An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study

Abstract

With the rapid development of the urbanization process, rainstorm water-logging events occur more frequently in big cities in China, which causes great impact on urban traffic safety and brings about severe economic losses. Water-logging has become a hot issue of widespread concern in China. As one kind of natural disasters and emergencies, rainstorm water-logging has the uncertainties of occurrence, development, and evolution. Thus, the emergency decision-making in rainstorm water-logging should be carried out in stages according to its development trend, which is very complicated. In this paper, an emergency decision-making method was proposed for urban water-logging with a hybrid use of dynamic network game technology, Bayesian analysis, and multi-attribute utility theory. The dynamic game process between “rainstorm water-logging” and “decision-making group” was established and the dynamic generation of emergency schemes was analyzed based on Bayesian analysis in various stages of water-logging. In terms of decision-making attributes, this paper mainly considered two goals, i.e., ensuring smooth traffic and controlling emergency cost. The multi-attribute utility theory was used to select the final scheme. An example analysis in Guangzhou of China showed that the method is more targeted and can achieve emergency management objectives more effectively when compared with traditional methods. Therefore, it can provide reference for the scientific decision-making of emergency management in urban rainstorm water-logging.

Understanding the Use of Heterogenous Data in Tackling Urban Flooding: An Integrative Literature Review

“…Chen et al evaluated evacuation plans by simulation, in which vehicles (e.g., ambulance and emergency communication vehicles) were assigned different degrees of mobility in terms of the number of grids they move at each single turn [50]. Concerning evacuation planning, Ding et al defined the costs of different sizes of rescue team based on the labor cost, equipment rental cost, and material consumption [72]. Earlier in Section 3.1, some studies used the runoff coefficient as a constant parameter in their inundation simulation models.…”

“…The parameter values are typically estimated by considering scenarios that represent the possible realistic situations or learned from the statistics [49,72].…”

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