Characterization of field-scale dryland salinity with depth by quasi-3d inversion of DUALEM-1 data

J. Huang, Tanya Kilminster, E. G. Barrett-Lennard, J. Triantafilis

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    To understand the limitations of saline soil and determine best management practices, simple methods need to be developed to determine the salinity distribution in a soil profile and map this variation across the landscape. Using a field study in southwestern Australia, we describe a method to map this distribution in three dimensions using a DUALEM-1 instrument and the EM4Soil inversion software. We identified suitable parameters to invert the apparent electrical conductivity (ECa - mS/m) data acquired with a DUALEM-1, by comparing the estimates of true electrical conductivity (sigma - mS/m) derived from electromagnetic conductivity images (EMCI) to values of soil electrical conductivity of a soil-paste extract (ECe) which exhibited large ranges at 0-0.25 (32.4 dS/m), 0.25-0.50 (18.6 dS/m) and 0.50-0.75 m (17.6 dS/m). We developed EMCI using EM4Soil and the quasi-3d (q-3d), cumulative function (CF) forward modelling and S2 inversion algorithm with a damping factor (lambda) of 0.07. Using a cross-validation approach, where we removed one in 15 of the calibration locations and predicted ECe, the prediction was shown to have high accuracy (RMSE = 2.24 dS/m), small bias (ME = -0.03 dS/m) and large Lin's concordance (0.94). The results were similar to those from linear regression models between ECa and ECe for each depth of interest but were slightly less accurate (2.26 dS/m). We conclude that the q-3d inversion was more efficient and allowed for estimates of ECe to be made at any depth. The method can be applied elsewhere to map soil salinity in three dimensions.

    Original languageEnglish
    Pages (from-to)205-215
    Number of pages11
    JournalSoil Use and Management
    Volume33
    Issue number2
    DOIs
    Publication statusPublished - Jun 2017

    Cite this

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    title = "Characterization of field-scale dryland salinity with depth by quasi-3d inversion of DUALEM-1 data",
    abstract = "To understand the limitations of saline soil and determine best management practices, simple methods need to be developed to determine the salinity distribution in a soil profile and map this variation across the landscape. Using a field study in southwestern Australia, we describe a method to map this distribution in three dimensions using a DUALEM-1 instrument and the EM4Soil inversion software. We identified suitable parameters to invert the apparent electrical conductivity (ECa - mS/m) data acquired with a DUALEM-1, by comparing the estimates of true electrical conductivity (sigma - mS/m) derived from electromagnetic conductivity images (EMCI) to values of soil electrical conductivity of a soil-paste extract (ECe) which exhibited large ranges at 0-0.25 (32.4 dS/m), 0.25-0.50 (18.6 dS/m) and 0.50-0.75 m (17.6 dS/m). We developed EMCI using EM4Soil and the quasi-3d (q-3d), cumulative function (CF) forward modelling and S2 inversion algorithm with a damping factor (lambda) of 0.07. Using a cross-validation approach, where we removed one in 15 of the calibration locations and predicted ECe, the prediction was shown to have high accuracy (RMSE = 2.24 dS/m), small bias (ME = -0.03 dS/m) and large Lin's concordance (0.94). The results were similar to those from linear regression models between ECa and ECe for each depth of interest but were slightly less accurate (2.26 dS/m). We conclude that the q-3d inversion was more efficient and allowed for estimates of ECe to be made at any depth. The method can be applied elsewhere to map soil salinity in three dimensions.",
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    Characterization of field-scale dryland salinity with depth by quasi-3d inversion of DUALEM-1 data. / Huang, J.; Kilminster, Tanya; Barrett-Lennard, E. G.; Triantafilis, J.

    In: Soil Use and Management, Vol. 33, No. 2, 06.2017, p. 205-215.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Characterization of field-scale dryland salinity with depth by quasi-3d inversion of DUALEM-1 data

    AU - Huang, J.

    AU - Kilminster, Tanya

    AU - Barrett-Lennard, E. G.

    AU - Triantafilis, J.

    PY - 2017/6

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    AB - To understand the limitations of saline soil and determine best management practices, simple methods need to be developed to determine the salinity distribution in a soil profile and map this variation across the landscape. Using a field study in southwestern Australia, we describe a method to map this distribution in three dimensions using a DUALEM-1 instrument and the EM4Soil inversion software. We identified suitable parameters to invert the apparent electrical conductivity (ECa - mS/m) data acquired with a DUALEM-1, by comparing the estimates of true electrical conductivity (sigma - mS/m) derived from electromagnetic conductivity images (EMCI) to values of soil electrical conductivity of a soil-paste extract (ECe) which exhibited large ranges at 0-0.25 (32.4 dS/m), 0.25-0.50 (18.6 dS/m) and 0.50-0.75 m (17.6 dS/m). We developed EMCI using EM4Soil and the quasi-3d (q-3d), cumulative function (CF) forward modelling and S2 inversion algorithm with a damping factor (lambda) of 0.07. Using a cross-validation approach, where we removed one in 15 of the calibration locations and predicted ECe, the prediction was shown to have high accuracy (RMSE = 2.24 dS/m), small bias (ME = -0.03 dS/m) and large Lin's concordance (0.94). The results were similar to those from linear regression models between ECa and ECe for each depth of interest but were slightly less accurate (2.26 dS/m). We conclude that the q-3d inversion was more efficient and allowed for estimates of ECe to be made at any depth. The method can be applied elsewhere to map soil salinity in three dimensions.

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    KW - ELECTROMAGNETIC INDUCTION

    KW - SOIL-SALINITY

    KW - ELECTRICAL-CONDUCTIVITY

    KW - SPATIAL-DISTRIBUTION

    KW - PROFILING DATA

    KW - SIGNAL DATA

    KW - SOFTWARE

    KW - EM38

    KW - SALINIZATION

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    DO - 10.1111/sum.12345

    M3 - Article

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    EP - 215

    JO - Soil Use and Management

    JF - Soil Use and Management

    SN - 0266-0032

    IS - 2

    ER -