Diagnosing evapotranspiration responses to water deficit across biomes using deep learning

© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.

Détails bibliographiques
Publié dans:The New phytologist. - 1979. - 240(2023), 3 vom: 25. Nov., Seite 968-983
Auteur principal: Giardina, Francesco (Auteur)
Autres auteurs: Gentine, Pierre, Konings, Alexandra G, Seneviratne, Sonia I, Stocker, Benjamin D
Format: Article en ligne
Langue:English
Publié: 2023
Accès à la collection:The New phytologist
Sujets:Journal Article climate change deep learning drought groundwater rock moisture root zone water storage capacity soil moisture vapor pressure deficit
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520 |a 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 
650 4 |a Journal Article 
650 4 |a climate change 
650 4 |a deep learning 
650 4 |a drought 
650 4 |a groundwater 
650 4 |a rock moisture 
650 4 |a root zone water storage capacity 
650 4 |a soil moisture 
650 4 |a vapor pressure deficit 
700 1 |a Gentine, Pierre  |e verfasserin  |4 aut 
700 1 |a Konings, Alexandra G  |e verfasserin  |4 aut 
700 1 |a Seneviratne, Sonia I  |e verfasserin  |4 aut 
700 1 |a Stocker, Benjamin D  |e verfasserin  |4 aut 
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