Abstract: The Russian wheat aphid, Diuraphis noxia, Kurdjumov (Homoptera: Aphididae) has been a major pest of small grains since its invasion of the United States. Losses to the cereal industry are estimated in the hundreds of millions. Understanding the dominant processes controlling spatial and temporal population dynamics of overwintering D. noxia enhances opportunities to develop a management system that makes more effective and judicious use of our management tools. Under typical Colorado winter conditions D. noxia mortality is spatially heterogeneous. Based on three field seasons of data collected at multiple sites in Colorado, we developed a model of D. noxia spatial and temporal overwintering densities. The model integrates two components: a small-scale, within-site, spatially explicit model using spatial statistical modeling; and a large-scale, between-site and between-year, spatially implicit model. Given overwinter weather conditions, remotely sensed data, and satellite imagery, the integrated model builds a map of D. noxia densities across the cropping system. Precipitation and temperature are dominant variables in the large-scale model and account for 63 % of the explained variation in the integrated model. The remaining variation is associated with the small-scale model and is attributed to differential within-field mortality. We have found that much of the within-field variation is significantly non-random and can be delineated to show areas of high and low mortality of D. noxia. Cross-validation of the integrated model quantifies the exceptional promise of this model for use in directed scouting and precision agriculture. This model, combined with current control costs (e.g. pesticides) and market value of the crop, identifies specific areas and conditions under which D. noxia populations will reach levels of economic importance.