Cost-effective runoff control scheme drafting involves localization, multi-sector coordination, and configuration of multifunctional infrastructures. Numerous independent variables, parameters, weights, and objectives make runoff control optimization quantitatively arduous. This study innovatively proposed a multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development. The quantitative methods of multi-objective evaluation, hydrological feature partition, and pressure-adapted multi-objective weight assignment were proposed. Remote sensing inversion of water quality, hydrological model simulation (using SWAT and SWMM software), landscape pattern index calculation, life cycle cost (LCC), life cycle assessment (LCA) on ecological impact, and NSGA-II optimization algorithm were applied. Wuhan, the most water-sensitive city in China, was studied as a case. Runoff control function (RCF), capital investment (CI), and ecological return on investment (EROI) served as optimized objectives. High, medium, and low built-up regions in Wuhan urban development planning district were extracted by topographic factors and landscape patterns, which comprised 28, 34, and 38% of the case area, respectively. Three corresponding hydrological models were then built to illustrate distinct runoff control cost-efficiency in each region. Pressure distributions on runoff control, economic constraints, and ecological resource scarcity were quantitatively evaluated. And four pressure zones were clustered, which occupied 36, 29, 16, and 19% of the case area, respectively. Then the zonal weighted optimization decision-making matrix (with 3 hydrological models and 5 wt) was established by overlaying the pressure zone and built-up zone. In high, medium, and low built-up regions, optimized solutions reduced annual runoff volume by 86, 82%, and 77%The average runoff investments per square meter of impervious underlying surface in high, medium, and low built-up regions were 34.2, 18.7, and 7.9 RMB yuan, respectively. Medium and low built-up regions may only need 55 and 23% of the high built-up region for the unitary impervious underlying surface to balance runoff control and ecological benefits. Runoff control and financial utilization efficiency enhance with hydrological differentiation zones. Thus, the optimization solutions are zonal adaptive, refined, comparable, replicable, and implementable.
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