To identify the optimal spatial scales for which carbon storage agreements can be designed, the uncertainty in estimating stocks of soil organic carbon at field management scales must be assessed. The objective of this study was to compare alternative approaches for estimating the stocks of soil organic carbon of agriculturally managed fields. We studied two fields (~15 and ~17 ha) in Iowa where soils were developed in Wisconsinan till and loess, respectively. Soils occurred on characteristic landscape positions in quintessential drainage sequences, ranging from well to poorly drained. The fields were sampled in grid patterns at 125 or 143 sampling locations to a depth of 30 cm. Organic carbon content and bulk density were determined for each of three depth increments. The stocks of organic carbon were estimated in three ways: (1) by using a county-specific, expert database to predict soil characteristics, (2) by using classical statistical analyses, in which (a) the data from all sampling points were lumped or (b) in which the data from each mapping unit were stratified and then compared with those from other mapping units, and (3) by using geostatistical analysis, in which data for the entire field were analyzed by semivariograms and kriged maps of the organic carbon distribution. Each approach resulted in a different estimate of the total organic carbon stock of the field. Each approach also yielded a different estimate of the uncertainty in the carbon stock value. For both fields, the expert database approach gave the largest estimate of carbon stocks, while block kriging gave the lowest estimate. The uncertainty associated with each estimate ranged from 10 to 20% of the estimated stock.