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
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