Multilayer canopy model outperforms big-leaf model for evapotranspiration predictions under high water and heat stress conditions

Multilayer canopy model outperforms big-leaf model for evapotranspiration predictions under high water and heat stress conditions | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 21 January 2026 V1 Latest version Share on Multilayer canopy model outperforms big-leaf model for evapotranspiration predictions under high water and heat stress conditions Authors : Pushpendra Raghav 0000-0002-2982-069X , Yanlan Liu 0000-0001-5129-6284 [email protected] , Mukesh Kumar 0000-0001-7114-9978 , and Gautam Bisht 0000-0001-6641-7595 Authors Info & Affiliations https://doi.org/10.22541/au.176901793.37447081/v1 150 views 85 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Accurate estimation of evapotranspiration (ET) is critical for understanding land–atmosphere interactions, assessing climate impacts on ecosystem function, and informing water resource management. Most land surface models (LSMs) represent vegetation using a simplified big-leaf formulation, in which the canopy is treated as a single, uniform layer. Multilayer canopy (MLCAN) models offer a more mechanistic alternative by explicitly resolving vertical gradients in radiative transfer, photosynthesis, aerodynamics, and leaf temperature, yet it remains unclear when this added complexity leads to improved ET estimates. Here, we compared ET estimates from multilayer and big-leaf models constrained by eddy covariance observations and GEDI-derived canopy structure across sites in diverse ecoclimate regions. We show that MLCAN outperforms the big-leaf model under high-stress environments, particularly during periods of low soil moisture (SM) and high vapor pressure deficit (VPD), under clear-sky conditions, at drier sites, and in canopies with dense and vertically symmetric leaf area distributions. In contrast, MLCAN amplifies model errors under low-stress or cloudy conditions, when within-canopy gradients are muted. Process-level diagnostics reveal that the improved performance of MLCAN stems from its ability to represent within-canopy microclimate, resulting in less negative leaf water potentials and cooler leaf temperatures during high-VPD and low-SM conditions. Together, these findings reveal the climate and vegetation configurations where multilayer canopy complexity enhances ET predictions, which becomes increasingly relevant under increasing climate stress. Supplementary Material File (1061882_0_merged_1768436897.pdf) Download 3.60 MB File (main_doc.pdf) Download 3.60 MB File (supplementary_doc.pdf) Download 7.35 MB Information & Authors Information Version history V1 Version 1 21 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords big-leaf model climatology (global change) evapotranspiration land surface modeling multilayer canopy model plant stress remote sensing Authors Affiliations Pushpendra Raghav 0000-0002-2982-069X University of Alabama, Tuscaloosa View all articles by this author Yanlan Liu 0000-0001-5129-6284 [email protected] University of California Los Angeles View all articles by this author Mukesh Kumar 0000-0001-7114-9978 The University of Alabama System View all articles by this author Gautam Bisht 0000-0001-6641-7595 Pacific Northwest National Laboratory View all articles by this author Metrics & Citations Metrics Article Usage 150 views 85 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Pushpendra Raghav, Yanlan Liu, Mukesh Kumar, et al. Multilayer canopy model outperforms big-leaf model for evapotranspiration predictions under high water and heat stress conditions. Authorea . 21 January 2026. DOI: https://doi.org/10.22541/au.176901793.37447081/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . Format Please select one from the list RIS (ProCite, Reference Manager) EndNote BibTex Medlars RefWorks Direct import Tips for downloading citations document.getElementById('citMgrHelpLink').addEventListener('click', function() { popupHelp(this.href); return false; }); $(".js__slcInclude").on("change", function(e){ if ($(this).val() == 'refworks') $('#direct').prop("checked", false); $('#direct').prop("disabled", ($(this).val() == 'refworks')); }); Cited by Pushpendra Raghav, Mukesh Kumar, PULSE: A Novel Potential Underlying Water Use Efficiency‐Based Method for Latent Heat and Surface Energy Imbalance Correction, Water Resources Research, 62 , 5, (2026). https://doi.org/10.1029/2025WR042766 Crossref Loading... View Options View options PDF View PDF Figures Tables Media Share Share Share article link Copy Link Copied! Copying failed. 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