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Irrigation Analysis Based on Long-Term Weather Data

Cropping Systems Research Laboratory, USDA-ARS, 3810 4th Street, Lubbock, TX 79415, USA
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Academic Editor: Mohammad Valipour
Agriculture 2016, 6(3), 42; https://doi.org/10.3390/agriculture6030042
Received: 11 July 2016 / Revised: 18 August 2016 / Accepted: 22 August 2016 / Published: 31 August 2016
(This article belongs to the Special Issue Innovative Approaches to Agricultural Water Management)
Irrigation management is based upon delivery of water to a crop in the correct amount and time, and the crop’s water need is determined by calculating evapotranspiration (ET) using weather data. In 1994, an ET-network was established in the Texas High Plains to manage irrigation on a regional scale. Though producers used the ET-network, by 2010 public access was discontinued. Why did producers allow a valuable irrigation-management tool to be eliminated? Our objective was to analyze the effect of declining well capacities on the usefulness of cotton ET (ETc) for irrigation. Thirty years (1975–2004) of daily ETc data were used to compare irrigation demand vs. irrigation responses at four locations, analyzed for multiple years and range of well capacities for three irrigation-intervals. Results indicated that when well capacities declined to the point that over-irrigation was not possible, the lower well capacities reduced the value of ETc in terms of the number of irrigations and total amount of water applied. At well capacities <1514 L·min−1 the fraction of irrigations for which ETc information was used to determine the irrigation amount was <35% across years and irrigation intervals. The value of an ETc-based irrigation may fall into disuse when irrigation-water supplies decline. View Full-Text
Keywords: cotton; irrigation scheduling; evapotranspiration; well-capacity; weather-network; water management cotton; irrigation scheduling; evapotranspiration; well-capacity; weather-network; water management
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Mahan, J.R.; Lascano, R.J. Irrigation Analysis Based on Long-Term Weather Data. Agriculture 2016, 6, 42.

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