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Article

Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine

1
School of Biological, Earth and Environmental Sciences, Faculty of Science, UNSW Sydney, Sydney, NSW 2052, Australia
2
Instituto Dom Luiz, Faculdade de Ciências da Universidade de Lisboa, Campo Grande, Ed. C1, Piso 1, 1749-016 Lisboa, Portugal
*
Author to whom correspondence should be addressed.
Soil Syst. 2020, 4(2), 25; https://doi.org/10.3390/soilsystems4020025
Received: 17 March 2020 / Revised: 14 April 2020 / Accepted: 16 April 2020 / Published: 22 April 2020
(This article belongs to the Special Issue Proximal Soil Sensing Applications)
The clay alluvial plains of Namoi Valley have been intensively developed for irrigation. A condition of a license is water needs to be stored on the farm. However, the clay plain was developed from prior stream channels characterised by sandy clay loam textures that are permeable. Cheap methods of soil physical and chemical characterisations are required to map the supply channels used to move water on farms. Herein, we collect apparent electrical conductivity (ECa) from a DUALEM-421 along a 4-km section of a supply channel. We invert ECa to generate electromagnetic conductivity images (EMCI) using EM4Soil software and evaluate two-dimensional models of estimates of true electrical conductivity (σ—mS m−1) against physical (i.e., clay and sand—%) and chemical properties (i.e., electrical conductivity of saturated soil paste extract (ECe—dS m−1) and the cation exchange capacity (CEC, cmol(+) kg−1). Using a support vector machine (SVM), we predict these properties from the σ and depth. Leave-one-site-out cross-validation shows strong 1:1 agreement (Lin’s) between the σ and clay (0.85), sand (0.81), ECe (0.86) and CEC (0.83). Our interpretation of predicted properties suggests the approach can identify leakage areas (i.e., prior stream channels). We suggest that, with this calibration, the approach can be used to predict soil physical and chemical properties beneath supply channels across the rest of the valley. Future research should also explore whether similar calibrations can be developed to enable characterisations in other cotton-growing areas of Australia. View Full-Text
Keywords: DUALEM-421; soil apparent electrical conductivity; inversion modelling; electromagnetic conductivity imaging (EMCI) DUALEM-421; soil apparent electrical conductivity; inversion modelling; electromagnetic conductivity imaging (EMCI)
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MDPI and ACS Style

Zare, E.; Li, N.; Khongnawang, T.; Farzamian, M.; Triantafilis, J. Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine. Soil Syst. 2020, 4, 25. https://doi.org/10.3390/soilsystems4020025

AMA Style

Zare E, Li N, Khongnawang T, Farzamian M, Triantafilis J. Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine. Soil Systems. 2020; 4(2):25. https://doi.org/10.3390/soilsystems4020025

Chicago/Turabian Style

Zare, Ehsan, Nan Li, Tibet Khongnawang, Mohammad Farzamian, and John Triantafilis. 2020. "Identifying Potential Leakage Zones in an Irrigation Supply Channel by Mapping Soil Properties Using Electromagnetic Induction, Inversion Modelling and a Support Vector Machine" Soil Systems 4, no. 2: 25. https://doi.org/10.3390/soilsystems4020025

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