Utility of the two-source energy balance (TSEB) model in vine and interrow flux partitioning over the growing season
For monitoring water use in vineyards, it becomes important to evaluate the evapotranspiration (ET) contributions from the two distinct management zones: the vines and the interrow. Often the interrow is not completely bare soil but contains a cover crop that is senescent during the main growing season (nominally May–August), which in Central California is also the dry season. Drip irrigation systems running during the growing season supply water to the vine plant and re-wet some of the surrounding bare soil. However, most of the interrow cover crop is dry stubble by the end of May. This paper analyzes the utility of the thermal-based two-source energy balance (TSEB) model for estimating daytime ET using tower-based land surface temperature (LST) estimates over two Pinot Noir (Vitis vinifera) vineyards at different levels of maturity in the Central Valley of California near Lodi, CA. The data were collected as part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Local eddy covariance (EC) flux tower measurements are used to evaluate the performance of the TSEB model output of the fluxes and the capability of partitioning the vine and cover crop transpiration (T) from the total ET or T/ET ratio. The results for the 2014–2016 growing seasons indicate that TSEB output of the energy balance components and ET, particularly, over the daytime period yield relative differences with flux tower measurements of less than 15%. However, the TSEB model in comparison with the correlation-based flux partitioning method overestimates T/ET during the winter and spring through bud break, but then underestimates during the growing season. A major factor that appears to affect this temporal behavior in T/ET is the daily LAI used as input to TSEB derived from a remote sensing product. An additional source of uncertainty is the use of local tower-based LST measurements, which are not representative of the flux tower measurement source area footprint.
Funding provided by E.&J. Gallo Winery contributed towards the acquisition and processing of the ground truth data collected during GRAPEX IOPs. In addition, we would like to thank the staff of Viticulture, Chemistry and Enology Division of E.&J. Gallo Winery for the assistance in the collection and processing of field data during GRAPEX IOPs. Finally, this project would not have been possible without the cooperation of Mr. Ernie Dosio of Pacific Agri Lands Management, along with the Borden vineyard staff, for logistical support of GRAPEX field and research activities. The senior author would like to acknowledge financial support for this research from NASA Applied Sciences-Water Resources Program [Announcement number NNH16ZDA001N-WATER]. Proposal no. 16-WATER16_2–0005, Request number: NNH17AE39I. USDA is an equal opportunity provider and employer.
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Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
- Alfieri JG, Kustas WP, Prueger JH, McKee LG, Hipps LE, Gao F (this issue) A multi-year intercomparison of micrometeorological observations at adjacent vineyards in California’s central valley during GRAPEX. Irrig SciGoogle Scholar
- Colaizzi PD, Agam N, Tolk JA, Evett SR, Howell TA, Gowda PH, O’Shaughnessy SA, Kustas WP, Anderson MC (2014) Two-source energy balance model to calculate E, T, and ET: comparison of Priestley–Taylor and Penman–Monteith formulations and two time scaling methods. Trans ASABE 57(2):479–498Google Scholar
- Colaizzi PD, Agam N, Tolk JA, Evett SR, Howell TA, O’Shaughnessy SA, Gowda PH, Kustas WP, Anderson MC (2016c) Advances in a two-source energy balance model: partitioning of evaporation and transpiration for cotton using component and composite surface temperatures. Trans ASABE 59(1):181–197. https://doi.org/10.13031/trans.59.11215 CrossRefGoogle Scholar
- Goudriaan J (1977) Crop micrometeorology: a simulation stud. Tech. rep. Center for Agricultural Publications and Documentation, WageningenGoogle Scholar
- Hillel D (1998) Environmental soil physics. Academic Press, New YorkGoogle Scholar
- Knipper KR, Kustas WP, Anderson MC, Aleri JG, Prueger JH, Hain CR, Gao F, Yang Y, McKee LG, Nieto H, Hipps LE, Alsina MM, Sanchez L (this issue) Evapotranspiration estimates derived using thermal-based satellite remote sensing and data fusion for irrigation management in California vineyards. Irrig SciGoogle Scholar
- Kustas WP, Nieto H, Morillas L, Anderson MC, Alfieri JG, Hipps LE, Villagarcía L, Domingo F, García M (2016) Revisiting the paper “using radiometric surface temperature for surface energy flux estimation in mediterranean drylands from a two-source perspective. Remote Sens Environ 184:645–653CrossRefGoogle Scholar
- Kustas WP, Agam N, Alfieri AJ, McKee LG, Preuger JH, Hipps LE, Howard AM, Heitman JL (this issue) Below canopy radiation divergence in a vineyard—implications on inter-row surface energy balance. Irrig SciGoogle Scholar
- Nieto H, Kustas WP, Torres-Rúa A, Alfieri JG, Gao F, Anderson MC, White WA, Song L, del Mar Alsina M, Prueger JH, McKee M, Elarab M, McKee LG (2018b) Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and multispectral imagery. Irrig Sci. https://doi.org/10.1007/s00271-018-0585-9 CrossRefGoogle Scholar
- Parry CK, Nieto H, Guillevic P, Agam N, Kustas WP, Alfieri J, McKee L, McElrone AJ (this issue) An intercomparison of radiation partitioning models in vineyard row structured canopies. Irrig SciGoogle Scholar
- Semmens KA, Anderson MC, Kustas WP, Gao F, Alfieri JG, McKee L, Prueger JH, Hain CR, Cammalleri C, Yang Y, Xia T, Sanchez L, Alsina MM, Vélez M (2016) Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach. Remote Sens Environ 185:155–170. https://doi.org/10.1016/j.rse.2015.10.025 CrossRefGoogle Scholar
- Sun L, Gao F, Anderson MC, Kustas WP, Alsina M, Sanchez L, Sams B, McKee LG, Dulaney WP, White A, Alfieri JG, Prueger JH, Melton F, Post K (2017) Daily mapping of 30 m LAI, NDVI for grape yield prediction in California vineyard. Remote Sens 9:317. https://doi.org/10.3390/rs9040317 CrossRefGoogle Scholar
- White AW, Alsina M, Nieto H, McKee L, Gao F, Kustas WP (this issue) Indirect measurement of leaf area index in California vineyards: utility for validation of remote sensing-based retrievals. Irrig SciGoogle Scholar