Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data-Reference-Cited by-同舟云学术

Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data

Published:2021-06 Issue:6 Volume:57 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Res

Author:

Gharari Shervan¹^ORCID,Gupta Hoshin V.²^ORCID,Clark Martyn P.¹^ORCID,Hrachowitz Markus³^ORCID,Fenicia Fabrizio⁴^ORCID,Matgen Patrick⁵^ORCID,Savenije Hubert H. G.³^ORCID

Affiliation:

1. Centre for Hydrology University of Saskatchewan Canmore Alberta Canada

2. Department of Hydrology and Atmospheric Sciences The University of Arizona Tucson Arizona USA

3. Faculty of Civil Engineering and Geosciences (CITG) Delft University of Technology Delft Netherlands

4. Swiss Federal Institute of Aquatic Science and Technology (Eawag) Dübendorf Switzerland

5. Luxembourg Institute of Science and Technology (LIST) Belval Luxembourg

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR027948

Reference145 articles.

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

3. A Ranking of Hydrological Signatures Based on Their Predictability in Space

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

5. All that glitters is not gold: the case of calibrating hydrological models

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