A new approach for sensitivity analysis of the StormWater Management Model applied in an airport

Sensitivity analysis of urban flood model parameters is important for efficient and accurate flood simulation. In order to explore the problems of large sampling parameters and nonlinear correlation between input and output variables, this paper proposed a new correlation analysis approach. The type...

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Published inWater science and technology Vol. 88; no. 9; pp. 2453 - 2464
Main Authors Peng, Jing, Zhao, Hucheng, Luo, Zihang, Ouyang, Jie, Yu, Lei
Format Journal Article
LanguageEnglish
Published London IWA Publishing 01.11.2023
Subjects
Aircraft
airport airfield area
Airports
Analysis
Conductivity
Correlation analysis
Drainage
Flood management
Flooding
Floods
Heat
Inflow
Integrated approach
latin hypercube sampling
Mathematical models
Optimization
Parameter sensitivity
parameter sensitivity analysis
Parameters
python programming
Rain
Rivers
Runoff
Sensitivity analysis
Simulation
Software
Stormwater
Stormwater management
swmm
Water management
United States > US
China
Chicago Illinois
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Summary:Sensitivity analysis of urban flood model parameters is important for efficient and accurate flood simulation. In order to explore the problems of large sampling parameters and nonlinear correlation between input and output variables, this paper proposed a new correlation analysis approach. The type, strength, and the order of sensitive parameters to the four outputs are analyzed using the proposed approach. The results show that the R values of Manning-N are biggest, its distribution is linear in heat maps, and the Manning-N has a strong linear correlation with Average Depth, Hour of Maximum Flooding, and Time to Peak. For Average Depth, the second sensitive parameter is Conductivity. For Hour of Maximum Flooding, the second and third more sensitive parameters are Conductivity and N-perv; however, there are certain nonlinear correlations from heat maps. For Total Inflow, the R values of each parameter are between 0.021 and 0.534. Most sensitive parameters are none; however, the more sensitive parameters are Conductivity, N-perv, and initial deficit. For Time to Peak, the second and third more sensitive parameters are N-perv and N-Imperv; however, there are certain non-linear correlations from heat maps. The results can provide theoretical guidance for application and parameter calibration of SWMM in airport.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0273-1223
1996-9732
DOI:10.2166/wst.2023.335