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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #299097
Title: Modeling cotton lint yield response to irrigation management as influenced by El Nino-Southern Oscillation

Author
item Baumhardt, Roland - Louis
item Mauget, Steven
item Gowda, Prasanna
item Brauer, David

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/29/2014
Publication Date: 6/14/2014
Citation: Baumhardt, R.L., Mauget, S.A., Gowda, P., Brauer, D.K. 2014. Modeling cotton lint yield response to variable irrigation and El Nino-southern oscillation climate phase. Agronomy Journal. 106:1559-1568.

Interpretive Summary: The falling Ogallala Aquifer level in the U.S. Great High Plains prompts farmers to improve water use and yield of crops like cotton that tolerate water stress. The El Niño-Southern Oscillation (ENSO) causes likely weather patterns in much of North America that could be used when making irrigation decisions. Our goal was to optimize cotton yield under variable irrigation during La Niña, neutral, and El Niño years. Actual 1959-2000 weather records were used with the GOSSYM simulation model to calculate cotton lint yields for high and low soil water contents, three emergence dates, and irrigation length (4 - 10 weeks) and rate (0.0 - 5.0 mm d-1). Simulated lint yield and its ratio to water use increased with higher irrigation amount and application rate. Growing season rain varied with ENSO phase, but phase classification in June wasn't usually the same as in the fall except for the La Niña phase. The La Niña years had less rain and poorer lint yields than neutral and El Niño phases. Yield increased with greater irrigation rate and length for drier La Niña growing seasons and weekly for the neutral and El Niño phases.

Technical Abstract: The declining Ogallala Aquifer in the U.S. Southern High Plains motivates producers to optimize water use and yield of crops that can tolerate short-term water stress like cotton [Gossypium hirsutum (L.)]. Measurable and systematic sea surface temperature anomalies (SSTA) drive the El Niño-Southern Oscillation (ENSO), resulting in predictable weather patterns in much of North America that could be exploited to optimize irrigation strategies. Our objective was to optimize cotton yield under variable application deficit irrigation as altered by the ENSO phase. To achieve this goal, cotton lint yields were simulated in response to initial soil water content, emergence date, and irrigation rate and duration combinations during La Niña, neutral, and El Niño ENSO phase years. Actual 1959-2000 weather records were used with the simulation model GOSSYM to calculate lint yields of cotton grown with 50 or 75 % initial plant available soil water. For three emergence dates, we compared cotton performance for all combinations of irrigation duration (4, 6, 8, and 10 weeks) and rate (2.5, 3.75, and 5.0 mm d-1 plus dryland). Simulated lint yield and its ratio to evapotranspiration increased with increasing irrigation amount and application rate. Growing season precipitation and thermal energy varied with ENSO phase, but phase classification in June was inconsistent with observed fall conditions except for the La Niña phase. The La Niña years had limited rain and a slightly extended growing season, but produced the poorest lint yields compared with wetter neutral and El Niño phases. Yield generally increased with increasing irrigation rate and duration during the drier La Niña growing season conditions and, to a lesser degree, the neutral and El Niño phases.