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Scheduling irrigation using an approach based on the van Genuchten model

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  • Liang, Xi
  • Liakos, Vasilis
  • Wendroth, Ole
  • Vellidis, George

Abstract

Crop irrigation which results in high water use efficiencies typically uses science-based irrigation scheduling tools to determine irrigation application timing and quantities. Although a large variety of sensors are available for measuring soil moisture status, there are a few easy-to-use irrigation scheduling tools which provide a yes/no irrigation decision or recommend how much water should be applied to return the soil profile to an optimal soil moisture condition. The work described here developed a method which uses soil water tension data from soil moisture sensors and the van Genuchten model to provide irrigation scheduling recommendations. The strength of the method is that it can use data readily available from USDA-NRCS soil surveys to predict soil water retention curves and calculate the volumetric water content and soil water tension of a soil at field capacity. Those parameters are then used to translate measured soil water tension into irrigation recommendations which are specific to the soil moisture status of the soil. The method was validated by comparing its results to other published methods and with continuous soil water tension data with multiple wetting and drying cycles from six fields in southern Georgia, USA. Finally, the model was incorporated into a web-based irrigation scheduling tool and used in conjunction with a wireless soil moisture sensing system to schedule irrigation in a large commercial field during 2015. By the van Genuchten model, we used about two thirds of the irrigation water and produced about the same yields as a commonly used yes/no irrigation decision tool. The presented method can be used to build resiliency to climate variability because it provides growers with data which they can use to make informed decisions about managing their water resources.

Suggested Citation

  • Liang, Xi & Liakos, Vasilis & Wendroth, Ole & Vellidis, George, 2016. "Scheduling irrigation using an approach based on the van Genuchten model," Agricultural Water Management, Elsevier, vol. 176(C), pages 170-179.
  • Handle: RePEc:eee:agiwat:v:176:y:2016:i:c:p:170-179
    DOI: 10.1016/j.agwat.2016.05.030
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    References listed on IDEAS

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    Cited by:

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    4. Lena, Bruno Patias & Bondesan, Luca & Pinheiro, Everton Alves Rodrigues & Ortiz, Brenda V. & Morata, Guilherme Trimer & Kumar, Hemendra, 2022. "Determination of irrigation scheduling thresholds based on HYDRUS-1D simulations of field capacity for multilayered agronomic soils in Alabama, USA," Agricultural Water Management, Elsevier, vol. 259(C).
    5. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Diamantopoulos, Efstathios & Ortiz, Brenda & Morata, Guilherme & Takhellambam, Bijoychandra & Bondesan, Luca, 2022. "Site-specific irrigation scheduling using one-layer soil hydraulic properties and inverse modeling," Agricultural Water Management, Elsevier, vol. 273(C).
    6. Abd El-Mageed, Taia A. & El- Samnoudi, Ibrahim M. & Ibrahim, Abd El-Aty M. & Abd El Tawwab, Ahmed R., 2018. "Compost and mulching modulates morphological, physiological responses and water use efficiency in sorghum (bicolor L. Moench) under low moisture regime," Agricultural Water Management, Elsevier, vol. 208(C), pages 431-439.
    7. Kumar, Hemendra & Srivastava, Puneet & Lamba, Jasmeet & Lena, Bruno & Diamantopoulos, Efstathios & Ortiz, Brenda & Takhellambam, Bijoychandra & Morata, Guilherme & Bondesan, Luca, 2023. "A methodology to optimize site-specific field capacity and irrigation thresholds," Agricultural Water Management, Elsevier, vol. 286(C).
    8. Fontanet, Mireia & Scudiero, Elia & Skaggs, Todd H. & Fernàndez-Garcia, Daniel & Ferrer, Francesc & Rodrigo, Gema & Bellvert, Joaquim, 2020. "Dynamic Management Zones for Irrigation Scheduling," Agricultural Water Management, Elsevier, vol. 238(C).

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