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Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors

Author

Listed:
  • Lo, Tsz Him
  • Rudnick, Daran R.
  • Singh, Jasreman
  • Nakabuye, Hope Njuki
  • Katimbo, Abia
  • Heeren, Derek M.
  • Ge, Yufeng

Abstract

Interreplicate variability—the spread in output values among units of the same sensor subjected to essentially the same condition—can be a major source of uncertainty in sensor data. To investigate the interreplicate variability among eight electromagnetic soil moisture sensors through a field study, eight units of TDR315, CS616, CS655, HydraProbe2, EC5, 5TE, and Teros12 were installed at a depth of 0.30 m within 3 m of each other, whereas three units of AquaSpy Vector Probe were installed within 3 m of each other. The magnitude of interreplicate variability in volumetric water content (θv) was generally similar between a static period near field capacity and a dynamic period of 85 consecutive days in the growing season. However, a wider range of variability was observed during the dynamic period primarily because interreplicate variability in θv increased sharply whenever infiltrated rainfall reached the sensor depth. Interreplicate variability for most sensors was thus smaller if comparing θv changes over several days that excluded this phenomenon than if comparing θv directly. Among the sensors that also reported temperature and/or apparent electrical conductivity, the sensors exhibiting the largest interreplicate variability in these outputs were characterized by units with consistently above or below average readings. Although manufacturers may continue to improve the technology in and the quality control of soil moisture sensors, users would still benefit from paying greater attention to interreplicate variability and adopting strategies to mitigate the consequences of interreplicate variability.

Suggested Citation

  • Lo, Tsz Him & Rudnick, Daran R. & Singh, Jasreman & Nakabuye, Hope Njuki & Katimbo, Abia & Heeren, Derek M. & Ge, Yufeng, 2020. "Field assessment of interreplicate variability from eight electromagnetic soil moisture sensors," Agricultural Water Management, Elsevier, vol. 231(C).
  • Handle: RePEc:eee:agiwat:v:231:y:2020:i:c:s0378377419307048
    DOI: 10.1016/j.agwat.2019.105984
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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. Kargas, George & Soulis, Konstantinos X., 2019. "Performance evaluation of a recently developed soil water content, dielectric permittivity, and bulk electrical conductivity electromagnetic sensor," Agricultural Water Management, Elsevier, vol. 213(C), pages 568-579.
    3. Thompson, R.B. & Gallardo, M. & Valdez, L.C. & Fernandez, M.D., 2007. "Determination of lower limits for irrigation management using in situ assessments of apparent crop water uptake made with volumetric soil water content sensors," Agricultural Water Management, Elsevier, vol. 92(1-2), pages 13-28, August.
    4. Singh, J. & Lo, T. & Rudnick, D.R. & Dorr, T.J. & Burr, C.A. & Werle, R. & Shaver, T.M. & Muñoz-Arriola, F., 2018. "Performance assessment of factory and field calibrations for electromagnetic sensors in a loam soil," Agricultural Water Management, Elsevier, vol. 196(C), pages 87-98.
    5. Barker, J. Burdette & Heeren, Derek M. & Neale, Christopher M.U. & Rudnick, Daran R., 2018. "Evaluation of variable rate irrigation using a remote-sensing-based model," Agricultural Water Management, Elsevier, vol. 203(C), pages 63-74.
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    Cited by:

    1. Hongbo Wang & Hui Cao & Fuchang Jiang & Xingpeng Wang & Yang Gao, 2022. "Analysis of Soil Moisture, Temperature, and Salinity in Cotton Field under Non-Mulched Drip Irrigation in South Xinjiang," Agriculture, MDPI, vol. 12(10), pages 1-15, October.
    2. Hodges, Blade & Tagert, Mary Love & Paz, Joel O. & Meng, Qingmin, 2023. "Assessing in-field soil moisture variability in the active root zone using granular matrix sensors," Agricultural Water Management, Elsevier, vol. 282(C).

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