Optimization and trade-off framework for coupled green-grey infrastructure considering environmental performance.

Implementing runoff control infrastructure has been regarded as an efficacious measure in stormwater management. The issue of its cost-effectiveness is a primary concern for decision makers since it is an exorbitant investment. However, most of existed studies only concentrated on the cost-effectiveness optimization of runoff control infrastructure, especially green infrastructure, between hydrological and economic aspects, and therefore, the potential layout scenarios with high extra environmental benefits could be neglected in the traditional two-dimensional frameworks. In this study, a novel carbon dioxide equivalent-based index was quantified to represent the extra environmental benefits of runoff control infrastructure besides stormwater management and was further integrated into the assessment framework. The effectiveness of green and grey infrastructure was comprehensively evaluated and traded off between hydrological, environmental and economic aspects. The results demonstrated that grey infrastructure is a better measure than green infrastructure when only hydrological (HF index) and economic (CI index) performances were considered. Nevertheless, the environmental performance (EROI index) of green infrastructure prevails over grey infrastructure, and when optimizing green and grey infrastructure simultaneously in the three-dimensional framework considering environmental effectiveness, green infrastructure is comparable with grey infrastructure. Furthermore, an appropriate composition of coupled green-grey infrastructure is requisite, which could achieve an optimal trade-off between hydrological and environmental effectiveness. The sources of environmental benefits were also identified and analyzed from three representative preference scenarios. The findings of the study could serve as a trade-off basis between green and grey infrastructure, as well as between EROI and HF.

Optimizing Green-Gray Infrastructure for Non-Point Source Pollution Control under Future Uncertainties.

Non-Point Source Pollution (NPS) caused by polluted and untreated stormwater runoff discharging into water bodies has become a serious threat to the ecological environment. Green infrastructure and gray infrastructure are considered to be the main stormwater management measures, and the issue of their cost-effectiveness is a widespread concern for decision makers. Multi-objective optimization is one of the most reliable and commonly used approaches in solving cost-effectiveness issues. However, many studies optimized green and gray infrastructure under an invariant condition, and the additional benefits of green infrastructure were neglected. In this study, a simulation-optimization framework was developed by integrated Stormwater Management Model (SWMM) and Non-dominated Sorting Genetic Algorithm (NSGA-II) to optimize green and gray infrastructure for NPS control under future scenarios, and a realistic area of Sponge City in Nanchang, China, was used as a typical case. Different levels of additional benefits of green infrastructure were estimated in the optimizing process. The results demonstrated that green-gray infrastructure can produce a co-benefit if the green infrastructure have appropriate Value of Additional Benefits (VAB), otherwise, gray infrastructure will be a more cost-effectiveness measure. Moreover, gray infrastructure is more sensitive than green infrastructure and green-gray infrastructure under future scenarios. The findings of the study could help decision makers to develop suitable planning for NPS control based on investment cost and water quality objectives.