灰色-绿色-蓝色基础设施的多目标阶段优化框架,用于数据稀缺地区的协同排水控制
Huayue Li1, Qinghua Luan2, Jun Liu3
1State Key Laboratory of Water Cycle and Water Security in River Basin, Hohai University, 210024, Nanjing, China; College of Hydrology and Water Resources, Hohai University, 210024, Nanjing, China.
Journal of environmental management
|January 14, 2026
概括
本研究介绍了城市洪水控制的阶段性优化框架,整合了绿色-绿色-蓝色基础设施 (GGBI) 和站. 它为数据稀缺地区的规划提供了数据效率高的解决方案.
科学领域:
- 环境工程 环境工程
- 城市规划 城市规划
- 水文学的水文学
背景情况:
- 灰色-绿色-蓝色基础设施 (GGBI) 对于城市洪水减缓至关重要,它结合了排水和源控制.
- 传统的优化模型往往忽略了因系统复杂性和数据需求而导致的站.
- 现有的水文模型需要广泛,高质量的数据,限制在数据稀缺地区的应用.
研究的目的:
- 为GGBI洪水控制提出一个多目标阶段优化框架.
- 将站排水流作为与绿色基础设施 (GI) 规模相关的动态变量.
- 在数据有限的场景中,优化年度总成本 (ATC) 和流量减少率 (RVRR).
主要方法:
- 开发了一个双相优化框架,使用水面比率和GI作为决策变量.
- 第一阶段:在数据稀缺地区进行初步规划,确定变量范围.
- 第二阶段:使用第一阶段输出作为约束的空间布局优化.
主要成果:
- 站促进了河流的快速排放,在有限的绿蓝基础设施 (GBI) 空间内控制了洪水水平.
- 第一个阶段的优化为站流量,水面比率和GI实施提供了特定的范围.
- 该模型为第二阶段的空间优化建立了科学约束,使有效的GGBI规划成为可能.
结论:
- 阶段性优化模型为数据稀缺地区的洪水控制提供了一个创新的解决方案.
- 它将站容量转化为动态变量,为GGBI提供定量决策.
- 这种方法支持在有限的预算和空间的限制下进行GGBI规划.
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