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Article

Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor

1
Department of Land, Air & Water Resources, University of California Davis, Davis, CA 95616, USA
2
Department of Biological and Agricultural Engineering, University of California Davis, Davis, CA 95616, USA
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(24), 7041; https://doi.org/10.3390/s20247041
Received: 24 November 2020 / Revised: 5 December 2020 / Accepted: 7 December 2020 / Published: 9 December 2020
(This article belongs to the Special Issue Sensors in Agriculture 2020)
Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the accuracy of low-cost sensors (e.g., based on resistivity or capacitance) can be affected by many factors, including salinity, temperature, and soil structure. Recent developments in wireless sensor networks offer new possibilities for field-scale monitoring of soil water content (SWC) at high spatiotemporal scales, but to install many sensors in the network, the cost of the sensors must be low, and the mechanism of operation needs to be robust, simple, and consume low energy for the technology to be practically relevant. This study evaluated the performance of a resistivity–capacitance-based wireless sensor (Sensoterra BV, 1018LE Amsterdam, Netherlands) under different salinity levels, temperature, and soil types in a laboratory. The sensors were evaluated in glass beads, Oso Flaco sand, Columbia loam, and Yolo clay loam soils. A nonlinear relationship was exhibited between the sensor measured resistance (Ω) and volumetric soil water content (θ). The Ωθ relationship differed by soil type and was affected by soil solution salinity. The sensor was extremely sensitive at higher water contents with high uncertainty, and insensitive at low soil water content accompanied by low uncertainty. The soil solution salinity effects on the Ωθ relationship were found to be reduced from sand to sandy loam to clay loam. In clay soils, surface electrical conductivity (ECs) of soil particles had a more dominant effect on sensor performance compared to the effect of solution electrical conductivity (ECw). The effect of temperature on sensor performance was minimal, but sensor-to-sensor variability was substantial. The relationship between bulk electrical conductivity (ECb) and volumetric soil water content was also characterized in this study. The results of this study reveal that if the sensor is properly calibrated, this low-cost wireless soil water sensor has the potential of improving soil water monitoring for precision irrigation and other applications at high spatiotemporal scales, due to the ease of integration into IoT frameworks. View Full-Text
Keywords: soil water sensor; capacitance sensor; laboratory calibration; wireless sensor; soil water content soil water sensor; capacitance sensor; laboratory calibration; wireless sensor; soil water content
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MDPI and ACS Style

Peddinti, S.R.; Hopmans, J.W.; Abou Najm, M.; Kisekka, I. Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor. Sensors 2020, 20, 7041. https://doi.org/10.3390/s20247041

AMA Style

Peddinti SR, Hopmans JW, Abou Najm M, Kisekka I. Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor. Sensors. 2020; 20(24):7041. https://doi.org/10.3390/s20247041

Chicago/Turabian Style

Peddinti, Srinivasa R., Jan W. Hopmans, Majdi Abou Najm, and Isaya Kisekka. 2020. "Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor" Sensors 20, no. 24: 7041. https://doi.org/10.3390/s20247041

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