Articles | Volume 22, issue 12
https://doi.org/10.5194/nhess-22-4139-2022
https://doi.org/10.5194/nhess-22-4139-2022
Research article
 | 
22 Dec 2022
Research article |  | 22 Dec 2022

A multi-strategy-mode waterlogging-prediction framework for urban flood depth

Zongjia Zhang, Jun Liang, Yujue Zhou, Zhejun Huang, Jie Jiang, Junguo Liu, and Lili Yang

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Latest update: 24 Jun 2024
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Short summary
An innovative multi-strategy-mode waterlogging-prediction framework for predicting waterlogging depth is proposed in the paper. The framework selects eight regression algorithms for comparison and tests the prediction accuracy and robustness of the model under different prediction strategies. Ultimately, the accuracy of predicting water depth after 30 min can exceed 86.1 %. This can aid decision-making in terms of issuing early warning information and determining emergency responses in advance.
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