Analysis and Visualization of Evapotranspiration Data
Faculty Mentor Information
Dr. John Shovic, University of Idaho; and Dr. Mary Everett, University of Idaho
Presentation Date
7-15-2026
Abstract
Evapotranspiration (ET) is an essential data factor for farmers and water managers as it accurately indicates how much water is lost to the atmosphere, unused by crops and plants. NASA’s OpenET infrastructure allows anyone to access ET data for free, but this tool does not contain long term storage or default compatibility with databases and other software packages. The goal of this project is to create a reusable workflow for getting this OpenET data into the Grafana visualization software package, so that weather data for precise coordinates could be accessed and understood at glance. Python programming to access the OpenET API was used along with the MongoDB database to query and organize the data respectively. GitHub Actions provided a stable workflow for automating the querying script. Using a specialized set of commands, connection between the database and Grafana is possible. The continuing goal is to provide farmers and water managers a shareable file of this workflow’s steps in simple terms, that our technology stack might be replicated to increase efficiency in water management.
Analysis and Visualization of Evapotranspiration Data
Evapotranspiration (ET) is an essential data factor for farmers and water managers as it accurately indicates how much water is lost to the atmosphere, unused by crops and plants. NASA’s OpenET infrastructure allows anyone to access ET data for free, but this tool does not contain long term storage or default compatibility with databases and other software packages. The goal of this project is to create a reusable workflow for getting this OpenET data into the Grafana visualization software package, so that weather data for precise coordinates could be accessed and understood at glance. Python programming to access the OpenET API was used along with the MongoDB database to query and organize the data respectively. GitHub Actions provided a stable workflow for automating the querying script. Using a specialized set of commands, connection between the database and Grafana is possible. The continuing goal is to provide farmers and water managers a shareable file of this workflow’s steps in simple terms, that our technology stack might be replicated to increase efficiency in water management.