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Confronting the water potential information gap

Nature Geoscience volume 15, pages 158–164 (2022)Cite this article

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Abstract

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

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Fig. 1: Ψ links environmental drivers to biophysical responses.
Fig. 2: Water-retention curve and PTF uncertainty.
Fig. 3: Water-retention-curve parameters are a key source of land-surface model uncertainty.
Fig. 4: ΨS better explains variability in GPP when compared with θ.

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Data availability

The FLUXNET tower data appearing in Fig. 3 are from the FLUXNET 2015 dataset (https://doi.org/10.18140/FLX/1440186 for SD-Dem, https://doi.org/10.18140/FLX/1440071 for US-HA1 and https://doi.org/10.18140/FLX/1440160 for FI-SOD). The AmeriFlux tower data appearing in Fig. 4 are available from the AmeriFlux network (https://doi.org/10.17190/AMF/1246080 for US-MMS, https://doi.org/10.17190/AMF/1246081 for US-MOz, https://doi.org/10.17190/AMF/1246104 for US-SRM and https://doi.org/10.17190/AMF/1245971 for US-TON).

Code availability

The HYDRUS 1D programme used to create the results of Fig. 2e–g is available for public download from https://www.pc-progress.com/en/Default.aspx?hydrus-1d. A reference version of the ORCHIDEE land-surface model, used for Fig. 3, is available at https://orchidee.ipsl.fr/. Details on the parameterizations of these models are presented in the Supplementary Information.

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Acknowledgements

K.A.N. acknowledges support from NSF (DEB, grant 1552747) and the AmeriFlux Management Project via the US Department of Energy, Office of Science Lawrence Berkeley National Laboratory. A.G.K. was supported by NASA Terrestrial Ecology (award 80NSSC18K0715). J.D.W. acknowledges support from the US Department of Energy, Office of Science, through Oak Ridge National Laboratory’s Terrestrial Ecosystem Science Focus Area. K.J.D. and Y.S. were supported by National Science Foundation grant EAR 1331726 (S. Brantley) for the Susquehanna Shale Hills Critical Zone Observatory.

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Authors and Affiliations

  1. O’Neill School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, USA

    Kimberly A. Novick

  2. Department of Geography, Indiana University Bloomington, Bloomington, IN, USA

    Darren L. Ficklin & Natasha MacBean

  3. Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA, USA

    Dennis Baldocchi

  4. Department of Meteorology and Atmospheric Science and Earth and Environmental Systems Institute, The Pennsylvania State University, University Park, PA, USA

    Kenneth J. Davis

  5. Life and Environmental Sciences Department, University of California Merced, Merced, CA, USA

    Teamrat A. Ghezzehei

  6. Department of Earth System Science, Stanford University, Stanford, CA, USA

    Alexandra G. Konings

  7. Laboratoire des Sciences du Climat et de l’Environnement, Paris, France

    Nina Raoult

  8. Southwest Watershed Research Center, USDA Agricultural Research Service, Tucson, AZ, USA

    Russell L. Scott

  9. Department of Plant Science, The Pennsylvania State University, University Park, PA, USA

    Yuning Shi

  10. Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Benjamin N. Sulman

  11. School of Natural Resources, University of Missouri, Columbia, MO, USA

    Jeffrey D. Wood

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Contributions

K.A.N. conceived of the study with substantial input from D.L.F., A.G.K., K.J.D., T.A.G., R.L.S., B.N.S., Y.S. and N.M. Data analyses were performed by K.A.N., T.A.G., D.L.F. and N.R., who also created the resulting figures. D.B., R.L.S., K.A.N. and J.D.W. contributed AmeriFlux data used in Fig. 4. All authors wrote the text and provided substantial conceptual input to the manuscript.

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Correspondence to Kimberly A. Novick.

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Supplementary Discussion, Tables 1–4 and Fig. 1.

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Novick, K.A., Ficklin, D.L., Baldocchi, D. et al. Confronting the water potential information gap. Nat. Geosci. 15, 158–164 (2022). https://doi.org/10.1038/s41561-022-00909-2

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