POLARIS Soil Properties: 30‐m Probabilistic Maps of Soil Properties Over the Contiguous United States-Reference-Cited by-同舟云学术

POLARIS Soil Properties: 30‐m Probabilistic Maps of Soil Properties Over the Contiguous United States

Published:2019-04 Issue:4 Volume:55 Page:2916-2938
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Chaney Nathaniel W.¹^ORCID,Minasny Budiman²,Herman Jonathan D.³^ORCID,Nauman Travis W.⁴^ORCID,Brungard Colby W.⁵,Morgan Cristine L. S.⁶,McBratney Alexander B.²,Wood Eric F.⁷^ORCID,Yimam Yohannes⁸

Affiliation:

1. Department of Civil and Environmental EngineeringDuke University Durham NC USA

2. Department of Environmental Sciences, Faculty of Agriculture and EnvironmentThe University of Sydney Sydney New South Wales Australia

3. Department of Civil and Environmental EngineeringUniversity of California Davis CA USA

4. U.S. Geological Survey, Southwest Biological Science Center Moab UT USA

5. Department of Plant and Environmental SciencesNew Mexico State University Las Cruces NM USA

6. Department of Soil and Crop SciencesTexas A&M University College Station TX USA

7. Department of Civil and Environmental EngineeringPrinceton University Princeton NJ USA

8. Formation Environmental LLC Sacramento CA USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018WR022797

Reference51 articles.

1. GlobalSoilMap

2. Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales

3. The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes

4. A manifesto for the equifinality thesis

5. Modelling soil attribute depth functions with equal-area quadratic smoothing splines

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