Location: Sustainable Agricultural Water Systems Research
Project Number: 2032-13220-002-025-A
Project Type: Cooperative Agreement
Start Date: Jan 1, 2024
End Date: Apr 30, 2026
Objective:
The overall objective of this project is to develop a 3-, 7-, and 14- day forecasted actual ET product based on satellite data and machine learning and improve stress detection using novel machine learning methods to determine optimal, site-specific crop water use with ground-based and remotely sensed data.
Approach:
Recent state regulations (e.g., Sustainable Groundwater Management Act [SGMA]) and an unprecedented drought have created a situation where farmers are required to grow the unique crops only found in California with less water. This situation is creating a need within the grower community for better crop water use information. This work will address the myriad of issues in current irrigation/water allocation practices. First, it will address the spatial component, providing crop water use estimates over thousands of acres via a satellite imagery approach. Second, it will provide an estimate of upcoming crop water use via a forecasted ET product. Lastly, site-specific crop water use based on paired satellite imagery and ground-based sensors will be implemented to increase the accuracy and frequency of crop water optimal demands, improving daily management decision making.
