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Soil water sensors for irrigation scheduling in the United States: A systematic review of literature

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  • Datta, Sumon
  • Taghvaeian, Saleh

Abstract

Soil water sensors (SWS) have been widely researched and practiced for irrigation scheduling. Due to popularity of this approach, there is a need for frequent reviews of the SWS literature to keep the researchers, extension professionals, and end-users updated and to help with defining and modifying future directions. In addition, existing literature reviews do not systematically report and summarize the results of previous studies. To address this gap, a systematic review was carried out to identify and analyze related literature published in the United States in the past two decades. Two focus areas were SWS accuracy assessment and SWS application in irrigation scheduling. The results showed that SWS accuracy was most susceptible to sensor calibration. The reported root mean square errors had similar ranges and means among different technologies, installation orientations, and study environments. Compared to other scheduling methods, SWS-based scheduling resulted in water saving, with average amounts ranging from 1 % when compared to canopy temperature methods to 38 % in case of traditional approaches. In addition, SWS-based scheduling led to larger or similar yields compared to other scheduling methods. Texas and Nebraska were the top two states in terms of the number of studies on SWS accuracy and irrigation scheduling.

Suggested Citation

  • Datta, Sumon & Taghvaeian, Saleh, 2023. "Soil water sensors for irrigation scheduling in the United States: A systematic review of literature," Agricultural Water Management, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:agiwat:v:278:y:2023:i:c:s0378377423000136
    DOI: 10.1016/j.agwat.2023.108148
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    References listed on IDEAS

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    1. Singh, J. & Lo, T. & Rudnick, D.R. & Irmak, S. & Blanco-Canqui, H., 2019. "Quantifying and correcting for clay content effects on soil water measurement by reflectometers," Agricultural Water Management, Elsevier, vol. 216(C), pages 390-399.
    2. Younsuk Dong & Steve Miller & Lyndon Kelley, 2020. "Performance Evaluation of Soil Moisture Sensors in Coarse- and Fine-Textured Michigan Agricultural Soils," Agriculture, MDPI, vol. 10(12), pages 1-11, December.
    3. Evett, Steven R. & Schwartz, Robert C. & Casanova, Joaquin J. & Heng, Lee K., 2012. "Soil water sensing for water balance, ET and WUE," Agricultural Water Management, Elsevier, vol. 104(C), pages 1-9.
    4. Matthew J Page & Joanne E McKenzie & Patrick M Bossuyt & Isabelle Boutron & Tammy C Hoffmann & Cynthia D Mulrow & Larissa Shamseer & Jennifer M Tetzlaff & Elie A Akl & Sue E Brennan & Roger Chou & Jul, 2021. "The PRISMA 2020 statement: An updated guideline for reporting systematic reviews," PLOS Medicine, Public Library of Science, vol. 18(3), pages 1-15, March.
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