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© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: original research article 05 Feb 2020

Submitted as: original research article | 05 Feb 2020

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This preprint is currently under review for the journal SOIL.

Monitoring soil salinity using time-lapse electromagnetic conductivity imaging

Maria Catarina Paz1,2, Mohammad Farzamian1,3, Ana Marta Paz3, Nádia Luísa Castanheira3, Maria Conceição Gonçalves3, and Fernando Monteiro Santos1 Maria Catarina Paz et al.
  • 1Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Edifício C1, Piso 1, 1749-016 Lisboa, Portugal
  • 2CIQuiBio, Barreiro School of Technology, Polytechnic Institute of Setúbal, Rua Américo da Silva Marinho, 2839-001 Lavradio, Portugal
  • 3Instituto Nacional de Investigação Agrária e Veterinária, Avenida da República, Quinta do Marquês (edifício sede), 2780-157 Oeiras, Portugal

Abstract. Lezíria Grande of Vila Franca de Xira, located in Portugal, is an important agricultural system where soil faces the risk of salinization, being thus prone to desertification and land abandonment. Soil salinity can be assessed over large areas by the following rationale: (1) use of electromagnetic induction (EMI) to measure the soil apparent electrical conductivity (ECa, dS m−1); (2) inversion of ECa to obtain electromagnetic conductivity images (EMCI) which provide the spatial distribution of the soil electrical conductivity (σ, mS m−1); (3) calibration process consisting of a regression between σ and the electrical conductivity of the saturated soil paste extract (ECe, dS m−1), used as a proxy for soil salinity; and (4) conversion of EMCI into salinity maps using the obtained calibration equation.

In this study, EMI surveys and soil sampling were carried out between May 2017 and October 2018 at four locations with different salinity levels across the study area of Lezíria de Vila Franca. A previously developed regional calibration was used for predicting ECe from EMCI. This study aims to evaluate the potential of time-lapse EMCI and the regional calibration to predict the spatiotemporal variability of soil salinity in the study area. The results showed that ECe was satisfactorily predicted, with a root mean square error (RMSE) of 3.22 dS m−1 in a range of 52.35 dS m−1 and a coefficient of determination (R2) of 0.89. Results also showed strong concordance with a Lin’s concordance correlation coefficient (CCC) of 0.93, although, ECe was slightly overestimated with a mean error (ME) of −1.30 dS m−1. Soil salinity maps for each location revealed salinity fluctuations related to the input of salts and water either through irrigation, precipitation or groundwater level and salinity. Time-lapse EMCI has proven to be a valid methodology for evaluating the risk of soil salinization, and can further support the evaluation and adoption of proper agricultural management strategies, especially in irrigated areas, where continuous monitoring of soil salinity dynamics is required.

Maria Catarina Paz et al.

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Maria Catarina Paz et al.

Maria Catarina Paz et al.


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Latest update: 04 Jul 2020
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Short summary
In this study electromagnetic induction (EMI) surveys and soil sampling were repeated over time to monitor soil salinity dynamics in an important agricultural area that faces risk of soil salinization. EMI data was converted to electromagnetic conductivity imaging through a mathematical inversion algorithm, and converted to 2D soil salinity maps until a depth of 1.35 m through a regional calibration. This is a non-invasive and cost-effective methodology that can be employed over large areas.
In this study electromagnetic induction (EMI) surveys and soil sampling were repeated over time...