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Determining sensor-based field capacity for irrigation scheduling

Author

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  • Vories, Earl
  • Sudduth, Ken

Abstract

Irrigated agriculture is a major consumer of freshwater and acreage of irrigated land has increased as producers have become increasingly reliant on irrigation to ensure adequate yields and reduce production risks. Information about the soil’s field capacity, or the water content after a saturated soil has drained for at least 24 h, is needed to determine the soil’s readily available water, or the amount of water that can be safely removed by plants. To address the challenges associated with using soil water sensors in highly variable soils, soil water measurements were included in ongoing cotton irrigation studies during the 2017 through 2019 growing seasons at the University of Missouri Fisher Delta Research Center near Portageville. Sensor-based field capacity values were compared among multiple commercially available sensors. Time-domain reflectometry sensors (Acclima TDR 315) were installed at four depths and five locations each of the three years. In addition, resistance-type sensors (Irrometer Watermark 200SS) were installed at five depths and five locations for two years. The goal was to provide guidance on how best to use soil moisture sensor data for irrigation management. Although water continued to move in the profile for more than 24 h after saturation, the average change between 24 and 48 h at each observed depth was < 0.015 m3 m−3. Observed values for coarser textured soils were much wetter after 24 h than expected based on published field capacity values and in one case, even a small difference in sensor location had a large effect on the observed field capacity. Furthermore, soil apparent electrical conductivity was highly correlated to measured field capacity, which could result in a much faster and less expensive way to estimate field capacity compared to collecting and analyzing soil cores. These findings demonstrate that the application of soil moisture sensors for irrigation management is site specific, and differences can be observed over short distances within a field. The research is continuing to better meet the needs of agricultural producers, consultants, research and extension personnel, and others for information to improve irrigation management.

Suggested Citation

  • Vories, Earl & Sudduth, Ken, 2021. "Determining sensor-based field capacity for irrigation scheduling," Agricultural Water Management, Elsevier, vol. 250(C).
  • Handle: RePEc:eee:agiwat:v:250:y:2021:i:c:s0378377421001256
    DOI: 10.1016/j.agwat.2021.106860
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    Cited by:

    1. Sangha, Laljeet & Shortridge, Julie & Frame, William, 2023. "The impact of nitrogen treatment and short-term weather forecast data in irrigation scheduling of corn and cotton on water and nutrient use efficiency in humid climates," Agricultural Water Management, Elsevier, vol. 283(C).
    2. Haddon, Antoine & Kechichian, Loïc & Harmand, Jérôme & Dejean, Cyril & Ait-Mouheb, Nassim, 2023. "Linking soil moisture sensors and crop models for irrigation management," Ecological Modelling, Elsevier, vol. 484(C).

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