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

Data sets

Catchment attributes for large-sample studies N. Addor, A. Newman, M. Mizukami, and M. P. Clark

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2 P. E. Thornton, M. M. Thornton, B. W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R. B. Cook

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.