Methods to predict the use of new technology at locations other than where experimental data exist also involved the use of spatially explicit analysis and the concept of geographic equivalence. First, the geographic characteristics of areas were identified in which experimental data existed on the performance of crops using new technology. Then, areas of geographic equivalence were identified – areas which had similar rainfall and soil patterns. For each of these simulation zones, the EPIC model was used to predict the performance of the major crops grown in the area. The model was used to determine both baseline conditions and estimates assuming adoption of the new technology. These results were based on biophysically defined zones, which did not correspond to politically defined boundaries under which economic data on agriculture is collected. The results from biophysically defined simulation zones were aggregated using weighted mean averages to define the performance of crops and livestock by politically defined areas. This allowed us to make biophysical inputs to economic models and vice versa in a holistic approach to assessing the utility of the new technology.