Abstract
The flood produced by short duration heavy rainfall events in cities will still exist after raining and continues to cause harm and impact. To accurately predict the depth and duration of the flood, a coupled model of the extreme gradient boosting and long short-term memory algorithms was proposed. A practical application of three representative flooded points in the Zhengzhou city, China, the results showed the coupled model could fit and forecast the flood. The average of Mean relative error, Nash–Sutcliffe efficiency coefficient and Qualified rate of validation data were 9.13%, 0.96 and 90.3% respectively, which verified the superiority of the method in the flood prediction. And the flood processes at the flooded points caused by design rainfall under different return periods were predicted by the coupled model. The growth rates of the flood duration and peak flood depth were all the highest during the return periods 1a-2a. This study proves that the coupled model has great potential in predictions of flood and could provide scientific basis guidance for disaster reduction.
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Funding
This work was supported by the National Key R&D Program of China (2022YFC3090601-4), the Key Projects of Natural Science Foundation of China (51739009), Excellent Youth Fund of Henan Province of China (212300410088) and the First class project of Yellow River Laboratory of Zhengzhou University (YRL22LT03). Corresponding author (Huiliang Wang) has received research support.
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Conceptualization, Methodology and Software: Hongfa Wang; Visualization and Investigation: Xinjian Guan; Software and Validation: Yu Meng; Supervision: Zening Wu; Data curation: Kun Wang; Writing-Original draft preparation: Huiliang Wang.
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Wang, H., Guan, X., Meng, Y. et al. Coupling Time and Non-Time Series Models to Simulate the Flood Depth at Urban Flooded Area. Water Resour Manage 37, 1275–1295 (2023). https://doi.org/10.1007/s11269-023-03430-2
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DOI: https://doi.org/10.1007/s11269-023-03430-2