Urban storm flood simulation using improved SWMM based on K‐means clustering of parameter samples

To address the two problems of unclear delineation of sub‐catchment and complicated and cumbersome parameter rate determination in the Storm Water Management Model (SWMM), this study proposes a rapid construction method of SWMM based on the principle of single urban functional area combined with K‐m...

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Vydáno v:Journal of flood risk management Ročník 15; číslo 4
Hlavní autoři: Sun, Yue, Liu, Chengshuai, Du, Xian, Yang, Fan, Yao, Yichen, Soomro, Shan‐e‐hyder, Hu, Caihong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford, UK Blackwell Publishing Ltd 01.12.2022
John Wiley & Sons, Inc
Wiley
Témata:
Algorithms
Clustering
Construction
Decision making
division of HRU
Flood control
Flood forecasting
Flood models
Flood prevention
flooding nodes
Floods
Hydrology
K‐means cluster algorithm parameter determination
Mathematical models
Mitigation
Parameter uncertainty
Rain
Rainfall
Rainfall runoff
Rainfall-runoff modeling
Rainfall-runoff relationships
risk management
River discharge
Runoff
Storms
Stormwater
Stormwater management
subwatersheds
SWMM
Technical services
Urban areas
urban storm flood model
Water management
Watersheds
China
ISSN:1753-318X, 1753-318X
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Popis
Shrnutí:To address the two problems of unclear delineation of sub‐catchment and complicated and cumbersome parameter rate determination in the Storm Water Management Model (SWMM), this study proposes a rapid construction method of SWMM based on the principle of single urban functional area combined with K‐means clustering algorithm, The research area is the southern part of Jinshui District, Zhengzhou City. The Hydrological Response Unit (HRU) contains only a single urban functional area, divided by combining the natural and social attributes of the urban surface. Calibrated uncertain parameters from 76 papers were selected as samples, and the K‐means clustering algorithm was used to cluster and calculate the parameter values, to improve the SWMM model, selecting three typical rainfall runoff processes for validation application. The results show that simulated runoff is consistent with measured runoff trends, with the NSE and R2 value scores of the flow processes of the three floods above 0.86 and the, locations and numbers of flooded nodes are consistent with the actual research. This provides a new idea and technical support for the construction of urban flood models in flood prevention and mitigation. The relevant results can provide scientific decision‐making reference for urban flood forecasting and warning.
Bibliografie:Funding information
National Natural Science Foundation of China, Grant/Award Numbers: 51739009, 51979250
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ISSN:1753-318X
1753-318X
DOI:10.1111/jfr3.12826