PROGRESS IN GEOGRAPHY ›› 2018, Vol. 37 ›› Issue (6): 772-780.doi: 10.18306/dlkxjz.2018.06.004

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Urban traffic congestion caused by rainstorms and innudation

Wenyan HU1,2(), Mengya LI1,2, Jun WANG1,2,*(), Qingyu HUANG1,2   

  1. 1. Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University, Shanghai 200241, China
    2. School of Geographic Sciences, East China Normal University, Shanghai 200241, China
  • Received:2017-07-18 Revised:2018-01-10 Online:2018-06-28 Published:2018-06-28
  • Contact: Jun WANG;
  • Supported by:
    National Natural Science Foundation of China, No.51761135024, No.41671095, No.71373084


In recent years, pluvial flash floods (PFF) have caused serious traffic congestion and disruption in many big cities. This study investigated the traffic congestion pattern due to PFFs in an intra-urban area through a macro traffic simulation method. A macro traffic flow model was built based on trip distribution and the characteristics of roads and routing. We incorporated rainfall data and simulated the hourly traffic volume on each road segment under two PFF scenarios of 50-year and 100-year return periods by the macro traffic flow model. Next, the variation of volume/capacity (V/C) on each road was calculated to derive the spatial pattern of traffic condition under different PFF scenarios. The results were contrasted to demonstrate the change of congestion pattern on the main roads and entrances/exits of the expressways in the city center of Shanghai to analyze the influence of different PFF scenarios on traffic congestion. The results indicate that ①PFFs of 50-year return period may have a marginal effect on the traffic system, but PFFs of 100-year return period can pose great threat to the traffic system in the central urban area of Shanghai. Seven exits and entrances of the expressways are closed due to serious inundation and a large portion of the road network becomes more congested; ②the effect of PFFs on V/C also exhibits spatial disparity over the entire network. Overall, 13.35% of the roads become more congested under 100-year return period. Additionally, the most obvious change of congestion pattern is found on the first-class highways (23.31%), such as Dalian Road, Wuning Road, Zhoujiazui Road, and Changshou Road.

Key words: macro traffic simulation, pluvial flash flood, road network, volume/capacity, Shanghai