Location: Soil and Water Management ResearchTitle: Optimizing irrigation strategies as influenced by El Nino southern oscillation Author
Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/21/2015
Publication Date: 7/22/2015
Citation: Baumhardt, R.L., Mauget, S.A., Gowda, P., Brauer, D.K., Marek, G.W. 2015. Optimizing irrigation strategies as influenced by El Nino southern oscillation Agronomy Journal. 107(5):1895-1904.
Interpretive Summary: The falling Ogallala Aquifer level under the U.S. Southern Great High Plains prompts farmers to improve water use and use more water smart crops like cotton; however new tools and management are needed to decrease dependence on the Ogallala Aquifer for irrigation water. The El Niño-Southern Oscillation (ENSO) causes likely weather patterns on the Southern Great Plains that could be used when making irrigation decisions. Goal of this research was to optimize cotton yield under variable irrigation during La Niña, neutral, and El Niño years. Weather records (1959-2000) were used with crop growth model to calculate cotton lint yields for various soil moisture conditions at planting, emergence dates, and irrigation length and rate. ARS scientists from Conservation and Production Research Laboratory (Bushland, Texas) and Cropping Systems Research Laboratory (Lubbock, Texas) found that the weather phase classification in June wasn't usually the same as in the fall except for the La Niña phase, indicating that fall predictions were more accurate. La Niña years had less rain during the growing season and lower lint yields than neutral and El Niño phases. Yield increased with greater irrigation rate and length for drier La Niña growing seasons. These results indicate that farmers need to plan for greater irrigation demand during a predicted La Niña growing season.
Technical Abstract: Equatorial Pacific sea surface temperature anomalies (SSTA) can cause a systematic El Niño-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 forecasted climatic conditions represents one potential innovative technique for managing the declining Ogallala Aquifer beneath the U.S. Southern High Plains. Our objective was to compare partial center pivot deficit irrigation strategies that optimize net cotton lint yield in relation to ENSO phase, initial soil water content, and emergence date. We used the crop simulation model GOSSYM with ENSO phase specific weather records during 1959-2000 at Bushland, TX to estimate net lint yields of cotton emerging on three dates from soil at 50 or 75% initial available water content for all possible combinations of irrigation duration (0, 4, 6, 8, and 10 weeks) and rate (2.5, 3.75, and 5.0 mm d-1). Although phase classification in June was inconsistent with maturing fall phases, the most accurately classified La Niña phase had limited rain that reduced lint yields compared with wetter Neutral and El Niño phases. During drier La Niña phase conditions, irrigation strategies that focused fixed water resources on a smaller area were better suited to increase net yield than spreading water over larger areas. Alternatively, during less predictable and wetter Neutral and El Niño phases, irrigation strategies that spread water increased net lint yield over focused applications except when both initial soil water and irrigation amount were limiting.