Soil-surface CO2 flux (Rs), which is a large component of the carbon (C) budgets in grasslands, usually is measured infrequently using static or dynamic chambers. Therefore, to quantify annual C budgets, estimates of Rs are required during days when no direct measurements of Rs are available. Other researchers have developed empirical models based on soil temperature, soil volumetric water content (θv), and leaf area index (LAI) that have provided reasonable estimates of Rs during the growing season in ungrazed tallgrass prairie. However, the effects of mowing and grazing, which are common in grasslands, on predictions of Rs from those models are uncertain. Predictions of Rs during dormancy (postsenescence to spring fire) also are uncertain. Data from a year-long mowing study, which simulated grazing, were used to refit these models. Output from the models then was compared to independent data collected from nearby prairie sites. Results showed that LAI must be included to accurately estimate Rs in mowed prairie ecosystems. When LAI was not included in the model, predicted daily Rs following mowing was nearly four times greater than measured Rs, and cumulative, annual Rs was overestimated by 95–102%. When LAI was included in the model, predictions of Rs were comparable to measured Rs in the mowing study. Annual estimates of cumulative Rs ranged from 3.93 to 4.92 kg CO2/m2. When comparing the model with independent chamber data from nearby sites, cumulative Rs during those studies was within ±9% of cumulative estimates calculated from measured Rs. The model overestimated daily Rs during a dry period, suggesting a nonlinear response of Rs to soil water content; soil water matric potential may be more appropriate than θv for modeling Rs. Data suggest that Rs, in addition to being dependent on soil temperature and soil water content, is dependent on the photosynthetic capacity of the canopy and the subsequent translocation of C belowground.