Including Regional Knowledge Improves Baseflow Signature Predictions in Large Sample Hydrology-Reference-Cited by-同舟云学术

Including Regional Knowledge Improves Baseflow Signature Predictions in Large Sample Hydrology

Published:2021-02 Issue:2 Volume:57 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Res.

Author:

Gnann Sebastian J.¹^ORCID,McMillan Hilary K.²^ORCID,Woods Ross A.¹^ORCID,Howden Nicholas J. K.¹^ORCID

Affiliation:

1. Department of Civil Engineering University of Bristol Bristol UK

2. Department of Geography San Diego State University San Diego CA USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR028354

Reference108 articles.

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2. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges

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. Quantifying hydrologic connectivity of wetlands to surface water systems

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