Multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development.

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.

Liu Z ，Han Z ，Shi X ，Liao X ，Leng L ，Jia H ... -  《-》

Adaptive pressure-driven multi-criteria spatial decision-making for a targeted placement of green and grey runoff control infrastructures.

Traditional runoff control measures ignore the spatial imbalance of regional pressures, thereby failing to achieve a site-specific placement for green and grey infrastructure simultaneously. A multi-criterion decision-making framework for runoff control infrastructure spatial planning was therefore developed in this study. The pressure-state-response framework was applied to creatively match the pressure induced adjustment demands with the infrastructure effectiveness. The pressures were quantified from the perspective of environment, economy, and ecology on a grid scale. States were considered as the relative priority of regional pressure adjustment demand in multiple perspectives. Responses were presented as state-targeted green and grey infrastructure placement. Multi-perspective effectiveness of different green and grey infrastructure was simultaneously evaluated at an effective scale of controlling 1 m3/s runoff for comparison. Methods such as data mining, hydrological model simulation, and remote sensing inversion were combined to quantify the regional pressures. The capital investment and ecological impact of infrastructures were quantified from a life cycle perspective. A case study was carried out in Wuhan, China. The study area was clustered by gridded pressure into three regions. In region Ⅰ, ecological and environmental pressure were of higher weight. In region Ⅱ, the environmental pressure was dominant. In region Ⅲ, the ecological pressure took precedence over the environmental and economic constraints. The area ratios of the region Ⅰ, Ⅱ, and Ⅲ were 43%, 36%, and 21% respectively. The result indicated a synergy and spatial heterogeneity of multi-perspective pressures, and further demonstrating that expert experience tends to fail to weigh the multi-function of green and grey infrastructures for coping with the pressures. Results also stated that green infrastructures were more acceptable in areas that aspire to achieve simultaneous runoff control and ecological improvement. The decision-making framework developed in this study can maximize the overall performance by providing targeted infrastructure placement solutions.

Jia H ，Liu Z ，Xu C ，Chen Z ，Zhang X ，Xia J ，Yu SL ... -  《-》

Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China.

Yu H ，Zhao Y ，Fu Y 《-》

Simulation of sponge city landscape pattern optimization based on the storm water management model (SWMM).

Chu YQ ，Zeng J ，Shi Y ，Xiu DX ... -  《-》

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

Dong X ，Yuan P ，Song Y ，Yi W ... -  《-》