3 results on '"Einara Zahn"'
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2. Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress
- Author
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Héctor Nieto, María Mar Alsina, William P. Kustas, Omar García-Tejera, Fan Chen, Nicolas Bambach, Feng Gao, Joseph G. Alfieri, Lawrence E. Hipps, John H. Prueger, Lynn G. McKee, Einara Zahn, Elie Bou-Zeid, Andrew J. McElrone, Sebastian J. Castro, Nick Dokoozlian, 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), and Nieto, Héctor
- Subjects
Soil Science ,Agronomy and Crop Science ,Water Science and Technology - 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. 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.
- Published
- 2022
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3. Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards
- Author
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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, Maria Mar Alsina, Lynn G. McKee, Einara Zahn, Elie Bou-Zeid, and Nick Dokoozlian
- Subjects
Crop and Pasture Production ,Soil Science ,Agronomy & Agriculture ,Other Agricultural and Veterinary Sciences ,Agronomy and Crop Science ,Water Science and Technology - 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 ~ 50W/m2 compared to EC measurements. 3SEB improved upon TSEB simulations, with the largest differences being concentrated in the spring season, when there is greater mixing between grapevine foliage and the cover crop. Additionally, 3SEB's modeled ET partitioning (T/ET) compared well against an EC T/ET retrieval method, being only slightly underestimated. Overall, these promising results indicate 3SEB can be of great utility to vineyard irrigation management, especially to improve T/ET estimations and to quantify the contribution of the cover crop to ET. Improved knowledge of T/ET can enhance grapevine water stress detection to support irrigation and water resource management.Supplementary informationThe online version contains supplementary material available at 10.1007/s00271-022-00787-x.
- Published
- 2022
- Full Text
- View/download PDF
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