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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #390339

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Evaluating different metrics from the thermal-based Two-Source Energy Balance model for monitoring grapevine water stress

Author
item NIETO, H. - University Of Alcala
item ALSINA, M. - E & J Gallo Winery
item Kustas, William - Bill
item GARCIA-TEJERA, O. - Consejo Superior De Investigaciones Cientificas (CSIC)
item CHEN, F. - Non ARS Employee
item BAMBACH, N. - University Of California, Davis
item Gao, Feng
item Alfieri, Joseph
item HIPPS, L. - Utah State University
item Prueger, John
item McKee, Lynn
item ZHAN, E. - Princeton University
item BOU-ZEID, E. - Princeton University
item McElrone, Andrew
item CASTRO, S. - University Of California, Davis
item DOKOOZLIAN, N. - E & J Gallo Winery

Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/26/2022
Publication Date: N/A
Citation: N/A

Interpretive Summary: Precision irrigation management requires operational monitoring of crop water status. Thermal remote sensing has shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Stress Water Index (CWSI). The Two-Source Energy Balance (TSEB) model a widely-used and robust evapotranspiration model using remote sensing and has the capability of partitioning ET into the crop transpiration and soil evaporation components, which we hypothesize is required for accurate CWSI estimates. This study evaluated different TSEB formulations related to its retrievals of actual ET, transpiration, and stomata conductance, in order to track crop water stress in a vineyard in California, part of the Grape Remote sensing Atmospheric Profile Evapotranspiration eXperiment (GRAPEX). Results showed that the most robust variable for tracking water stress was the TSEB-derived leaf stomata conductance, with the strongest correlation with both the measured root-zone soil moisture and stomata conductance gas exchange measurements. This suggests application of TSEB with satellite data deriving leaf stomata conductance may serve as the best proxy for CWSI mapping and improve precision irrigation management of tree and vine crop systems.

Technical Abstract: Precision irrigation management requires operational monitoring of crop water status. However there is still some controversy on how to account for crop water stress, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomata conductance, or sap flow. On the other hand, thermal remote sensing has shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Stress Water 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 and robust evapotranspiration model for remote sensing and has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is hypothesized required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomata conductance, in order 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 drip irrigation system in a merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomata 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 stomata conductance, with the strongest correlation with both the measured root-zone soil moisture and stomata conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early afternoon.