Published October 15, 2020 | Version v1
Dataset Open

Data for "Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network"

Creators

  • 1. David R. Cheriton School of Computer Science, University of Waterloo
  • 2. Institiute for Machine Learning, Johannes Kepler University Linz
  • 3. Google Research

Description

Data for the paper "Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network"

GitHub: https://github.com/gauchm/mts-lstm

This dataset contains the hourly NLDAS forcings and USGS streamflow data.

For training with our codebase, we recommend using the combined NetCDF file, but you can also use the csv files (but it will take much longer to load the data).

 

Related Datasets: https://doi.org/10.5281/zenodo.4071885 contains the models trained with the forcings and streamflow from this dataset.

Files

README.md

Files (37.5 GB)

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md5:c7e9e5d92af2153ca83114b70fe315b8
17.0 GB Download
md5:08629d5916181a1be932b2c94389dfd7
551 Bytes Preview Download
md5:3697b57134c9498478b730576d401e93
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md5:9b1f154c1504b06bc4d1504a0afd4a08
1.0 GB Download

Additional details

Related works

Is supplement to
Dataset: 10.5281/zenodo.4071885 (DOI)