Diagnosing evapotranspiration responses to water deficit across biomes using deep learning

Author:

Giardina Francesco12ORCID,Gentine Pierre34ORCID,Konings Alexandra G.5ORCID,Seneviratne Sonia I.6ORCID,Stocker Benjamin D.1278ORCID

Affiliation:

1. Institute of Agricultural Sciences, Department of Environmental Systems Science ETH Zürich Zürich CH‐8092 Switzerland

2. Swiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf CH‐8903 Switzerland

3. Department of Earth and Environmental Engineering Columbia University New York NY 10027 USA

4. Center for Learning the Earth with Artificial Intelligence and Physics (LEAP) Columbia University New York NY 10027 USA

5. Department of Earth System Science Stanford University Stanford CA 94305 USA

6. Institute for Atmospheric and Climate Science, Department of Environmental Systems Science ETH Zurich Zürich CH‐8092 Switzerland

7. Institute of Geography University of Bern Hallerstrasse 12 Bern 3012 Switzerland

8. Oeschger Centre for Climate Change Research University of Bern Falkenplatz 16 Bern 3012 Switzerland

Abstract

Summary Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole‐column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water‐unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

National Science Foundation

National Aeronautics and Space Administration

Publisher

Wiley

Subject

Plant Science,Physiology

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