具有成本效益的径流控制方案起草涉及本地化,多部门协调,和多功能基础设施的配置。许多独立变量,参数,重量,和目标使径流控制优化在数量上艰巨。本研究创新性地提出了一种适应自然禀赋和城市发展空间异质性的绿灰色耦合径流控制基础设施多目标优化方法。多目标评价的定量方法,水文特征分区,提出了压力自适应多目标权重分配方法。水质遥感反演,水文模型模拟(使用SWAT和SWMM软件),景观格局指数计算,生命周期成本(LCC),对生态影响的生命周期评估(LCA),并应用NSGA-II优化算法。武汉,中国对水最敏感的城市,作为一个案例进行了研究。径流控制功能(RCF),资本投资(CI),和生态投资回报(EROI)作为优化目标。High,中等,利用地形因子和景观格局提取武汉市城市发展规划区低建成区,占病例面积的28%,34%和38%,分别。然后建立了三个相应的水文模型,以说明每个地区不同的径流控制成本效率。径流控制的压力分布,经济约束,并对生态资源稀缺性进行了定量评价。四个压力区聚集在一起,占病例面积的36%,29%,16%和19%,分别。然后通过叠加压力区和建成区,建立了区域加权优化决策矩阵(具有3个水文模型和5wt)。在高,中等,和低建筑区,优化的解决方案将年径流量减少了86%,82%,和77%的高不透水下垫面每平方米的平均径流投资,中等,低建成区分别为34.2、18.7和7.9元,分别。中,低建筑区域可能只需要高建筑区域的55%和23%即可获得整体不透水的下垫面,以平衡径流控制和生态效益。径流控制和财政利用效率随着水文分化带的提高而提高。因此,优化方案是区域自适应的,精致,可比性,可复制,并且可实施。
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.