The Temperature Correction for the Electrical Resistivity Measurements in Undisturbed Soil Samples

Besson, Arlène; Cousin, Isabelle; Dorigny, Abel; Dabas, Michel; King, D.

doi:10.1097/ss.0b013e318189397f

Cited by 39 publications

(42 citation statements)

References 23 publications

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“…The commonly used relationship for correcting EC measurement to a standard 25°C is the ratio model (Hayashi 2004;Persson and Berndtsson 1998;Heimovaara et al 1995;Sorensen and Glass 1987;Franson 1985;Barry et al 2008;Besson et al 2008;Keller and Frischknecht 1966) …”

Section: Temperature Correction Modelsmentioning

confidence: 99%

“…Groundwater textbooks frequently cite '2% increase in EC per°C increase of temperature', which equates to d = 0.02. Geophysicists commonly use d = 0.025 (Hayashi 2004;Besson et al 2008;Keller and Frischknecht 1966). For soil data, Persson and Berndtsson (1998) found that d = 0.023°C -1 fitted their soil data best.…”

Section: Temperature Correction Modelsmentioning

confidence: 99%

“…Corwin and Lesch (2005) gave various models for the temperature conversion factor, either as polynomial equations (Stogryn 1971;Rhoades et al 1999;Wraith and Or 1999), or as an exponential equation (Sheets and Hendrickx 1995). Besson et al (2008) also introduced some temperature conversion models, but the work has some errors in the citation. It is relevant to analyze these models and to determine whether they are consistent with each other.…”

Section: Introductionmentioning

confidence: 98%

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Comparing temperature correction models for soil electrical conductivity measurement

et al. 2010

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There are various factors that affect soil electrical conductivity (EC) measurements, including soil texture, soil water content, cation exchange capacity (CEC) and others. Temperature is an important environmental variable, and different models can be used to correct for its effect on EC measurements and standardize the measurements to 25°C. It is relevant to analyze these models and to determine whether they are consistent with each other. Some models were wrongly cited. We found that the exponential model of Sheets and Hendrickx as corrected by Corwin and Lesch in 2005 performs the best. The ratio model also performs well between 3°C and 47°C.

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Section: Temperature Correction Modelsmentioning

confidence: 99%

Section: Temperature Correction Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Comparing temperature correction models for soil electrical conductivity measurement

et al. 2010

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“…[24] There are numerous other empirical formulations for the dependence of s f , s 0 , or b on temperature given in literature [e.g., Sorensen and Glass, 1987;Sen and Goode, 1992;Besson et al, 2008, and references therein], but these have been used less frequently than the above cited formulations.…”

Section: Dependence On Temperaturementioning

confidence: 99%

Dependence of spectral‐induced polarization response of sandstone on temperature and its relevance to permeability estimation

Zisser¹,

Kemna²,

Nover³

2010

J. Geophys. Res.

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[1] The possibility to estimate permeability from the electrical spectral induced polarization (SIP) response might be the most important benefit offered by SIP measurements. It can thus be deduced that, in the future, SIP measurements will be carried out more frequently at the field scale or in a well-logging context to estimate permeability. In the shallow subsurface, however, the temperature generally exhibits seasonal variability, and in the deeper subsurface, it usually increases with depth. Hence, knowledge about the dependence of the SIP response on temperature is necessary in order to avoid possible misinterpretation of datasets impacted by thermal effects. In our study, we present a semiempirical framework to describe the temperature dependence of the SIP response. We briefly introduce the SIP response and its relation to permeability in terms of an electrochemical polarization mechanism and combine this formulation with relationships for the dependence of ionic mobility on temperature. We compare the predictions of our formulation with the experimental data from SIP measurements performed on sandstone at temperatures from 0°C to 80°C. The measured SIP response was transformed into a relaxation time distribution, using the empirical Cole-Cole model and a regularized Debye decomposition procedure. The SIP response was found to be in good agreement with the theoretical model. The temperature dependence of both direct current conductivity and relaxation time is controlled mainly by the dependence of ionic mobility on temperature, and the shape of the relaxation time distribution of the investigated sandstone is almost independent of temperature. The temperature effect on the SIP response can therefore be easily corrected.Citation: Zisser, N., A. Kemna, and G. Nover (2010), Dependence of spectral-induced polarization response of sandstone on temperature and its relevance to permeability estimation,

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“…The test site has been also equipped with a weather station to record meteorological parameters for data interpretation since resistivity values are influenced by air and soil temperature as well as by rainfalls. In the last decades several studies have deeply investigated the relationship between temperature and resistivity and many approaches have been proposed to remove the effect of temperature from collected datasets [47][48][49][50][51][52][53]. On the contrary, only a few studies analysed how to remove the influence of rainfalls from field measurements [54].…”

Section: Introductionmentioning

confidence: 99%

A customized resistivity system for monitoring saturation and seepage in earthen levees: installation and validation

et al. 2017

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This work is based on the assumption that a resistivity meter can effectively monitor water saturation in earth levees and can be used as a warning system when saturation exceeds the expected seasonal maxima. We performed time-lapse ERT measurements to assess the capability of this method to detect areas where seepage is critical. These measurements were also very useful to design a prototype monitoring system with remarkable savings by customizing the specifications according to field observations. The prototype consists of a remotely controlled low-power resistivity meter with a spread of 48 stainless steel 20 × 20 cm plate electrodes buried at half-meter depth. We deployed the newly-designed permanent monitoring system on a critical levee segment. A weather station and an ultrasonic water level sensor were also installed in order to analyse the correlation of resistivity with temperature, rainfalls and water level seasonal variations. The preliminary analysis of the monitoring data shows that the resistivity maps follow a very reasonable trend related with the saturation/drying cycle of the levee caused by the seasonal variations of the water level in the irrigation channel. Sharp water level changes cause delayed and smooth resistivity variations. Rainfalls and, to a lesser extent, temperature seem to have an influence on the collected data but effects are apparently negligible beyond 1 m depth. The system is currently operating and results are continuously monitored.

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The Temperature Correction for the Electrical Resistivity Measurements in Undisturbed Soil Samples

Cited by 39 publications

References 23 publications

Comparing temperature correction models for soil electrical conductivity measurement

Comparing temperature correction models for soil electrical conductivity measurement

Dependence of spectral‐induced polarization response of sandstone on temperature and its relevance to permeability estimation

A customized resistivity system for monitoring saturation and seepage in earthen levees: installation and validation

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