Articles | Volume 29, issue 6
https://doi.org/10.5194/hess-29-1749-2025
https://doi.org/10.5194/hess-29-1749-2025
Technical note
 | 
26 Mar 2025
Technical note |  | 26 Mar 2025

Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell

Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret

Viewed

Total article views: 797 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
614 167 16 797 13 13
  • HTML: 614
  • PDF: 167
  • XML: 16
  • Total: 797
  • BibTeX: 13
  • EndNote: 13
Views and downloads (calculated since 12 Dec 2024)
Cumulative views and downloads (calculated since 12 Dec 2024)

Viewed (geographical distribution)

Total article views: 797 (including HTML, PDF, and XML) Thereof 769 with geography defined and 28 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 May 2025
Download
Short summary
Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Share