Multi-objective phased optimization framework of gray-green-blue infrastructure for synergistic runoff control in...

Gray-Green-Blue Infrastructure (GGBI) plays a critical role in urban flood mitigation through the integrated operation of rapid pumping drainage and source control measures. However, conventional multi-objective optimization models typically focus on individual flood control measures, overlooking pumping stations due to complex system interactions and uncertain synergies. Furthermore, the hydrological models coupled with optimization algorithms necessitate exceptionally high standards for data quantity, quality, and precision. To address this issue, this study proposes a multi-objective phased optimization framework with water surface ratio and Green Infrastructure (GI) as decision variables, while incorporating pumping station drainage flow determined through fitting relationships, focusing on the objectives of annual total cost (ATC) and runoff volume reduction rate (RVRR). Phase I optimization is particularly suitable for preliminary planning in data-scarce regions, and its determined decision variable ranges served as boundary constraints for the Phase Ⅱ spatial layout optimization. A case study was conducted in Handan, Hebei Province, China. The results demonstrate that pumping stations enable rapid river discharge in limited Green-Blue Infrastructure (GBI) space, effectively controlling water levels below 5.1m. The decision variables corresponding to Phase I optimization are 16.09-37.13 m³/s pumping station drainage flow, 1 % lake and 5 % river water surface ratios, 31.6 %-69 % sunken green space, and 10 %-26.4 % permeable pavement ratios, respectively, establishing scientific constraints for Phase II spatial optimization. This multi-objective phased optimization model provides an innovative solution for flood control optimization in data-scarce regions. By transforming the drainage capacity of pumping stations from a pre-defined fixed value into a dynamic variable determined by the scale of Green-Blue Infrastructure, the model offers a quantitative decision-making basis for GGBI under constraints of limited engineering budgets and space.