Journal of Changjiang River Scientific Research Institute ›› 2026, Vol. 43 ›› Issue (6) : 118-126.
PDF(6107 KB)
PDF(6107 KB)
Risk Analysis of Urban Public Transit System under Multiple Rainstorm Waterlogging Scenarios: A Case Study of Tianjin
[Objective] This study assesses the waterlogging risk of the bus system in Tianjin’s central urban area using a zonal layered numerical simulation model. The systematic assessment includes identifying risks at bus routes and stops,analyzing the spatial distribution of waterlogging risk,and quantifying the length of inundated road sections. [Methods] The waterlogging disaster risks on bus routes in Tianjin’s central urban area were assessed and analyzed under short-duration (3-hour) and long duration (24-hour) design storm hyetographs. The Pilgrim & Cordery hyetograph was used for the short-duration design storm,and a frequency-consistent hyetograph design method was used for the long-duration one. A zonal layered mathematical model for urban rainstorm waterlogging was established,incorporating both two-dimensional planar and three-dimensional spatial simulation approaches to account for the heterogeneity of the urban underlying surface. This model coupled hydrodynamic modules for communities,roads,rivers,and pipe networks,enabling refined simulation of the central urban area and the prediction of waterlogging risks on road sections. Using design storms of various return periods (for both 3-hour and 24-hour durations) as precipitation boundaries,and based on the current status of drainage facilities,the model simulated the waterlogging risks on bus routes within the area inside the Outer Ring Road under different return periods. [Results] 1) Case study simulations of waterlogging risks on bus routes were performed for two rainstorm events of different intensity. In terms of the simulation of key road sections,12 out of the 14 waterlogged and closed roads announced by the traffic management department during Event 1 were simulated to meet the traffic interruption criteria (i.e.,waterlogging risk at Level 3 or above). During Event 2,all four simulated underpass interruption points met the criteria. The model demonstrated high accuracy in simulating road traffic interruption risks and could well match the actual waterlogging-induced traffic interruption situations. From the perspective of simulating the waterlogging risk distribution of individual bus routes,the model could clearly reflect the spatial distribution characteristics of waterlogging risks on a single bus route,providing customized support for the refined assessment and management of waterlogging risks on individual bus routes. 2) Under the scenarios of design storms with different return periods,the impacts of short-duration (3-hour) and long-duration (24-hour) rainfall on waterlogging risks of bus routes were simulated,and the waterlogging risks of bus routes under various return periods were further analyzed. The results indicated that the number of bus routes and stops with Level 1 waterlogging risk caused by short-duration rainstorms was larger than that caused by long-duration ones. In contrast,the number of bus routes and stops with waterlogging risk at Level 2 or above induced by long-duration rainfall was higher than that induced by short-duration rainfall. Under each return period,the maximum rainfall intensity of the 24-hour duration was greater than that of the 3-hour duration,which resulted in more prominent waterlogging risks at Level 2 or above under long-duration rainfall. Meanwhile,the relatively long duration of short-duration intense precipitation led to a wider impact range of Level 1 waterlogging risk. [Conclusion] Bus routes with high waterlogging risks in the central urban area are highly agglomerated in six old urban districts,where the public transit network is densely distributed. Once a waterlogging disaster occurs,it is prone to triggering severe public transportation paralysis. The simulation results from two rainstorm case studies validated the model’s effectiveness. It accurately identified key points of transit service interruption and mapped the risk distribution along individual routes,thereby providing a scientific research method for the flood control and dispatch of public transit systems. Restricted by the current status of built-up areas,it is recommended that the drainage capacity of waterlogging-prone road sections should be improved by constructing new pumping stations and adding temporary drainage measures. Meanwhile,traffic management department should establish a mechanism for waterlogging risk assessment and emergency response of public transit routes based on the early warning information from multiple departments,formulate transit flood response plans,and timely adjust or suspend the operation of transit routes to avoid losses.
bus routes / bus stops / waterlogging simulation / waterlogging disaster / risk assessment
| [1] |
|
| [2] |
|
| [3] |
薄坤, 杨正, 赖雄飞, 等. 暴雨内涝下城市公交线网应急点识别方法[J]. 交通运输工程与信息学报, 2022, 20(3): 57-67.
(
|
| [4] |
尹志聪, 郭文利, 李乃杰, 等. 北京城市内涝积水的数值模拟[J]. 气象, 2015, 41(9): 1111-1118.
(
|
| [5] |
|
| [6] |
丛翔宇, 倪广恒, 惠士博, 等. 基于SWMM的北京市典型城区暴雨洪水模拟分析[J]. 水利水电技术, 2006, 37(4): 64-67.
(
|
| [7] |
董欣, 陈吉宁, 赵冬泉. SWMM模型在城市排水系统规划中的应用[J]. 给水排水, 2006, 32(5): 106-109.
(
|
| [8] |
李建勇. Infoworks ICM在城市排水系统分析中的应用[J]. 中国给水排水, 2014, 30(8): 21-24.
(
|
| [9] |
黄国如, 王欣, 黄维. 基于InfoWorks ICM模型的城市暴雨内涝模拟[J]. 水电能源科学, 2017, 35(2): 66-70, 60.
(
|
| [10] |
Danish Hydraulic Institute. Mike Flood 1D-2D Modelling User Manual[M]. Copenhagen: Danish Hydraulic Institute, 2012.
|
| [11] |
徐向阳. 平原城市雨洪过程模拟[J]. 水利学报, 1998, 29(8):34-37.
(
|
| [12] |
陈靖, 李大鸣, 郝莹, 等. 分区层化立体多重天津城市暴雨内涝模型研究[J]. 水动力学研究与进展(A辑), 2019, 34(3):367-376.
(
|
| [13] |
陈靖. 城市暴雨内涝仿真模拟技术及其应用[M]. 北京: 气象出版社, 2021.
(
|
| [14] |
解以扬, 李大鸣, 李培彦, 等. 城市暴雨内涝数学模型的研究与应用[J]. 水科学进展, 2005, 16(3): 384-390.
(
|
| [15] |
|
| [16] |
解以扬, 韩素芹, 由立宏, 等. 天津市暴雨内涝灾害风险分析[J]. 气象科学, 2004, 24(3): 342-349.
(
|
| [17] |
朱呈浩, 夏军强, 陈倩, 等. 基于SWMM模型的城市洪涝过程模拟及风险评估[J]. 灾害学, 2018, 33(2):224-230.
(
|
| [18] |
徐奎, 马超. 福州市主城区洪涝灾害成因分析及对策研究[J]. 水利水电技术, 2011, 42(10): 113-118.
(
|
| [19] |
|
| [20] |
李熙莹, 梁靖茹, 郝腾龙. 考虑连锁冲突的城市公交车行车风险量化分析方法[J]. 交通信息与安全, 2022, 40(3): 19-29.
(
|
| [21] |
俞峥嵘, 张彤, 罗建宇, 等. 公交行车安全风险研判与预警信息系统研究[J]. 安全, 2021, 42(8):20-24.
(
|
| [22] |
姚国胜. 浅谈天津公交线网规划[C]// 第二十一届海峡两岸都市交通学术研讨会论文集. 成都:四川省科学技术协会,2013. (YAO Guo-sheng.A Brief Discussion on the Planning of Tianjin Public Transport Network[C]// The Proceedings of the 21th Cross-Strait Transportation Academic Seminar. Chengdu: Sichuan Association for Science and Technology, 2013.) (in Chinese)
|
| [23] |
|
| [24] |
|
| [25] |
牟金磊. 北京市设计暴雨雨型分析[D]. 兰州: 兰州交通大学, 2011.
(
|
/
| 〈 |
|
〉 |