Several geospatial technologies are now available for applications in precision irrigation, including soil property mapping, remote imaging from unmanned aerial systems (drones), spatial crop evapotranspiration modeling, and site-specific irrigation application technology. However, the potential contribution of different geospatial technologies toward improving crop production and water use efficiency remains unclear. The objective of this study was to determine agronomic outcomes using a cascade of increasingly complex geospatial technologies to assist irrigation decisions and applications. The four treatments from least to greatest complexity were 1) an FAO-56 water balance model with field-average soil data, 2) treatment #1 applied geospatially with site-specific soil information, 3) treatment #2 with FAO-56 basal crop coefficients (Kcb) estimated from weekly drone images, and 4) treatment #3 with irrigation applications occurring via commercial, map-based, site-specific irrigation technology. The field trial was conducted with cotton in the 2019 growing season at Maricopa, AZ. Results demonstrated no improvement in cotton fiber yield or irrigation water use efficiency by incorporating geospatial information into the FAO-56 water balance model. Fiber yield for the drone-based treatments were significantly lower than yield for less complex management technologies. The most positive outcome of the study was the development of an image processing pipeline to use drone-based images for irrigation decisions. Future irrigation management research in Arizona should develop technologies for improving temporal (rather than spatial) aspects of irrigation scheduling.