Urban flood risk assessment and analysis with a 3D visualization method coupling the PP-PSO algorithm and building data

• Published in: Journal of environmental management Vol. 268; p. 110521
• Main Authors: Zhi, Guozheng, Liao, Zhenliang, Tian, Wenchong, Wu, Jiang
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15.08.2020
• Subjects: 3D visualization; algorithms; case studies; China; drainage; environmental management; Flood risk assessment; Multi-source heterogeneous data; PP-PSO algorithm; rain; risk; simulation models; spatial data; China; PP-PSO algorithm; 3D visualization; Multi-source heterogeneous data; Flood risk assessment
• ISSN: 0301-4797; 1095-8630; 1095-8630
• DOI: 10.1016/j.jenvman.2020.110521

Due to the influence of buildings on the distribution of flood and their economic and social attributes, 3D spatial information such as the size of buildings and the flooded ratio of buildings relative to their height has an increasing impact on urban flood risk. However, existing flood risk assessment methods mainly use data in 2D and analysis methods are mostly 2D. In this study, flood variation processes were analyzed in the form of 3D dynamic visualization by coupling an urban drainage model and a flood simulation model with 3D visualization methods. By further combining with 3D building models, the 3D spatial information of buildings related to flood was obtained. In order to study the influence of 3D information on flood risk and combine with other multi-source heterogeneous data for integrated analysis, a 3D visualization assessment and analysis method for flood risk, coupled with the projection pursuit-particle swarm optimization algorithm (PP–PSO) was established (3DVAAM-PP-PSO). A case study from Chaohu City, China, was used to demonstrate the method. The results showed that the PP-PSO algorithm can process high-dimensional information and obtain the objective weight of each index. The 3D information from the influenced buildings had an impact on the evaluation results, which needed to be considered. Through the 3D visualization analysis, the overall distribution of flood risk and that around the buildings were obtained in multi-perspectives. The flood risk during different rainfall return periods were analyzed intuitively and comparatively. This study furnishes a novel method for flood risk assessment and analysis by making the most of 3D spatial information. •A 3D visualization assessment and analysis method for flood risk was established.•The 3D information from the influenced buildings had an impact on flood risk.•The assessment results were analyzed in 3D coupling with multi-source data.