A simplified modeling approach for optimization of urban river systems

被引:5
|
作者
Feng, Wenwen [1 ,2 ]
Wang, Chao [3 ]
Lei, Xiaohui [3 ]
Wang, Hao [3 ]
机构
[1] Changan Univ, Sch Water & Environm, Xian 710054, Peoples R China
[2] Changan Univ, Minist Educ, Key Lab Subsurface Hydrol & Ecol Effects Arid Reg, Xian 710054, Peoples R China
[3] China Inst Water Resources & Hydropower Res, Beijing 100038, Peoples R China
关键词
Urban River systems; Flooding; Optimization; Simplification of models; Computational time; NEURAL-NETWORK;
D O I
10.1016/j.jhydrol.2023.129689
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Effective strategies for operating gates and pumping stations can help urban river systems to better control flooding. However, the computing cost of optimizing urban river systems prevents their application to large-scale problems. We propose a new simplified approach to urban river system optimization that allows a portion of the river network to be simulated, while the remainder is represented by a simplified model consisting of multiple surrogate models. The surrogate model reflects changes at the boundaries of the region of interest at prediction points within the system. To verify the accuracy of the simplified model, a numerical model based on storm water management model (SWMM) is established. The accuracy of the numerical model, the surrogate model and the simplified model were tested by multiple precipitation events. The average simulation time has been reduced by 574 times, demonstrating that the simplified model has effectively replaced the urban river network. This method is used to optimize multi-objective flood control in coastal cities. By adjusting the opening and closing state of 28 gates and pumping stations, the water level of 4 observation sections is controlled. The results show that 60% of the flood volume and 84% of the flood duration of the observed section are reduced, indicating that this method can better control the flooding process of the section. Compared with the numerical model, the calculation time is reduced by 184 times, indicating that the proposed method can solve the problem of long calculation time for urban river system optimization. This approach will reduce the risk of flooding in cities.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] A network modeling and structure optimization approach for technology system of systems
    You, Hanlin
    Li, Mengjun
    Jiang, Jiang
    Luo, Jili
    Xu, Jianguo
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2014, 36 (06): : 123 - 127
  • [32] Systems dynamics modelling, simulation and optimization of integrated urban systems: a soft computing approach
    Satsangi, PS
    Mishra, DS
    Gaur, SK
    Singh, BK
    KYBERNETES, 2003, 32 (5-6) : 808 - 817
  • [33] A Disaggregation-Emulation Approach for Optimization of Large Urban Drainage Systems
    Seyedashraf, Omid
    Bottacin-Busolin, Andrea
    Harou, Julien J.
    WATER RESOURCES RESEARCH, 2021, 57 (08)
  • [34] A simplified approach for preliminary design and process performance modeling of soil vapor extraction systems
    Staudinger, J
    Roberts, PV
    Hartley, JD
    ENVIRONMENTAL PROGRESS, 1997, 16 (03): : 215 - 226
  • [35] A systems approach to carbon cycling and emissions modeling at an urban neighborhood scale
    Kellett, Ronald
    Christen, Andreas
    Coops, Nicholas C.
    van der Laan, Michael
    Crawford, Ben
    Tooke, Thoreau Rory
    Olchovski, Irina
    LANDSCAPE AND URBAN PLANNING, 2013, 110 : 48 - 58
  • [36] Multi-agent approach to modeling and simulation of urban transportation systems
    Gruer, P
    Hilaire, V
    Koukam, A
    2001 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5: E-SYSTEMS AND E-MAN FOR CYBERNETICS IN CYBERSPACE, 2002, : 2499 - 2504
  • [37] Geospatial Modeling of River Systems
    Lindenschmidt, Karl-Erich
    Carr, Meghan Kathleen
    WATER, 2018, 10 (03)
  • [38] Indicators for the optimization of sustainable urban energy systems based on energy system modeling
    Christian Klemm
    Frauke Wiese
    Energy, Sustainability and Society, 12
  • [39] Indicators for the optimization of sustainable urban energy systems based on energy system modeling
    Klemm, Christian
    Wiese, Frauke
    ENERGY SUSTAINABILITY AND SOCIETY, 2022, 12 (01)
  • [40] Why rehabilitate urban river systems?
    Findlay, Sophia Jane
    Taylor, Mark Patrick
    AREA, 2006, 38 (03) : 312 - 325