This paper presents a case study of the first application of the dynamic Variable Rate Irrigation (VRI) System developed by the University of Georgia to cotton. The system consists of the EZZone management zone software, the University of Georgia Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2017 in a cotton field to evaluate the performance of the system in cotton. The field was divided into four parallel strips. All four strips were 240 m wide. Two strips received variable rates of irrigation based on the UGA SSA decision support tool (DST) while the other two received uniform irrigation based on the grower’s practice. Sentinel-2 satellite images from the last two years were analyzed to find the NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) variability of the field. Additionally soil electrical conductivity data, soil type data as well as elevation data were combined in the EZZone software to delineate irrigation management zones (IMZs). IMZs were delineated for the entire field but used only in the strips where irrigation was applied with variable rates. Eighteen UGA SSA sensor probes were installed in the 4 strips after planting to measure soil moisture. The UGA SSA system reported soil moisture data hourly and they were visualized on the UGA SSA web portal. The DST converted soil moisture data to actionable irrigation recommendations based on the latest soil moisture readings. This paper presents the results of the yield and irrigation water use efficiency (IWUE) comparison between the two irrigation treatments. The analysis of the data showed that the IWUE was considerably higher in the VRI strips than the strips irrigated uniformly.