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.
Dong X
，Yi W
，Yuan P
，Song Y
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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
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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
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Assessing and optimizing the hydrological performance of Grey-Green infrastructure systems in response to climate change and non-stationary time series.
Climate change has led to the increased intensity and frequency of extreme meteorological events, threatening the drainage capacity in urban catchments and densely built-up cities. To alleviate urban flooding disasters, strategies coupled with green and grey infrastructure have been proposed to support urban stormwater management. However, most strategies rely largely on diachronic rainfall data and ignore long-term climate change impacts. This study described a novel framework to assess and to identify the optimal solution in response to uncertainties following climate change. The assessment framework consists of three components: (1) assess and process climate data to generate long-term time series of meteorological parameters under different climate conditions; (2) optimise the design of Grey-Green infrastructure systems to establish the optimal design solutions; and (3) perform a multi-criteria assessment of economic and hydrological performance to support decision-making. A case study in Guangzhou, China was carried out to demonstrate the usability and application processes of the framework. The results of the case study illustrated that the optimised Grey-Green infrastructure could save life cycle costs and reduce total outflow (56-66%), peak flow (22-85%), and TSS (more than 60%) compared to the fully centralised grey infrastructure system, indicating its high superior in economic competitiveness and hydrological performance under climate uncertainties. In terms of spatial configuration, the contribution of green infrastructure appeared not as critical as the adoption of decentralisation of the drainage networks. Furthermore, under extreme drought scenarios, the decentralised infrastructure system exhibited an exceptionally high degree of removal performance for non-point source pollutants.
Wang M
，Liu M
，Zhang D
，Qi J
，Fu W
，Zhang Y
，Rao Q
，Bakhshipour AE
，Tan SK
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ResearchGate
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钛学术
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