An integrated modelling framework for optimization of the placement of grey-green-blue infrastructure to mitigate and adapt flood risk: An application to the Upper Ting River Watershed, China

Abstract

Study regions

This study focuses on the Upper Ting River Watershed (UTRW) in the Ting River Basin, China.

Study focus

The study investigates the adverse impacts of urbanization and land-use change on hydrology, proposing the implementation of grey-green-blue infrastructure (GGBI) practices to mitigate these effects. An integrated modeling framework is developed to optimize the placement of GGBI, demonstrated through a case application in the UTRW.

New hydrological insights for the region

（1）The proposed modeling framework is highly effective in identifying key nodes and corridors for stormwater processes and flood inundation at both the watershed and city levels. It guides the reconstruction of GGBI spatial patterns at the watershed level and optimizes GGBI placement at the city level.

（2）In the central city, flooding covers an area of 8.44 km², or 18.53 % of the total area, with average flood depths of 0.99 m and maximum depths reaching 1.69 m. Areas most suitable for GGBI construction are located along the Ting River, showing clear continuity and concentration in the central city and Xinqiao Town.

（3）The optimized placement of GGBI, based on the SWMM model and non-dominated sorting genetic algorithm (NSGA-III), effectively reduces flood damage. Multi-objective optimization solutions outperform alternatives in terms of runoff reduction, pipeline overload duration, and construction costs.