Groundwater provides the primary water supply for irrigated agriculture in many hyper-arid climate zones. Due to limited precipitation, water withdrawals in these regions often outpace groundwater recharge, leaving them vulnerable to accelerating groundwater-level declines. This project aims to understand how the expansion of cultivated land areas and irrigation intensity correspond to groundwater level changes in hyper-arid regions. Satellite imagery offers a way to track agricultural practices and model their relationship to groundwater levels over time. However, accessing, processing, and tracking this relationship requires specialized software and coding experience, creating a technical barrier that prevents many potential users from efficiently using available data to understand these groundwater-agricultural relationships. To address this problem, this project will develop a reproducible workflow and written report for modeling the relationship between groundwater-level changes and evapotranspiration (ET) at 16 hyper-arid study sites. This report will include visualizations of ET over time for each site using 12–36-month boxcar-filtered time windows; summary tables of ET changes across 12-, 24-, and 36-month windows; and statistical testing examining relationships between groundwater-level change and ET. Furthermore, this report will include interpretations of the findings and detailed documentation for reproducing the analysis. This work will help better characterize the drivers leading to groundwater depletion in hyper-arid regions and reduce technical barriers to conducting groundwater-agriculture research. Organizations such as the FAO (Food and Agriculture Organization), IGRAC (International Groundwater Resources Assessment Centre), SDG6 (Sustainable Development Goal 6), and regional agencies like the Groundwater Sustainability Agency for Cuyama could use this accessible workflow and report to inform policy decisions that promote sustainable groundwater use for irrigation.