Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress

Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon.

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Main Authors: Nieto, Héctor, Alsina, María Mar, Kustas, William P., García-Tejera, Omar, Chen, Fan, Bambach, Nicolas, Gao, Feng, Alfieri, Joseph G., Hipps, Lawrence E., Prueger, John H., McKee, Lynn G., Zahn, Einara, Bou-Zeid, Elie, McElrone, Andrew J., Castro, Sebastian J., Dokoozlian, Nick
Other Authors: National Aeronautics and Space Administration (US)
Format: artículo biblioteca
Language:English
Published: Springer Nature 2022-09-01
Online Access:http://hdl.handle.net/10261/286704
http://dx.doi.org/10.13039/100007917
http://dx.doi.org/10.13039/501100003339
http://dx.doi.org/10.13039/100000199
http://dx.doi.org/10.13039/100000104
https://api.elsevier.com/content/abstract/scopus_id/85130205231
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spelling dig-ias-es-10261-2867042024-05-19T20:51:13Z Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress Nieto, Héctor Alsina, María Mar Kustas, William P. García-Tejera, Omar Chen, Fan Bambach, Nicolas Gao, Feng Alfieri, Joseph G. Hipps, Lawrence E. Prueger, John H. McKee, Lynn G. Zahn, Einara Bou-Zeid, Elie McElrone, Andrew J. Castro, Sebastian J. Dokoozlian, Nick National Aeronautics and Space Administration (US) Department of Agriculture (US) Agricultural Research Service (US) Conferencia de Rectores de las Universidades Españolas Consejo Superior de Investigaciones Científicas (España) Nieto, Héctor [0000-0003-4250-6424] Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon. Funding and logistical support for the GRAPEX project were provided by E. & J. Gallo Winery and from the NASA Applied Sciences-Water Resources Program (Grant no. NNH17AE39I). This research was also supported in part by the U.S. Department of Agriculture, Agricultural Research Service. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Peer reviewed 2023-01-12T14:50:30Z 2023-01-12T14:50:30Z 2022-09-01 artículo http://purl.org/coar/resource_type/c_6501 Irrigation Science 40: 697-713 (2022) 0342-7188 http://hdl.handle.net/10261/286704 10.1007/s00271-022-00790-2 http://dx.doi.org/10.13039/100007917 http://dx.doi.org/10.13039/501100003339 http://dx.doi.org/10.13039/100000199 http://dx.doi.org/10.13039/100000104 2-s2.0-85130205231 https://api.elsevier.com/content/abstract/scopus_id/85130205231 en Publisher's version The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI 10.1007/s00271-022-00790-2 https://doi.org/10.1007/s00271-022-00790-2 Sí open application/pdf Springer Nature
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country España
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libraryname Biblioteca del IAS España
language English
description Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon.
author2 National Aeronautics and Space Administration (US)
author_facet National Aeronautics and Space Administration (US)
Nieto, Héctor
Alsina, María Mar
Kustas, William P.
García-Tejera, Omar
Chen, Fan
Bambach, Nicolas
Gao, Feng
Alfieri, Joseph G.
Hipps, Lawrence E.
Prueger, John H.
McKee, Lynn G.
Zahn, Einara
Bou-Zeid, Elie
McElrone, Andrew J.
Castro, Sebastian J.
Dokoozlian, Nick
format artículo
author Nieto, Héctor
Alsina, María Mar
Kustas, William P.
García-Tejera, Omar
Chen, Fan
Bambach, Nicolas
Gao, Feng
Alfieri, Joseph G.
Hipps, Lawrence E.
Prueger, John H.
McKee, Lynn G.
Zahn, Einara
Bou-Zeid, Elie
McElrone, Andrew J.
Castro, Sebastian J.
Dokoozlian, Nick
spellingShingle Nieto, Héctor
Alsina, María Mar
Kustas, William P.
García-Tejera, Omar
Chen, Fan
Bambach, Nicolas
Gao, Feng
Alfieri, Joseph G.
Hipps, Lawrence E.
Prueger, John H.
McKee, Lynn G.
Zahn, Einara
Bou-Zeid, Elie
McElrone, Andrew J.
Castro, Sebastian J.
Dokoozlian, Nick
Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
author_sort Nieto, Héctor
title Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
title_short Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
title_full Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
title_fullStr Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
title_full_unstemmed Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
title_sort evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
publisher Springer Nature
publishDate 2022-09-01
url http://hdl.handle.net/10261/286704
http://dx.doi.org/10.13039/100007917
http://dx.doi.org/10.13039/501100003339
http://dx.doi.org/10.13039/100000199
http://dx.doi.org/10.13039/100000104
https://api.elsevier.com/content/abstract/scopus_id/85130205231
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