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ET Partitioning Assessment Using the TSEB Model and sUAS Information across California Central Valley Vineyards

Authors :
Agricultural Research Service (US)
Federal Government of the United States
National Aeronautics and Space Administration (US)
Utah State University
Nieto, Héctor [0000-0003-4250-6424]
Gao, Rui
Torres-Rua, Alfonso F.
Nieto, Héctor
Zahn, Einara
Hipps, Lawrence E.
Kustas, William P.
Alsina, María Mar
Bambach, Nicolas
Castro, Sebastian J.
Prueger, John H.
Alfieri, Joseph G.
McKee, Lynn G.
White, William A.
Gao, Feng
McElrone, Andrew J.
Anderson, Martha C.
Knipper, Kyle
Coopmans, Calvin
Gowing, Ian
Agam, Nurit
Sánchez, Luis
Dokoozlian, Nick
Agricultural Research Service (US)
Federal Government of the United States
National Aeronautics and Space Administration (US)
Utah State University
Nieto, Héctor [0000-0003-4250-6424]
Gao, Rui
Torres-Rua, Alfonso F.
Nieto, Héctor
Zahn, Einara
Hipps, Lawrence E.
Kustas, William P.
Alsina, María Mar
Bambach, Nicolas
Castro, Sebastian J.
Prueger, John H.
Alfieri, Joseph G.
McKee, Lynn G.
White, William A.
Gao, Feng
McElrone, Andrew J.
Anderson, Martha C.
Knipper, Kyle
Coopmans, Calvin
Gowing, Ian
Agam, Nurit
Sánchez, Luis
Dokoozlian, Nick
Publication Year :
2023

Abstract

Evapotranspiration (ET) is a crucial part of commercial grapevine production in California, and the partitioning of this quantity allows the separate assessment of soil and vine water and energy fluxes. This partitioning has an important role in agriculture since it is related to grapevine stress, yield quality, irrigation efficiency, and growth. Satellite remote sensing-based methods provide an opportunity for ET partitioning at a subfield scale. However, medium-resolution satellite imagery from platforms such as Landsat is often insufficient for precision agricultural management at the plant scale. Small, unmanned aerial systems (sUAS) such as the AggieAir platform from Utah State University enable ET estimation and its partitioning over vineyards via the two-source energy balance (TSEB) model. This study explores the assessment of ET and ET partitioning (i.e., soil water evaporation and plant transpiration), considering three different resistance models using ground-based information and aerial high-resolution imagery from the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). We developed a new method for temperature partitioning that incorporated a quantile technique separation (QTS) and high-resolution sUAS information. This new method, coupled with the TSEB model (called TSEB-2TQ), improved sensible heat flux (H) estimation, regarding the bias, with around 61% and 35% compared with the H from the TSEB-PT and TSEB-2T, respectively. Comparisons among ET partitioning estimates from three different methods (Modified Relaxed Eddy Accumulation—MREA; Flux Variance Similarity—FVS; and Conditional Eddy Covariance—CEC) based on EC flux tower data show that the transpiration estimates obtained from the FVS method are statistically different from the estimates from the MREA and the CEC methods, but the transpiration from the MREA and CEC methods are statistically the same. By using the transpiration from the CEC method to compare with th

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1431961710
Document Type :
Electronic Resource