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Soil electrical conductivity estimated by time domain reflectometry and electromagnetic induction sensors: Accounting for the different sensor observation volumes

Ali Saeed, Alessandro Comegna, Giovanna Dragonetti, Nicola Lamaddalena, Angelo Sommella, Antonio Coppola
  • Ali Saeed
    School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
  • Alessandro Comegna
    School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy
  • Giovanna Dragonetti
    Land and Water Division, Mediterranean Agronomic Institute - International Centre for Advanced Mediterranean Agronomic Studies, Bari, Italy
  • Nicola Lamaddalena
    Land and Water Division, Mediterranean Agronomic Institute - International Centre for Advanced Mediterranean Agronomic Studies, Bari, Italy
  • Angelo Sommella
    Department of Agriculture, Federico II University, Naples, Italy
  • Antonio Coppola
    School of Agricultural, Forestry, Food and Environmental Sciences, University of Basilicata, Potenza, Italy | antonio.coppola@unibas.it

Abstract

This paper dealt with the calibration of an EMI sensor for monitoring the time dynamics of root zone salinity under irrigation with saline water. Calibration was based on an empirical multiple regression approach largely adopted in the past and still applied in practice for its relative simplicity. Compared to the more complex inversion approaches, it requires an independent dataset of local σb measured within discrete depth intervals, to be compared to horizontal and vertical electrical conductivity (ECaH and ECaV) readings for estimating the parameters of the empirical regression equations. In this paper, we used time domain reflectometry (TDR) readings to replace direct sampling for these local σb measurements. When using this approach, there is the important issue of taking into account the effect of the different sensor observation volumes, making the readings not immediately comparable for empirical calibration. Accordingly, a classical Fourier’s filtering technique was applied to remove the high frequency part (at small spatial scale) of the original data variability, which, due to the different observation volume, was the main source of dissimilarity between the two datasets. Thus, calibration focused only on the lower frequency information, that is, the information at a spatial scale larger than the observation volume of the sensors. By this analysis, we showed and quantified the degree to which the information of the set of TDR readings came from a combination of local and larger scale heterogeneities and how they have to be manipulated for use in EMI electromagnetic induction sensor calibration.

Keywords

Soil salinity; electromagnetic induction; time domain reflectometry; sensors observation volume; Fourier’s analysis.

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Submitted: 2017-05-10 22:39:50
Published: 2017-12-04 16:55:05
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Copyright (c) 2017 Ali Saeed, Alessandro Comegna, Giovanna Dragonetti, Nicola Lamaddalena, Angelo Sommella, Antonio Coppola

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