Pest phenology models allow producers to anticipate pest outbreaks and deploy integrated pest management (IPM) strategies. Phenology models are particularly useful for cropping systems with multiple economically damaging pests throughout a season. Potato (Solanum tuberosum L.) crops of Washington State, USA, are attacked by many insect pests including the potato tuberworm (Phthorimaea operculella Zeller), the beet leafhopper (Circulifer tenellus Baker), and the green peach aphid (Myzus persicae Sulzer). Each of these pests directly damages potato foliage or tubers; C. tenellus and M. persicae also transmit pathogens that can drastically reduce potato yields. We monitored the seasonal population dynamics of these pests by conducting weekly sampling on a network of commercial farms from 2007 to 2014. Using these data, we developed phenology models to characterize the seasonal population dynamics of each pest based on accumulated degree-days (DD). All three pests exhibited consistent population dynamics across seasons that were mediated by temperature. Of the three pests, C. tenellus was generally the first detected in potato crops, with 90% of adults captured by 936 DD. In contrast, populations of P. operculella and M. persicae built up more slowly over the course of the season, with 90% cumulative catch by 1,590 and 2,634 DD, respectively. Understanding these seasonal patterns could help potato producers plan their IPM strategies while allowing them to move away from calendar-based applications of insecticides. More broadly, our results show how long-term monitoring studies that explore dynamics of multiple pest species can aid in developing IPM strategies in crop systems.