Multi-Mode Surface Generalization Supports a Detailed Urban Flooding Simulation Model

Abstract

With the aim of achieving high precision and high efficiency, recent research on hydraulic flood models has tended to focus on the algorithms for solving the shallow water equations of Saint-Venant. While development of the algorithms will help to improve the simulation precision and the solving of specific problems, the other influential factor in flood risk modeling is the precision and reasonable generalization of the data. This is even more important for increasing the model’s computational accuracy and efficiency but is frequently undervalued. Frequent rainstorm waterlogging is having a serious impact on China’s large cities. Early warning of waterlogging risk following a rainstorm forecast is an effective method for preventing or reducing potential losses. Concrete waterlogging information including locations, depth, and process is essential for early warnings. This paper focuses on the influence of data precision and reasonable generalization on an urban flooding model. A detailed hydraulic urban flooding model characterized by detailed data processing and component coupling can help to provide advance information. In Beijing city, road networks, overpasses, and buildings are so highly concentrated that rainstorms easily result in waterlogging in low-lying locations. Therefore, partial microrelief is the determinate factor in waterlogging simulation. This paper shows that multi-mode surface data generalization and detailed model coupling support a perfect simulation of a Beijing urban flooding model. The influence of buildings, roads, and overpasses on surface water flow was carefully considered based on the innovative aspect of a fine generalization of partial microrelief. One novelty is the simulation of the whole overland flow from the beginning of rainfall to mesh, not only from manhole overflow, because the waterlogging is caused mainly by initial surface water runoff rather than by manhole overflow. A second novelty is the use of a new kind of coupling mode based on physical mechanisms between surface and pipe models. Here, rain perforated strainers instead of manholes play a role as flow exchange points between pipe and surface. This coupling mode is much closer to the real world. Based on a detailed Beijing urban flooding model, a scenarios library of typical rainfall events and corresponding waterlogging results was constructed. Several years of practice have demonstrated that a rich library of scenarios can be used effectively for the quick identification and early warning of waterlogging risk for a forecast rainfall. Test results show that multi-mode surface generalization is effective in improving outcomes and useful for scientific decision making in controlling urban waterlogging.

Enhanced reservoir flood prevention by using leveraging sensor technology

“…Effective flood management is vital because flooding in the basin poses serious dangers to infrastructure, agriculture, and communities. It also demonstrates the promise of data-driven solutions and cutting-edge hardware in reducing the impact of natural calamities [10]. A state-of-the-art project called the Sensor-Based Flood Prevention for Reservoirs Project aims to address one of nature's most difficult problems: flooding brought on by excessive rainfall.…”

Risk analysis of waterlogging in a big city based on a bow-tie Bayesian network model, using the megacity of Wuhan as an example

“…Zhang et al (2023) proposed a method of urban storm flooding risk assessment integrating social information to address the problem that the existing urban storm flooding risk assessment did not fully consider social information, obtained natural information of flooding disasters based on urban rainfall and flooding models, captured social information using web crawler technology, established an urban storm flooding risk assessment index system coupling natural and social information, and comprehensively assessed the risk through an index model. Xu et al (2021) constructed a flooding model based on an InfoWorks ICM model for Beijing City and analyzed the drainage capacity of the urban pipe network and waterlogging characteristics. Using an ArcGIS network analysis module to evaluate the reach and response time of three types of emergency services (public security, medical, and fire) under single and combined scenarios, the city's emergency response capability was determined.…”