Influence of temperature on soil water content measured by ECH2O-TE sensors

Kočárek, Martin; Kodešová, Radka

doi:10.2478/v10247-012-0038-2

Cited by 13 publications

(11 citation statements)

References 20 publications

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“…However, the observed effect was actually in the opposite direction, with decreasing soil water potentials under lower soil temperatures, indicating that the sensors were not just reacting to the permittivity of pure water. This result was already found for other dielectric sensors ( e.g ., Seyfried and Grant , ; Kočárek and Kodešová , ).…”

Section: Discussionmentioning

confidence: 99%

“…In our opinion, it was most reasonable to correct the soil water potential readings for a temperature of 22°C because the sensors were calibrated at this temperature by the manufacturer. An analogous approach, i.e ., conversion of apparent soil water content to a reference temperature, has been successfully accomplished in several studies for dielectric soil moisture sensors ( e.g ., Kočárek and Kodešová , ; Mittelbach et al, ; Saito et al, ). The result of the compensation presented here is the water potential that the considered soil would have at the reference temperature of 22°C, which may differ from its true potential at the current temperature.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, temperature changes may affect the soil bulk dielectric conductivity in connection with temperature‐induced changes in the gradients of free and bound soil water ( Or and Wraith , ). Additionally, in some studies temperature effects have been attributed to temperature sensitivity of the sensor electronics ( e.g ., Verhoef et al, ; Seyfried and Grant , ; Rosenbaum et al, ; Kočárek and Kodešová , ; Chandler et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Equations to compensate for the temperature effect on readings from dielectric Decagon MPS‐2 and MPS‐6 water potential sensors in soils

Walthert

Schleppi

2018

J. Plant Nutr. Soil Sci.

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Dielectric sensors use electrical permittivity as a proxy for water content. They determine permittivity by using sensor‐type‐specific techniques and calibration functions, and relate it to a volumetric water content. Water potential sensors then translate the water content into a potential based on the sensor‐specific moisture characteristic curve. Dielectric readings are affected by temperature, which may distort hydraulically‐induced changes in soil water content. Methods for the removal of spurious temperature effects are lacking for dielectric water potential sensors. With this study, we aimed to fill this knowledge gap for the dielectric Decagon MPS‐2 and MPS‐6 water potential sensors. We first determined the temperature effect on MPS readings with laboratory experiments in which temperature was cycled between 4 and 26°C in different soil types. We then fitted single empirical equations that compensated for the temperature effect on MPS readings. Finally, we validated temperature‐compensated MPS soil water potentials, and therefore the equations, in a multi‐year field study in two forest soils where hourly data from three sensor models were available, i.e., from MPS‐2, MPS‐6, and a heat capacity sensor (ecoTech pF‐Meter) that is not sensitive to temperature effects. The temperature fluctuation experiments showed that the strongest temperature effects on MPS readings occur under dry conditions and that the MPS sensors themselves are largely responsible for these effects. Likewise, the field‐based validation showed that the MPS readings were highly affected by temperature under dry conditions. Applying a temperature compensation to these readings, using the equations from the temperature fluctuation experiments, resulted in strong correlations near the 1:1 line between data from the MPS and pF‐Meter sensors. Therefore, we recommend using the equations to remove spurious temperature effects from MPS‐2 and MPS‐6 readings in non‐saline soils with water potentials between –100 and –2000 kPa (at 22°C) and temperatures between 4 and 26°C.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Equations to compensate for the temperature effect on readings from dielectric Decagon MPS‐2 and MPS‐6 water potential sensors in soils

Walthert

Schleppi

2018

J. Plant Nutr. Soil Sci.

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“…Both sensors were attached to the LI‐8100A ACU. The EC‐5 determines the VWC by measuring the dielectric constant media using capacitance domain technology (Kočárek & Kodešová, ). The system was powered at the beginning of the observations with a 55‐Ah/12 volt battery and a 60‐W solar panel but upgraded to a 180 Ah/12 Volt battery with 260‐W solar panels after several power failures.…”

Section: Methodsmentioning

confidence: 99%

Analyzing High‐Frequency Soil Respiration Using a Probabilistic Model in a Semiarid, Mediterranean Climate

et al. 2019

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High‐frequency (subhourly) changes in soil respiration (Rs), a critical component of the carbon cycle, are not well documented in semiarid ecosystems. We investigate the response of Rs to subhourly soil temperature (Tsoil) and soil volumetric water content (VWC) variation in a semiarid ecosystem across a year of highly variable weather. We propose a probabilistic model to estimate the likelihood of Rs exceeding its annual mean (1.2 μmol CO2/m2s), conditioned on different Tsoil and VWC values. The results show that Rs follows a Gaussian‐like pattern as Tsoil increases, where it follows an upward trend until ~18 °C, and then begins to decline. Rs remains constant at Tsoil beyond ~27 °C. Using our novel conditional probability model, we show both the increasing and decreasing response of Rs to rising Tsoil through two ranges (14–17 and 20–23 °C) where Rs observations show opposing responses. We demonstrate that an increase in Tsoil from 14 to 17 °C causes a rise in Rs by a factor of 1.4 relative to the mean. The proposed model also describes how Rs reduces as Tsoil continues to increase above ~18 °C. Considering VWC and Tsoil into the proposed model, we show that when Tsoil is low (e.g., 17 °C), a rise in VWC yields a decrease of Rs by a factor of 3.6. However, when Tsoil is high (e.g., 23 °C), Rs increases with increasing VWC by a factor of 2.5. Overall, the probabilistic model enables us to detect and characterize changes in Rs distribution in response to different environmental variables and thresholds.

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“…The influence of temperature on soil-water content values measured using the ECH 2 O-TE sensors was reduced as described by Kočárek and Kodešová (2012). In addition, data measured during the freezing period were not reliable and were not included in this study.…”

Section: Soilmentioning

confidence: 99%