What Role Does Hydrological Science Play in the Age of Machine Learning?-Reference-Cited by-同舟云学术

What Role Does Hydrological Science Play in the Age of Machine Learning?

Published:2021-03 Issue:3 Volume:57 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Res

Author:

Nearing Grey S.¹^ORCID,Kratzert Frederik²^ORCID,Sampson Alden Keefe³^ORCID,Pelissier Craig S.⁴,Klotz Daniel²^ORCID,Frame Jonathan M.¹^ORCID,Prieto Cristina⁵^ORCID,Gupta Hoshin V.⁶^ORCID

Affiliation:

1. Department of Land Air & Water Resources University of California Davis Davis CA USA

2. LIT AI Lab and Institute for Machine Learning Johannes Kepler University Linz Austria

3. Upstream Tech Natel Energy Inc. Alameda CA USA

4. NASA Center for Climate Simulation NASA Goddard Space Flight Center Greenbelt MD USA

5. IHCantabria Instituto de Hidrulica Ambiental Universidad de Cantabria Santander Spain

6. Department of Hydrology and Atmospheric Sciences University of Arizona Tucson AZ USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR028091

Reference114 articles.

1. Towards a benchmark for land surface models

2. Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models

3. The CAMELS data set: catchment attributes and meteorology for large-sample studies

4. Debates-Hypothesis testing in hydrology: Pursuing certainty versus pursuing uberty

5. FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem–Scale Carbon Dioxide, Water Vapor, and Energy Flux Densities

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