Giardina, Francesco; Gentine, Pierre; Konings, Alexandra G; Seneviratne, Sonia I; Stocker, Benjamin D (2023). Diagnosing evapotranspiration responses to water deficit across biomes using deep learning. New Phytologist, 240(3), pp. 968-983. Wiley 10.1111/nph.19197
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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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
08 Faculty of Science > Institute of Geography |
UniBE Contributor: |
Stocker, Benjamin David |
Subjects: |
900 History > 910 Geography & travel 300 Social sciences, sociology & anthropology > 330 Economics |
ISSN: |
1469-8137 |
Publisher: |
Wiley |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
25 Aug 2023 16:28 |
Last Modified: |
06 Oct 2023 00:14 |
Publisher DOI: |
10.1111/nph.19197 |
PubMed ID: |
37621238 |
Uncontrolled Keywords: |
climate change deep learning drought groundwater rock moisture root zone water storage capacity soil moisture vapor pressure deficit |
BORIS DOI: |
10.48350/185749 |
URI: |
https://boris.unibe.ch/id/eprint/185749 |
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