CSC Workshop: How Machine Learning Can Help Us Estimate Crop Water Demand and Inform Irrigation Decisions?

​Precise irrigation is essential for sustainable agriculture, especially in arid and semi-arid regions. Determining when and how much water to apply is key to improving water use efficiency and supporting crop productivity. In this workshop, we will explore how various factors, including crop type, climate, and soil conditions, affect irrigation decisions, and how environmental monitoring tools can help guide these decisions. 

Participants will be introduced to different types of datasets commonly used in irrigation management, including plant sensor data, weather observations, and remote sensing imagery. We will discuss how machine learning can be used to integrate these diverse data sources and estimate crop water demand. The session will conclude with a hands-on activity to build a simple machine learning model for irrigation support.

This workshop is taught by Jamie Duan (Postdoctoral Research Scientist at the Lamont-Doherty Earth Observatory of Columbia University).

This workshop is planned to take place in-person only (Milstein 516).

​​​​​​We look forward to seeing you there!

​​​​​​For more information about the Barnard CSC, go to https://www.csc.barnard.edu or follow us on Instagram and X (@barnard_csc).