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Parameter sensitivity analysis of SWMM: a case study of airport airfield area

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Abstract

Storm Water Management Model and Geographic Information System can provide prediction and management for airport flood problems. Efficient and accurate acquisition of sensitive parameters is the key to real-time model calibration. Due to the influence of special land types, functional zoning, and use requirements of airports, there are many problems in parameter sensitivity analysis, such as large sampling parameters, large amount of calculation, and nonlinear correlation between input and output variables. In this paper, the SWMM of airport airfield area is built, combining GIS and Python programming technology and using Latin hypercube sampling, and a correlation analysis method is proposed to study whether the input parameters have nonlinear correlation with the output results and its strength and compared with the improved Morris screening method. The results show that, the sensitivity of parameters is more balanced for the total inflow, there is no very sensitive parameter, and the nonlinear correlation between the parameters and the total inflow is weak. Manning-N is sensitive to average depth, hour of maximum flooding, and time to peak, which indicates that there is a strong nonlinear correlation between them and Manning-N. From the improved Morris screening analysis, it can be seen that there are no highly sensitive parameters for peak flow, and the sensitive parameters are Zero-Imperv and Manning-N. Highly sensitive parameters for time to peak are Manning-N, N-perv, S-Imperv, and N-Imperv. This paper quantitatively analyzes the influence of input parameters of the storm water management model on the output results, effectively identify the important parameters that affecting the output results, and analyze the nonlinear correlation between the input parameters and the output results. The results can greatly improve the accuracy of airport flood model and provide theoretical guidance for the application and parameter calibration of SWMM in airport.

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Data availability

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request (water withdrawals, water supply, and airport rain drainage system).

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Acknowledgements

The authors wish to thank the anonymous reviewers for their comments and suggestions and people who have supported this study.

Funding

This research was funded by [the Research Centre for Environment and Sustainable Development of Civil Aviation Administration of China Open Fund] grant number [2022YB03] and [Research Base for China Civil Aviation Airport Engineering Research of Open Fund] grant number [JCGC2020KFJJ001].

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Authors and Affiliations

  1. School of Transportation Science and Engineering, Civil Aviation University of China, Tian**, 300300, China

    **g Peng, Hucheng Zhao, Rui Li & Runzhao Xue

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  1. **g Peng
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  2. Hucheng Zhao
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  3. Rui Li
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  4. Runzhao Xue
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Contributions

**g Peng performed conceptualization, methodology, software, supervision, writing—reviewing, and editing. Hucheng Zhao analyzed data curation, writing—original draft preparation, visualization, investigation, and software. Rui Li presented validation, writing, editing. Runzhao Xue did drawing and revision.

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Correspondence to **g Peng.

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Peng, J., Zhao, H., Li, R. et al. Parameter sensitivity analysis of SWMM: a case study of airport airfield area. Nat Hazards 120, 6551–6568 (2024). https://doi.org/10.1007/s11069-024-06453-z

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