Research on the Prediction of Waterlogging Points and Flood Prevention in Urban Pipe Network based on SWMM Modeling

Abstract

Global climate change, increasing extreme precipitation, and the growing problem of urban flooding. Establishing a model that can quickly and accurately simulate the prediction of urban pipeline waterlogging points is a problem that needs to be solved urgently. In this paper, based on the Storm Water Management Model(SWMM), the distribution of pipeline network node ponding points in Baolong Street, Longgang District, Shenzhen City, Guangdong Province, is simulated under different recurrence periods of heavy rainfall, and the pipeline node ponding is used to predict the ponding points in the study area. The results show that the model can accurately predict the historical waterlogging points in the area and realize the simulation of urban flooding waterlogging. Deficiencies in the stormwater carrying capacity of the pipes in the study area were also identified. The model is different from other complex two-dimensional models, simplifies the complexity of the model, reduces the amount of computation can quickly and accurately simulate the prediction of urban waterlogging points. It has an important role in early warning and forecasting for urban flood prevention and control.