Research On Commuters’ Exposure To Pluvial Flash Flooding And Its Impacts On The Peak Traffic Features

In the context of global climate change and unprecedented rapid urbanization,and with the effect of inefficient drainage systems and flood control infrastructure,pluvial flash flood(PFF)disasters have been quite usual in most of China’s big cities.In the face of PFF events,inundation is often found on urban roads which are also important channels for flood water diffusing in the form of “point→line→area”.However,road network also plays a vital role in maintaining the normal functioning of the urban system,because it carries the transportation of production and living materials as well as all citizens’ daily travel activities.Therefore,once a PFF event causes traffic disruption or paralysis,the overall urban life would be seriously and negatively impacted.At present,China’s research work on accurately quantifying the impact of floods on urban traffic is not adequate.In this research,FloodMap-HydroInundation 2D and high-precision terrain data(with a resolution of 5 m)were used to simulate the dynamic diffusion process of PFF in the traffic network.Special attention was paid to the commuting group.Specifically,commuters’ flood exposure was assessed and their response regarding departure time and travel mode choices were analyzed under PFF scenarios.Meanwhile,commuting delays during the morning peak hours and the spatiotemporal variation of traffic congestion caused by a 100-year PFF event were investigated.Additionally,this research also studied the potential effect of PFF on metro accessibility and ridership.The target is to provide theoretical and case supports for building an urban transport system capable of coping with future climate change and extreme PFF events.Specific research contents and key conclusions are as follows.(1)In general,commuting is the most important source and incentive for traffic congestion during peak hours.To better delineate the impact of PFF disasters on urban commuting,it is essential to study the commuting patterns under normal weather conditions at first.Specifically,this research proposes a method for using points-ofinterest(POI)data to estimate employment locations,and combined with resident workers data,to implement a gravity-based model to estimate interzonal commuting patterns in the central urban area(CUA)of Shanghai,China.The results reveal that there are 7 noticeable job centers in the CUA,including Caoyang New Village,Hongqiao Development Zone,Xujiahui,Zhongshan Park,Nanjing Road,Wujiaochang and Lujiazui,6 of which are in Puxi(the west of Huangpu River).Moreover,there is a “busy corridor” in the west of the CUA during the morning peak hours.Here is the zone which witnesses the largest commuting volume,the heaviest traffic and the most awful congestion.(2)As an important originality point,this research proposes a trip-based method to measure exposure,which used two trip datasets: the path data extracted from commuting patterns estimated by the gravity model,and the survey data collected from sample commuters throughout Shanghai.Based on the measure results,the spatial and social heterogeneity of commuters’ flood exposure were analyzed respectively.Meanwhile,a preliminary investigation was conducted to identify factors causing heterogeneity in exposure between different zones and different social groups.The results show that the average exposure in the outer ring zone is higher than that in the middle ring zone and the inner ring zone;average exposure in Pudong is higher than that in Puxi.Besides,average exposure of the male,the married,the middle-aged,the middle-high income groups,and people who work for the basic functional service are relatively higher.The zonal average exposure is significantly correlated with the commuting distance which is significantly correlated with the zone’s industry composition,but this correlation cannot be transmitted through the intermediary variable: commuting distance.The average exposure of different commuters shows very weak correlation with their social attributes except for gender and occupation.Moreover,due to strict time and space constraints,about 80% commuters would slightly or not postpone the departure time.The other 20% would ask for work leave or wait until the rain stops,indicating that the travel demand under PFF scenarios will be reduced by 20% or so.In addition,most people would choose to travel by car(38%)or public transit(31%)under PFF scenarios.(3)To study the impact of PFFs on commuters traveling by cars,this research constructs a traffic simulation method and tool capable of integrating flood modeling and traffic analysis to reveal the interplay between these two dynamic processes.Specifically,the “busy corridor” was selected as the simulation area,and the traffic flow during the morning peak hours was simulated under the 100-year PFF scenario.The results indicate that PFFs have significant impact on travel time but trifling impact on travel distance.The delay of most vehicles diverted to dry links is lower than 10 min,but the delay of vehicles trapped in flooded links may reach 1~3 h.If a 100-year PFF occurred,the congestion period would be postponed by 1 h(from 8:00~10:00 AM to 9:00~11:00 AM).The largest vehicle volume variation is found during the last hour of the simulation period(11:00~11:00 AM),as well as found on major arterial roads(level-Ⅰ)and local roads(level-Ⅳ),which are of primary concern in the traffic control and grooming work under PFF scenarios.(4)To study the impact of PFFs on commuters traveling by public transit which also constitutes a sizeable share of the travel modes under PFF scenarios,this research pays special attention to Shanghai Metro and focuses on the metro station’s accessibility and ridership.Specifically,taking time as the impedance,accessibility to metro stations by three access modes(walking,cycling,and driving)was measured through three impedance functions(inverse power,negative exponential,and modified Gaussian).Meanwhile,taking distance as the impedance,ridership was measured with consideration of the distance-decay effect on stations’ attraction for passengers.The results reveal that metro accessibility in central Shanghai is quite equitable,even in the PFF scenario.87% of the communities can access the metro stations at the medium and medium-high accessibility levels in the normal scenario,but 80% can access only at the low and medium levels in the PFF scenario.Moreover,since road links with serious inundation impose notable restrictions on access journeys especially by cycling and driving,45 stations would be less or not accessible,and 15 more stations may face the challenge of serving more than 50,000 passengers,which is much larger than their normal ridership.These findings have important implications for the formulation of safer usage of public transport in the face of heavy rainfall and associated flood events.