Water Resources Management

, Volume 33, Issue 12, pp 4201–4214 | Cite as

A Surrogate-Based Optimization Design and Uncertainty Analysis for Urban Flood Mitigation

  • Wen Zhang
  • Jing Li
  • Yunhao ChenEmail author
  • Yang Li


This study proposes a surrogate-based optimization framework (SBO) to help analyze the tradeoff between flood damages and investment while considering uncertainty originating from surrogates. The surrogate models were constructed based on the relationship between drainage specifications and simulated flood information and used to replace the numerical model in optimization, thereby reducing the computational burden. The bootstrapping approach was employed to quantify the uncertainty originating from surrogate models, which were incorporated into the NSGA-II optimization algorithm to seek the interval of optimal solutions. Through a case study, the results showed that the uncertainties caused by surrogate models have a significant influence on the reliability of the optimal solutions, but require lower computational efforts. Moreover, the local design conditions (i.e., various designed rainfalls) had an impact on the design and performance of the detention tanks. The proposed framework will facilitate cost-effective planning of flood mitigation systems with an awareness of associated uncertainty in order to resolve tradeoffs, particularly for large-scale problems.


Urban flood mitigation design Surrogate model Multi-objective optimization Uncertainty analysis Bootstrapping method Ensemble-based 



We would like to thank Dr. Jianjun Yu, Chunyue Niu, and Zhihua Xu for helpful discussions that improved the manuscript. This work was supported through projects of the Beijing Laboratory of Water Resources Security and Beijing Flash Flood Disaster Monitoring and Risk Assessment, and Natural Science Foundation of China (51579135), and Science and Technology Plans of Ministry of Housing and Urban-Rural Development of the People’s Republic of China, and Opening Projects of Beijing Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture (UDC2017030212, UDC201650100).

Compliance with Ethical Standards

Conflict of Interest


Supplementary material

11269_2019_2355_MOESM1_ESM.docx (271 kb)
ESM 1 (DOCX 270 kb)


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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Remote Sensing Science, Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina
  2. 2.Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical ScienceBeijing Normal UniversityBeijingChina

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