Spatial layout optimization of green infrastructure based on life-cycle multi-objective optimization algorithm and SWMM model

被引:38
|
作者
Zhu, Yifei [1 ,2 ]
Xu, Changqing [1 ,3 ]
Liu, Zijing [1 ]
Yin, Dingkun [1 ]
Jia, Haifeng [1 ,4 ]
Guan, Yuntao [5 ,6 ]
机构
[1] Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Shenzhen Int, Grad Sch, Shenzhen 518055, Peoples R China
[3] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[4] Suzhou Univ Sci & Technol, Jiangsu Collaborat Innovat Ctr Technol & Mat Water, Suzhou 215009, Peoples R China
[5] Tsinghua Univ, Inst Environm & Ecol, Guangdong Prov Engn Technol Res Ctr Urban Water Cy, Tsinghua Shenzhen Int,Grad Sch, Shenzhen 518055, Peoples R China
[6] Tsinghua Univ, Sch Environm, State Environm Protect Key Lab Microorganism Appli, Beijing 100084, Peoples R China
基金
中国博士后科学基金;
关键词
Sponge city; Green infrastructure; Multi -objective optimization; NSGA-II; SWMM; SPONGE CITY CONSTRUCTION; SYSTEM;
D O I
10.1016/j.resconrec.2023.106906
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Rapid urbanization and more frequent urban floods instigated by climate change make traditional gray infrastructure become less effective and efficient. Green infrastructure (GI) have proved to be effective measures to address urban floods. Whether the GI layout can yield significant benefits and low investment cost requires further exploration. Besides, the type, size, and location of GI needs to be optimized to achieve better performance. A life-cycle evaluation framework coupled with a multi-objective optimization algorithm (NSGA-II) and SWMM was proposed for GI layout optimization. The framework took investment cost, economic-environmentalsocial monetization benefit, and runoff control capacity into consideration. Tongzhou District in Beijing was selected for empirical analysis. Simulation results reveled that GIs performed good in runoff control and the optimal layout under 10-year return period was recommended. The total cost and benefit of the recommended layout is 6.34x109 RMB and 8.36x106 RMB/Design rainfall, respectively, which outperforms than other scenarios. Permeable pavement accounted for the highest proportion in the optimized layout scenario. For actual construction, decision-makers should select appropriate measures according to local conditions (e.g., precipitation, land use type, cost of GIs) and choose the optimal layout scheme according to their preference. Results displayed can provide a reproducible and dependable planning scheme for future Sponge City construction in China.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Multi-objective optimization of OTEC Rankine cycle based on PSO algorithm
    Wang, Meng
    Zhao, Yingru
    Zhang, Haoran
    Wang, Bingzhen
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2019, 40 (10): : 2716 - 2724
  • [22] A spatial multi-objective optimization model for sustainable urban wastewater system layout planning
    Dong, X.
    Zeng, S.
    Chen, J.
    WATER SCIENCE AND TECHNOLOGY, 2012, 66 (02) : 267 - 274
  • [23] Simulation-Based Multi-Objective Optimization of institutional building renovation considering energy consumption, Life-Cycle Cost and Life-Cycle Assessment
    Sharif, Seyed Amirhosain
    Hammad, Amin
    JOURNAL OF BUILDING ENGINEERING, 2019, 21 : 429 - 445
  • [24] Research on the layout of coal resource project development in China based on multi-objective optimization algorithm in the context of infrastructure construction
    Yang X.
    Zhao L.
    Huo D.
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [25] Study on Multi-objective Optimization Model for VMS Layout on Expressways
    Wang, Jianjun
    Wu, Qiong
    SUSTAINABLE CITIES DEVELOPMENT AND ENVIRONMENT PROTECTION, PTS 1-3, 2013, 361-363 : 2012 - +
  • [26] MULTI-OBJECTIVE OPTIMIZATION OF SHIP PASSAGEWAY LAYOUT BASED ON PEDESTRIAN TRANSITION MODEL
    Zhao, Jiutian
    Wang, Hao
    Liang, Fangyan
    Xiao, Tianli
    Luo, Liang
    PROCEEDINGS OF ASME 2024 43RD INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, OMAE2024, VOL 5B, 2024,
  • [27] Multi-objective optimization algorithm based on artificial physics optimization
    Wang, Yan
    Zeng, Jian-Chao
    Kongzhi yu Juece/Control and Decision, 2010, 25 (07): : 1040 - 1044
  • [28] Multi-Objective Optimization Based on Brain Storm Optimization Algorithm
    Shi, Yuhui
    Xue, Jingqian
    Wu, Yali
    INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH, 2013, 4 (03) : 1 - 21
  • [29] A new multi-objective optimization model for an integrated energy system based on life-cycle composite technical, economic and environmental indices
    Han, Zepeng
    Han, Wei
    Song, Xinyang
    Lv, Liangguo
    Zhang, Na
    Sui, Jun
    ENERGY CONVERSION AND MANAGEMENT, 2025, 327
  • [30] Pareto Artificial Life Algorithm for Multi-Objective Optimization
    Song, Jin-Dae
    Yang, Bo-Suk
    JOURNAL OF INFORMATION TECHNOLOGY RESEARCH, 2011, 4 (02) : 43 - 60