Articles | Volume 30, issue 6
https://doi.org/10.5194/hess-30-1625-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Research article
| 
30 Mar 2026
Research article |
| 30 Mar 2026
| 30 Mar 2026
A highly generalizable data-driven model for spatiotemporal urban flood dynamics real-time forecasting based on coupled CNN and ConvLSTM
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Hydrol. Earth Syst. Sci., 25, 6023–6039, 2021
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Aderyani, F. R., Jafarzadegan, K., and Moradkhani, H.: A surrogate machine learning modeling approach for enhancing the efficiency of urban flood modeling at metropolitan scales, Sustain. Cities Soc., 123, 106277, https://doi.org/10.1016/j.scs.2025.106277, 2025. a
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