U.S. Department of Agriculture: Forest Service -- National Agroforestry Center

 

Authors

Y. Fan, State University of New Jersey RutgersFollow
M. Clark, National Center for Atmospheric Research
D. M. Lawrence, National Center for Atmospheric Research
S. Swenson, National Center for Atmospheric Research
L.E. Band, University of Virginia
S. L. Brantley, The Pennsylvania State University
P. D. Brooks, University of Utah
W. E. Dietrich, University of California - Berkeley
A. Flores, Boise State University
G. Grant, Oregon State University
J.W. Kirchner, ETH Zürich
D. S. Mackay, The State University of New York at Buffalo
J. J. McDonnell, University of Saskatchewan
P. C. D. Milly, U.S. Geological Survey
P. L. Sullivan, University of Kansas
C. Tague, University of California, Santa Barbara
H. Ajami, University of California, Riverside
N. Chaney, Duke University
A. Hartmann, Universities of Freiburg & University of Arizona
P. Hazenberg, University of Arizona
J. McNamara, Boise State University
J. Pelletier, Ghent University
J. Perket, 2National Center for Atmospheric Research
E. Rouholahnejad‐Freund, University of Bristol
T. Wagener, University of Arizona
X. Zeng, University of Arizona
E. Beighley, Northeastern University
J. Buzan, Purdue University
M. Huang, Pacific Northwest National Laboratory
B. Livneh, University of Colorado Boulder
B. P. Mohanty, Texas A&M University
B. Nijssen, University of Washington
M. Safeeq, University of California, Merced & USDA Forest Service
C. Shen, Pennsylvania State University
W. van Verseveld, 31Department of Catchment and Urban Hydrology
J. Volk, University of Nevada
D. Yamazaki, The University of Tokyo

ORCID IDs

https://orcid.org/0000-0002-0024-7965

https://orcid.org/0000-0002-2186-2625

https://orcid.org/0000-0002-2968-3023

https://orcid.org/0000-0002-2923-1203

https://orcid.org/0000-0003-4320-2342

https://orcid.org/0000-0001-9201-1062

https://orcid.org/0000-0002-7240-9265

https://orcid.org/0000-0002-3012-5192

https://orcid.org/0000-0001-6577-3619

https://orcid.org/0000-0003-0477-9755

https://orcid.org/0000-0003-4389-3139

https://orcid.org/0000-0001-8780-8501

https://orcid.org/0000-0003-1463-308X

https://orcid.org/0000-0001-6883-7630

https://orcid.org/0000-0001-7120-1713

https://orcid.org/0000-0003-3107-4689

https://orcid.org/0000-0001-7625-4507

https://orcid.org/0000-0002-0702-2646

https://orcid.org/0000-0001-9195-6419

https://orcid.org/0000-0002-4316-2013

https://orcid.org/0000-0003-3881-5849

https://orcid.org/0000-0001-7352-2764

https://orcid.org/0000-0002-8199-3264

https://orcid.org/0000-0001-9154-9485

https://orcid.org/0000-0001-5445-2473

https://orcid.org/0000-0001-9381-7279

https://orcid.org/0000-0002-4062-0322

https://orcid.org/0000-0003-0529-3925

https://orcid.org/0000-0002-0685-1901

https://orcid.org/0000-0001-9994-1545

Document Type

Article

Date of this Version

2-27-2019

Citation

2019. American Geophysical Union.

Comments

Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., et al. (2019). Hillslope hydrology in global change research and Earth system modeling. Water Resources Research, 55, 1737–1772. https://doi. org/10.1029/2018WR023903

Abstract

Earth System Models (ESMs) are essential tools for understanding and predicting global change, but they cannot explicitly resolve hillslope‐scale terrain structures that fundamentally organize water, energy, and biogeochemical stores and fluxes at subgrid scales. Here we bring together hydrologists, Critical Zone scientists, and ESM developers, to explore how hillslope structures may modulate ESM grid‐level water, energy, and biogeochemical fluxes. In contrast to the one‐dimensional (1‐D), 2‐ to 3‐mdeep, and free‐draining soil hydrology in most ESM land models, we hypothesize that 3‐D, lateral ridge‐to‐valley flow through shallow and deep paths and insolation contrasts between sunny and shady slopes are the top two globally quantifiable organizers of water and energy (and vegetation) within an ESM grid cell. We hypothesize that these two processes are likely to impact ESM predictions where (and when) water and/or energy are limiting. We further hypothesize that, if implemented in ESM land models, these processes will increase simulated continental water storage and residence time, buffering terrestrial ecosystems against seasonal and interannual droughts. We explore efficient ways to capture these mechanisms in ESMs and identify critical knowledge gaps preventing us from scaling up hillslope to global processes. One such gap is our extremely limited knowledge of the subsurface, where water is stored (supporting vegetation) and released to stream baseflow (supporting aquatic ecosystems). We conclude with a set of organizing hypotheses and a call for global syntheses activities and model experiments to assess the impact of hillslope hydrology on global change predictions.

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