Articles | Volume 22, issue 12
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

Related authors

Graphical representation of global water models
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
EGUsphere,,, 2024
Short summary
A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)
Xinyu Chen, Liguang Jiang, Yuning Luo, and Junguo Liu
Earth Syst. Sci. Data, 15, 4463–4479,,, 2023
Short summary
History of anthropogenic Nitrogen inputs (HaNi) to the terrestrial biosphere: a 5 arcmin resolution annual dataset from 1860 to 2019
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568,,, 2022
Short summary
Dynamic risk assessment of compound hazards based on VFS–IEM–IDM: a case study of typhoon–rainstorm hazards in Shenzhen, China
Wenwu Gong, Jie Jiang, and Lili Yang
Nat. Hazards Earth Syst. Sci., 22, 3271–3283,,, 2022
Short summary
Understanding each other's models: an introduction and a standard representation of 16 global water models to support intercomparison, improvement, and communication
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878,,, 2021
Short summary

Related subject area

Hydrological Hazards
Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany
Jan Sodoge, Christian Kuhlicke, Miguel D. Mahecha, and Mariana Madruga de Brito
Nat. Hazards Earth Syst. Sci., 24, 1757–1777,,, 2024
Short summary
The value of multi-source data for improved flood damage modelling with explicit input data uncertainty treatment: INSYDE 2.0
Mario Di Bacco, Daniela Molinari, and Anna Rita Scorzini
Nat. Hazards Earth Syst. Sci., 24, 1681–1696,,, 2024
Short summary
Limited effect of the confluence angle and tributary gradient on Alpine confluence morphodynamics under intense sediment loads
Théo St. Pierre Ostrander, Thomé Kraus, Bruno Mazzorana, Johannes Holzner, Andrea Andreoli, Francesco Comiti, and Bernhard Gems
Nat. Hazards Earth Syst. Sci., 24, 1607–1634,,, 2024
Short summary
Does a convection-permitting regional climate model bring new perspectives on the projection of Mediterranean floods?
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci., 24, 1163–1183,,, 2024
Short summary
Added value of seasonal hindcasts to create UK hydrological drought storylines
Wilson C. H. Chan, Nigel W. Arnell, Geoff Darch, Katie Facer-Childs, Theodore G. Shepherd, and Maliko Tanguy
Nat. Hazards Earth Syst. Sci., 24, 1065–1078,,, 2024
Short summary

Cited articles

Abedin, S. and Stephen, H.: GIS Framework for Spatiotemporal Mapping of Urban Flooding, Geosci. J., 9, 77,, 2019. 
Ali, M., Prasad, R., Xiang, Y., and Yaseen, Z. M.: Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts, J. Hydrol., 584, 124647,, 2020. 
Ben Taieb, S., Bontempi, G., Atiya, A. F., and Sorjamaa, A.: A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition, Expert Syst. Appl., 39, 7067–7083,, 2012. 
Chang, F., Chen, P., Lu, Y., Huang, E., and Chang, K.: Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control, J. Hydrol., 517, 836–846,, 2014. 
Danso-Amoako, E., Scholz, M., Kalimeris, N., Yang, Q., and Shao, J.: Predicting dam failure risk for sustainable flood retention basins: A generic case study for the wider Greater Manchester area, Comput. Environ. Urban, 36, 423–433,, 2012. 
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.
Final-revised paper