Modeling Cotton Lint Yield Response to Irrigation Management as Influenced by El Nino-Southern Oscillation

摘要

The declining High Plains or Ogallala Aquifer motivates U.S. producers to optimize water use and yield of drought-tolerant crops like cotton [Gossypium hirsuium (L)]. Systematic sea surface temperature anomalies (SSTA) drive the El Nino-Southern Oscillation (ENSO), resulting in predictable weather patterns in North America that could be exploited by irrigation strategies. Our objective was to compare cotton yield response to irrigation as altered by La Nina, Neutral, or El Nino phases for the Texas High Plains. We used actual 1959 to 2000 weather records with the simulation model GOSSYM to estimate lint yields for three progressively later emergence dates under 50 or 75% initial soil water conditions and all combinations of irrigation duration (0, 4, 6, 8, and 10 wk) and rate (2.5, 3.75,and 5.0 mm d(-1)). Simulated lint yield and its ratio to evapotranspiration generally decreased with emergence delays and increased with increasing irrigation amount and application rate. Growing season precipitation varied with ENSO phase, but April to June phase classification was inconsistent with fall conditions except for La Nina. Compared with yield estimates for Neutral and EL Nino phases, limited rain during La Nina years reduced lint yields from 5 to 30% when initial soil water was 75 and 50%. Yield increased with increasing irrigation rate and duration during drier La Nina growing seasons, but irrigation benefits decreased during Neutral and El Nino years having greater precipitation. Early ENSO based extended forecasts for La Nina related consistently to irrigation effects on yield and could determine application strategies.