Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 9
Articles | Volume 26, issue 9
https://doi.org/10.5194/hess-26-2387-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-2387-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 9
Research article
 | 
09 May 2022
Research article |  | 09 May 2022

Impact of spatial distribution information of rainfall in runoff simulation using deep learning method

Yang Wang and Hassan A. Karimi

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Short summary
We found that rainfall data with spatial information can improve the model's performance, especially when simulating the future multi-day discharges. We did not observe that regional LSTM as a regional model achieved better results than LSTM as individual model. This conclusion applies to both one-day and multi-day simulations. However, we found that using spatially distributed rainfall data can reduce the difference between individual LSTM and regional LSTM.
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