Integrating socioecological indexes in multiobjective intelligent optimization of green-grey coupled infrastructures

Ecological conservation is an important objective in urban runoff management today. Maintaining a sustainable ecological system is as equally important a task as to ensure the safety of drainage systems and runoff management cost control. Thus, the socioecological influences of runoff control infrastructure are innovatively included in a uniform evaluation framework with the control functions and capital investments in this study. These indexes are quantified through hydrological model simulation, life cycle cost analysis, and life cycle assessment. Traditional grey infrastructure and rapidly developing green infrastructure for runoff control are optimized simultaneously. For the trade-off between multiobjectives and configurations of multi-infrastructures, nondominated sorting genetic algorithm-II is utilized to achieve automatic optimization of runoff control infrastructure scale, thereby avoiding the dilemma where manually arranged schemes cannot perform optimally. This multiobjective intelligent optimization is applied to a sponge city pilot region in Wuhan, China, and trade-offs are made in the Pareto optimal solution set. A breakthrough is claimed in quantifying the respective contribution of green and grey infrastructures to the optimal scenario in terms of runoff control function, cost input, and socioecological influence. For socioecological influence, the paybacks can meet the investment in the aspect of toxicity health hazard, pathogenic matter, global warming, terrestrial acidification, and water eutrophication (average socioecological paybacks are 2.0, 2.1, 2.9, 1.9, and 2.1 times to the investments respectively). Results prove the necessity of considering multiobjective optimization and green-grey couple infrastructures in a uniform framework.