Estimating vineyard water use with remote sensing: Lessons learned from the GRAPEX project

W. P. Kustas, K. Knipper, M. Anderson, J. G. Alfieri, M. M. Alsina, A. F. Torres-Rua, L. McKee, J. H. Prueger, L. Hipps, A. J. McElrone, N. E. Bambach-Ortiz, F. Gao, H. Nieto, W. A. White, C. Hain, Nurit Agam, K. Alstad, W. T. Crow, F. Lei, A. KarnieliL. Sanchez, N. Dokoozlian, F. S. Melton

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The Grape Remote sensing Atmospheric Profile and Evapotranspiration experiment (GRAPEX) has a goal of developing remote sensing-based evapotranspiration (ET) toolkit using earth observations for monitoring vineyard water use and stress from with-in vineyard block to regional scales in the California Central Valley. This information is key to improving water use efficiency and water conservation in such water limited environments in order to have a sustainable agroecosystem. Through this research project, new insights and understandings of vine physiology, water, carbon and energy exchange processes and relationships between remote sensing retrieval algorithms of vine biomass, cover and land surface temperature have emerged. The unique canopy architecture, row structure and large interrow spacing often with a cover crop make for a challenging system to model ET with remote sensing. This presentation will provide a summary of key GRAPEX findings from in situ and remote sensing measurements from the leaf and canopy level to the field and landscape scales in estimating vine water use and stress. In addition, future research directions involving new sensor technologies will be presented and discussed.
Original languageEnglish
Title of host publicationAmerican Geophysical Union, Fall Meeting 2020
StatePublished - Dec 2020


  • 1814 Energy budgets
  • 1818 Evapotranspiration
  • 1855 Remote sensing
  • 1895 Instruments and techniques: monitoring


Dive into the research topics of 'Estimating vineyard water use with remote sensing: Lessons learned from the GRAPEX project'. Together they form a unique fingerprint.

Cite this