Abstract

In urban water management, the green infrastructures and grey infrastructures are complementary in function, effectively alleviating urban flooding and non-point source pollution. Coupled grey-green infrastructures will bring multiple benefits to cities, such as ecological, environmental, economic, and social benefits. However, there is still a lack of a coupled optimization layout method for green and grey infrastructures under different objective oriented benefits. The optimal layout ratio of each infrastructure is not clear. In this study, a multi-objective optimization framework was proposed to optimize the layout of coupled grey-green infrastructures. Firstly, this framework established a hierarchy structure of benefits evaluation with a monetization method to estimate the monetized net benefits, costs and environmental benefits for directly comparing the benefits and cost. Secondly, the monetized benefits and costs were used as the objective functions in the optimization problem, which were resolved by an elitist non-dominated sorting genetic algorithm (NSGA-II) to obtain the optimal grey-green infrastructure layout ratios (i.e., decision variables) for balancing the conflicting objectives. A case study of a district in Xi'an was used for validation. Results show that the green roof layout ratio is 7.6%–9.9%, and tends to be within the higher ratio values in all return periods. The other two green infrastructures have a larger range of optimal layout ratios, which varies significantly with different solutions. Although the optimal layout scenarios are different for different objectives, the coupled grey-green layout significantly improves the net benefits and environmental benefits. Compared to the deterministic scenario, the net benefit of the optimized scenario increase by 2.39 × 106CNY and 2.31 × 106CNY under the same cost or environmental benefit, respectively. This study provides a piece of evidence in support of urban stormwater management and evaluates the effectiveness of coupled grey-green infrastructures.

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