Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling

Abstract

In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM) and TELAMAC-2D. Second, an agent-based model (ABM) was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km 2 . It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10-and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.

Development of models for assessing a driver's failure­free operation in a transportation system under conditions of traffic congestion

“…Authors of paper [9] carried out a study and found a relationship between the duration of floods due to rainfall in some parts of China and the behavior of drivers, which led to traffic jams. They revealed in a simulation process that the behavior of a driver had a different impact on the formation of traffic jams of different durations.…”

“…Formulas (8) and (9) for the assessment of the probability of an accident at sections of a transport network and at transport nodal points with an individual traffic participant considering model (10)…”

Impact of the Storm Sewer Network Complexity on Flood Simulations According to the Stroke Scaling Method

“…We constructed Chicago design storms [43,44] with four different return periods (2, 10, 50, and 100 years) with a rainfall duration of 2 h based on the following Nanjing storm intensity equation, which was derived from local rainfall records for more than 60 years: i = 64.300 + 53.800lgP (t + 32.900) 1.011 (9) where i is the rainfall intensity (mm/min), t is the rainfall duration (min), and p is the return period (year) of the rainfall event. We chose a rainfall duration of 2 h for the modeling and simulation because the Chicago hyetograph with a rainfall duration of 2 h is considered an appropriate way to simulate extreme rainfall in China [45,46]. The error would increase if a storm longer than 2 h was simulated [45,46].…”

“…We chose a rainfall duration of 2 h for the modeling and simulation because the Chicago hyetograph with a rainfall duration of 2 h is considered an appropriate way to simulate extreme rainfall in China [45,46]. The error would increase if a storm longer than 2 h was simulated [45,46]. Therefore, we designed 16 scenarios for the three sub-basins, as listed in Table 2.…”

Analysis of Flood Evacuation Process in Vulnerable Community with Mutual Aid Mechanism: An Agent-Based Simulation Framework

“…As for the simulation models, in the existing studies, agent-based model (ABM) has been suggested as an appropriate tool to solve the kind of complex system problems such as emergency evacuation. ABM is a type of computational model that can provide the most natural description and simulation of complex adaptive systems, and implement the assumptions of model [15]. Through the simulation of the behaviors and interaction of autonomous agents in the ABM, the dynamic feedback of subsystem components, their inherent complexities and their effects on the system can be captured.…”