Equatorial Pacific sea surface temperature anomalies can cause a systematic El Nino-Southern Oscillation (ENSO) coupling with the atmosphere to produce predictable weather patterns in much of North America. Adapting irrigation strategies for drought-tolerant crops like cotton ( Gossypium hirsutum L.) to exploit forecast climatic conditions represents one potential innovative technique for managing the declining Ogallala Aquifer beneath the US Southern High Plains. The crop simulation model GOSSYM was used with ENSO phase-specific weather records during 1959 to 2000 at Bushland, TX, to estimate lint yields of cotton emerging on three dates from soil at 50 or 75% available water content for all possible combinations of irrigation durations (0, 4, 6, 8, and 10 wk) and rates (2.5, 3.75, and 5.0 mm d -1). From those data, our objective was to compare partial center pivot deficit irrigation strategies that optimize calculated net cotton lint yield in relation to ENSO phase, initial soil water content, and emergence date. Although phase classification in June was inconsistent with maturing fall phases, the most accurately classified La Nina phase had limited rain that reduced lint yields compared with wetter Neutral and El Nino phases. During La Nina phase conditions, irrigation strategies that focused fixed water resources on smaller areas were better suited to increase net yield than spreading water across larger areas. Alternatively, during less predictable and wetter Neutral and El Nino phases, irrigation strategies that spread water increased net lint yield over focused applications except when both initial soil water and irrigation amount were limiting.
