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Comparison of vineyard evapotranspiration estimates from surface renewal using measured and modelled energy balance components in the GRAPEX project

  • Christopher K. Parry
  • William P. Kustas
  • Kyle R. Knipper
  • Martha C. Anderson
  • Joseph G. Alfieri
  • John H. Prueger
  • Andrew J. McElroneEmail author
Original Paper
  • 15 Downloads

Abstract

Surface renewal (SR) is a biometeorological technique that uses high frequency air temperature measurements above a crop surface to estimate sensible heat flux (H). The H derived from SR is then combined with net radiation (Rn) and ground heat flux (G) measurements to estimate latent heat flux (LE) as the residual of an energy balance equation. Recent advances in SR theory enabled its use beyond research settings, and led to the development of an inexpensive, stand-alone SR system for use in commercial agricultural settings. However, these commercial applications require replacing expensive net radiometers with clear sky models designed to estimate Rn for the energy balance approach, while also assuming G is zero on a daily basis. The accuracy of substituting Rn measurements with modelled values is unknown, and the assumption of an inconsequential G requires additional testing. Here, we compare the accuracy of the SR derived estimates of H and LE when Rn is either measured directly or modelled, and we compare results to two eddy covariance (EC) LE observations, namely LE measured via EC with an infrared gas analyzer (ECIRGA) and LE solved as a residual in the surface energy balance (ECresid). These measurements were collected at the Grape Remote sensing Atmospheric Profile & Evapotranspiration eXperiment (GRAPEX) conducted over a vineyard within the Lodi, CA wine growing region. LE from SR using tower Rn data measured directly onsite was significantly correlated with LE from ECresid and from ECIRGA with a least squares regression slope ~ 1. LE derived with the modelled incoming solar radiation (SWi) and DisALEXI Rn approaches were also significantly correlated with LE from ECresid, but both modelling approaches overestimated LE at higher fluxes. Patterns were similar, but with more scatter for correlations between LE from ECIRGA and LE from SR using either modelled or remotely sensed Rn. Incorporating direct measurements of G had minimal impact on the agreement of several SR approaches and LE from both EC approaches, however, when differences did occur direct measures of G reduced scatter and bias especially for the empirical SR approach. Our results suggest that LE derived from the new SR method requires fairly accurate Rn modelling approaches to obtain reliable and unbiased estimates of daily LE in comparison to measured LE using EC techniques.

Notes

Acknowledgements

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. USDA is an equal opportunity provider and employer. The use of trade, firm, or corporation names in this article is for the information and convenience of the reader. Such use does not constitute official endorsement or approval by the US Department of Agriculture or the Agricultural Research Service of any product or service to the exclusion of others that may be suitable.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.USDA-ARS Crops Pathology and Genetics Research UnitDavisUSA
  2. 2.USDA-ARS Hydrology and Remote Sensing LaboratoryBeltsvilleUSA
  3. 3.USDA-ARS National Laboratory for Agriculture and the EnvironmentAmesUSA
  4. 4.Department of Viticulture and EnologyUniversity of CaliforniaDavisUSA

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