The Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX)

Melton, F. (2018), The Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) , Bull. Am. Meteorol. Soc.(manuscript in preparation), doi:10.1175/BAMS-D-16-.
Abstract

Development of better water management tools is the focus of the GRAPEX (Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment) project. An overview of GRAPEX and preliminary results are presented.

Particularly in light of California’s recent multi-year drought, there is a critical need for accurate and timely evapotranspiration (ET) and crop stress information to ensure long-term sustainability of high-value crops. Providing this information requires the development of tools applicable across the continuum from sub-field scales to improve water management within individual fields up to watershed and regional scales to assess water resources at county and state levels. High value perennial crops (vineyards and orchards) are major water users and growers will need better tools to improve water use efficiency to remain economically viable and sustainable during periods of prolonged drought. In order to develop these tools, government, university, and industry partners are evaluating a multi-scale remote sensing-based modeling system for application over vineyards. During the 2013 to 2017 growing seasons, the GRAPEX (Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment) project has collected micrometeorological and biophysical data within adjacent Pinot noir vineyards in the Central Valley of California. Additionally, each year ground, airborne and satellite remote sensing data were collected during Intensive Observation Periods (IOPs) representing different vine phenological stages. An overview of the measurements and some initial results regarding the impact of vine canopy architecture on modeling ET and plant stress are presented here. Refinements to the ET modeling system based on GRAPEX are being implemented initially at the field scale for validation and then will be integrated into the regional modeling toolkit for large area assessment.

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