A coupled multi-model framework for waterlogging projection: Towards achieving sustainable development goal 11.5.

Modeling potential changes in flooding from urbanization enhances urban risk perception and supports decision-makers in preventative actions of high-risk areas. This study proposes a coupled multi-model framework for projecting the distribution and severity of urban floods and tests for Shenzhen City in China under multi-scenarios. The results show that the coupled multi-model framework has a high accuracy level at 78%. In Shenzhen, the flood-prone areas are more frequently found in the west and less frequently in the east, while the valley regions in the southeast are vulnerable to deep waterlogging. The growth rate of the inundated region slows down as the inundation depth rises after rainfall intensity exceeds that of the 20-year event. The projected results show that the flooding area and waterlogging disaster intensity (WDI) in each watershed in 2035 would be larger those in 2015. In the basins of Chi'ao Reservoir, Ejing Reservoir, and Guangming Farm in the Maozhou River midstream watersheds, the risk of the flood area expanding would be greater than the risk of the flood deepening. The findings provide a spatial reference for flood control and strategic urban drainage design and facilitate the achievement of sustainable development goal 11.5 (SDG11.5) in Shenzhen and other regions. • A coupled multi-model framework for waterlog prediction. • The flooding pattern in Shenzhen shows more in the west and less in the east. • The expansion of the flooding area slows down as rainfall intensifies. • Flood risk assessed by ADWAB and WDI in 2035 is higher than in 2015. [ABSTRACT FROM AUTHOR]