Simple Models Outperform More Complex Big-Leaf Models of Daily Transpiration in Forested Biomes

© 2022. The Authors.

Bibliographische Detailangaben
Veröffentlicht in:Geophysical research letters. - 1984. - 49(2022), 18 vom: 28. Sept., Seite e2022GL100100
1. Verfasser: Bright, Ryan M (VerfasserIn)
Weitere Verfasser: Miralles, Diego G, Poyatos, Rafael, Eisner, Stephanie
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2022
Zugriff auf das übergeordnete Werk:Geophysical research letters
Schlagworte:Journal Article Fluxnet Sapfluxnet antecedent precipitation index canopy conductance model evaluation triple collocation
Beschreibung
Zusammenfassung:© 2022. The Authors.
Transpiration makes up the bulk of total evaporation in forested environments yet remains challenging to predict at landscape-to-global scales. We harnessed independent estimates of daily transpiration derived from co-located sap flow and eddy-covariance measurement systems and applied the triple collocation technique to evaluate predictions from big leaf models requiring no calibration. In total, four models in 608 unique configurations were evaluated at 21 forested sites spanning a wide diversity of biophysical attributes and environmental backgrounds. We found that simpler models that neither explicitly represented aerodynamic forcing nor canopy conductance achieved higher accuracy and signal-to-noise levels when optimally configured (rRMSE = 20%; R 2 = 0.89). Irrespective of model type, optimal configurations were those making use of key plant functional type dependent parameters, daily LAI, and constraints based on atmospheric moisture demand over soil moisture supply. Our findings have implications for more informed water resource management based on hydrological modeling and remote sensing
Beschreibung:Date Revised 09.09.2024
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:0094-8276
DOI:10.1029/2022GL100100