Published April 7, 2021 | Version 1.0
Journal article Open

Pre-trained models for "A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling"

  • 1. LIT AI Lab & Institute for Machine Learning, Johannes Kepler University Linz, Austria
  • 2. Google Research, Mountain View, CA United States

Description

This dataset contains the pre-trained models from the publication "A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling". For each input configuration, the dataset contains 10 model repetitions. Each run has a separate folder, containing the model weights, run configuration, validation and test set results. The models were trained using the code available at https://github.com/kratzert/multiple_forcing

Paper reference (accepted for publication):

Kratzert, F., Klotz, D., Hochreiter, S., and Nearing, G. S.: A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-221, in review, 2020.

The paper is available at https://doi.org/10.5194/hess-2020-221

Files

multi-forcing-models.zip

Files (6.2 GB)

Name Size Download all
md5:9a5d25809ef212e0967e54849f89bbcb
6.2 GB Preview Download