Location: Hydrology and Remote Sensing Laboratory
Title: Energy partitioning between plant canopy and soil, performance of the two-source energy balance model in a vineyardAuthor
KOOL, D. - Ben Gurion University Of Negev | |
Kustas, William - Bill | |
BEN-GAL, A. - Gilat Research Center | |
AGAM, N. - Ben Gurion University Of Negev |
Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 1/13/2021 Publication Date: 1/28/2021 Citation: Kool, D., Kustas, W.P., Ben-Gal, A., Agam, N. 2021. Energy partitioning between plant canopy and soil, performance of the two-source energy balance model in a vineyard. Agricultural and Forest Meteorology. 300:108328. https://doi.org/10.1016/j.agrformet.2021.108328. DOI: https://doi.org/10.1016/j.agrformet.2021.108328 Interpretive Summary: Partitioning of evapotranspiration (ET) into soil water evaporation and transpiration allows separate assessment of soil and plant water, energy, and carbon exchange, and thus provides critical information on water resources, agricultural production, and climate. Although models using remotely sensed data are ideally suited to maximize global coverage, one study over the contiguous US shows ratios of transpiration relative to ET ranging between 30% and 83%. This study evaluated the two-source energy balance model’s capability to partition ET into soil water evaporation and transpiration over a vineyard and resulted in improvements in the model parameterizations and the partitioning of soil and plant canopy temperatures, which will have universal application. These advancements in two-source energy balance model parameterizations will be implemented into the regional model using satellites, providing more reliable ET partitioning over complex canopies. Technical Abstract: Partitioning of evapotranspiration (ET) into soil water evaporation and transpiration allows separate assessment of soil and plant water, energy, and carbon exchange; providing critical information on water resources, agricultural production, and climate. Remote sensing based models are ideally suited to monitor ET over large areas but ET partitioning estimates vary widely. The objective of this study was to evaluate the two-source energy balance (TSEB) model for seasonal ET partitioning using total, soil, and vine canopy energy balance fluxes measured over a vineyard in the Negev desert in Israel. Energy fluxes were evaluated with the original TSEB and three adapted versions using 1) measured soil heat flux, 2) optimized plant transpiration parameterization, and 3) measured soil and vine temperatures instead of composite surface temperature as model inputs. Optimization of plant transpiration parameters revealed a model tendency to underestimate transpiration due to underestimation of available energy and potential transpiration. Adaptations included, among others, accounting for higher leaf radiation absorption expected in dense clumped canopies, which increases available energy, and increasing the Priestley-Taylor coefficient from 1.26 to 2, which increases potential transpiration. While the original TSEB gave reasonable total energy fluxes, the vine energy fluxes were greatly underestimated. Both soil heat flux and plant transpiration adaptations improved modeled vine energy fluxes throughout the season under both well-watered and water-stressed conditions. However, the performance of the TSEB version using measured soil and vine temperatures was inferior to applying the standard TSEB with composite temperature, likely due to a lack of sampling representative soil and plant canopy temperatures. While daily energy fluxes could be estimated with reasonable accuracy, sub-daily fluxes proved to be more challenging and merit further research. Finally, changes in ET partitioning with canopy development and in response to water stress could be detected quite well albeit it with an underestimation of the transpiration fraction of ET, which, on average, amounted to 39% using standard TSEB and 6% with optimized plant transpiration parameters. |