Affiliations: [a] Institute of Data Science, City University of Macau, China
| [b]
The Post-Doctoral Research Center of Zhuhai Da Hengqin Science and Technology Development Co., Ltd, China
| [c] Zhuhai Da Hengqin Science and Technology Development Co., Ltd, Hengqin New Area, China
Correspondence:
[*]
Corresponding author. Li Daming, E-mail: dmli@cityu.mo.
Abstract: With the rapid development of urban construction and the further improvement of the degree of urbanization, despite the intensification of the drainage system construction, the problem of urban waterlogging is still showing an increasingly significant trend. In this paper, the authors analyze the risk evaluation of urban rainwater system waterlogging based on neural network and dynamic hydraulic model. This article introduces the concept of risk into the study of urban waterlogging problems, combines advanced computer simulation methods to simulate different conditions of rainwater systems, and conducts urban waterlogging risk assessment. Because the phenomenon of urban waterlogging is vague, it is affected by a variety of factors and requires comprehensive evaluation. Therefore, the fuzzy comprehensive evaluation method is very suitable for solving the risk evaluation problem of urban waterlogging. In order to improve the scientificity of drainage and waterlogging prevention planning, sponge cities should gradually establish rainwater impact assessment and waterlogging risk evaluation systems, comprehensively evaluate the current capacity of urban drainage and waterlogging prevention facilities and waterlogging risks, draw a map of urban rainwater and waterlogging risks, and determine the risk level. At the same time, delineate drainage and waterlogging prevention zones and risk management zones to provide effective technical support for the formulation of drainage and storm waterlogging prevention plans and emergency management.
