Comparison of Laboratory and Field Calibration of a Soil-Moisture Capacitance Probe for Various Soils

Kinzli, Kristoph-Dietrich; Manana, Nkosinathi; Oad, Ramchand

doi:10.1061/(asce)ir.1943-4774.0000418

Cited by 40 publications

(33 citation statements)

References 42 publications

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“…This fact is intrinsically associated with the nature of the water movement and retention is such soils. Similar 'bad' experience with the field calibration of electromagnetic sensors is reported by Kinzli et al (2012), who prefer laboratory calibration to the field one. We disagree with them, as long as the final purpose is the field measurement, because the field techniques of sensor installation can hardly be mimicked in the laboratory, especially when the sensors are large and the soil is structured.…”

Section: Resultssupporting

confidence: 53%

Percolation in macropores and performance of large time-domain reflectometry sensors

Dolezal¹,

Matula²,

Barradas³

2012

PLANT SOIL ENVIRON

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The large-diameter time-domain reflectometry soil water sensors placed horizontally in a structured loamy soil are very sensitive to rapid preferential percolation events. Their readings on these occasions rise considerably, often becoming higher than the native soil's porosity. The effect is caused by gaps between the native soil and the sensors. The geometry of the gaps, even if filled with soil slurry at installation, is not exactly reproducible, which leads to sensor-to-sensor variability of readings. Field calibration in percolation-free periods lead to non-unique trajectories rather than monotonous calibration curves, which can be commented in terms of soil heterogeneity and the dual porosity theory. Data of two typical percolation events are presented. Sensors of this type can be used for detection of preferential flux.

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Section: Resultssupporting

confidence: 53%

Percolation in macropores and performance of large time-domain reflectometry sensors

Dolezal¹,

Matula²,

Barradas³

2012

PLANT SOIL ENVIRON

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“…Both capacitive sensors had accuracy measures comparable to the previous literature pertaining to low-cost capacitive sensors, in terms of MAE and RMSE [33,66]. In terms of RAE, the SMEC300 sensor was accurate across all soils (average σ e f f = 0.47, Standard Error SE σ e f f = 0.07) barring Soil 3, in which the σ e f f reduced to 0.69.…”

Section: Sensor Accuracysupporting

confidence: 65%

“…The performance of the calibration equations developed for the capacitive sensors was comparable to that of other low-cost capacitive sensors reported in the literature [66]. The SM100 sensor (average overall R 2 = 0.94) performed at par with other low-cost capacitive sensors for sandy soils (average R 2 = 0.95 compared to R 2 = 0.97 from the literature [66]), and surpassed previous work for silty-loams (average R 2 = 0.93 compared to R 2 = 0.88 from the literature [66]). The SMEC300 performed equally well as the SM100 in sands (average R 2 = 0.95), but not in silty-loam soils (average R 2 = 0.82); nevertheless, being comparable to previous literature [66].…”

Section: Calibration Equations Developed Between Measured (θ) and Actsupporting

confidence: 57%

“…The SM100 sensor (average overall R 2 = 0.94) performed at par with other low-cost capacitive sensors for sandy soils (average R 2 = 0.95 compared to R 2 = 0.97 from the literature [66]), and surpassed previous work for silty-loams (average R 2 = 0.93 compared to R 2 = 0.88 from the literature [66]). The SMEC300 performed equally well as the SM100 in sands (average R 2 = 0.95), but not in silty-loam soils (average R 2 = 0.82); nevertheless, being comparable to previous literature [66]. Overall, the calibration results reinforce the inference that the SM100 sensor is more robust (due to its superior performance in a field soil) compared to the SMEC300 sensor.…”

Section: Calibration Equations Developed Between Measured (θ) and Actmentioning

confidence: 68%

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Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors

Adla

Kumar²,

Karumanchi³

et al. 2020

Sensors

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Soil volumetric water content ( V W C ) is a vital parameter to understand several ecohydrological and environmental processes. Its cost-effective measurement can potentially drive various technological tools to promote data-driven sustainable agriculture through supplemental irrigation solutions, the lack of which has contributed to severe agricultural distress, particularly for smallholder farmers. The cost of commercially available V W C sensors varies over four orders of magnitude. A laboratory study characterizing and testing sensors from this wide range of cost categories, which is a prerequisite to explore their applicability for irrigation management, has not been conducted. Within this context, two low-cost capacitive sensors—SMEC300 and SM100—manufactured by Spectrum Technologies Inc. (Aurora, IL, USA), and two very low-cost resistive sensors—the Soil Hygrometer Detection Module Soil Moisture Sensor (YL100) by Electronicfans and the Generic Soil Moisture Sensor Module (YL69) by KitsGuru—were tested for performance in laboratory conditions. Each sensor was calibrated in different repacked soils, and tested to evaluate accuracy, precision and sensitivity to variations in temperature and salinity. The capacitive sensors were additionally tested for their performance in liquids of known dielectric constants, and a comparative analysis of the calibration equations developed in-house and provided by the manufacturer was carried out. The value for money of the sensors is reflected in their precision performance, i.e., the precision performance largely follows sensor costs. The other aspects of sensor performance do not necessarily follow sensor costs. The low-cost capacitive sensors were more accurate than manufacturer specifications, and could match the performance of the secondary standard sensor, after soil specific calibration. SMEC300 is accurate ( M A E , R M S E , and R A E of 2.12%, 2.88% and 0.28 respectively), precise, and performed well considering its price as well as multi-purpose sensing capabilities. The less-expensive SM100 sensor had a better accuracy ( M A E , R M S E , and R A E of 1.67%, 2.36% and 0.21 respectively) but poorer precision than the SMEC300. However, it was established as a robust, field ready, low-cost sensor due to its more consistent performance in soils (particularly the field soil) and superior performance in fluids. Both the capacitive sensors responded reasonably to variations in temperature and salinity conditions. Though the resistive sensors were less accurate and precise compared to the capacitive sensors, they performed well considering their cost category. The YL100 was more accurate ( M A E , R M S E , and R A E of 3.51%, 5.21% and 0.37 respectively) than YL69 ( M A E , R M S E , and R A E of 4.13%, 5.54%, and 0.41, respectively). However, YL69 outperformed YL100 in terms of precision, and response to temperature and salinity variations, to emerge as a more robust resistive sensor. These very low-cost sensors may be used in combination with more accurate sensors to better characterize the spatiotemporal variability of field scale soil moisture. The laboratory characterization conducted in this study is a prerequisite to estimate the effect of low- and very low-cost sensor measurements on the efficiency of soil moisture based irrigation scheduling systems.

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“…The calibration equation used to derive the volumetric water content is

θ = 0.0007 {(period_C)}^{2} - 0.0063 (period_C) - 0.0663

where θ is the volumetric water content (cm 3 cm −3 ). It is well established that a soil‐specific calibration can improve reading accuracy (Kinzli et al, 2012). It has also been shown, however, that standard equations perform well for soils with low organic C content (Vaz et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

Comparison of Soil Water Potential Sensors: A Drying Experiment

Degré

Ploeg

Caldwell

et al. 2017

Vadose Zone Journal

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Core Ideas In situ water retention curve is key to capture the dynamics of root zone functions. Some of the water potential probes can cover a wide range of water potential levels. The potential probes ability to capture an in situ retention curve is tested. The soil water retention curve (WRC) plays a major role in a soil's hydrodynamic behavior. Many measurement techniques are currently available for determining the WRC in the laboratory. Direct in situ WRC can be obtained from simultaneous soil moisture and water potential readings covering a wide tension range, from saturation to the wilting point. There are many widely used soil moisture probes. Whereas near‐saturation tension can be measured using water‐filled tensiometers, wider ranges of water potential require new, more expensive, and less widely used probes. We compared three types of soil water potential sensors that could allow us to measure water potential in the field, with a range relevant to water uptake by plants. Polymer tensiometers (POTs), MPS‐2 probes, and pF meters were compared in a controlled drying experiment. The study showed that the POTs and MPS‐2 probes had good reliability in their respective ranges. Combined with a soil moisture probe, these two sensors can provide observed WRCs. The pF meters below −30 kPa were inaccurate, and their response was sensitive to measurement interval, with greater estimated suction at shorter measurement intervals. In situ WRC can provide supplementary information, particularly with regard to its spatial and temporal variability. It could also improve the results of other measurement techniques, such as geophysical observations.

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Comparison of Laboratory and Field Calibration of a Soil-Moisture Capacitance Probe for Various Soils

Cited by 40 publications

References 42 publications

Percolation in macropores and performance of large time-domain reflectometry sensors

Percolation in macropores and performance of large time-domain reflectometry sensors

Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors

Comparison of Soil Water Potential Sensors: A Drying Experiment

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