Location: Sustainable Agricultural Water Systems Research
Project Number: 2032-13220-002-024-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Jan 1, 2024
End Date: Jun 30, 2026
Objective:
The objective of this proposal is to develop a forecasted evapotranspiration (crop water use) product based entirely on satellite remote sensing to improve irrigation management decision making in California specialty crops.
Approach:
We will develop a machine learning-based framework using satellite-derived products as input to the machine learning model. This model will train on evapotranspiration estimates derived using the ALEXI-DisALEXI ET modeling framework. Applicability of this approach will be tested using common machine learning approaches (i.e., 80/20 split) as well as comparison to eddy covariance flux towers installed in wine grape vineyards, almond orchards, and olive orchards across the state that are a part of ongoing research activities within ARS.
