Evidence map›Paper›PMID 36172254›Full record

ArticleIrrigation science2022

Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards.

Vicente Burchard-Levine, Héctor Nieto, William P Kustas, Feng Gao, Joseph G Alfieri, John H Prueger, Lawrence E Hipps, Nicolas Bambach-Ortiz, Andrew J McElrone, Sebastian J Castro and 5 more

Abstract read
In one paragraph

Article in Irrigation science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Vicente Burchard-LevineEnvironmental Remote Sensing and Spectroscopy Laboratory (SpecLab), Spanish National Research Council (CSIC), Madrid, Spain.ORCID 0000-0003-0222-8706
Héctor NietoInstitute of Agricultural Sciences, Spanish National Research Council (CSIC), 28006 Madrid, Spain.
William P KustasAgriculture Research Service, U.S. Department of Agriculture, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.
Feng GaoAgriculture Research Service, U.S. Department of Agriculture, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.
Joseph G AlfieriAgriculture Research Service, U.S. Department of Agriculture, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.
John H PruegerUSDA-ARS, National Laboratory for Agriculture and the Environment, Ames, IA USA.
Lawrence E HippsDepartment of Plants Soils and Climate, Utah State University, Logan, UT USA.
Nicolas Bambach-OrtizDepartment of Land, Air and Water Resources, University of California, Davis, CA USA.
Andrew J McElroneUSDA-ARS Crops Pathology and Genetics Research Unit, Davis, CA USA.
Sebastian J CastroDepartment of Viticulture and Enology, University of California, Davis, CA USA.
Maria Mar AlsinaE and J Gallo Winery, Winegrowing Research, Modesto, CA USA.
Lynn G McKeeAgriculture Research Service, U.S. Department of Agriculture, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705 USA.
Einara ZahnDepartment of Civil and Environmental Engineering, Princeton University, Princeton, NJ USA.
Elie Bou-ZeidDepartment of Civil and Environmental Engineering, Princeton University, Princeton, NJ USA.
Nick DokoozlianE and J Gallo Winery, Winegrowing Research, Modesto, CA USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improved accuracy of evapotranspiration (ET) estimation, including its partitioning between transpiration (T) and surface evaporation (E), is key to monitor agricultural water use in vineyards, especially to enhance water use efficiency in semi-arid regions such as California, USA. Remote-sensing methods have shown great utility in retrieving ET from surface energy balance models based on thermal infrared data. Notably, the two-source energy balance (TSEB) has been widely and robustly applied in numerous landscapes, including vineyards. However, vineyards add an additional complexity where the landscape is essentially made up of two distinct zones: the grapevine and the interrow, which is often seasonally covered by an herbaceous cover crop. Therefore, it becomes more complex to disentangle the various contributions of the different vegetation elements to total ET, especially through TSEB, which assumes a single vegetation source over a soil layer. As such, a remote-sensing-based three-source energy balance (3SEB) model, which essentially adds a vegetation source to TSEB, was applied in an experimental vineyard located in California's Central Valley to investigate whether it improves the depiction of the grapevine-interrow system. The model was applied in four different blocks in 2019 and 2020, where each block had an eddy-covariance (EC) tower collecting continuous flux, radiometric, and meteorological measurements. 3SEB's latent and sensible heat flux retrievals were accurate with an overall RMSD ~ 50 W/m Supplementary Information: The online version contains supplementary material available at 10.1007/s00271-022-00787-x.

Identifiers

PMID36172254
PMCPMC9509310

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.