Quantifying the spatiotemporal dynamics of urban flooding susceptibility in the greater bay area under shared socio-economic pathways using the SD-PLUS-LightGBM framework

Urbanization and climate change keep intensifying extreme rainfall events. Previous studies have explored urban flood susceptibility, yet a comprehensive approach that unifies these perspectives has remained underdeveloped. This study established a holistic framework using the SD-PLUS-LightGBM model with multiple variables under three SSP-RCP scenarios to predict spatial-temporal dynamics of flood susceptibility in the Greater Bay Area between 2030 and 2050. Compared with traditional models, LightGBM established superior predictive accuracy and operational reliability for urban flood susceptibility mapping. The results indicated a non-linear expansion of high-susceptibility zones, with SSP5–8.5 projections showing a two-fold increase in vulnerable areas by 2050 relative to 2020 baselines. Regions experiencing pronounced susceptibility transitions were expected to grow significantly (0.23 % of the total area), concentrated in historic urban cores and peri‑urban interfaces. This study offered an in-depth approach to stormwater management along with targeted recommendations for sustainable urban planning and design. © 2025

Publisher: Elsevier B.V.