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Robust inference of ecosystem soil water stress from eddy covariance data.

Authors :
Sloan, Brandon P.
Feng, Xue
Source :
Agricultural & Forest Meteorology. Dec2023, Vol. 343, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. We develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site's soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data. [Display omitted] • Most eddy covariance sites do not have a robust soil water stress signal. • Deficient model performance is a key contributor to the lack of robustness. • The robustness of ecosystem soil water stress signals is site-specific. • Grass/annual vegetation sites have more robust stress signals than forested sites. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01681923
Volume :
343
Database :
Academic Search Index
Journal :
Agricultural & Forest Meteorology
Publication Type :
Academic Journal
Accession number :
173559568
Full Text :
https://doi.org/10.1016/j.agrformet.2023.109744