Spatial-temporal evolution of influencing mechanism of urban flooding in the Guangdong Hong Kong Macao greater bay area, China - Zhang, Chunbo; Xu, Tao; Wang, Teng; Zhao, Yaolong (Frontiers in Earth Science, 2023)
Extreme weather has been more frequent in recent years. Urban agglomerations, as areas with high density of human activities, have been plagued by storm waterlogging. Historically, the main focus of attention on flood control in urban agglomerations has gradually shifted from underground pipe networks to impervious surface, reflecting profound changes in the influencing mechanism of urban waterlogging. Exploring the evolution of the mechanisms influencing storm waterlogging in the Guangdong Hong Kong Macao Greater Bay Area (GBA) urban agglomeration is of great reference significance for formulating storm waterlogging prevention and control measures and promoting high-quality development of the GBA city cluster. In this paper, we make full use of the collected information on urban storm waterlogging events from 1980 to 2018 in the GBA city cluster. Correlation analysis and geographically weighted regression (GWR) are used to analyze the influence of impervious surface percentage (ISP), impervious surface aggregation index (AI), impervious surface mean shape index (Shape_MN), vegetation cover (FVC), water surface ratio (WSR), relative elevation (RE) and Slope on storm waterlogging in urban clusters and their evolution characteristics over time from global perspective and spatial heterogeneity, respectively. The results show that: (1) ISP, AI, Shape_MN and WSR are positively correlated with urban waterlogging, while FVC, RE and Slope are negatively correlated with urban waterlogging. The correlations of each factor showed a general trend of gradual strengthening in time, and the increase rate slowed down after 2000, and the correlation of WSR showed a relatively obvious decrease. (2) The results of GWR show that the influence of each factor on urban storm waterlogging has obvious spatial-temporal heterogeneity, and each factor shows different distribution characteristics. This study uses long time series of urban storm waterlogging point data to explore the spatial-temporal evolution of the influencing mechanism of storm waterlogging in the GBA urban agglomeration. We hope to provide a scientific basis for an in-depth understanding of the causes of urban storm waterlogging in the GBA, with a view to providing auxiliary decision-making support for the formulation of waterlogging prevention and control measures.