Cotton production is an important component of the culture, economy, and landscape in the Southern Ogallala Aquifer region and is reliant on irrigation using water pumped from the non-rechargeable aquifer. It is estimated that ~ 60% of the irrigation in the area uses center pivot equipment. As water from the aquifer becomes an increasingly limited and regulated resource, cotton producers, consultants, and researchers could benefit from using simulation models that account for spatial and temporal variability in irrigation, inter-seasonal weather, and soil pedology. In order to provide decision support information that can interact with current variable rate equipment abilities, such models must be effective at the production scale (> 50 ha) and at a spatial and temporal resolutions relevant to management decisions (e.g., 20-m grid and 1-h time steps). The Precision Agricultural-Landscape Modeling System was specifically developed to meet these scale and resolution requirements, but lacked a specific cotton model. It was hypothesized that integrating the cotton growth model Cotton2K with PALMS to produce PALMScot would provide an approach towards modeling pivot irrigated cotton systems at a landscape-scale. Our experimental objectives were i) to integrate the Cotton2K and PALMS models to form PALMScot; ii) evaluate the use of the model and its capability to calculate soil water content and plant growth in two contrasting soil series, across two growing seasons, and two levels of irrigation; iii) evaluate the model’s capability to calculate soil water content and plant growth at multiple locations within a production-scale, pivot irrigated cotton field across two growing seasons with divergent weather conditions; and iv) evaluate the model’s capability to calculate soil water content, plant growth, and boll and lint production at multiple locations across a ~ 56-ha production field characterized by variability in soil pedology. Results showed that PALMScot provides a continuous accounting of mass and energy balances, and integrates interactions between the atmosphere, soil, and above and below ground physiological plant processes. Deviations of model-calculated from measured soil water content values were consistently < 0.02 m3 m 3, measures of calculation efficiency were positive in most cases, and deviation between calculated and measured plant heights were consistently < 0.10 m in both Amarillo fine sandy loam and Pullman clay loam soil series. Therefore, we conclude that PALMScot correctly calculates soil water content and crop growth across the unique scale of a production field and could provide decision support input at the fine spatial and temporal resolution required for precision agriculture and management of pivot irrigated cotton systems at a landscape-scale